A Beta Oscillation Network in the Rat Olfactory System During a 2-Alternative Choice Odor Discrimination Task

PubMed Central

Beshel, Jennifer

2010-01-01

We previously showed that in a two-alternative choice (2AC) task, olfactory bulb (OB) gamma oscillations (∼70 Hz in rats) were enhanced during discrimination of structurally similar odorants (fine discrimination) versus discrimination of dissimilar odorants (coarse discrimination). In other studies (mostly employing go/no-go tasks) in multiple labs, beta oscillations (15–35 Hz) dominate the local field potential (LFP) signal in olfactory areas during odor sampling. Here we analyzed the beta frequency band power and pairwise coherence in the 2AC task. We show that in a task dominated by gamma in the OB, beta oscillations are also present in three interconnected olfactory areas (OB and anterior and posterior pyriform cortex). Only the beta band showed consistently elevated coherence during odor sniffing across all odor pairs, classes (alcohols and ketones), and discrimination types (fine and coarse), with stronger effects in first than in final criterion sessions (>70% correct). In the first sessions for fine discrimination odor pairs, beta power for incorrect trials was the same as that for correct trials for the other odor in the pair. This pattern was not repeated in coarse discrimination, in which beta power was elevated for correct relative to incorrect trials. This difference between fine and coarse odor discriminations may relate to different behavioral strategies for learning to differentiate similar versus dissimilar odors. Phase analysis showed that the OB led both pyriform areas in the beta frequency band during odor sniffing. We conclude that the beta band may be the means by which information is transmitted from the OB to higher order areas, even though task specifics modify dominance of one frequency band over another within the OB. PMID:20538778

Parasites as biological tags of fish stocks: a meta-analysis of their discriminatory power.

PubMed

Poulin, Robert; Kamiya, Tsukushi

2015-01-01

The use of parasites as biological tags to discriminate among marine fish stocks has become a widely accepted method in fisheries management. Here, we first link this approach to its unstated ecological foundation, the decay in the similarity of the species composition of assemblages as a function of increasing distance between them, a phenomenon almost universal in nature. We explain how distance decay of similarity can influence the use of parasites as biological tags. Then, we perform a meta-analysis of 61 uses of parasites as tags of marine fish populations in multivariate discriminant analyses, obtained from 29 articles. Our main finding is that across all studies, the observed overall probability of correct classification of fish based on parasite data was about 71%. This corresponds to a two-fold improvement over the rate of correct classification expected by chance alone, and the average effect size (Zr = 0·463) computed from the original values was also indicative of a medium-to-large effect. However, none of the moderator variables included in the meta-analysis had a significant effect on the proportion of correct classification; these moderators included the total number of fish sampled, the number of parasite species used in the discriminant analysis, the number of localities from which fish were sampled, the minimum and maximum distance between any pair of sampling localities, etc. Therefore, there are no clear-cut situations in which the use of parasites as tags is more useful than others. Finally, we provide recommendations for the future usage of parasites as tags for stock discrimination, to ensure that future applications of the method achieve statistical rigour and a high discriminatory power.

Comprehensive combinatory standard correction: a calibration method for handling instrumental drifts of gas chromatography-mass spectrometry systems.

PubMed

Deport, Coralie; Ratel, Jérémy; Berdagué, Jean-Louis; Engel, Erwan

2006-05-26

The current work describes a new method, the comprehensive combinatory standard correction (CCSC), for the correction of instrumental signal drifts in GC-MS systems. The method consists in analyzing together with the products of interest a mixture of n selected internal standards, and in normalizing the peak area of each analyte by the sum of standard areas and then, select among the summation operator sigma(p = 1)(n)C(n)p possible sums, the sum that enables the best product discrimination. The CCSC method was compared with classical techniques of data pre-processing like internal normalization (IN) or single standard correction (SSC) on their ability to correct raw data from the main drifts occurring in a dynamic headspace-gas chromatography-mass spectrometry system. Three edible oils with closely similar compositions in volatile compounds were analysed using a device which performance was modulated by using new or used dynamic headspace traps and GC-columns, and by modifying the tuning of the mass spectrometer. According to one-way ANOVA, the CCSC method increased the number of analytes discriminating the products (31 after CCSC versus 25 with raw data or after IN and 26 after SSC). Moreover, CCSC enabled a satisfactory discrimination of the products irrespective of the drifts. In a factorial discriminant analysis, 100% of the samples (n = 121) were well-classified after CCSC versus 45% for raw data, 90 and 93%, respectively after IN and SSC.

Discrimination among spawning aggregations of lake herring from Lake Superior using whole-body morphometric characters

USGS Publications Warehouse

Hoff, Michael H.

2004-01-01

The lake herring (Coregonus artedi) was one of the most commercially and ecologically valuable Lake Superior fishes, but declined in the second half of the 20th century as the result of overharvest of putatively discrete stocks. No tools were previously available that described lake herring stock structure and accurately classified lake herring to their spawning stocks. The accuracy of discriminating among spawning aggregations was evaluated using whole-body morphometrics based on a truss network. Lake herring were collected from 11 spawning aggregations in Lake Superior and two inland Wisconsin lakes to evaluate morphometrics as a stock discrimination tool. Discriminant function analysis correctly classified 53% of all fish from all spawning aggregations, and fish from all but one aggregation were classified at greater rates than were possible by chance. Discriminant analysis also correctly classified 66% of fish to nearest neighbor groups, which were groups that accounted for the possibility of mixing among the aggregations. Stepwise discriminant analysis showed that posterior body length and depth measurements were among the best discriminators of spawning aggregations. These findings support other evidence that discrete stocks of lake herring exist in Lake Superior, and fishery managers should consider all but one of the spawning aggregations as discrete stocks. Abundance, annual harvest, total annual mortality rate, and exploitation data should be collected from each stock, and surplus production of each stock should be estimated. Prudent management of stock surplus production and exploitation rates will aid in restoration of stocks and will prevent a repeat of the stock collapses that occurred in the middle of the 20th century, when the species was nearly extirpated from the lake.

Fast discrimination of traditional Chinese medicine according to geographical origins with FTIR spectroscopy and advanced pattern recognition techniques

NASA Astrophysics Data System (ADS)

Li, Ning; Wang, Yan; Xu, Kexin

2006-08-01

Combined with Fourier transform infrared (FTIR) spectroscopy and three kinds of pattern recognition techniques, 53 traditional Chinese medicine danshen samples were rapidly discriminated according to geographical origins. The results showed that it was feasible to discriminate using FTIR spectroscopy ascertained by principal component analysis (PCA). An effective model was built by employing the Soft Independent Modeling of Class Analogy (SIMCA) and PCA, and 82% of the samples were discriminated correctly. Through use of the artificial neural network (ANN)-based back propagation (BP) network, the origins of danshen were completely classified.

An automated image processing method for classification of diabetic retinopathy stages from conjunctival microvasculature images

NASA Astrophysics Data System (ADS)

Khansari, Maziyar M.; O'Neill, William; Penn, Richard; Blair, Norman P.; Chau, Felix; Shahidi, Mahnaz

2017-03-01

The conjunctiva is a densely vascularized tissue of the eye that provides an opportunity for imaging of human microcirculation. In the current study, automated fine structure analysis of conjunctival microvasculature images was performed to discriminate stages of diabetic retinopathy (DR). The study population consisted of one group of nondiabetic control subjects (NC) and 3 groups of diabetic subjects, with no clinical DR (NDR), non-proliferative DR (NPDR), or proliferative DR (PDR). Ordinary least square regression and Fisher linear discriminant analyses were performed to automatically discriminate images between group pairs of subjects. Human observers who were masked to the grouping of subjects performed image discrimination between group pairs. Over 80% and 70% of images of subjects with clinical and non-clinical DR were correctly discriminated by the automated method, respectively. The discrimination rates of the automated method were higher than human observers. The fine structure analysis of conjunctival microvasculature images provided discrimination of DR stages and can be potentially useful for DR screening and monitoring.

Varietal discrimination of hop pellets by near and mid infrared spectroscopy.

PubMed

Machado, Julio C; Faria, Miguel A; Ferreira, Isabel M P L V O; Páscoa, Ricardo N M J; Lopes, João A

2018-04-01

Hop is one of the most important ingredients of beer production and several varieties are commercialized. Therefore, it is important to find an eco-real-time-friendly-low-cost technique to distinguish and discriminate hop varieties. This paper describes the development of a method based on vibrational spectroscopy techniques, namely near- and mid-infrared spectroscopy, for the discrimination of 33 commercial hop varieties. A total of 165 samples (five for each hop variety) were analysed by both techniques. Principal component analysis, hierarchical cluster analysis and partial least squares discrimination analysis were the chemometric tools used to discriminate positively the hop varieties. After optimizing the spectral regions and pre-processing methods a total of 94.2% and 96.6% correct hop varieties discrimination were obtained for near- and mid-infrared spectroscopy, respectively. The results obtained demonstrate the suitability of these vibrational spectroscopy techniques to discriminate different hop varieties and consequently their potential to be used as an authenticity tool. Compared with the reference procedures normally used for hops variety discrimination these techniques are quicker, cost-effective, non-destructive and eco-friendly. Copyright © 2017 Elsevier B.V. All rights reserved.

An in-depth evaluation of accuracy and precision in Hg isotopic analysis via pneumatic nebulization and cold vapor generation multi-collector ICP-mass spectrometry.

PubMed

Rua-Ibarz, Ana; Bolea-Fernandez, Eduardo; Vanhaecke, Frank

2016-01-01

Mercury (Hg) isotopic analysis via multi-collector inductively coupled plasma (ICP)-mass spectrometry (MC-ICP-MS) can provide relevant biogeochemical information by revealing sources, pathways, and sinks of this highly toxic metal. In this work, the capabilities and limitations of two different sample introduction systems, based on pneumatic nebulization (PN) and cold vapor generation (CVG), respectively, were evaluated in the context of Hg isotopic analysis via MC-ICP-MS. The effect of (i) instrument settings and acquisition parameters, (ii) concentration of analyte element (Hg), and internal standard (Tl)-used for mass discrimination correction purposes-and (iii) different mass bias correction approaches on the accuracy and precision of Hg isotope ratio results was evaluated. The extent and stability of mass bias were assessed in a long-term study (18 months, n = 250), demonstrating a precision ≤0.006% relative standard deviation (RSD). CVG-MC-ICP-MS showed an approximately 20-fold enhancement in Hg signal intensity compared with PN-MC-ICP-MS. For CVG-MC-ICP-MS, the mass bias induced by instrumental mass discrimination was accurately corrected for by using either external correction in a sample-standard bracketing approach (SSB) or double correction, consisting of the use of Tl as internal standard in a revised version of the Russell law (Baxter approach), followed by SSB. Concomitant matrix elements did not affect CVG-ICP-MS results. Neither with PN, nor with CVG, any evidence for mass-independent discrimination effects in the instrument was observed within the experimental precision obtained. CVG-MC-ICP-MS was finally used for Hg isotopic analysis of reference materials (RMs) of relevant environmental origin. The isotopic composition of Hg in RMs of marine biological origin testified of mass-independent fractionation that affected the odd-numbered Hg isotopes. While older RMs were used for validation purposes, novel Hg isotopic data are provided for the latest generations of some biological RMs.

Suppression of the µ Rhythm during Speech and Non-Speech Discrimination Revealed by Independent Component Analysis: Implications for Sensorimotor Integration in Speech Processing

PubMed Central

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Background Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.) Methods Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80–100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. Results ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13–30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Conclusions Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed. PMID:23991030

Suppression of the µ rhythm during speech and non-speech discrimination revealed by independent component analysis: implications for sensorimotor integration in speech processing.

PubMed

Bowers, Andrew; Saltuklaroglu, Tim; Harkrider, Ashley; Cuellar, Megan

2013-01-01

Constructivist theories propose that articulatory hypotheses about incoming phonetic targets may function to enhance perception by limiting the possibilities for sensory analysis. To provide evidence for this proposal, it is necessary to map ongoing, high-temporal resolution changes in sensorimotor activity (i.e., the sensorimotor μ rhythm) to accurate speech and non-speech discrimination performance (i.e., correct trials.). Sixteen participants (15 female and 1 male) were asked to passively listen to or actively identify speech and tone-sweeps in a two-force choice discrimination task while the electroencephalograph (EEG) was recorded from 32 channels. The stimuli were presented at signal-to-noise ratios (SNRs) in which discrimination accuracy was high (i.e., 80-100%) and low SNRs producing discrimination performance at chance. EEG data were decomposed using independent component analysis and clustered across participants using principle component methods in EEGLAB. ICA revealed left and right sensorimotor µ components for 14/16 and 13/16 participants respectively that were identified on the basis of scalp topography, spectral peaks, and localization to the precentral and postcentral gyri. Time-frequency analysis of left and right lateralized µ component clusters revealed significant (pFDR<.05) suppression in the traditional beta frequency range (13-30 Hz) prior to, during, and following syllable discrimination trials. No significant differences from baseline were found for passive tasks. Tone conditions produced right µ beta suppression following stimulus onset only. For the left µ, significant differences in the magnitude of beta suppression were found for correct speech discrimination trials relative to chance trials following stimulus offset. Findings are consistent with constructivist, internal model theories proposing that early forward motor models generate predictions about likely phonemic units that are then synthesized with incoming sensory cues during active as opposed to passive processing. Future directions and possible translational value for clinical populations in which sensorimotor integration may play a functional role are discussed.

A simple randomisation procedure for validating discriminant analysis: a methodological note.

PubMed

Wastell, D G

1987-04-01

Because the goal of discriminant analysis (DA) is to optimise classification, it designedly exaggerates between-group differences. This bias complicates validation of DA. Jack-knifing has been used for validation but is inappropriate when stepwise selection (SWDA) is employed. A simple randomisation test is presented which is shown to give correct decisions for SWDA. The general superiority of randomisation tests over orthodox significance tests is discussed. Current work on non-parametric methods of estimating the error rates of prediction rules is briefly reviewed.

Determination of trace metal concentrations in ginseng (Panax Quinquefolius (American)) roots for forensic comparison using Inductively Coupled Plasma Mass-Spectrometry.

PubMed

Peake, Barrie M; Tong, Alfred Y C; Wells, William J; Harraway, John A; Niven, Brian E; Weege, Butch; LaFollette, Douglas J

2015-06-01

The trace metal content of roots of samples of the American ginseng natural herbal plant species (Panax quinquefolius) was investigated as a means of differentiating between this species grown on Wisconsin and New Zealand farms, and from Canadian and Chinese sources. ICP-MS measurements were undertaken by ashing samples of the roots and then digestion with conc. HNO3 and H2O2. There was considerable variation in the concentrations of 28 detectable elements along the length of a root, between different roots, between different farms/sources and between different countries. Statistical processing of the log-transformed concentration data was undertaken using principal component analysis (PCA) and discriminant function analysis (DFA). Although PCA showed some differentiation between samples, a much clearer discrimination of the Panax quinquefolius species of ginseng from the four countries was observed using DFA. 88% of the variation between countries could be accounted for by only using discriminant function 1 while 80% of the remaining 12% of the variation between countries is accounted for by discriminant function 2. The Fisher Classification Functions classify 98% of the 87 samples to the correct country of origin with 97% of the cross-validated cases correctly classified. The predictive ability of this DFA model was further tested by constructing 100 discriminant models each using a random selection of the data for two thirds of the 87 sampled ginseng root tops, and then using the resulting classification functions to determine correctly the country of origin of the remaining third of the cases. The mean success rate of the 100 classifications was 92%. These results suggest that measurement and statistical analysis of just the trace metal content of the roots of Panax quinquefolius promises to be an excellent predictor of the country of origin of this ginseng species. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Classification of typical and atypical antipsychotic drugs on the basis of dopamine D-1, D-2 and serotonin2 pKi values.

PubMed

Meltzer, H Y; Matsubara, S; Lee, J C

1989-10-01

The pKi values of 13 reference typical and 7 reference atypical antipsychotic drugs (APDs) for rat striatal dopamine D-1 and D-2 receptor binding sites and cortical serotonin (5-HT2) receptor binding sites were determined. The atypical antipsychotics had significantly lower pKi values for the D-2 but not 5-HT2 binding sites. There was a trend for a lower pKi value for the D-1 binding site for the atypical APD. The 5-HT2 and D-1 pKi values were correlated for the typical APD whereas the 5-HT2 and D-2 pKi values were correlated for the atypical APD. A stepwise discriminant function analysis to determine the independent contribution of each pKi value for a given binding site to the classification as a typical or atypical APD entered the D-2 pKi value first, followed by the 5-HT2 pKi value. The D-1 pKi value was not entered. A discriminant function analysis correctly classified 19 of 20 of these compounds plus 14 of 17 additional test compounds as typical or atypical APD for an overall correct classification rate of 89.2%. The major contributors to the discriminant function were the D-2 and 5-HT2 pKi values. A cluster analysis based only on the 5-HT2/D2 ratio grouped 15 of 17 atypical + one typical APD in one cluster and 19 of 20 typical + two atypical APDs in a second cluster, for an overall correct classification rate of 91.9%. When the stepwise discriminant function was repeated for all 37 compounds, only the D-2 and 5-HT2 pKi values were entered into the discriminant function.(ABSTRACT TRUNCATED AT 250 WORDS)

Discrimination of whisky brands and counterfeit identification by UV-Vis spectroscopy and multivariate data analysis.

PubMed

Martins, Angélica Rocha; Talhavini, Márcio; Vieira, Maurício Leite; Zacca, Jorge Jardim; Braga, Jez Willian Batista

2017-08-15

The discrimination of whisky brands and counterfeit identification were performed by UV-Vis spectroscopy combined with partial least squares for discriminant analysis (PLS-DA). In the proposed method all spectra were obtained with no sample preparation. The discrimination models were built with the employment of seven whisky brands: Red Label, Black Label, White Horse, Chivas Regal (12years), Ballantine's Finest, Old Parr and Natu Nobilis. The method was validated with an independent test set of authentic samples belonging to the seven selected brands and another eleven brands not included in the training samples. Furthermore, seventy-three counterfeit samples were also used to validate the method. Results showed correct classification rates for genuine and false samples over 98.6% and 93.1%, respectively, indicating that the method can be helpful for the forensic analysis of whisky samples. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discrimination among populations of sockeye salmon fry with Fourier analysis of otolith banding patterns formed during incubation

USGS Publications Warehouse

Finn, James E.; Burger, Carl V.; Holland-Bartels, Leslie E.

1997-01-01

We used otolith banding patterns formed during incubation to discriminate among hatchery- and wild-incubated fry of sockeye salmon Oncorhynchus nerka from Tustumena Lake, Alaska. Fourier analysis of otolith luminance profiles was used to describe banding patterns: the amplitudes of individual Fourier harmonics were discriminant variables. Correct classification of otoliths to either hatchery or wild origin was 83.1% (cross-validation) and 72.7% (test data) with the use of quadratic discriminant function analysts on 10 Fourier amplitudes. Overall classification rates among the six test groups (one hatchery and five wild groups) were 46.5% (cross-validation) and 39.3% (test data) with the use of linear discriminant function analysis on 16 Fourier amplitudes. Although classification rates for wild-incubated fry from any one site never exceeded 67% (cross-validation) or 60% (test data), location-specific information was evident for all groups because the probability of classifying an individual to its true incubation location was significantly greater than chance. Results indicate phenotypic differences in otolith microstructure among incubation sites separated by less than 10 km. Analysis of otolith luminance profiles is a potentially useful technique for discriminating among and between various populations of hatchery and wild fish.

Statistically Correct Methodology for Compositional Data in New Discriminant Function Tectonomagmatic Diagrams and Application to Ophiolite Origin

NASA Astrophysics Data System (ADS)

Verma, Surendra P.; Pandarinath, Kailasa; Verma, Sanjeet K.

2011-07-01

In the lead presentation (invited talk) of Session SE05 (Frontiers in Geochemistry with Reference to Lithospheric Evolution and Metallogeny) of AOGS2010, we have highlighted the requirement of correct statistical treatment of geochemical data. In most diagrams used for interpreting compositional data, the basic statistical assumption of open space for all variables is violated. Among these graphic tools, discrimination diagrams have been in use for nearly 40 years to decipher tectonic setting. The newer set of five tectonomagmatic discrimination diagrams published in 2006 (based on major-elements) and two sets made available in 2008 and 2011 (both based on immobile elements) fulfill all statistical requirements for correct handling of compositional data, including the multivariate nature of compositional variables, representative sampling, and probability-based tectonic field boundaries. Additionally in the most recent proposal of 2011, samples having normally distributed, discordant-outlier free, log-ratio variables were used in linear discriminant analysis. In these three sets of five diagrams each, discrimination was successfully documented for four tectonic settings (island arc, continental rift, ocean-island, and mid-ocean ridge). The discrimination diagrams have been extensively evaluated for their performance by different workers. We exemplify these two sets of new diagrams (one set based on major-elements and the other on immobile elements) using ophiolites from Boso Peninsula, Japan. This example is included for illustration purposes only and is not meant for testing of these newer diagrams. Their evaluation and comparison with older, conventional bivariate or ternary diagrams have been reported in other papers.

An Initial Analysis of LANDSAT-4 Thematic Mapper Data for the Discrimination of Agricultural, Forested Wetland, and Urban Land Covers

NASA Technical Reports Server (NTRS)

Quattrochi, D. A.

1984-01-01

An initial analysis of LANDSAT 4 Thematic Mapper (TM) data for the discrimination of agricultural, forested wetland, and urban land covers is conducted using a scene of data collected over Arkansas and Tennessee. A classification of agricultural lands derived from multitemporal LANDSAT Multispectral Scanner (MSS) data is compared with a classification of TM data for the same area. Results from this comparative analysis show that the multitemporal MSS classification produced an overall accuracy of 80.91% while the TM classification yields an overall classification accuracy of 97.06% correct.

Stability and bias of classification rates in biological applications of discriminant analysis

USGS Publications Warehouse

Williams, B.K.; Titus, K.; Hines, J.E.

1990-01-01

We assessed the sampling stability of classification rates in discriminant analysis by using a factorial design with factors for multivariate dimensionality, dispersion structure, configuration of group means, and sample size. A total of 32,400 discriminant analyses were conducted, based on data from simulated populations with appropriate underlying statistical distributions. Simulation results indicated strong bias in correct classification rates when group sample sizes were small and when overlap among groups was high. We also found that stability of the correct classification rates was influenced by these factors, indicating that the number of samples required for a given level of precision increases with the amount of overlap among groups. In a review of 60 published studies, we found that 57% of the articles presented results on classification rates, though few of them mentioned potential biases in their results. Wildlife researchers should choose the total number of samples per group to be at least 2 times the number of variables to be measured when overlap among groups is low. Substantially more samples are required as the overlap among groups increases

Predictive models reduce talent development costs in female gymnastics.

PubMed

Pion, Johan; Hohmann, Andreas; Liu, Tianbiao; Lenoir, Matthieu; Segers, Veerle

2017-04-01

This retrospective study focuses on the comparison of different predictive models based on the results of a talent identification test battery for female gymnasts. We studied to what extent these models have the potential to optimise selection procedures, and at the same time reduce talent development costs in female artistic gymnastics. The dropout rate of 243 female elite gymnasts was investigated, 5 years past talent selection, using linear (discriminant analysis) and non-linear predictive models (Kohonen feature maps and multilayer perceptron). The coaches classified 51.9% of the participants correct. Discriminant analysis improved the correct classification to 71.6% while the non-linear technique of Kohonen feature maps reached 73.7% correctness. Application of the multilayer perceptron even classified 79.8% of the gymnasts correctly. The combination of different predictive models for talent selection can avoid deselection of high-potential female gymnasts. The selection procedure based upon the different statistical analyses results in decrease of 33.3% of cost because the pool of selected athletes can be reduced to 92 instead of 138 gymnasts (as selected by the coaches). Reduction of the costs allows the limited resources to be fully invested in the high-potential athletes.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Independent components analysis to increase efficiency of discriminant analysis methods (FDA and LDA): Application to NMR fingerprinting of wine.

PubMed

Monakhova, Yulia B; Godelmann, Rolf; Kuballa, Thomas; Mushtakova, Svetlana P; Rutledge, Douglas N

2015-08-15

Discriminant analysis (DA) methods, such as linear discriminant analysis (LDA) or factorial discriminant analysis (FDA), are well-known chemometric approaches for solving classification problems in chemistry. In most applications, principle components analysis (PCA) is used as the first step to generate orthogonal eigenvectors and the corresponding sample scores are utilized to generate discriminant features for the discrimination. Independent components analysis (ICA) based on the minimization of mutual information can be used as an alternative to PCA as a preprocessing tool for LDA and FDA classification. To illustrate the performance of this ICA/DA methodology, four representative nuclear magnetic resonance (NMR) data sets of wine samples were used. The classification was performed regarding grape variety, year of vintage and geographical origin. The average increase for ICA/DA in comparison with PCA/DA in the percentage of correct classification varied between 6±1% and 8±2%. The maximum increase in classification efficiency of 11±2% was observed for discrimination of the year of vintage (ICA/FDA) and geographical origin (ICA/LDA). The procedure to determine the number of extracted features (PCs, ICs) for the optimum DA models was discussed. The use of independent components (ICs) instead of principle components (PCs) resulted in improved classification performance of DA methods. The ICA/LDA method is preferable to ICA/FDA for recognition tasks based on NMR spectroscopic measurements. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaluation of five guidelines for option development in multiple-choice item-writing.

PubMed

Martínez, Rafael J; Moreno, Rafael; Martín, Irene; Trigo, M Eva

2009-05-01

This paper evaluates certain guidelines for writing multiple-choice test items. The analysis of the responses of 5013 subjects to 630 items from 21 university classroom achievement tests suggests that an option should not differ in terms of heterogeneous content because such error has a slight but harmful effect on item discrimination. This also occurs with the "None of the above" option when it is the correct one. In contrast, results do not show the supposedly negative effects of a different-length option, the use of specific determiners, or the use of the "All of the above" option, which not only decreases difficulty but also improves discrimination when it is the correct option.

Application of multivariate statistical techniques for differentiation of ripe banana flour based on the composition of elements.

PubMed

Alkarkhi, Abbas F M; Ramli, Saifullah Bin; Easa, Azhar Mat

2009-01-01

Major (sodium, potassium, calcium, magnesium) and minor elements (iron, copper, zinc, manganese) and one heavy metal (lead) of Cavendish banana flour and Dream banana flour were determined, and data were analyzed using multivariate statistical techniques of factor analysis and discriminant analysis. Factor analysis yielded four factors explaining more than 81% of the total variance: the first factor explained 28.73%, comprising magnesium, sodium, and iron; the second factor explained 21.47%, comprising only manganese and copper; the third factor explained 15.66%, comprising zinc and lead; while the fourth factor explained 15.50%, comprising potassium. Discriminant analysis showed that magnesium and sodium exhibited a strong contribution in discriminating the two types of banana flour, affording 100% correct assignation. This study presents the usefulness of multivariate statistical techniques for analysis and interpretation of complex mineral content data from banana flour of different varieties.

Meat mixture detection in Iberian pork sausages.

PubMed

Ortiz-Somovilla, V; España-España, F; De Pedro-Sanz, E J; Gaitán-Jurado, A J

2005-11-01

Five homogenized meat mixture treatments of Iberian (I) and/or Standard (S) pork were set up. Each treatment was analyzed by NIRS as a fresh product (N=75) and as dry-cured sausage (N=75). Spectra acquisition was carried out using DA 7000 equipment (Perten Instruments), obtaining a total of 750 spectra. Several absorption peaks and bands were selected as the most representative for homogenized dry-cured and fresh sausages. Discriminant analysis and mixture prediction equations were carried out based on the spectral data gathered. The best results using discriminant models were for fresh products, with 98.3% (calibration) and 60% (validation) correct classification. For dry-cured sausages 91.7% (calibration) and 80% (validation) of the samples were correctly classified. Models developed using mixture prediction equations showed SECV=4.7, r(2)=0.98 (calibration) and 73.3% of validation set were correctly classified for the fresh product. These values for dry-cured sausages were SECV=5.9, r(2)=0.99 (calibration) and 93.3% correctly classified for validation.

Metacarpophalangeal pattern profile analysis: useful diagnostic tool for differentiating between dyschondrosteosis, Turner syndrome, and hypochondroplasia.

PubMed

Laurencikas, E; Sävendahl, L; Jorulf, H

2006-06-01

To assess the value of the metacarpophalangeal pattern profile (MCPP) analysis as a diagnostic tool for differentiating between patients with dyschondrosteosis, Turner syndrome, and hypochondroplasia. Radiographic and clinical data from 135 patients between 1 and 51 years of age were collected and analyzed. The study included 25 patients with hypochondroplasia (HCP), 39 with dyschondrosteosis (LWD), and 71 with Turner syndrome (TS). Hand pattern profiles were calculated and compared with those of 110 normal individuals. Pearson correlation coefficient (r) and multivariate discriminant analysis were used for pattern profile analysis. Pattern variability index, a measure of dysmorphogenesis, was calculated for LWD, TS, HCP, and normal controls. Our results demonstrate that patients with LWD, TS, or HCP have distinct pattern profiles that are significantly different from each other and from those of normal controls. Discriminant analysis yielded correct classification of normal versus abnormal individuals in 84% of cases. Classification of the patients into LWD, TS, and HCP groups was successful in 75%. The correct classification rate was higher (85%) when differentiating two pathological groups at a time. Pattern variability index was not helpful for differential diagnosis of LWD, TS, and HCP. Patients with LWD, TS, or HCP have distinct MCPPs and can be successfully differentiated from each other using advanced MCPP analysis. Discriminant analysis is to be preferred over Pearson correlation coefficient because it is a more sensitive and specific technique. MCPP analysis is a helpful tool for differentiating between syndromes with similar clinical and radiological abnormalities.

Comparative genome analysis of a large Dutch Legionella pneumophila strain collection identifies five markers highly correlated with clinical strains

PubMed Central

2010-01-01

Background Discrimination between clinical and environmental strains within many bacterial species is currently underexplored. Genomic analyses have clearly shown the enormous variability in genome composition between different strains of a bacterial species. In this study we have used Legionella pneumophila, the causative agent of Legionnaire's disease, to search for genomic markers related to pathogenicity. During a large surveillance study in The Netherlands well-characterized patient-derived strains and environmental strains were collected. We have used a mixed-genome microarray to perform comparative-genome analysis of 257 strains from this collection. Results Microarray analysis indicated that 480 DNA markers (out of in total 3360 markers) showed clear variation in presence between individual strains and these were therefore selected for further analysis. Unsupervised statistical analysis of these markers showed the enormous genomic variation within the species but did not show any correlation with a pathogenic phenotype. We therefore used supervised statistical analysis to identify discriminating markers. Genetic programming was used both to identify predictive markers and to define their interrelationships. A model consisting of five markers was developed that together correctly predicted 100% of the clinical strains and 69% of the environmental strains. Conclusions A novel approach for identifying predictive markers enabling discrimination between clinical and environmental isolates of L. pneumophila is presented. Out of over 3000 possible markers, five were selected that together enabled correct prediction of all the clinical strains included in this study. This novel approach for identifying predictive markers can be applied to all bacterial species, allowing for better discrimination between strains well equipped to cause human disease and relatively harmless strains. PMID:20630115

Alzheimer's disease detection using 11C-PiB with improved partial volume effect correction

NASA Astrophysics Data System (ADS)

Raniga, Parnesh; Bourgeat, Pierrick; Fripp, Jurgen; Acosta, Oscar; Ourselin, Sebastien; Rowe, Christopher; Villemagne, Victor L.; Salvado, Olivier

2009-02-01

Despite the increasing use of 11C-PiB in research into Alzheimer's disease (AD), there are few standardized analysis procedures that have been reported or published. This is especially true with regards to partial volume effects (PVE) and partial volume correction. Due to the nature of PET physics and acquisition, PET images exhibit relatively low spatial resolution compared to other modalities, resulting in bias of quantitative results. Although previous studies have applied PVE correction techniques on 11C-PiB data, the results have not been quantitatively evaluated and compared against uncorrected data. The aim of this study is threefold. Firstly, a realistic synthetic phantom was created to quantify PVE. Secondly, MRI partial volume estimate segmentations were used to improve voxel-based PVE correction instead of using hard segmentations. Thirdly, quantification of PVE correction was evaluated on 34 subjects (AD=10, Normal Controls (NC)=24), including 12 PiB positive NC. Regional analysis was performed using the Anatomical Automatic Labeling (AAL) template, which was registered to each patient. Regions of interest were restricted to the gray matter (GM) defined by the MR segmentation. Average normalized intensity of the neocortex and selected regions were used to evaluate the discrimination power between AD and NC both with and without PVE correction. Receiver Operating Characteristic (ROC) curves were computed for the binary discrimination task. The phantom study revealed signal losses due to PVE between 10 to 40 % which were mostly recovered to within 5% after correction. Better classification was achieved after PVE correction, resulting in higher areas under ROC curves.

Discriminant function analysis as tool for subsurface geologist

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chesser, K.

1987-05-01

Sedimentary structures such as cross-bedding control porosity, permeability, and other petrophysical properties in sandstone reservoirs. Understanding the distribution of such structures in the subsurface not only aids in the prediction of reservoir properties but also provides information about depositional environments. Discriminant function analysis (DFA) is a simple yet powerful method incorporating petrophysical data from wireline logs, core analyses, or other sources into groups that have been previously defined through direct observation of sedimentary structures in cores. Once data have been classified into meaningful groups, the geologist can predict the distribution of specific sedimentary structures or important reservoir properties in areasmore » where cores are unavailable. DFA is efficient. Given several variables, DFA will choose the best combination to discriminate among groups. The initial classification function can be computed from relatively few observations, and additional data may be included as necessary. Furthermore, DFA provides quantitative goodness-of-fit estimates for each observation. Such estimates can be used as mapping parameters or to assess risk in petroleum ventures. Petrophysical data from the Skinner sandstone of Strauss field in southeastern Kansas tested the ability of DFA to discriminate between cross-bedded and ripple-bedded sandstones. Petroleum production in Strauss field is largely restricted to the more permeable cross-bedded sandstones. DFA based on permeability correctly placed 80% of samples into cross-bedded or ripple-bedded groups. Addition of formation factor to the discriminant function increased correct classifications to 83% - a small but statistically significant gain.« less

Discrimination of chicken seasonings and beef seasonings using electronic nose and sensory evaluation.

PubMed

Tian, Huaixiang; Li, Fenghua; Qin, Lan; Yu, Haiyan; Ma, Xia

2014-11-01

This study examines the feasibility of electronic nose as a method to discriminate chicken and beef seasonings and to predict sensory attributes. Sensory evaluation showed that 8 chicken seasonings and 4 beef seasonings could be well discriminated and classified based on 8 sensory attributes. The sensory attributes including chicken/beef, gamey, garlic, spicy, onion, soy sauce, retention, and overall aroma intensity were generated by a trained evaluation panel. Principal component analysis (PCA), discriminant factor analysis (DFA), and cluster analysis (CA) combined with electronic nose were used to discriminate seasoning samples based on the difference of the sensor response signals of chicken and beef seasonings. The correlation between sensory attributes and electronic nose sensors signal was established using partial least squares regression (PLSR) method. The results showed that the seasoning samples were all correctly classified by the electronic nose combined with PCA, DFA, and CA. The electronic nose gave good prediction results for all the sensory attributes with correlation coefficient (r) higher than 0.8. The work indicated that electronic nose is an effective method for discriminating different seasonings and predicting sensory attributes. © 2014 Institute of Food Technologists®

Differentiation of Chinese rice wines from different wineries based on mineral elemental fingerprinting.

PubMed

Shen, Fei; Wu, Jian; Ying, Yibin; Li, Bobin; Jiang, Tao

2013-12-15

Discrimination of Chinese rice wines from three well-known wineries ("Guyuelongshan", "Kuaijishan", and "Pagoda") in China has been carried out according to mineral element contents in this study. Nineteen macro and trace mineral elements (Na, Mg, Al, K, Ca, Mn, Fe, Cu, Zn, V, Cr, Co, Ni, As, Se, Mo, Cd, Ba and Pb) were determined by inductively coupled plasma mass spectrometry (ICP-MS) in 117 samples. Then the experimental data were subjected to analysis of variance (ANOVA) and principal component analysis (PCA) to reveal significant differences and potential patterns between samples. Stepwise linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA) were applied to develop classification models and achieved correct classified rates of 100% and 97.4% for the prediction sample set, respectively. The discrimination could be attributed to different raw materials (mainly water) and elaboration processes employed. The results indicate that the element compositions combined with multivariate analysis can be used as fingerprinting techniques to protect prestigious wineries and enable the authenticity of Chinese rice wine. Copyright © 2013 Elsevier Ltd. All rights reserved.

Mathematical and Statistical Software Index.

DTIC Science & Technology

1986-08-01

geometric) mean HMEAN - harmonic mean MEDIAN - median MODE - mode QUANT - quantiles OGIVE - distribution curve IQRNG - interpercentile range RANGE ... range mutliphase pivoting algorithm cross-classification multiple discriminant analysis cross-tabul ation mul tipl e-objecti ve model curve fitting...Statistics). .. .. .... ...... ..... ...... ..... .. 21 *RANGEX (Correct Correlations for Curtailment of Range ). .. .. .... ...... ... 21 *RUMMAGE II (Analysis

Influence of electrolytes in the QCM response: discrimination and quantification of the interference to correct microgravimetric data.

PubMed

Encarnação, João M; Stallinga, Peter; Ferreira, Guilherme N M

2007-02-15

In this work we demonstrate that the presence of electrolytes in solution generates desorption-like transients when the resonance frequency is measured. Using impedance spectroscopy analysis and Butterworth-Van Dyke (BVD) equivalent electrical circuit modeling we demonstrate that non-Kanazawa responses are obtained in the presence of electrolytes mainly due to the formation of a diffuse electric double layer (DDL) at the sensor surface, which also causes a capacitor like signal. We extend the BVD equivalent circuit by including additional parallel capacitances in order to account for such capacitor like signal. Interfering signals from electrolytes and DDL perturbations were this way discriminated. We further quantified as 8.0+/-0.5 Hz pF-1 the influence of electrolytes to the sensor resonance frequency and we used this factor to correct the data obtained by frequency counting measurements. The applicability of this approach is demonstrated by the detection of oligonucleotide sequences. After applying the corrective factor to the frequency counting data, the mass contribution to the sensor signal yields identical values when estimated by impedance analysis and frequency counting.

Identification of important image features for pork and turkey ham classification using colour and wavelet texture features and genetic selection.

PubMed

Jackman, Patrick; Sun, Da-Wen; Allen, Paul; Valous, Nektarios A; Mendoza, Fernando; Ward, Paddy

2010-04-01

A method to discriminate between various grades of pork and turkey ham was developed using colour and wavelet texture features. Image analysis methods originally developed for predicting the palatability of beef were applied to rapidly identify the ham grade. With high quality digital images of 50-94 slices per ham it was possible to identify the greyscale that best expressed the differences between the various ham grades. The best 10 discriminating image features were then found with a genetic algorithm. Using the best 10 image features, simple linear discriminant analysis models produced 100% correct classifications for both pork and turkey on both calibration and validation sets. 2009 Elsevier Ltd. All rights reserved.

Sexual orientation and boyhood gender conformity: development of the Boyhood Gender Conformity Scale (BGCS)

PubMed

Hockenberry, S L; Billingham, R E

1987-12-01

Two hundred twenty-five [corrected] respondents (109 [corrected] heterosexuals and 116 [corrected] homosexuals) completed a survey containing a 20-item Boyhood Gender Conformity Scale (BGCS). This scale was largely composed of edited and abridged gender items from Part A of Freund et al.'s Feminine Gender Identity Scale (FGIS-A) and Whitam's "childhood indicators." The combined scale was developed in an attempt to obtain a reliable, valid, and potent discriminating instrument for accurately classifying adult male respondents for sexual orientation on the basis of their reported boyhood gender conformity or nonconforming behavior and identity. In addition, 33% of these respondents were administered the original FGIS-A and Whitam inventory during a 2-week test-retest analysis conducted to determine the validity and reliability of the new instrument. All the original items significantly discriminated between heterosexual and homosexual respondents. From these a 13-item function and a 5-item function proved to be the most powerful discriminators between the two groups. Significant correlations between each of the three scales and a very high test-retest correlation coefficient supported the reliability and validity assumption for the BGCS. The conclusion was made that the five-item function (playing with boys, preferring [corrected] boys' games, imagining self as sports figure, reading adventure and sports stories, considered a "sissy") was the most potent and parsimonious discriminator among adult males for sexual orientation. It was similarly noted that the absence of masculine behaviors and traits appeared to be a more powerful predictor of later homosexual orientation than the traditionally feminine or cross-sexed traits and behaviors.

Moving beyond Univariate Post-Hoc Testing in Exercise Science: A Primer on Descriptive Discriminate Analysis

ERIC Educational Resources Information Center

Barton, Mitch; Yeatts, Paul E.; Henson, Robin K.; Martin, Scott B.

2016-01-01

There has been a recent call to improve data reporting in kinesiology journals, including the appropriate use of univariate and multivariate analysis techniques. For example, a multivariate analysis of variance (MANOVA) with univariate post hocs and a Bonferroni correction is frequently used to investigate group differences on multiple dependent…

[Study on the genuineness and producing area of Panax notoginseng based on infrared spectroscopy combined with discriminant analysis].

PubMed

Liu, Fei; Wang, Yuan-zhong; Yang, Chun-yan; Jin, Hang

2015-01-01

The genuineness and producing area of Panax notoginseng were studied based on infrared spectroscopy combined with discriminant analysis. The infrared spectra of 136 taproots of P. notoginseng from 13 planting point in 11 counties were collected and the second derivate spectra were calculated by Omnic 8. 0 software. The infrared spectra and their second derivate spectra in the range 1 800 - 700 cm-1 were used to build model by stepwise discriminant analysis, which was in order to distinguish study on the genuineness of P. notoginseng. The model built based on the second derivate spectra showed the better recognition effect for the genuineness of P. notoginseng. The correct rate of returned classification reached to 100%, and the prediction accuracy was 93. 4%. The stability of model was tested by cross validation and the method was performed extrapolation validation. The second derivate spectra combined with the same discriminant analysis method were used to distinguish the producing area of P. notoginseng. The recognition effect of models built based on different range of spectrum and different numbers of samples were compared and found that when the model was built by collecting 8 samples from each planting point as training sample and the spectrum in the range 1 500 - 1 200 cm-1 , the recognition effect was better, with the correct rate of returned classification reached to 99. 0%, and the prediction accuracy was 76. 5%. The results indicated that infrared spectroscopy combined with discriminant analysis showed good recognition effect for the genuineness of P. notoginseng. The method might be a hopeful new method for identification of genuineness of P. notoginseng in practice. The method could recognize the producing area of P. notoginseng to some extent and could be a new thought for identification of the producing area of P. natoginseng.

Discrimination of Geographical Origin of Asian Garlic Using Isotopic and Chemical Datasets under Stepwise Principal Component Analysis.

PubMed

Liu, Tsang-Sen; Lin, Jhen-Nan; Peng, Tsung-Ren

2018-01-16

Isotopic compositions of δ 2 H, δ 18 O, δ 13 C, and δ 15 N and concentrations of 22 trace elements from garlic samples were analyzed and processed with stepwise principal component analysis (PCA) to discriminate garlic's country of origin among Asian regions including South Korea, Vietnam, Taiwan, and China. Results indicate that there is no single trace-element concentration or isotopic composition that can accomplish the study's purpose and the stepwise PCA approach proposed does allow for discrimination between countries on a regional basis. Sequentially, Step-1 PCA distinguishes garlic's country of origin among Taiwanese, South Korean, and Vietnamese samples; Step-2 PCA discriminates Chinese garlic from South Korean garlic; and Step-3 and Step-4 PCA, Chinese garlic from Vietnamese garlic. In model tests, countries of origin of all audit samples were correctly discriminated by stepwise PCA. Consequently, this study demonstrates that stepwise PCA as applied is a simple and effective approach to discriminating country of origin among Asian garlics. © 2018 American Academy of Forensic Sciences.

Age determination of bottled Chinese rice wine by VIS-NIR spectroscopy

NASA Astrophysics Data System (ADS)

Yu, Haiyan; Lin, Tao; Ying, Yibin; Pan, Xingxiang

2006-10-01

The feasibility of non-invasive visible and near infrared (VIS-NIR) spectroscopy for determining wine age (1, 2, 3, 4, and 5 years) of Chinese rice wine was investigated. Samples of Chinese rice wine were analyzed in 600 mL square brown glass bottles with side length of approximately 64 mm at room temperature. VIS-NIR spectra of 100 bottled Chinese rice wine samples were collected in transmission mode in the wavelength range of 350-1200 nm by a fiber spectrometer system. Discriminant models were developed based on discriminant analysis (DA) together with raw, first and second derivative spectra. The concentration of alcoholic degree, total acid, and °Brix was determined to validate the NIR results. The calibration result for raw spectra was better than that for first and second derivative spectra. The percentage of samples correctly classified for raw spectra was 98%. For 1-, 2-, and 3-year-old sample groups, the sample were all correctly classified, and for 4- and 5-year-old sample groups, the percentage of samples correctly classified was 92.9%, respectively. In validation analysis, the percentage of samples correctly classified was 100%. The results demonstrated that VIS-NIR spectroscopic technique could be used as a non-invasive, rapid and reliable method for predicting wine age of bottled Chinese rice wine.

Discriminant analysis of functional optical topography for schizophrenia diagnosis

NASA Astrophysics Data System (ADS)

Chuang, Ching-Cheng; Nakagome, Kazuyuki; Pu, Shenghong; Lan, Tsuo-Hung; Lee, Chia-Yen; Sun, Chia-Wei

2014-01-01

Abnormal prefrontal function plays a central role in the cognition deficits of schizophrenic patients; however, the character of the relationship between discriminant analysis and prefrontal activation remains undetermined. Recently, evidence of low prefrontal cortex (PFC) activation in individuals with schizophrenia has also been found during verbal fluency tests (VFT) and other cognitive tests with several neuroimaging methods. The purpose of this study is to assess the hemodynamic changes of the PFC and discriminant analysis between schizophrenia patients and healthy controls during VFT task by utilizing functional optical topography. A total of 99 subjects including 53 schizophrenic patients and 46 age- and gender-matched healthy controls were studied. The results showed that the healthy group had larger activation in the right and left PFC than in the middle PFC. Besides, the schizophrenic group showed weaker task performance and lower activation in the whole PFC than the healthy group. The result of the discriminant analysis showed a significant difference with P value <0.001 in six channels (CH 23, 29, 31, 40, 42, 52) between the schizophrenic and healthy groups. Finally, 68.69% and 71.72% of subjects are correctly classified as being schizophrenic or healthy with all 52 channels and six significantly different channels, respectively. Our findings suggest that the left PFC can be a feature region for discriminant analysis of schizophrenic diagnosis.

Personality and affect characteristics of outpatients with depression.

PubMed

Petrocelli, J V; Glaser, B A; Calhoun, G B; Campbell, L F

2001-08-01

This investigation was designed to examine the relationship between depression severity and personality disorders measured by the Millon Clinical Multiaxial Inventory-II (Millon, 1987) and affectivity measured by the Positive Affectivity/Negative Affectivity Schedule (Watson, Clark, & Tellegen, 1988). Discriminant analyses were employed to identify the personality and affective dimensions that maximally discriminate between 4 different levels of depressive severity. Differences between the 4 levels of depressive severity are suggestive of unique patterns of personality characteristics. Discriminant analysis showed that 74.8% of the cases were correctly classified by a single linear discriminant function, and that 61% of the variance in depression severity was accounted for by selected personality and affect variables. Results extend current conceptualizations of comorbidity and are discussed with respect to depression severity.

Classification of collected trot, passage and piaffe based on temporal variables.

PubMed

Clayton, H M

1997-05-01

The objective was to determine whether collected trot, passage and piaffe could be distinguished as separate gaits on the basis of temporal variables. Sagittal plane, 60 Hz videotapes of 10 finalists in the dressage competitions at the 1992 Olympic Games were analysed to measure the temporal variables in absolute terms and as percentages of stride duration. Classification was based on analysis of variance, a graphical method and discriminant analysis. Stride duration was sufficient to distinguish collected trot from passage and piaffe in all horses. The analysis of variance showed that the mean values of most variables differed significantly between passage and piaffe. When hindlimb stance percentage was plotted against diagonal advanced placement percentage, some overlap was found between all 3 movements indicating that individual horses could not be classified reliably in this manner. Using hindlimb stance percentage and diagonal advanced placement percentage as input in a discriminant analysis, 80% of the cases were classified correctly, but at least one horse was misclassified in each movement. When the absolute, rather than percentage, values of the 2 variables were used as input in the discriminant analysis, 90% of the cases were correctly classified and the only misclassifications were between passage and piaffe. However, the 2 horses in which piaffe was misclassified as passage were the gold and silver medallists. In general, higher placed horses tended toward longer diagonal advanced placements, especially in collected trot and passage, and shorter hindlimb stance percentages in passage and piaffe.

Authentication of animal origin of heparin and low molecular weight heparin including ovine, porcine and bovine species using 1D NMR spectroscopy and chemometric tools.

PubMed

Monakhova, Yulia B; Diehl, Bernd W K; Fareed, Jawed

2018-02-05

High resolution (600MHz) nuclear magnetic resonance (NMR) spectroscopy is used to distinguish heparin and low-molecular weight heparins (LMWHs) produced from porcine, bovine and ovine mucosal tissues as well as their blends. For multivariate analysis several statistical methods such as principal component analysis (PCA), factor discriminant analysis (FDA), partial least squares - discriminant analysis (PLS-DA), linear discriminant analysis (LDA) were utilized for the modeling of NMR data of more than 100 authentic samples. Heparin and LMWH samples from the independent test set (n=15) were 100% correctly classified according to its animal origin. Moreover, by using 1 H NMR coupled with chemometrics and several batches of bovine heparins from two producers were differentiated. Thus, NMR spectroscopy combined with chemometrics is an efficient tool for simultaneous identification of animal origin and process based manufacturing difference in heparin products. Copyright © 2017 Elsevier B.V. All rights reserved.

FT-IR spectroscopy and multivariate analysis as an auxiliary tool for diagnosis of mental disorders: Bipolar and schizophrenia cases

NASA Astrophysics Data System (ADS)

Ogruc Ildiz, G.; Arslan, M.; Unsalan, O.; Araujo-Andrade, C.; Kurt, E.; Karatepe, H. T.; Yilmaz, A.; Yalcinkaya, O. B.; Herken, H.

2016-01-01

In this study, a methodology based on Fourier-transform infrared spectroscopy and principal component analysis and partial least square methods is proposed for the analysis of blood plasma samples in order to identify spectral changes correlated with some biomarkers associated with schizophrenia and bipolarity. Our main goal was to use the spectral information for the calibration of statistical models to discriminate and classify blood plasma samples belonging to bipolar and schizophrenic patients. IR spectra of 30 samples of blood plasma obtained from each, bipolar and schizophrenic patients and healthy control group were collected. The results obtained from principal component analysis (PCA) show a clear discrimination between the bipolar (BP), schizophrenic (SZ) and control group' (CG) blood samples that also give possibility to identify three main regions that show the major differences correlated with both mental disorders (biomarkers). Furthermore, a model for the classification of the blood samples was calibrated using partial least square discriminant analysis (PLS-DA), allowing the correct classification of BP, SZ and CG samples. The results obtained applying this methodology suggest that it can be used as a complimentary diagnostic tool for the detection and discrimination of these mental diseases.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

PubMed

De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie

2015-09-01

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise. Copyright © 2015 Elsevier Inc. All rights reserved.

Discriminative factor analysis of juvenile delinquency in South Korea.

PubMed

Kim, Hyun Sil; Kim, Hun Soo

2006-12-01

The present study was intended to compare difference in research variables between delinquent adolescents and student adolescents, and to analyze discriminative factors of delinquent behaviors among Korean adolescents. The research design of this study was a questionnaire survey. Questionnaires were administered to 2,167 adolescents (1,196 students and 971 delinquents), sampled from 8 middle and high school and 6 juvenile corrective institutions, using the proportional stratified random sampling method. Statistical methods employed were Chi-square, t-test, and logistic regression analysis. The discriminative factors of delinquent behaviors were smoking, alcohol use, other drug use, being sexually abused, viewing time of media violence and pornography. Among these discriminative factors, the factor most strongly associated with delinquency was smoking (odds ratio: 32.32). That is, smoking adolescent has a 32-fold higher possibility of becoming a delinquent adolescent than a non-smoking adolescent. Our findings, that smoking was the strongest discriminative factor of delinquent behavior, suggest that educational strategies to prevent adolescent smoking may reduce the rate of juvenile delinquency. Antismoking educational efforts are therefore urgently needed in South Korea.

Screening analysis of biodiesel feedstock using UV-vis, NIR and synchronous fluorescence spectrometries and the successive projections algorithm.

PubMed

Insausti, Matías; Gomes, Adriano A; Cruz, Fernanda V; Pistonesi, Marcelo F; Araujo, Mario C U; Galvão, Roberto K H; Pereira, Claudete F; Band, Beatriz S F

2012-08-15

This paper investigates the use of UV-vis, near infrared (NIR) and synchronous fluorescence (SF) spectrometries coupled with multivariate classification methods to discriminate biodiesel samples with respect to the base oil employed in their production. More specifically, the present work extends previous studies by investigating the discrimination of corn-based biodiesel from two other biodiesel types (sunflower and soybean). Two classification methods are compared, namely full-spectrum SIMCA (soft independent modelling of class analogies) and SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm). Regardless of the spectrometric technique employed, full-spectrum SIMCA did not provide an appropriate discrimination of the three biodiesel types. In contrast, all samples were correctly classified on the basis of a reduced number of wavelengths selected by SPA-LDA. It can be concluded that UV-vis, NIR and SF spectrometries can be successfully employed to discriminate corn-based biodiesel from the two other biodiesel types, but wavelength selection by SPA-LDA is key to the proper separation of the classes. Copyright © 2012 Elsevier B.V. All rights reserved.

The distinct emotional flavor of Gnostic writings from the early Christian era.

PubMed

Whissell, Cynthia

2008-02-01

More than 500,000 scored words in 83 documents were used to conclude that it is possible to identify the source of documents (proto-orthodox Christian versus early Gnostic) on the basis of the emotions underlying the words. Twenty-seven New Testament works and seven Gnostic documents (including the gospels of Thomas, Judas, and Mary [Magdalene]) were scored with the Dictionary of Affect in Language. Patterns of emotional word use focusing on eight types of extreme emotional words were employed in a discriminant function analysis to predict source. Prediction was highly successful (canonical r = .81, 97% correct identification of source). When the discriminant function was tested with more than 30 additional Gnostic and Christian works including a variety of translations and some wisdom books, it correctly classified all of them. The majority of the predictive power of the function (97% of all correct categorizations, 70% of the canonical r2) was associated with the preferential presence of passive and passive/pleasant words in Gnostic documents.

Detection of non-milk fat in milk fat by gas chromatography and linear discriminant analysis.

PubMed

Gutiérrez, R; Vega, S; Díaz, G; Sánchez, J; Coronado, M; Ramírez, A; Pérez, J; González, M; Schettino, B

2009-05-01

Gas chromatography was utilized to determine triacylglycerol profiles in milk and non-milk fat. The values of triacylglycerol were subjected to linear discriminant analysis to detect and quantify non-milk fat in milk fat. Two groups of milk fat were analyzed: A) raw milk fat from the central region of Mexico (n = 216) and B) ultrapasteurized milk fat from 3 industries (n = 36), as well as pork lard (n = 2), bovine tallow (n = 2), fish oil (n = 2), peanut (n = 2), corn (n = 2), olive (n = 2), and soy (n = 2). The samples of raw milk fat were adulterated with non-milk fats in proportions of 0, 5, 10, 15, and 20% to form 5 groups. The first function obtained from the linear discriminant analysis allowed the correct classification of 94.4% of the samples with levels <10% of adulteration. The triacylglycerol values of the ultrapasteurized milk fats were evaluated with the discriminant function, demonstrating that one industry added non-milk fat to its product in 80% of the samples analyzed.

(13)C NMR pattern recognition techniques for the classification of Atlantic salmon (Salmo salar L.) according to their wild, farmed, and geographical origin.

PubMed

Aursand, Marit; Standal, Inger B; Praël, Angelika; McEvoy, Lesley; Irvine, Joe; Axelson, David E

2009-05-13

(13)C nuclear magnetic resonance (NMR) in combination with multivariate data analysis was used to (1) discriminate between farmed and wild Atlantic salmon ( Salmo salar L.), (2) discriminate between different geographical origins, and (3) verify the origin of market samples. Muscle lipids from 195 Atlantic salmon of known origin (wild and farmed salmon from Norway, Scotland, Canada, Iceland, Ireland, the Faroes, and Tasmania) in addition to market samples were analyzed by (13)C NMR spectroscopy and multivariate analysis. Both probabilistic neural networks (PNN) and support vector machines (SVM) provided excellent discrimination (98.5 and 100.0%, respectively) between wild and farmed salmon. Discrimination with respect to geographical origin was somewhat more difficult, with correct classification rates ranging from 82.2 to 99.3% by PNN and SVM, respectively. In the analysis of market samples, five fish labeled and purchased as wild salmon were classified as farmed salmon (indicating mislabeling), and there were also some discrepancies between the classification and the product declaration with regard to geographical origin.

Discrimination of Clover and Citrus Honeys from Egypt According to Floral Type Using Easily Assessable Physicochemical Parameters and Discriminant Analysis: An External Validation of the Chemometric Approach.

PubMed

Karabagias, Ioannis K; Karabournioti, Sofia

2018-05-03

Twenty-two honey samples, namely clover and citrus honeys, were collected from the greater Cairo area during the harvesting year 2014⁻2015. The main purpose of the present study was to characterize the aforementioned honey types and to investigate whether the use of easily assessable physicochemical parameters, including color attributes in combination with chemometrics, could differentiate honey floral origin. Parameters taken into account were: pH, electrical conductivity, ash, free acidity, lactonic acidity, total acidity, moisture content, total sugars (degrees Brix-°Bx), total dissolved solids and their ratio to total acidity, salinity, CIELAB color parameters, along with browning index values. Results showed that all honey samples analyzed met the European quality standards set for honey and had variations in the aforementioned physicochemical parameters depending on floral origin. Application of linear discriminant analysis showed that eight physicochemical parameters, including color, could classify Egyptian honeys according to floral origin ( p < 0.05). Correct classification rate was 95.5% using the original method and 90.9% using the cross validation method. The discriminatory ability of the developed model was further validated using unknown honey samples. The overall correct classification rate was not affected. Specific physicochemical parameter analysis in combination with chemometrics has the potential to enhance the differences in floral honeys produced in a given geographical zone.

Discrimination of Clover and Citrus Honeys from Egypt According to Floral Type Using Easily Assessable Physicochemical Parameters and Discriminant Analysis: An External Validation of the Chemometric Approach

PubMed Central

Karabournioti, Sofia

2018-01-01

Twenty-two honey samples, namely clover and citrus honeys, were collected from the greater Cairo area during the harvesting year 2014–2015. The main purpose of the present study was to characterize the aforementioned honey types and to investigate whether the use of easily assessable physicochemical parameters, including color attributes in combination with chemometrics, could differentiate honey floral origin. Parameters taken into account were: pH, electrical conductivity, ash, free acidity, lactonic acidity, total acidity, moisture content, total sugars (degrees Brix-°Bx), total dissolved solids and their ratio to total acidity, salinity, CIELAB color parameters, along with browning index values. Results showed that all honey samples analyzed met the European quality standards set for honey and had variations in the aforementioned physicochemical parameters depending on floral origin. Application of linear discriminant analysis showed that eight physicochemical parameters, including color, could classify Egyptian honeys according to floral origin (p < 0.05). Correct classification rate was 95.5% using the original method and 90.9% using the cross validation method. The discriminatory ability of the developed model was further validated using unknown honey samples. The overall correct classification rate was not affected. Specific physicochemical parameter analysis in combination with chemometrics has the potential to enhance the differences in floral honeys produced in a given geographical zone. PMID:29751543

Influence of handling-relevant factors on the behaviour of a novel calculus-detection device.

PubMed

Meissner, Grit; Oehme, Bernd; Strackeljan, Jens; Kocher, Thomas

2005-03-01

The aim of periodontal therapy is always the complete debridement of root surfaces with the removal of calculus and without damaging cementum. We have recently demonstrated the feasibility of a surface recognition device that discriminates dental surfaces by mathematical analysis of reflected ultrasound waves. This principle should enable the construction of calculus detecting ultrasonic device. Pre-clinical test results are presented here. An impulse generator, coupled to a conventional piezo-driven ultrasonic scaler, sends signals to the cementum via the tip of an ultrasound device. The oscillation signal reflected from the surface contains the information necessary to analyse its characteristics. In order to discriminate different surfaces, learning sets were generated from 70 extracted teeth using standardized tip angle/lateral force combinations. The complete device was then used to classify root surfaces unknown to the system. About 80% of enamel and cementum was correctly identified in vivo (sensitivity: 75%, specificity: 82%). The surface discrimination method was not influenced by the application conditions examined. A new set of 200 tests on 10 teeth was correctly recognized in 82% of the cases (sensitivity: 87%, specificity: 76%). It was shown in vitro that the tooth surface recognition system is able to function correctly, independent of the lateral forces and the tip angle of the instrument. Copyright 2005 Blackwell Munksgaard.

Root Cause Analysis of Quality Defects Using HPLC-MS Fingerprint Knowledgebase for Batch-to-batch Quality Control of Herbal Drugs.

PubMed

Yan, Binjun; Fang, Zhonghua; Shen, Lijuan; Qu, Haibin

2015-01-01

The batch-to-batch quality consistency of herbal drugs has always been an important issue. To propose a methodology for batch-to-batch quality control based on HPLC-MS fingerprints and process knowledgebase. The extraction process of Compound E-jiao Oral Liquid was taken as a case study. After establishing the HPLC-MS fingerprint analysis method, the fingerprints of the extract solutions produced under normal and abnormal operation conditions were obtained. Multivariate statistical models were built for fault detection and a discriminant analysis model was built using the probabilistic discriminant partial-least-squares method for fault diagnosis. Based on multivariate statistical analysis, process knowledge was acquired and the cause-effect relationship between process deviations and quality defects was revealed. The quality defects were detected successfully by multivariate statistical control charts and the type of process deviations were diagnosed correctly by discriminant analysis. This work has demonstrated the benefits of combining HPLC-MS fingerprints, process knowledge and multivariate analysis for the quality control of herbal drugs. Copyright © 2015 John Wiley & Sons, Ltd.

Evaluation of repetitive extragenic palindromic-PCR for discrimination of fecal Escherichia coli from humans, and different domestic- and wild-animals.

PubMed

Mohapatra, Bidyut R; Broersma, Klaas; Nordin, Rick; Mazumder, Asit

2007-01-01

The objective of this study was to investigate the potential of repetitive extragenic palindromic anchored polymerase chain reaction (rep-PCR) in differentiating fecal Escherichia coli isolates of human, domestic- and wild-animal origin that might be used as a molecular tool to identify the possible source(s) of fecal pollution of source water. A total of 625 fecal E. coli isolates of human, 3 domestic- (cow, dog and horse) and 7 wild-animal (black bear, coyote, elk, marmot, mule deer, raccoon and wolf) species were characterized by rep-PCR DNA fingerprinting technique coupled with BOX A1R primer and discriminant analysis. Discriminant analysis of rep-PCR DNA fingerprints of fecal E. coli isolates from 11 host sources revealed an average rate of correct classification of 79.89%, and 84.6%, 83.8%, 83.3%, 82.5%, 81.6%, 80.8%, 79.8%, 79.3%, 77.4%, 73.2% and 63.6% of elk, human, marmot, mule deer, cow, coyote, raccoon, horse, dog, wolf and black bear fecal E. coli isolates were assigned to the correct host source. These results suggest that rep-PCR DNA fingerprinting procedures can be used as a source tracking tool for detection of human- as well as animal-derived fecal contamination of water.

Pattern recognition and genetic algorithms for discrimination of orange juices and reduction of significant components from headspace solid-phase microextraction.

PubMed

Rinaldi, Maurizio; Gindro, Roberto; Barbeni, Massimo; Allegrone, Gianna

2009-01-01

Orange (Citrus sinensis L.) juice comprises a complex mixture of volatile components that are difficult to identify and quantify. Classification and discrimination of the varieties on the basis of the volatile composition could help to guarantee the quality of a juice and to detect possible adulteration of the product. To provide information on the amounts of volatile constituents in fresh-squeezed juices from four orange cultivars and to establish suitable discrimination rules to differentiate orange juices using new chemometric approaches. Fresh juices of four orange cultivars were analysed by headspace solid-phase microextraction (HS-SPME) coupled with GC-MS. Principal component analysis, linear discriminant analysis and heuristic methods, such as neural networks, allowed clustering of the data from HS-SPME analysis while genetic algorithms addressed the problem of data reduction. To check the quality of the results the chemometric techniques were also evaluated on a sample. Thirty volatile compounds were identified by HS-SPME and GC-MS analyses and their relative amounts calculated. Differences in composition of orange juice volatile components were observed. The chosen orange cultivars could be discriminated using neural networks, genetic relocation algorithms and linear discriminant analysis. Genetic algorithms applied to the data were also able to detect the most significant compounds. SPME is a useful technique to investigate orange juice volatile composition and a flexible chemometric approach is able to correctly separate the juices.

An electronic nose for reliable measurement and correct classification of beverages.

PubMed

Mamat, Mazlina; Samad, Salina Abdul; Hannan, Mahammad A

2011-01-01

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results.

An Electronic Nose for Reliable Measurement and Correct Classification of Beverages

PubMed Central

Mamat, Mazlina; Samad, Salina Abdul; Hannan, Mahammad A.

2011-01-01

This paper reports the design of an electronic nose (E-nose) prototype for reliable measurement and correct classification of beverages. The prototype was developed and fabricated in the laboratory using commercially available metal oxide gas sensors and a temperature sensor. The repeatability, reproducibility and discriminative ability of the developed E-nose prototype were tested on odors emanating from different beverages such as blackcurrant juice, mango juice and orange juice, respectively. Repeated measurements of three beverages showed very high correlation (r > 0.97) between the same beverages to verify the repeatability. The prototype also produced highly correlated patterns (r > 0.97) in the measurement of beverages using different sensor batches to verify its reproducibility. The E-nose prototype also possessed good discriminative ability whereby it was able to produce different patterns for different beverages, different milk heat treatments (ultra high temperature, pasteurization) and fresh and spoiled milks. The discriminative ability of the E-nose was evaluated using Principal Component Analysis and a Multi Layer Perception Neural Network, with both methods showing good classification results. PMID:22163964

Usefulness of 3-dimensional stereotactic surface projection FDG PET images for the diagnosis of dementia

PubMed Central

Kim, Jahae; Cho, Sang-Geon; Song, Minchul; Kang, Sae-Ryung; Kwon, Seong Young; Choi, Kang-Ho; Choi, Seong-Min; Kim, Byeong-Chae; Song, Ho-Chun

2016-01-01

Abstract To compare diagnostic performance and confidence of a standard visual reading and combined 3-dimensional stereotactic surface projection (3D-SSP) results to discriminate between Alzheimer disease (AD)/mild cognitive impairment (MCI), dementia with Lewy bodies (DLB), and frontotemporal dementia (FTD). [18F]fluorodeoxyglucose (FDG) PET brain images were obtained from 120 patients (64 AD/MCI, 38 DLB, and 18 FTD) who were clinically confirmed over 2 years follow-up. Three nuclear medicine physicians performed the diagnosis and rated diagnostic confidence twice; once by standard visual methods, and once by adding of 3D-SSP. Diagnostic performance and confidence were compared between the 2 methods. 3D-SSP showed higher sensitivity, specificity, accuracy, positive, and negative predictive values to discriminate different types of dementia compared with the visual method alone, except for AD/MCI specificity and FTD sensitivity. Correction of misdiagnosis after adding 3D-SSP images was greatest for AD/MCI (56%), followed by DLB (13%) and FTD (11%). Diagnostic confidence also increased in DLB (visual: 3.2; 3D-SSP: 4.1; P < 0.001), followed by AD/MCI (visual: 3.1; 3D-SSP: 3.8; P = 0.002) and FTD (visual: 3.5; 3D-SSP: 4.2; P = 0.022). Overall, 154/360 (43%) cases had a corrected misdiagnosis or improved diagnostic confidence for the correct diagnosis. The addition of 3D-SSP images to visual analysis helped to discriminate different types of dementia in FDG PET scans, by correcting misdiagnoses and enhancing diagnostic confidence in the correct diagnosis. Improvement of diagnostic accuracy and confidence by 3D-SSP images might help to determine the cause of dementia and appropriate treatment. PMID:27930593

Eyewitness identification across the life span: A meta-analysis of age differences.

PubMed

Fitzgerald, Ryan J; Price, Heather L

2015-11-01

Lineup identifications are often a critical component of criminal investigations. Over the past 35 years, researchers have been conducting empirical studies to assess the impact of witness age on identification accuracy. A previous meta-analysis indicated that children are less likely than adults to correctly reject a lineup that does not contain the culprit, but children 5 years and older are as likely as adults to make a correct identification if the culprit is in the lineup (Pozzulo & Lindsay, 1998). We report an updated meta-analysis of age differences in eyewitness identification, summarizing data from 20,244 participants across 91 studies. Contrary to extant reviews, we adopt a life span approach and examine witnesses from early childhood to late adulthood. Children's increased tendency to erroneously select a culprit-absent lineup member was replicated. Children were also less likely than young adults to correctly identify the culprit. Group data from culprit-absent and culprit-present lineups were used to produce signal detection measures, which indicated young adults were better able than children to discriminate between guilty and innocent suspects. A strikingly similar pattern emerged for older adults, who had even stronger deficits in discriminability than children, relative to adults. Although identifications by young adults were the most reliable, identifications by all witnesses had probative value. (c) 2015 APA, all rights reserved).

Discriminative analysis of early Alzheimer's disease based on two intrinsically anti-correlated networks with resting-state fMRI.

PubMed

Wang, Kun; Jiang, Tianzi; Liang, Meng; Wang, Liang; Tian, Lixia; Zhang, Xinqing; Li, Kuncheng; Liu, Zhening

2006-01-01

In this work, we proposed a discriminative model of Alzheimer's disease (AD) on the basis of multivariate pattern classification and functional magnetic resonance imaging (fMRI). This model used the correlation/anti-correlation coefficients of two intrinsically anti-correlated networks in resting brains, which have been suggested by two recent studies, as the feature of classification. Pseudo-Fisher Linear Discriminative Analysis (pFLDA) was then performed on the feature space and a linear classifier was generated. Using leave-one-out (LOO) cross validation, our results showed a correct classification rate of 83%. We also compared the proposed model with another one based on the whole brain functional connectivity. Our proposed model outperformed the other one significantly, and this implied that the two intrinsically anti-correlated networks may be a more susceptible part of the whole brain network in the early stage of AD.

Tracing the Geographical Origin of Onions by Strontium Isotope Ratio and Strontium Content.

PubMed

Hiraoka, Hisaaki; Morita, Sakie; Izawa, Atsunobu; Aoyama, Keisuke; Shin, Ki-Cheol; Nakano, Takanori

2016-01-01

The strontium (Sr) isotope ratio ((87)Sr/(86)Sr) and Sr content were used to trace the geographical origin of onions from Japan and other countries, including China, the United States of America, New Zealand, Australia, and Thailand. The mean (87)Sr/(86)Sr ratio and Sr content (dry weight basis) for onions from Japan were 0.70751 and 4.6 mg kg(-1), respectively, and the values for onions from the other countries were 0.71199 and 12.4 mg kg(-1), respectively. Linear discriminant analysis was performed to classify onions produced in Japan from those produced in the other countries based on the Sr data. The discriminant equation derived from linear discriminant analysis was evaluated by 10-fold cross validation. As a result, the origins of 92% of onions were correctly classified between Japan and the other countries.

Trace element analysis of rough diamond by LA-ICP-MS: a case of source discrimination?

PubMed

Dalpé, Claude; Hudon, Pierre; Ballantyne, David J; Williams, Darrell; Marcotte, Denis

2010-11-01

Current profiling of rough diamond source is performed using different physical and/or morphological techniques that require strong knowledge and experience in the field. More recently, chemical impurities have been used to discriminate diamond source and with the advance of laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) empirical profiling of rough diamonds is possible to some extent. In this study, we present a LA-ICP-MS methodology that we developed for analyzing ultra-trace element impurities in rough diamond for origin determination ("profiling"). Diamonds from two sources were analyzed by LA-ICP-MS and were statistically classified by accepted methods. For the two diamond populations analyzed in this study, binomial logistic regression produced a better overall correct classification than linear discriminant analysis. The results suggest that an anticipated matrix match reference material would improve the robustness of our methodology for forensic applications. © 2010 American Academy of Forensic Sciences.

Differentiating clinical groups using the serial color-word test (S-CWT).

PubMed

Hentschel, Uwe; Rubino, I Alex; Bijleveld, Catrien

2011-04-01

The present study attempted to differentiate 11 diagnostic groups by means of the Serial Color-Word Test (S-CWT), using multivariate discriminant analysis. Two alternative scoring systems of the S-CWT were outlined. Asample of 514 individuals who had clinical diagnoses of various types and 397 controls who had no diagnostic findings comprised the sample. The first discriminant analysis failed to differentiate the groups adequately. The groups were consequently reduced to four (schizophrenia, bipolar disorders, temporo-mandibular joint pain dysfunction syndrome, and eating disturbances), which gave better reclassification findings for a clinical application of the test. This classification gave over 55% correct assignments. The final four groups had a statistically significant discrimination on the test, which remained stable also in a bootstrap procedure. Implications for treatment indications and outcomes as well as strategies for further studies using the S-CWT are discussed.

Rapid characterization of transgenic and non-transgenic soybean oils by chemometric methods using NIR spectroscopy

NASA Astrophysics Data System (ADS)

Luna, Aderval S.; da Silva, Arnaldo P.; Pinho, Jéssica S. A.; Ferré, Joan; Boqué, Ricard

Near infrared (NIR) spectroscopy and multivariate classification were applied to discriminate soybean oil samples into non-transgenic and transgenic. Principal Component Analysis (PCA) was applied to extract relevant features from the spectral data and to remove the anomalous samples. The best results were obtained when with Support Vectors Machine-Discriminant Analysis (SVM-DA) and Partial Least Squares-Discriminant Analysis (PLS-DA) after mean centering plus multiplicative scatter correction. For SVM-DA the percentage of successful classification was 100% for the training group and 100% and 90% in validation group for non transgenic and transgenic soybean oil samples respectively. For PLS-DA the percentage of successful classification was 95% and 100% in training group for non transgenic and transgenic soybean oil samples respectively and 100% and 80% in validation group for non transgenic and transgenic respectively. The results demonstrate that NIR spectroscopy can provide a rapid, nondestructive and reliable method to distinguish non-transgenic and transgenic soybean oils.

Determination of Chinese rice wine from different wineries by near-infrared spectroscopy combined with chemometrics methods

NASA Astrophysics Data System (ADS)

Niu, Xiaoying; Ying, Yibin; Yu, Haiyan; Xie, Lijuan; Fu, Xiaping; Zhou, Ying; Jiang, Xuesong

2007-09-01

In this paper, 104 samples of Chinese rice wines of the same variety (Shaoxing rice wine), collected in three winery ("guyuelongshan", "pagoda" brand, "kuaijishan"), three brewed years (2002, 2004, 2004-2006) were analyzed by near-infrared transmission spectroscopy between 800 and 2500 nm. The spectral differences were studied by principal components analysis (PCA), and Classifications, according the brand, were carried out by discriminant analysis (DA) and partial least squares discriminant analysis (PLSDA). The DA model gained a total accuracy of 94.23% and when used to predict the brand of the validation set samples, a better result, correctly classified all of the three kinds of Chinese rice wine up to 100%, are obtained by PLSDA model. The work reported here is a feasibility study and requires further development with considerable samples of more different brands. Further studies are needed in order to improve the accuracy and robustness, and to extend the discrimination to other Chinese rice wine varieties or brands.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features.

PubMed

McDonald, Linda S; Panozzo, Joseph F; Salisbury, Phillip A; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective.

Discriminant Analysis of Defective and Non-Defective Field Pea (Pisum sativum L.) into Broad Market Grades Based on Digital Image Features

PubMed Central

McDonald, Linda S.; Panozzo, Joseph F.; Salisbury, Phillip A.; Ford, Rebecca

2016-01-01

Field peas (Pisum sativum L.) are generally traded based on seed appearance, which subjectively defines broad market-grades. In this study, we developed an objective Linear Discriminant Analysis (LDA) model to classify market grades of field peas based on seed colour, shape and size traits extracted from digital images. Seeds were imaged in a high-throughput system consisting of a camera and laser positioned over a conveyor belt. Six colour intensity digital images were captured (under 405, 470, 530, 590, 660 and 850nm light) for each seed, and surface height was measured at each pixel by laser. Colour, shape and size traits were compiled across all seed in each sample to determine the median trait values. Defective and non-defective seed samples were used to calibrate and validate the model. Colour components were sufficient to correctly classify all non-defective seed samples into correct market grades. Defective samples required a combination of colour, shape and size traits to achieve 87% and 77% accuracy in market grade classification of calibration and validation sample-sets respectively. Following these results, we used the same colour, shape and size traits to develop an LDA model which correctly classified over 97% of all validation samples as defective or non-defective. PMID:27176469

Fuzzy cluster analysis of simple physicochemical properties of amino acids for recognizing secondary structure in proteins.

PubMed Central

Mocz, G.

1995-01-01

Fuzzy cluster analysis has been applied to the 20 amino acids by using 65 physicochemical properties as a basis for classification. The clustering products, the fuzzy sets (i.e., classical sets with associated membership functions), have provided a new measure of amino acid similarities for use in protein folding studies. This work demonstrates that fuzzy sets of simple molecular attributes, when assigned to amino acid residues in a protein's sequence, can predict the secondary structure of the sequence with reasonable accuracy. An approach is presented for discriminating standard folding states, using near-optimum information splitting in half-overlapping segments of the sequence of assigned membership functions. The method is applied to a nonredundant set of 252 proteins and yields approximately 73% matching for correctly predicted and correctly rejected residues with approximately 60% overall success rate for the correctly recognized ones in three folding states: alpha-helix, beta-strand, and coil. The most useful attributes for discriminating these states appear to be related to size, polarity, and thermodynamic factors. Van der Waals volume, apparent average thickness of surrounding molecular free volume, and a measure of dimensionless surface electron density can explain approximately 95% of prediction results. hydrogen bonding and hydrophobicity induces do not yet enable clear clustering and prediction. PMID:7549882

High wavenumber Raman spectroscopy in the characterization of urinary metabolites of normal subjects, oral premalignant and malignant patients

NASA Astrophysics Data System (ADS)

Brindha, Elumalai; Rajasekaran, Ramu; Aruna, Prakasarao; Koteeswaran, Dornadula; Ganesan, Singaravelu

2017-01-01

Urine has emerged as one of the diagnostically potential bio fluids, as it has many metabolites. As the concentration and the physiochemical properties of the urinary metabolites may vary under pathological transformation, Raman spectroscopic characterization of urine has been exploited as a significant tool in identifying several diseased conditions, including cancers. In the present study, an attempt was made to study the high wavenumber (HWVN) Raman spectroscopic characterization of urine samples of normal subjects, oral premalignant and malignant patients. It is concluded that the urinary metabolites flavoproteins, tryptophan and phenylalanine are responsible for the observed spectral variations between the normal and abnormal groups. Principal component analysis-based linear discriminant analysis was carried out to verify the diagnostic potentiality of the present technique. The discriminant analysis performed across normal and oral premalignant subjects classifies 95.6% of the original and 94.9% of the cross-validated grouped cases correctly. In the second analysis performed across normal and oral malignant groups, the accuracy of the original and cross-validated grouped cases was 96.4% and 92.1% respectively. Similarly, the third analysis performed across three groups, normal, oral premalignant and malignant groups, classifies 93.3% and 91.2% of the original and cross-validated grouped cases correctly.

Spring distributions and relationships with land cover and hydrogeologic strata in a karst landscape in Winona County, Minnesota, USA

USGS Publications Warehouse

Williams, M.A.; Vondracek, B.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota USA, a karst landscape. Nearestneighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology. ?? 2010 Springer-Verlag.

Spring distribution in Winona County, Minnesota, USA and the relationship with geologic strata in a karst landscape

USGS Publications Warehouse

Vondracek, Bruce C.; Williams, Mary A.

2010-01-01

Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota, USA, a karst landscape. Nearest-neighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology.

Comparative analysis of the volatile composition of honeys from Brazilian stingless bees by static headspace GC-MS.

PubMed

de Lima Morais da Silva, Patricia; de Lima, Liliane Schier; Caetano, Ísis Kaminski; Torres, Yohandra Reyes

2017-12-01

The volatile composition of honeys produced by eight species of stingless bees collected in three municipalities in the state of Paraná (Brazil) was compared by combining static headspace GC-MS and chemometrics methods. Forty-four compounds were identified using NIST library and linear retention index relative to n-alkanes (C 8 -C 40 ). Linalool derivatives were the most abundant peaks in most honeys regardless geographical or entomological origin. However, Principal Component Analysis discriminated honeys from different geographical origins considering their distinctive minor volatile components. Honey samples from Guaraqueçaba were characterized by the presence of hotrienol while those from Cambará showed epoxylinalol, benzaldehyde and TDN as minor discriminating compounds. Punctual species such as Borá showed similar fingerprints regardless geographical origin, with ethyl octanoate and ethyl decanoate as characteristic intense chromatographic peaks, which may suggest a specialized behavior for nectar collection. Discriminant Analysis allowed correct geographic discrimination of most honeys produced in the three spots tested. We concluded that volatile profile of stingless bee honeys can be used to attest authenticity related to regional origin of honeys. Copyright © 2017. Published by Elsevier Ltd.

Secrets in the eyes of Black Oystercatchers: A new sexing technique

USGS Publications Warehouse

Guzzetti, B.M.; Talbot, S.L.; Tessler, D.F.; Gill, V.A.; Murphy, E.C.

2008-01-01

Sexing oystercatchers in the field is difficult because males and females have identical plumage and are similar in size. Although Black Oystercatchers (Haematopus bachmani) are sexually dimorphic, using morphology to determine sex requires either capturing both pair members for comparison or using discriminant analyses to assign sex probabilistically based on morphometric traits. All adult Black Oystercatchers have bright yellow eyes, but some of them have dark specks, or eye flecks, in their irides. We hypothesized that this easily observable trait was sex-linked and could be used as a novel diagnostic tool for identifying sex. To test this, we compared data for oystercatchers from genetic molecular markers (CHD-W/CHD-Z and HINT-W/HINT-Z), morphometric analyses, and eye-fleck category (full eye flecks, slight eye flecks, and no eye flecks). Compared to molecular markers, we found that discriminant analyses based on morphological characteristics yielded variable results that were confounded by geographical differences in morphology. However, we found that eye flecks were sex-linked. Using an eye-fleck model where all females have full eye flecks and males have either slight eye flecks or no eye flecks, we correctly assigned the sex of 117 of 125 (94%) oystercatchers. Using discriminant analysis based on morphological characteristics, we correctly assigned the sex of 105 of 119 (88%) birds. Using the eye-fleck technique for sexing Black Oystercatchers may be preferable for some investigators because it is as accurate as discriminant analysis based on morphology and does not require capturing the birds. ??2008 Association of Field Ornithologists.

Application of Near Infrared Reflectance Spectroscopy for Rapid and Non-Destructive Discrimination of Hulled Barley, Naked Barley, and Wheat Contaminated with Fusarium

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Kim, Geonseob; Ham, Hyeonheui; Kim, Seongmin; Kim, Moon S.

2018-01-01

Fusarium is a common fungal disease in grains that reduces the yield of barley and wheat. In this study, a near infrared reflectance spectroscopic technique was used with a statistical prediction model to rapidly and non-destructively discriminate grain samples contaminated with Fusarium. Reflectance spectra were acquired from hulled barley, naked barley, and wheat samples contaminated with Fusarium using near infrared reflectance (NIR) spectroscopy with a wavelength range of 1175–2170 nm. After measurement, the samples were cultured in a medium to discriminate contaminated samples. A partial least square discrimination analysis (PLS-DA) prediction model was developed using the acquired reflectance spectra and the culture results. The correct classification rate (CCR) of Fusarium for the hulled barley, naked barley, and wheat samples developed using raw spectra was 98% or higher. The accuracy of discrimination prediction improved when second and third-order derivative pretreatments were applied. The grains contaminated with Fusarium could be rapidly discriminated using spectroscopy technology and a PLS-DA discrimination model, and the potential of the non-destructive discrimination method could be verified. PMID:29301319

Low-dose caffeine discrimination and self-reported mood effects in normal volunteers.

PubMed Central

Silverman, K; Griffiths, R R

1992-01-01

A caffeine versus placebo discrimination procedure was used to determine the lowest caffeine dose that could produce discrimination and self-reported mood effects in normal volunteers. During daily sessions under double-blind conditions, caffeine-abstinent subjects orally ingested a capsule containing 178 mg caffeine or placebo. Before beginning discrimination training, the compounds were identified to subjects by letter codes. Fifteen, 30, and 45 min after capsule ingestion, subjects guessed the capsule's letter code. Correct guesses at 45 min earned money. After each session, subjects received a supplementary capsule containing caffeine or placebo to ensure that, within each phase of the study, subjects received the same daily dose of caffeine equal to the training dose. Five of the 15 subjects acquired the caffeine versus placebo discrimination within the first 20 sessions (greater than or equal to 75% correct); 6 other subjects acquired the discrimination with additional training. Nine subjects who acquired the discrimination were subsequently trained at progressively lower caffeine doses. In general, the lowest dose to produce discrimination (greater than or equal to 75% correct) was also the lowest dose to produce self-reported mood effects: 4 subjects showed discrimination and self-reported mood effects at 100 mg caffeine, 2 at 56 mg, 1 at 32 mg, and 1 at 18 mg. One of these subjects also showed self-reported mood effects at 10 mg. The present study documents discriminative stimulus and self-reported mood effects of caffeine at doses below those previously shown to affect any behavior in normal volunteers. PMID:1548451

Discrimination of Gastrodia elata from Different Geographical Origin for Quality Evaluation Using Newly-Build Near Infrared Spectrum Coupled with Multivariate Analysis.

PubMed

Zuo, Yamin; Deng, Xuehua; Wu, Qing

2018-05-04

Discrimination of Gastrodia elata ( G. elata ) geographical origin is of great importance to pharmaceutical companies and consumers in China. this paper focuses on the feasibility of near infrared spectrum (NIRS) combined multivariate analysis as a rapid and non-destructive method to prove its fit for this purpose. Firstly, 16 batches of G. elata samples from four main-cultivation regions in China were quantified by traditional HPLC method. It showed that samples from different origins could not be efficiently differentiated by the contents of four phenolic compounds in this study. Secondly, the raw near infrared (NIR) spectra of those samples were acquired and two different pattern recognition techniques were used to classify the geographical origins. The results showed that with spectral transformation optimized, discriminant analysis (DA) provided 97% and 99% correct classification for the calibration and validation sets of samples from discriminating of four different main-cultivation regions, and provided 98% and 99% correct classifications for the calibration and validation sets of samples from eight different cities, respectively, which all performed better than the principal component analysis (PCA) method. Thirdly, as phenolic compounds content (PCC) is highly related with the quality of G. elata , synergy interval partial least squares (Si-PLS) was applied to build the PCC prediction model. The coefficient of determination for prediction (R p ²) of the Si-PLS model was 0.9209, and root mean square error for prediction (RMSEP) was 0.338. The two regions (4800 cm −1 ⁻5200 cm −1 , and 5600 cm −1 ⁻6000 cm −1 ) selected by Si-PLS corresponded to the absorptions of aromatic ring in the basic phenolic structure. It can be concluded that NIR spectroscopy combined with PCA, DA and Si-PLS would be a potential tool to provide a reference for the quality control of G. elata.

Gender identification of Caspian Terns using external morphology and discriminant function analysis

USGS Publications Warehouse

Ackerman, Joshua T.; Takekawa, John Y.; Bluso, J.D.; Yee, J.L.; Eagles-Smith, Collin A.

2008-01-01

Caspian Tern (Sterna caspia) plumage characteristics are sexually monochromatic and gender cannot easily be distinguished in the field without extensive behavioral observations. We assessed sexual size dimorphism and developed a discriminant function to assign gender in Caspian Terns based on external morphology. We collected and measured Caspian Terns in San Francisco Bay, California, and confirmed their gender based on necropsy and genetic analysis. Of the eight morphological measurements we examined, only bill depth at the gonys and head plus bill length differed between males and females with males being larger than females. A discriminant function using both bill depth at the gonys and head plus bill length accurately assigned gender of 83% of terns for which gender was known. We improved the accuracy of our discriminant function to 90% by excluding individuals that had less than a 75% posterior probability of correctly being assigned to gender. Caspian Terns showed little sexual size dimorphism in many morphometries, but our results indicate they can be reliably assigned to gender in the field using two morphological measurements.

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 2 of 2

NASA Technical Reports Server (NTRS)

Schlosser, E. H.

1980-01-01

A generalized four-channel hyperplane to discriminate water from non-water was developed using LANDSAT-3 multispectral scanner (MSS) scences and matching same/next-day color infrared aerial photography. The MSS scenes over upstate New York, eastern Washington, Montana and Louisiana taken between May and October 1978 varied in Sun elevation angle from 40 to 58 degrees. The 28 matching air photo frames selected for analysis contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. Approximately 1300 pixels, half of them non-edge water pixels and half non-water pixels spectrally close to water, were labelled. A linear discriminant was iteratively fitted to the labelled pixels, giving more weight to those pixels that were difficult to discriminate. This discriminant correctly classified 98.7 percent of the water pixels and 98.6 percent of the non-water pixels.

Problems of stock definition in estimating relative contributions of Atlantic striped bass to the coastal fishery

USGS Publications Warehouse

Waldman, John R.; Fabrizio, Mary C.

1994-01-01

Stock contribution studies of mixed-stock fisheries rely on the application of classification algorithms to samples of unknown origin. Although the performance of these algorithms can be assessed, there are no guidelines regarding decisions about including minor stocks, pooling stocks into regional groups, or sampling discrete substocks to adequately characterize a stock. We examined these questions for striped bass Morone saxatilis of the U.S. Atlantic coast by applying linear discriminant functions to meristic and morphometric data from fish collected from spawning areas. Some of our samples were from the Hudson and Roanoke rivers and four tributaries of the Chesapeake Bay. We also collected fish of mixed-stock origin from the Atlantic Ocean near Montauk, New York. Inclusion of the minor stock from the Roanoke River in the classification algorithm decreased the correct-classification rate, whereas grouping of the Roanoke River and Chesapeake Bay stock into a regional (''southern'') group increased the overall resolution. The increased resolution was offset by our inability to obtain separate contribution estimates of the groups that were pooled. Although multivariate analysis of variance indicated significant differences among Chesapeake Bay substocks, increasing the number of substocks in the discriminant analysis decreased the overall correct-classification rate. Although the inclusion of one, two, three, or four substocks in the classification algorithm did not greatly affect the overall correct-classification rates, the specific combination of substocks significantly affected the relative contribution estimates derived from the mixed-stock sample. Future studies of this kind must balance the costs and benefits of including minor stocks and would profit from examination of the variation in discriminant characters among all Chesapeake Bay substocks.

Spectral identification of melon seeds variety based on k-nearest neighbor and Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Li, Cuiling; Jiang, Kai; Zhao, Xueguan; Fan, Pengfei; Wang, Xiu; Liu, Chuan

2017-10-01

Impurity of melon seeds variety will cause reductions of melon production and economic benefits of farmers, this research aimed to adopt spectral technology combined with chemometrics methods to identify melon seeds variety. Melon seeds whose varieties were "Yi Te Bai", "Yi Te Jin", "Jing Mi NO.7", "Jing Mi NO.11" and " Yi Li Sha Bai "were used as research samples. A simple spectral system was developed to collect reflective spectral data of melon seeds, including a light source unit, a spectral data acquisition unit and a data processing unit, the detection wavelength range of this system was 200-1100nm with spectral resolution of 0.14 7.7nm. The original reflective spectral data was pre-treated with de-trend (DT), multiple scattering correction (MSC), first derivative (FD), normalization (NOR) and Savitzky-Golay (SG) convolution smoothing methods. Principal Component Analysis (PCA) method was adopted to reduce the dimensions of reflective spectral data and extract principal components. K-nearest neighbour (KNN) and Fisher discriminant analysis (FDA) methods were used to develop discriminant models of melon seeds variety based on PCA. Spectral data pretreatments improved the discriminant effects of KNN and FDA, FDA generated better discriminant results than KNN, both KNN and FDA methods produced discriminant accuracies reaching to 90.0% for validation set. Research results showed that using spectral technology in combination with KNN and FDA modelling methods to identify melon seeds variety was feasible.

A Psychophysiological Analysis of Developmental Differences in the Ability to Resist Interference.

ERIC Educational Resources Information Center

Ridderinkhof, K. Richard; van der Molen, Maurits W.

1995-01-01

Examined age-related changes in visual selective attention--ability to resist interference--in children 5 to 12 years old and adults. The interference effect on stimulus evaluation did not discriminate between age groups; however, the interference effect on correct response activation showed a pronounced age-related reduction, suggesting a…

Risk factors for eating disorders in Greek- and Anglo-Australian adolescent girls.

PubMed

Mildred, H; Paxton, S J; Wertheim, E H

1995-01-01

Past research indicates ethnicity may be related to eating disorder and related risk factors. The present study examines risk factors for eating disorders in 50 Anglo- and 50 Greek-Australian girls (mean age = 13.5 years). The variables assessed included bulimic tendencies, body dissatisfaction, use of extreme weight loss behaviors (EWLBs), self-esteem, depression and family cohesion and adaptability. Cultural eating patterns were also explored. A stepwise discriminant function analysis to examine whether the two groups could be discriminated on these variables was significant and correctly classified 73.9% of the sample, the chief discriminating variables being Pressure to Eat, EWLBs, and Family Adaptability. Univariate analyses indicated differences between the groups on Pressure to Eat, Family Adaptability, and Mother's Shape. Although the groups were discriminable, a number of variables generally associated with eating disorder did not contribute to the function. These data are discussed in terms of cultural assimilation.

Exploring the Effects of Geographical Origin on the Chemical Composition and Quality Grading of Vitis vinifera L. cv. Chardonnay Grapes.

PubMed

Gambetta, Joanna M; Cozzolino, Daniel; Bastian, Susan E P; Jeffery, David W

2017-01-31

The relationship between berry chemical composition, region of origin and quality grade was investigated for Chardonnay grapes sourced from vineyards located in seven South Australian Geographical Indications (GI). Measurements of basic chemical parameters, amino acids, elements, and free and bound volatiles were conducted for grapes collected during 2015 and 2016. Multiple factor analysis (MFA) was used to determine the sets of data that best discriminated each GI and quality grade. Important components for the discrimination of grapes based on GI were 2-phenylethanol, benzyl alcohol and C6 compounds, as well as Cu, Zn, and Mg, titratable acidity (TA), total soluble solids (TSS), and pH. Discriminant analysis (DA) based on MFA results correctly classified 100% of the samples into GI in 2015 and 2016. Classification according to grade was achieved based on the results for elements such as Cu, Na, Fe, volatiles including C6 and aryl alcohols, hydrolytically-released volatiles such as (Z)-linalool oxide and vitispirane, pH, TSS, alanine and proline. Correct classification through DA according to grade was 100% for both vintages. Significant correlations were observed between climate, GI, grade, and berry composition. Climate influenced the synthesis of free and bound volatiles as well as amino acids, sugars, and acids, as a result of higher temperatures and precipitation.

Benchmark data on the separability among crops in the southern San Joaquin Valley of California

NASA Technical Reports Server (NTRS)

Morse, A.; Card, D. H.

1984-01-01

Landsat MSS data were input to a discriminant analysis of 21 crops on each of eight dates in 1979 using a total of 4,142 fields in southern Fresno County, California. The 21 crops, which together account for over 70 percent of the agricultural acreage in the southern San Joaquin Valley, were analyzed to quantify the spectral separability, defined as omission error, between all pairs of crops. On each date the fields were segregated into six groups based on the mean value of the MSS7/MSS5 ratio, which is correlated with green biomass. Discriminant analysis was run on each group on each date. The resulting contingency tables offer information that can be profitably used in conjunction with crop calendars to pick the best dates for a classification. The tables show expected percent correct classification and error rates for all the crops. The patterns in the contingency tables show that the percent correct classification for crops generally increases with the amount of greenness in the fields being classified. However, there are exceptions to this general rule, notably grain.

Discriminability and Sensitivity to Reinforcer Magnitude in a Detection Task

ERIC Educational Resources Information Center

Alsop, Brent; Porritt, Melissa

2006-01-01

Three pigeons discriminated between two sample stimuli (intensities of red light). The difficulty of the discrimination was varied over four levels. At each level, the relative reinforcer magnitude for the two correct responses was varied across conditions, and the reinforcer rates were equal. Within levels, discriminability between the sample…

Local connected fractal dimension analysis in gill of fish experimentally exposed to toxicants.

PubMed

Manera, Maurizio; Giari, Luisa; De Pasquale, Joseph A; Sayyaf Dezfuli, Bahram

2016-06-01

An operator-neutral method was implemented to objectively assess European seabass, Dicentrarchus labrax (Linnaeus, 1758) gill pathology after experimental exposure to cadmium (Cd) and terbuthylazine (TBA) for 24 and 48h. An algorithm-derived local connected fractal dimension (LCFD) frequency measure was used in this comparative analysis. Canonical variates (CVA) and linear discriminant analysis (LDA) were used to evaluate the discrimination power of the method among exposure classes (unexposed, Cd exposed, TBA exposed). Misclassification, sensitivity and specificity, both with original and cross-validated cases, were determined. LCFDs frequencies enhanced the differences among classes which were visually selected after their means, respective variances and the differences between Cd and TBA exposed means, with respect to unexposed mean, were analyzed by scatter plots. Selected frequencies were then scanned by means of LDA, stepwise analysis, and Mahalanobis distance to detect the most discriminative frequencies out of ten originally selected. Discrimination resulted in 91.7% of cross-validated cases correctly classified (22 out of 24 total cases), with sensitivity and specificity, respectively, of 95.5% (1 false negative with respect to 21 really positive cases) and 75% (1 false positive with respect to 3 really negative cases). CVA with convex hull polygons ensured prompt, visually intuitive discrimination among exposure classes and graphically supported the false positive case. The combined use of semithin sections, which enhanced the visual evaluation of the overall lamellar structure; of LCFD analysis, which objectively detected local variation in complexity, without the possible bias connected to human personnel; and of CVA/LDA, could be an objective, sensitive and specific approach to study fish gill lamellar pathology. Furthermore this approach enabled discrimination with sufficient confidence between exposure classes or pathological states and avoided misdiagnosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Metacarpophalangeal pattern profile analysis in Leri-Weill dyschondrosteosis.

PubMed

Laurencikas, E; Soderman, E; Grigelioniene, G; Hagenäs, L; Jorulf, H

2005-04-01

To analyze the metacarpophalangeal profile (MCPP) in individuals with Leri-Weill dyschondrosteosis (LWD) and to assess its value as a possible contributor to early diagnosis. Hand profiles of 39 individuals with a diagnosis of LWD were calculated and analyzed. Discriminant analysis was applied to differentiate between LWD and normal individuals. There was a distinct pattern profile in LWD. Mean pattern profile showed two bone-shortening gradients, with increasing shortening from distal to proximal and from medial to lateral. Distal phalanx 2 was disproportionately long and second metacarpal was disproportionately short. Discriminant analysis yielded correct classification in 72% of analyzed cases. MCPP is not age-related and the analysis can be applied at any age, facilitating early diagnosis of LWD. In view of its availability, low costs, and diagnostic value, MCPP analysis should be considered as a routine method in the patients of short stature where LWD is suspected.

Applications of stable isotope analysis in mammalian ecology.

PubMed

Walter, W David; Kurle, Carolyn M; Hopkins, John B

2014-01-01

In this editorial, we provide a brief introduction and summarize the 10 research articles included in this Special Issue on Applications of stable isotope analysis in mammalian ecology. The first three articles report correction and discrimination factors that can be used to more accurately estimate the diets of extinct and extant mammals using stable isotope analysis. The remaining seven applied research articles use stable isotope analysis to address a variety of wildlife conservation and management questions from the oceans to the mountains.

REGIONAL SEISMIC CHEMICAL AND NUCLEAR EXPLOSION DISCRIMINATION: WESTERN U.S. EXAMPLES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walter, W R; Taylor, S R; Matzel, E

2006-07-07

We continue exploring methodologies to improve regional explosion discrimination using the western U.S. as a natural laboratory. The western U.S. has abundant natural seismicity, historic nuclear explosion data, and widespread mine blasts, making it a good testing ground to study the performance of regional explosion discrimination techniques. We have assembled and measured a large set of these events to systematically explore how to best optimize discrimination performance. Nuclear explosions can be discriminated from a background of earthquakes using regional phase (Pn, Pg, Sn, Lg) amplitude measures such as high frequency P/S ratios. The discrimination performance is improved if the amplitudesmore » can be corrected for source size and path length effects. We show good results are achieved using earthquakes alone to calibrate for these effects with the MDAC technique (Walter and Taylor, 2001). We show significant further improvement is then possible by combining multiple MDAC amplitude ratios using an optimized weighting technique such as Linear Discriminant Analysis (LDA). However this requires data or models for both earthquakes and explosions. In many areas of the world regional distance nuclear explosion data is lacking, but mine blast data is available. Mine explosions are often designed to fracture and/or move rock, giving them different frequency and amplitude behavior than contained chemical shots, which seismically look like nuclear tests. Here we explore discrimination performance differences between explosion types, the possible disparity in the optimization parameters that would be chosen if only chemical explosions were available and the corresponding effect of that disparity on nuclear explosion discrimination. Even after correcting for average path and site effects, regional phase ratios contain a large amount of scatter. This scatter appears to be due to variations in source properties such as depth, focal mechanism, stress drop, in the near source material properties (including emplacement conditions in the case of explosions) and in variations from the average path and site correction. Here we look at several kinds of averaging as a means to try and reduce variance in earthquake and explosion populations and better understand the factors going into a minimum variance level as a function of epicenter (see Anderson ee et al. this volume). We focus on the performance of P/S ratios over the frequency range from 1 to 16 Hz finding some improvements in discrimination as frequency increases. We also explore averaging and optimally combining P/S ratios in multiple frequency bands as a means to reduce variance. Similarly we explore the effects of azimuthally averaging both regional amplitudes and amplitude ratios over multiple stations to reduce variance. Finally we look at optimal performance as a function of magnitude and path length, as these put limits the availability of good high frequency discrimination measures.« less

Alcoholic beverage strength discrimination by taste may have an upper threshold.

PubMed

Lachenmeier, Dirk W; Kanteres, Fotis; Rehm, Jürgen

2014-09-01

Given the association between alcohol consumption and negative health consequences, there is a need for individuals to be aware of their consumption of ethanol, which requires knowledge of serving sizes and alcoholic strength. This study is one of the first to systematically investigate the ability to discriminate alcoholic strength by taste. Nine discrimination tests (total n = 413) according to International Standardization Organization (ISO) 4120 sensory analysis methodology "triangle test" were performed. A perceptible difference was found for vodka in orange juice (0.0 vs. 0.5% vol; 0 vs. 1% vol), pilsner and wheat beer (0.5 vs. 5% vol), and vodka in orange juice (5 vs. 10% vol, 20 vs. 30% vol, and 30 vs. 40% vol). The percentage of the population perceiving a difference between the beverages varied between 36 and 73%. Alcoholic strength (higher vs. lower) was correctly assigned in only 4 of the 7 trials at a significant level, with 30 to 66% of the trial groups assigning the correct strength. For the trials that included beverages above 40% vol (vodka unmixed, 40 vs. 50% vol and vodka in orange juice, 40 vs. 50% vol), testers could neither perceive a difference between the samples nor assign correct alcoholic strength. Discrimination of alcoholic strength by taste was possible to a limited degree in a window of intermediate alcoholic strengths, but not at higher concentrations. This result is especially relevant for drinkers of unlabeled, over-proof unrecorded alcoholic beverages who would potentially ingest more alcohol than if they were to ingest commercial alcohol. Our study provides strong evidence for the strict implementation and enforcement of labeling requirements for all alcoholic beverages to allow informed decision making by consumers. Copyright © 2014 by the Research Society on Alcoholism.

[Discrimination of donkey meat by NIR and chemometrics].

PubMed

Niu, Xiao-Ying; Shao, Li-Min; Dong, Fang; Zhao, Zhi-Lei; Zhu, Yan

2014-10-01

Donkey meat samples (n = 167) from different parts of donkey body (neck, costalia, rump, and tendon), beef (n = 47), pork (n = 51) and mutton (n = 32) samples were used to establish near-infrared reflectance spectroscopy (NIR) classification models in the spectra range of 4,000~12,500 cm(-1). The accuracies of classification models constructed by Mahalanobis distances analysis, soft independent modeling of class analogy (SIMCA) and least squares-support vector machine (LS-SVM), respectively combined with pretreatment of Savitzky-Golay smooth (5, 15 and 25 points) and derivative (first and second), multiplicative scatter correction and standard normal variate, were compared. The optimal models for intact samples were obtained by Mahalanobis distances analysis with the first 11 principal components (PCs) from original spectra as inputs and by LS-SVM with the first 6 PCs as inputs, and correctly classified 100% of calibration set and 98. 96% of prediction set. For minced samples of 7 mm diameter the optimal result was attained by LS-SVM with the first 5 PCs from original spectra as inputs, which gained an accuracy of 100% for calibration and 97.53% for prediction. For minced diameter of 5 mm SIMCA model with the first 8 PCs from original spectra as inputs correctly classified 100% of calibration and prediction. And for minced diameter of 3 mm Mahalanobis distances analysis and SIMCA models both achieved 100% accuracy for calibration and prediction respectively with the first 7 and 9 PCs from original spectra as inputs. And in these models, donkey meat samples were all correctly classified with 100% either in calibration or prediction. The results show that it is feasible that NIR with chemometrics methods is used to discriminate donkey meat from the else meat.

Optical Fourier diffractometry applied to degraded bone structure recognition

NASA Astrophysics Data System (ADS)

Galas, Jacek; Godwod, Krzysztof; Szawdyn, Jacek; Sawicki, Andrzej

1993-09-01

Image processing and recognition methods are useful in many fields. This paper presents the hybrid optical and digital method applied to recognition of pathological changes in bones involved by metabolic bone diseases. The trabecular bone structure, registered by x ray on the photographic film, is analyzed in the new type of computer controlled diffractometer. The set of image parameters, extracted from diffractogram, is evaluated by statistical analysis. The synthetic image descriptors in discriminant space, constructed on the base of 3 training groups of images (control, osteoporosis, and osteomalacia groups) by discriminant analysis, allow us to recognize bone samples with degraded bone structure and to recognize the disease. About 89% of the images were classified correctly. This method after optimization process will be verified in medical investigations.

Fat discrimination: A phenotype with potential implications for studying fat intake behaviors and obesity

PubMed Central

Liang, Lisa C.H.; Sakimura, Johannah; May, Daniel; Breen, Cameron; Driggin, Elissa; Tepper, Beverly J.; Chung, Wendy K.; Keller, Kathleen L.

2013-01-01

Variations in fat preference and intake across humans are poorly understood in part because of difficulties in studying this behavior. The objective of this study was to develop a simple procedure to assess fat discrimination, the ability to accurately perceive differences in the fat content of foods, and assess the associations between this phenotype and fat ingestive behaviors and adiposity. African-American adults (n=317) were tested for fat discrimination using 7 forced choice same/different tests with Italian salad dressings that ranged in fat-by-weight content from 5–55%. Performance on this procedure was determined by tallying the number of trials in which a participant correctly identified the pair of samples as “same” or “different” across all test pairs (ranging from 1–7). Individuals who received the lowest scores on this task (≤3 out of 7 correct) were classified as fat non-discriminators (n=33) and those who received the highest scores (7 out of 7 correct) were classified as fat discriminators (n=59). These 2 groups were compared for the primary outcome variables: reported food intake, preferences, and adiposity. After adjusting for BMI, sex, age, and dietary restraint and disinhibition, fat non-discriminators reported greater consumption of both added fats and reduced fat foods (p<0.05 for both). Fat non-discriminators also had greater abdominal adiposity compared to fat discriminators (p<0.05). Test-retest scores performed in a subset of participants (n=40) showed moderate reliability of the fat discrimination test (rho=0.53;p<0.01). If these results are replicated, fat discrimination may serve as clinical research tool to identify participants who are at risk for obesity and other chronic diseases due to increased fat intake. PMID:21925524

Fat discrimination: a phenotype with potential implications for studying fat intake behaviors and obesity.

PubMed

Liang, Lisa C H; Sakimura, Johannah; May, Daniel; Breen, Cameron; Driggin, Elissa; Tepper, Beverly J; Chung, Wendy K; Keller, Kathleen L

2012-01-18

Variations in fat preference and intake across humans are poorly understood in part because of difficulties in studying this behavior. The objective of this study was to develop a simple procedure to assess fat discrimination, the ability to accurately perceive differences in the fat content of foods, and assess the associations between this phenotype and fat ingestive behaviors and adiposity. African-American adults (n=317) were tested for fat discrimination using 7 forced choice same/different tests with Italian salad dressings that ranged in fat-by-weight content from 5 to 55%. Performance on this procedure was determined by tallying the number of trials in which a participant correctly identified the pair of samples as "same" or "different" across all test pairs (ranging from 1 to 7). Individuals who received the lowest scores on this task (≤3 out of 7 correct) were classified as fat non-discriminators (n=33) and those who received the highest scores (7 out of 7 correct) were classified as fat discriminators (n=59). These 2 groups were compared for the primary outcome variables: reported food intake, preferences, and adiposity. After adjusting for BMI, sex, age, and dietary restraint and disinhibition, fat non-discriminators reported greater consumption of both added fats and reduced fat foods (p<0.05 for both). Fat non-discriminators also had greater abdominal adiposity compared to fat discriminators (p<0.05). Test-retest scores performed in a subset of participants (n=40) showed moderate reliability of the fat discrimination test (rho=0.53; p<0.01). If these results are replicated, fat discrimination may serve as clinical research tool to identify participants who are at risk for obesity and other chronic diseases due to increased fat intake. Copyright © 2011 Elsevier Inc. All rights reserved.

Source-Type Identification Analysis Using Regional Seismic Moment Tensors

NASA Astrophysics Data System (ADS)

Chiang, A.; Dreger, D. S.; Ford, S. R.; Walter, W. R.

2012-12-01

Waveform inversion to determine the seismic moment tensor is a standard approach in determining the source mechanism of natural and manmade seismicity, and may be used to identify, or discriminate different types of seismic sources. The successful applications of the regional moment tensor method at the Nevada Test Site (NTS) and the 2006 and 2009 North Korean nuclear tests (Ford et al., 2009a, 2009b, 2010) show that the method is robust and capable for source-type discrimination at regional distances. The well-separated populations of explosions, earthquakes and collapses on a Hudson et al., (1989) source-type diagram enables source-type discrimination; however the question remains whether or not the separation of events is universal in other regions, where we have limited station coverage and knowledge of Earth structure. Ford et al., (2012) have shown that combining regional waveform data and P-wave first motions removes the CLVD-isotropic tradeoff and uniquely discriminating the 2009 North Korean test as an explosion. Therefore, including additional constraints from regional and teleseismic P-wave first motions enables source-type discrimination at regions with limited station coverage. We present moment tensor analysis of earthquakes and explosions (M6) from Lop Nor and Semipalatinsk test sites for station paths crossing Kazakhstan and Western China. We also present analyses of smaller events from industrial sites. In these sparse coverage situations we combine regional long-period waveforms, and high-frequency P-wave polarity from the same stations, as well as from teleseismic arrays to constrain the source type. Discrimination capability with respect to velocity model and station coverage is examined, and additionally we investigate the velocity model dependence of vanishing free-surface traction effects on seismic moment tensor inversion of shallow sources and recovery of explosive scalar moment. Our synthetic data tests indicate that biases in scalar seismic moment and discrimination for shallow sources are small and can be understood in a systematic manner. We are presently investigating the frequency dependence of vanishing traction of a very shallow (10m depth) M2+ chemical explosion recorded at several kilometer distances, and preliminary results indicate at the typical frequency passband we employ the bias does not affect our ability to retrieve the correct source mechanism but may affect the retrieval of the correct scalar seismic moment. Finally, we assess discrimination capability in a composite P-value statistical framework.

Assessing Visuospatial Skills in Parkinson's: Comparison of Neuropsychological Assessment Battery Visual Discrimination to the Judgment of Line Orientation.

PubMed

Renfroe, Jenna B; Turner, Travis H; Hinson, Vanessa K

2017-02-01

Judgment of Line Orientation (JOLO) test is widely used in assessing visuospatial deficits in Parkinson's disease (PD). The neuropsychological assessment battery (NAB) offers the Visual Discrimination test, with age and education correction, parallel forms, and co-normed standardization sample for comparisons within and between domains. However, NAB Visual Discrimination has not been validated in PD, and may not measure the same construct as JOLO. A heterogeneous sample of 47 PD patients completed the JOLO and NAB Visual Discrimination within a broader neuropsychological evaluation. Pearson correlations assessed relationships between JOLO and NAB Visual Discrimination performances. Raw and demographically corrected scores from JOLO and Visual Discrimination were only weakly correlated. NAB Visual Discrimination subtest was moderately correlated with overall cognitive functioning, whereas the JOLO was not. Despite apparent virtues, results do not support NAB Visual Discrimination as an alternative to JOLO in assessing visuospatial functioning in PD. © The Author 2016. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Ratios and effect size.

PubMed

Robinson, Jasper

2017-10-01

Responding to a related pair of measurements is often expressed as a single discrimination ratio. Authors have used various discrimination ratios; yet, little information exists to guide their choice. A second use of ratios is to correct for the influence of a nuisance variable on the measurement of interest. I examine 4 discrimination ratios using simulated data sets. Three ratios, of the form a/(a + b), b/(a + b), and (a - b)/(a + b), introduced distortions to their raw data. The fourth ratio, (b - a)/b largely avoided such distortions and was the most sensitive at detecting statistical differences. Effect size statistics were also often improved with a correction ratio. Gustatory sensory preconditioning experiments involved measurement of rats' sucrose and saline consumption; these flavors served as either a target flavor or a control flavor and were counterbalanced across rats. However, sensory preconditioning was often masked by a bias for sucrose over saline. Sucrose and saline consumption scores were multiplied by the ratio of the overall consumption to the consumption of that flavor alone, which corrected the bias. The general utility of discrimination and correction ratios for data treatment is discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Radar image processing for rock-type discrimination

NASA Technical Reports Server (NTRS)

Blom, R. G.; Daily, M.

1982-01-01

Image processing and enhancement techniques for improving the geologic utility of digital satellite radar images are reviewed. Preprocessing techniques such as mean and variance correction on a range or azimuth line by line basis to provide uniformly illuminated swaths, median value filtering for four-look imagery to eliminate speckle, and geometric rectification using a priori elevation data. Examples are presented of application of preprocessing methods to Seasat and Landsat data, and Seasat SAR imagery was coregistered with Landsat imagery to form composite scenes. A polynomial was developed to distort the radar picture to fit the Landsat image of a 90 x 90 km sq grid, using Landsat color ratios with Seasat intensities. Subsequent linear discrimination analysis was employed to discriminate rock types from known areas. Seasat additions to the Landsat data improved rock identification by 7%.

Global crop production forecasting data system analysis

NASA Technical Reports Server (NTRS)

Castruccio, P. A. (Principal Investigator); Loats, H. L.; Lloyd, D. G.

1978-01-01

The author has identified the following significant results. Findings led to the development of a theory of radiometric discrimination employing the mathematical framework of the theory of discrimination between scintillating radar targets. The theory indicated that the functions which drive accuracy of discrimination are the contrast ratio between targets, and the number of samples, or pixels, observed. Theoretical results led to three primary consequences, as regards the data system: (1) agricultural targets must be imaged at correctly chosen times, when the relative evolution of the crop's development is such as to maximize their contrast; (2) under these favorable conditions, the number of observed pixels can be significantly reduced with respect to wall-to-wall measurements; and (3) remotely sensed radiometric data must be suitably mixed with other auxiliary data, derived from external sources.

Classification of adulterated honeys by multivariate analysis.

PubMed

Amiry, Saber; Esmaiili, Mohsen; Alizadeh, Mohammad

2017-06-01

In this research, honey samples were adulterated with date syrup (DS) and invert sugar syrup (IS) at three concentrations (7%, 15% and 30%). 102 adulterated samples were prepared in six batches with 17 replications for each batch. For each sample, 32 parameters including color indices, rheological, physical, and chemical parameters were determined. To classify the samples, based on type and concentrations of adulterant, a multivariate analysis was applied using principal component analysis (PCA) followed by a linear discriminant analysis (LDA). Then, 21 principal components (PCs) were selected in five sets. Approximately two-thirds were identified correctly using color indices (62.75%) or rheological properties (67.65%). A power discrimination was obtained using physical properties (97.06%), and the best separations were achieved using two sets of chemical properties (set 1: lactone, diastase activity, sucrose - 100%) (set 2: free acidity, HMF, ash - 95%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Infrared Microtransmission And Microreflectance Of Biological Systems

NASA Astrophysics Data System (ADS)

Hill, Steve L.; Krishnan, K.; Powell, Jay R.

1989-12-01

The infrared microsampling technique has been successfully applied to a variety of biological systems. A microtomed tissue section may be prepared to permit both visual and infrared discrimination. Infrared structural information may be obtained for a single cell, and computer-enhanced images of tissue specimens may be calculated from spectral map data sets. An analysis of a tissue section anomaly may gg suest eitherprotein compositional differences or a localized concentration of foreign matterp. Opaque biological materials such as teeth, gallstones, and kidney stones may be analyzed by microreflectance spectroscop. Absorption anomalies due to specular dispersion are corrected with the Kraymers-Kronig transformation. Corrected microreflectance spectra may contribute to compositional analysis and correlate diseased-related spectral differences to visual specimen anomalies.

Can early hepatic fibrosis stages be discriminated by combining ultrasonic parameters?

PubMed

Bouzitoune, Razika; Meziri, Mahmoud; Machado, Christiano Bittencourt; Padilla, Frédéric; Pereira, Wagner Coelho de Albuquerque

2016-05-01

In this study, we put forward a new approach to classify early stages of fibrosis based on a multiparametric characterization using backscatter ultrasonic signals. Ultrasonic parameters, such as backscatter coefficient (Bc), speed of sound (SoS), attenuation coefficient (Ac), mean scatterer spacing (MSS), and spectral slope (SS), have shown their potential to differentiate between healthy and pathologic samples in different organs (eye, breast, prostate, liver). Recently, our group looked into the characterization of stages of hepatic fibrosis using the parameters cited above. The results showed that none of them could individually distinguish between the different stages. Therefore, we explored a multiparametric approach by combining these parameters in two and three, to test their potential to discriminate between the stages of liver fibrosis: F0 (normal), F1, F3, and/without F4 (cirrhosis), according to METAVIR Score. Discriminant analysis showed that the most relevant individual parameter was Bc, followed by SoS, SS, MSS, and Ac. The combination of (Bc, SoS) along with the four stages was the best in differentiating between the stages of fibrosis and correctly classified 85% of the liver samples with a high level of significance (p<0.0001). Nevertheless, when taking into account only stages F0, F1, and F3, the discriminant analysis showed that the parameters (Bc, SoS) and (Bc, Ac) had a better classification (93%) with a high level of significance (p<0.0001). The combination of the three parameters (Bc, SoS, and Ac) led to a 100% correct classification. In conclusion, the current findings show that the multiparametric approach has great potential in differentiating between the stages of fibrosis, and thus could play an important role in the diagnosis and follow-up of hepatic fibrosis. Copyright © 2016 Elsevier B.V. All rights reserved.

Consumers' Motivations and Dairy Production Beliefs Regarding Participation in an Educational Dairy Farm Event

ERIC Educational Resources Information Center

LaFollette, Lindsay K.; Knobloch, Neil A.; Schutz, Michael M.; Brady, Colleen M.

2015-01-01

Exploratory discriminant analysis was used to determine the extent adult consumers' interest motivation to participate in a free educational dairy farm event and their beliefs of the dairy industry could correctly classify the respondents' predicted participation in a nonformal educational event. The most prominent conclusion of the study was that…

Evaluation of facial expression in acute pain in cats.

PubMed

Holden, E; Calvo, G; Collins, M; Bell, A; Reid, J; Scott, E M; Nolan, A M

2014-12-01

To describe the development of a facial expression tool differentiating pain-free cats from those in acute pain. Observers shown facial images from painful and pain-free cats were asked to identify if they were in pain or not. From facial images, anatomical landmarks were identified and distances between these were mapped. Selected distances underwent statistical analysis to identify features discriminating pain-free and painful cats. Additionally, thumbnail photographs were reviewed by two experts to identify discriminating facial features between the groups. Observers (n = 68) had difficulty in identifying pain-free from painful cats, with only 13% of observers being able to discriminate more than 80% of painful cats. Analysis of 78 facial landmarks and 80 distances identified six significant factors differentiating pain-free and painful faces including ear position and areas around the mouth/muzzle. Standardised mouth and ear distances when combined showed excellent discrimination properties, correctly differentiating pain-free and painful cats in 98% of cases. Expert review supported these findings and a cartoon-type picture scale was developed from thumbnail images. Initial investigation into facial features of painful and pain-free cats suggests potentially good discrimination properties of facial images. Further testing is required for development of a clinical tool. © 2014 British Small Animal Veterinary Association.

Similar discriminative-stimulus effects of D-amphetamine in women and men.

PubMed

Vansickel, Andrea R; Lile, Joshua A; Stoops, William W; Rush, Craig R

2007-01-01

The results of controlled non-human animal and human laboratory studies are mixed regarding whether women and men respond differently to stimulant drugs. In order to assess potential gender differences in the effects of D-amphetamine, we conducted a retrospective analysis of six studies conducted in our laboratory that used identical procedures and measures. Thirteen women and fourteen men learned to discriminate 15 mg oral D-amphetamine. After acquiring the discrimination (i.e., >or=80% correct responding on 4 consecutive sessions), the effects of a range of doses of D-amphetamine (0, 2.5, 5, 10, and 15 mg) alone and in combination with other drugs, were assessed. Only data from sessions in which D-amphetamine was administered alone were included in this analysis. D-amphetamine functioned as a discriminative stimulus and dose-dependently increased drug-appropriate responding. Women and men did not differ in their ability to discriminate D-amphetamine. Women and men differed on participant-ratings of high (womenmen) and sluggish (women

The role of critical ethnic awareness and social support in the discrimination-depression relationship among Asian Americans: path analysis.

PubMed

Kim, Isok

2014-01-01

This study used a path analytic technique to examine associations among critical ethnic awareness, racial discrimination, social support, and depressive symptoms. Using a convenience sample from online survey of Asian American adults (N = 405), the study tested 2 main hypotheses: First, based on the empowerment theory, critical ethnic awareness would be positively associated with racial discrimination experience; and second, based on the social support deterioration model, social support would partially mediate the relationship between racial discrimination and depressive symptoms. The result of the path analysis model showed that the proposed path model was a good fit based on global fit indices, χ²(2) = 4.70, p = .10; root mean square error of approximation = 0.06; comparative fit index = 0.97; Tucker-Lewis index = 0.92; and standardized root mean square residual = 0.03. The examinations of study hypotheses demonstrated that critical ethnic awareness was directly associated (b = .11, p < .05) with the racial discrimination experience, whereas social support had a significant indirect effect (b = .48; bias-corrected 95% confidence interval [0.02, 1.26]) between the racial discrimination experience and depressive symptoms. The proposed path model illustrated that both critical ethnic awareness and social support are important mechanisms for explaining the relationship between racial discrimination and depressive symptoms among this sample of Asian Americans. This study highlights the usefulness of the critical ethnic awareness concept as a way to better understand how Asian Americans might perceive and recognize racial discrimination experiences in relation to its mental health consequences.

Identification of pesticide varieties by testing microalgae using Visible/Near Infrared Hyperspectral Imaging technology

NASA Astrophysics Data System (ADS)

Shao, Yongni; Jiang, Linjun; Zhou, Hong; Pan, Jian; He, Yong

2016-04-01

In our study, the feasibility of using visible/near infrared hyperspectral imaging technology to detect the changes of the internal components of Chlorella pyrenoidosa so as to determine the varieties of pesticides (such as butachlor, atrazine and glyphosate) at three concentrations (0.6 mg/L, 3 mg/L, 15 mg/L) was investigated. Three models (partial least squares discriminant analysis combined with full wavelengths, FW-PLSDA; partial least squares discriminant analysis combined with competitive adaptive reweighted sampling algorithm, CARS-PLSDA; linear discrimination analysis combined with regression coefficients, RC-LDA) were built by the hyperspectral data of Chlorella pyrenoidosa to find which model can produce the most optimal result. The RC-LDA model, which achieved an average correct classification rate of 97.0% was more superior than FW-PLSDA (72.2%) and CARS-PLSDA (84.0%), and it proved that visible/near infrared hyperspectral imaging could be a rapid and reliable technique to identify pesticide varieties. It also proved that microalgae can be a very promising medium to indicate characteristics of pesticides.

Glycomics meets artificial intelligence - Potential of glycan analysis for identification of seropositive and seronegative rheumatoid arthritis patients revealed.

PubMed

Chocholova, Erika; Bertok, Tomas; Jane, Eduard; Lorencova, Lenka; Holazova, Alena; Belicka, Ludmila; Belicky, Stefan; Mislovicova, Danica; Vikartovska, Alica; Imrich, Richard; Kasak, Peter; Tkac, Jan

2018-06-01

In this study, one hundred serum samples from healthy people and patients with rheumatoid arthritis (RA) were analyzed. Standard immunoassays for detection of 10 different RA markers and analysis of glycan markers on antibodies in 10 different assay formats with several lectins were applied for each serum sample. A dataset containing 2000 data points was data mined using artificial neural networks (ANN). We identified key RA markers, which can discriminate between healthy people and seropositive RA patients (serum containing autoantibodies) with accuracy of 83.3%. Combination of RA markers with glycan analysis provided much better discrimination accuracy of 92.5%. Immunoassays completely failed to identify seronegative RA patients (serum not containing autoantibodies), while glycan analysis correctly identified 43.8% of these patients. Further, we revealed other critical parameters for successful glycan analysis such as type of a sample, format of analysis and orientation of captured antibodies for glycan analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Highly sensitive molecular diagnosis of prostate cancer using surplus material washed off from biopsy needles

PubMed Central

Bermudo, R; Abia, D; Mozos, A; García-Cruz, E; Alcaraz, A; Ortiz, Á R; Thomson, T M; Fernández, P L

2011-01-01

Introduction: Currently, final diagnosis of prostate cancer (PCa) is based on histopathological analysis of needle biopsies, but this process often bears uncertainties due to small sample size, tumour focality and pathologist's subjective assessment. Methods: Prostate cancer diagnostic signatures were generated by applying linear discriminant analysis to microarray and real-time RT–PCR (qRT–PCR) data from normal and tumoural prostate tissue samples. Additionally, after removal of biopsy tissues, material washed off from transrectal biopsy needles was used for molecular profiling and discriminant analysis. Results: Linear discriminant analysis applied to microarray data for a set of 318 genes differentially expressed between non-tumoural and tumoural prostate samples produced 26 gene signatures, which classified the 84 samples used with 100% accuracy. To identify signatures potentially useful for the diagnosis of prostate biopsies, surplus material washed off from routine biopsy needles from 53 patients was used to generate qRT–PCR data for a subset of 11 genes. This analysis identified a six-gene signature that correctly assigned the biopsies as benign or tumoural in 92.6% of the cases, with 88.8% sensitivity and 96.1% specificity. Conclusion: Surplus material from prostate needle biopsies can be used for minimal-size gene signature analysis for sensitive and accurate discrimination between non-tumoural and tumoural prostates, without interference with current diagnostic procedures. This approach could be a useful adjunct to current procedures in PCa diagnosis. PMID:22009027

Paper spray mass spectrometry and chemometric tools for a fast and reliable identification of counterfeit blended Scottish whiskies.

PubMed

Teodoro, Janaína Aparecida Reis; Pereira, Hebert Vinicius; Sena, Marcelo Martins; Piccin, Evandro; Zacca, Jorge Jardim; Augusti, Rodinei

2017-12-15

A direct method based on the application of paper spray mass spectrometry (PS-MS) combined with a chemometric supervised method (partial least square discriminant analysis, PLS-DA) was developed and applied to the discrimination of authentic and counterfeit samples of blended Scottish whiskies. The developed methodology employed the negative ion mode MS, included 44 authentic whiskies from diverse brands and batches and 44 counterfeit samples of the same brands seized during operations of the Brazilian Federal Police, totalizing 88 samples. An exploratory principal component analysis (PCA) model showed a reasonable discrimination of the counterfeit whiskies in PC2. In spite of the samples heterogeneity, a robust, reliable and accurate PLS-DA model was generated and validated, which was able to correctly classify the samples with nearly 100% success rate. The use of PS-MS also allowed the identification of the main marker compounds associated with each type of sample analyzed: authentic or counterfeit. Copyright © 2017 Elsevier Ltd. All rights reserved.

Genotypic and environmental effects on coffee (Coffea arabica L.) bean fatty acid profile: impact on variety and origin chemometric determination.

PubMed

Villarreal, Diana; Laffargue, Andreina; Posada, Huver; Bertrand, Benoit; Lashermes, Philippe; Dussert, Stephane

2009-12-09

In a previous study, the effectiveness of chlorogenic acids, fatty acids (FA), and elements was compared for the discrimination of Arabica varieties and growing terroirs. Since FA provided the best results, the aim of the present work was to validate their discrimination ability using an extended experimental design, including twice the number of location x variety combinations and 2 years of study. It also aimed at understanding how the environment influences FA composition through correlation analysis using different climatic parameters. Percentages of correct classification of known samples remained very high, independent of the classification criterion. However, cross-validation tests across years indicated that prediction of unknown locations was less efficient than that of unknown genotypes. Environmental temperature during the development of coffee beans had a dramatic influence on their FA composition. Analysis of climate patterns over years enabled us to understand the efficient location discrimination within a single year but only moderate efficiency across years.

[Nondestructive discrimination of strawberry varieties by NIR and BP-ANN].

PubMed

Niu, Xiao-ying; Shao, Li-min; Zhao, Zhi-lei; Zhang, Xiao-yu

2012-08-01

Strawberry variety is a main factor that can influence strawberry fruit quality. The use of near-infrared reflectance spectroscopy was explored discriminate among samples of strawberry of different varieties. And the significance of difference among different varieties was analyzed by comparison of the chemical composition of the different varieties samples. The performance of models established using back propagation-artificial neural networks (BP-ANN), least squares-support vector machine and discriminant analysis were evaluated on spectra range of 4545-9090 cm(-1). The optimal model was obtained by BP-ANN with a topology of 12-18-3, which correctly classified 96.68% of calibration set and 97.14% of prediction set. And the 94.95%, 97% and 98.29% classifications were given respectively for "Tianbao" (n=99), "Fengxiang" (n=100) and "Mingxing" (n=117). One-way analysis of variance was made for comparison of the mean values for soluble solids content (SSC), titratable acid (TA), pH value and SSC-TA ratio, and the statistically significant differences were found. Principal component analysis was performed on the four chemical compositions, and obvious clustering tendencies for different varieties were found. These results showed that NIR combined with BP-ANN can discriminate strawberry of different varieties effectively, and the difference in chemical compositions of different varieties strawberry might be a chemical validation for NIR results.

Tactical metrics that discriminate winning, drawing and losing teams in UEFA Euro 2012®.

PubMed

Winter, Christian; Pfeiffer, Mark

2016-01-01

The objectives of this article are twofold: first, an innovative approach to notational analysis in football is outlined. By considering the important theoretical requirements for the analysis of sports games (like the interaction between two parties, the procedural sequence of action or the significance of tactical behaviour) the meaning of the introduced parameters, called tactical metrics, is illustrated. In a second step, the validity of this approach is tested using matches of the Union of European Football Associations (UEFA) Euro 2012® to investigate a connection between these metrics and success. The results show that 11 tactical metrics model tactical behaviour in 4 different dimensions (game speed, transition play after ball recovery, transition play after ball loss and offence efficiency (OE)). Discriminant analysis based on the factor values leads to a correct classification of 64.8% identifying winners, losers and drawers. This successful discrimination reveals a connection between match success and the presented metrics. Especially, the transition play after losing the ball and the OE seem to be factors connected directly with the result of a match, since those were important values for a successful discrimination. Furthermore, the procedural description of tactical behaviour provides the opportunity to conduct meaningful recommendations for the training and coaching process.

Classification of the Correct Quranic Letters Pronunciation of Male and Female Reciters

NASA Astrophysics Data System (ADS)

Khairuddin, Safiah; Ahmad, Salmiah; Embong, Abdul Halim; Nur Wahidah Nik Hashim, Nik; Altamas, Tareq M. K.; Nuratikah Syd Badaruddin, Syarifah; Shahbudin Hassan, Surul

2017-11-01

Recitation of the Holy Quran with the correct Tajweed is essential for every Muslim. Islam has encouraged Quranic education since early age as the recitation of the Quran correctly will represent the correct meaning of the words of Allah. It is important to recite the Quranic verses according to its characteristics (sifaat) and from its point of articulations (makhraj). This paper presents the identification and classification analysis of Quranic letters pronunciation for both male and female reciters, to obtain the unique representation of each letter by male as compared to female expert reciters. Linear Discriminant Analysis (LDA) was used as the classifier to classify the data with Formants and Power Spectral Density (PSD) as the acoustic features. The result shows that linear classifier of PSD with band 1 and band 2 power spectral combinations gives a high percentage of classification accuracy for most of the Quranic letters. It is also shown that the pronunciation by male reciters gives better result in the classification of the Quranic letters.

The Emergence of Symmetry in a Conditional Discrimination Task Using Different Responses as Propioceptive Samples in Pigeons

ERIC Educational Resources Information Center

Garcia, Andres; Benjumea, Santiago

2006-01-01

In Experiment 1, 10 pigeons were exposed to a successive symbolic matching-to-sample procedure in which the sample was generated by the pigeons' own behavior. Each trial began with both response keys illuminated white, one being the "correct" key and the other the "incorrect" key. The pigeons had no way of discriminating which key was correct and…

Cathodal transcranial direct-current stimulation over right posterior parietal cortex enhances human temporal discrimination ability.

PubMed

Oyama, Fuyuki; Ishibashi, Keita; Iwanaga, Koichi

2017-12-04

Time perception associated with durations from 1 s to several minutes involves activity in the right posterior parietal cortex (rPPC). It is unclear whether altering the activity of the rPPC affects an individual's timing performance. Here, we investigated the human timing performance under the application of transcranial direct-current stimulation (tDCS) that altered the neural activities of the rPPC. We measured the participants' duration-discrimination threshold by administering a behavioral task during the tDCS application. The tDCS conditions consisted of anodal, cathodal, and sham conditions. The electrodes were placed over the P4 position (10-20 system) and on the left supraorbital forehead. On each task trial, the participant observed two visual stimuli and indicated which was longer. The amount of difference between the two stimulus durations was varied repeatedly throughout the trials according to the participant's responses. The correct answer rate of the trials was calculated for each amount of difference, and the minimum amount with the correct answer rate exceeding 75% was selected as the threshold. The data were analyzed by a linear mixed-effects models procedure. Nineteen volunteers participated in the experiment. We excluded three participants from the analysis: two who reported extreme sleepiness while performing the task and one who could recognize the sham condition correctly with confidence. Our analysis of the 16 participants' data showed that the average value of the thresholds observed under the cathodal condition was lower than that of the sham condition. This suggests that inhibition of the rPPC leads to an improvement in temporal discrimination performance, resulting in improved timing performance. In the present study, we found a new effect that cathodal tDCS over the rPPC enhances temporal discrimination performance. In terms of the existence of anodal/cathodal tDCS effects on human timing performance, the results were consistent with a previous study that investigated temporal reproduction performance during tDCS application. However, the results of the current study further indicated that cathodal tDCS over the rPPC increases accuracy of observed time duration rather than inducing an overestimation as a previous study reported.

Characterization of Chinese rice wine taste attributes using liquid chromatographic analysis, sensory evaluation, and an electronic tongue.

PubMed

Yu, HaiYan; Zhao, Jie; Li, Fenghua; Tian, Huaixiang; Ma, Xia

2015-08-01

To evaluate the taste characteristics of Chinese rice wine, wine samples sourced from different vintage years were analyzed using liquid chromatographic analysis, sensory evaluation, and an electronic tongue. Six organic acids and seventeen amino acids were measured using high performance liquid chromatography (HPLC). Five monosaccharides were measured using anion-exchange chromatography. The global taste attributes were analyzed using an electronic tongue (E-tongue). The correlations between the 28 taste-active compounds and the sensory attributes, and the correlations between the E-tongue response and the sensory attributes were established via partial least square discriminant analysis (PLSDA). E-tongue response data combined with linear discriminant analysis (LDA) were used to discriminate the Chinese rice wine samples sourced from different vintage years. Sensory evaluation indicated significant differences in the Chinese rice wine samples sourced from 2003, 2005, 2008, and 2010 vintage years in the sensory attributes of harmony and mellow. The PLSDA model for the taste-active compounds and the sensory attributes showed that proline, fucose, arabinose, lactic acid, glutamic acid, arginine, isoleucine, valine, threonine, and lysine had an influence on the taste characteristic of Chinese rice wine. The Chinese rice wine samples were all correctly classified using the E-tongue and LDA. The electronic tongue was an effective tool for rapid discrimination of Chinese rice wine. Copyright © 2015 Elsevier B.V. All rights reserved.

Characterization and forensic analysis of soil samples using laser-induced breakdown spectroscopy (LIBS).

PubMed

Jantzi, Sarah C; Almirall, José R

2011-07-01

A method for the quantitative elemental analysis of surface soil samples using laser-induced breakdown spectroscopy (LIBS) was developed and applied to the analysis of bulk soil samples for discrimination between specimens. The use of a 266 nm laser for LIBS analysis is reported for the first time in forensic soil analysis. Optimization of the LIBS method is discussed, and the results compared favorably to a laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) method previously developed. Precision for both methods was <10% for most elements. LIBS limits of detection were <33 ppm and bias <40% for most elements. In a proof of principle study, the LIBS method successfully discriminated samples from two different sites in Dade County, FL. Analysis of variance, Tukey's post hoc test and Student's t test resulted in 100% discrimination with no type I or type II errors. Principal components analysis (PCA) resulted in clear groupings of the two sites. A correct classification rate of 99.4% was obtained with linear discriminant analysis using leave-one-out validation. Similar results were obtained when the same samples were analyzed by LA-ICP-MS, showing that LIBS can provide similar information to LA-ICP-MS. In a forensic sampling/spatial heterogeneity study, the variation between sites, between sub-plots, between samples and within samples was examined on three similar Dade sites. The closer the sampling locations, the closer the grouping on a PCA plot and the higher the misclassification rate. These results underscore the importance of careful sampling for geographic site characterization.

[Rapid Identification of Epicarpium Citri Grandis via Infrared Spectroscopy and Fluorescence Spectrum Imaging Technology Combined with Neural Network].

PubMed

Pan, Sha-sha; Huang, Fu-rong; Xiao, Chi; Xian, Rui-yi; Ma, Zhi-guo

2015-10-01

To explore rapid reliable methods for detection of Epicarpium citri grandis (ECG), the experiment using Fourier Transform Attenuated Total Reflection Infrared Spectroscopy (FTIR/ATR) and Fluorescence Spectrum Imaging Technology combined with Multilayer Perceptron (MLP) Neural Network pattern recognition, for the identification of ECG, and the two methods are compared. Infrared spectra and fluorescence spectral images of 118 samples, 81 ECG and 37 other kinds of ECG, are collected. According to the differences in tspectrum, the spectra data in the 550-1 800 cm(-1) wavenumber range and 400-720 nm wavelength are regarded as the study objects of discriminant analysis. Then principal component analysis (PCA) is applied to reduce the dimension of spectroscopic data of ECG and MLP Neural Network is used in combination to classify them. During the experiment were compared the effects of different methods of data preprocessing on the model: multiplicative scatter correction (MSC), standard normal variable correction (SNV), first-order derivative(FD), second-order derivative(SD) and Savitzky-Golay (SG). The results showed that: after the infrared spectra data via the Savitzky-Golay (SG) pretreatment through the MLP Neural Network with the hidden layer function as sigmoid, we can get the best discrimination of ECG, the correct percent of training set and testing set are both 100%. Using fluorescence spectral imaging technology, corrected by the multiple scattering (MSC) results in the pretreatment is the most ideal. After data preprocessing, the three layers of the MLP Neural Network of the hidden layer function as sigmoid function can get 100% correct percent of training set and 96.7% correct percent of testing set. It was shown that the FTIR/ATR and fluorescent spectral imaging technology combined with MLP Neural Network can be used for the identification study of ECG and has the advantages of rapid, reliable effect.

Incidental recall on WAIS-R digit symbol discriminates Alzheimer's and Parkinson's diseases.

PubMed

Demakis, G J; Sawyer, T P; Fritz, D; Sweet, J J

2001-03-01

The purpose of this study was to examine how Alzheimer's (n = 37) and Parkinson's (n = 21) patients perform on the incidental recall adaptation to the Digit Symbol of the Wechsler Adult Intelligence Scale-Revised (WAIS-R) and how such performance is related to established cognitive efficiency and memory measures. This adaptation requires the examinee to complete the entire subtest and then, without warning, to immediately recall the symbols associated with each number. Groups did not differ significantly on standard Digit Symbol administration (90 seconds), but on recall Parkinson's patients recalled significantly more symbols and symbol-number pairs than Alzheimer's patients. Using only the number of symbols recalled, discriminate function analysis correctly classified 76% of these patients. Correlations between age-corrected scaled score, symbols incidentally recalled, and established measures of cognitive efficiency and memory provided evidence of convergent and divergent validity. Age-corrected scaled scores were more consistently and strongly related to cognitive efficiency, whereas symbols recalled were more consistently and strongly related to memory measures. These findings suggest that the Digit Symbol recall adaptation is actually assessing memory and that it can be another useful way to detect memory impairment. Copyright 2001 John Wiley & Sons, Inc.

Use of rpoB gene analysis for identification of nitrogen-fixing Paenibacillus species as an alternative to the 16S rRNA gene.

PubMed

da Mota, F F; Gomes, E A; Paiva, E; Rosado, A S; Seldin, L

2004-01-01

To avoid the limitations of 16S rRNA-based phylogenetic analysis for Paenibacillus species, the usefulness of the RNA polymerase beta-subunit encoding gene (rpoB) was investigated as an alternative to the 16S rRNA gene for taxonomic studies. Partial rpoB sequences were generated for the type strains of eight nitrogen-fixing Paenibacillus species. The presence of only one copy of rpoB in the genome of P. graminis strain RSA19(T) was demonstrated by denaturing gradient gel electrophoresis and hybridization assays. A comparative analysis of the sequences of the 16S rRNA and rpoB genes was performed and the eight species showed between 91.6-99.1% (16S rRNA) and 77.9-97.3% (rpoB) similarity, allowing a more accurate discrimination between the different species using the rpoB gene. Finally, 24 isolates from the rhizosphere of different cultivars of maize previously identified as Paenibacillus spp. were assigned correctly to one of the nitrogen-fixing species. The data obtained in this study indicate that rpoB is a powerful identification tool, which can be used for the correct discrimination of the nitrogen-fixing species of agricultural and industrial importance within the genus Paenibacillus.

Attractor structure discriminates sleep states: recurrence plot analysis applied to infant breathing patterns.

PubMed

Terrill, Philip Ian; Wilson, Stephen James; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2010-05-01

Breathing patterns are characteristically different between infant active sleep (AS) and quiet sleep (QS), and statistical quantifications of interbreath interval (IBI) data have previously been used to discriminate between infant sleep states. It has also been identified that breathing patterns are governed by a nonlinear controller. This study aims to investigate whether nonlinear quantifications of infant IBI data are characteristically different between AS and QS, and whether they may be used to discriminate between these infant sleep states. Polysomnograms were obtained from 24 healthy infants at six months of age. Periods of AS and QS were identified, and IBI data extracted. Recurrence quantification analysis (RQA) was applied to each period, and recurrence calculated for a fixed radius in the range of 0-8 in steps of 0.02, and embedding dimensions of 4, 6, 8, and 16. When a threshold classifier was trained, the RQA variable recurrence was able to correctly classify 94.3% of periods in a test dataset. It was concluded that RQA of IBI data is able to accurately discriminate between infant sleep states. This is a promising step toward development of a minimal-channel automatic sleep state classification system.

Genetic component in learning ability in bees.

PubMed

Kerr, W E; Moura Duarte, F A; Oliveira, R S

1975-10-01

Twenty-five bees, five from each of five hives, were trained to collect food at a table. When the bee reached the table, time was recorded for 12 visits. Then a blue and yellow pan was substituted for the original metal pan, and time and correct responses were recorded for 30 trips (discrimination phase). Finally, food was taken from the pan and extinction was recorded as incorrect responses for 20 visits. Variance analysis was carried out, and genetic variance was undetected for discrimination, but was detected for extinction. It is concluded that learning is very important for bees, so that any impairment in such ability affects colony survival.

Non-destructive fraud detection in rosehip oil by MIR spectroscopy and chemometrics.

PubMed

Santana, Felipe Bachion de; Gontijo, Lucas Caixeta; Mitsutake, Hery; Mazivila, Sarmento Júnior; Souza, Leticia Maria de; Borges Neto, Waldomiro

2016-10-15

Rosehip oil (Rosa eglanteria L.) is an important oil in the food, pharmaceutical and cosmetic industries. However, due to its high added value, it is liable to adulteration with other cheaper or lower quality oils. With this perspective, this work provides a new simple, fast and accurate methodology using mid-infrared (MIR) spectroscopy and partial least squares discriminant analysis (PLS-DA) as a means to discriminate authentic rosehip oil from adulterated rosehip oil containing soybean, corn and sunflower oils in different proportions. The model showed excellent sensitivity and specificity with 100% correct classification. Therefore, the developed methodology is a viable alternative for use in the laboratory and industry for standard quality analysis of rosehip oil since it is fast, accurate and non-destructive. Copyright © 2016 Elsevier Ltd. All rights reserved.

Delayed temporal discrimination in pigeons: A comparison of two procedures

PubMed Central

Chatlosh, Diane L.; Wasserman, Edward A.

1987-01-01

A within-subjects comparison was made of pigeons' performance on two temporal discrimination procedures that were signaled by differently colored keylight samples. During stimulus trials, a peck on the key displaying a slanted line was reinforced following short keylight samples, and a peck on the key displaying a horizontal line was reinforced following long keylight samples, regardless of the location of the stimuli on those two choice keys. During position trials, a peck on the left key was reinforced following short keylight samples and a peck on the right key was reinforced following long keylight samples, regardless of which line stimulus appeared on the correct key. Thus, on stimulus trials, the correct choice key could not be discriminated prior to the presentation of the test stimuli, whereas on position trials, the correct choice key could be discriminated during the presentation of the sample stimulus. During Phase 1, with a 0-s delay between sample and choice stimuli, discrimination learning was faster on position trials than on stimulus trials for all 4 birds. During Phase 2, 0-, 0.5-, and 1.0-s delays produced differential loss of stimulus control under the two tasks for 2 birds. Response patterns during the delay intervals provided some evidence for differential mediation of the two delayed discriminations. These between-task differences suggest that the same processes may not mediate performance in each. PMID:16812483

Discrimination and chemical phylogenetic study of seven species of Dendrobium using infrared spectroscopy combined with cluster analysis

NASA Astrophysics Data System (ADS)

Luo, Congpei; He, Tao; Chun, Ze

2013-04-01

Dendrobium is a commonly used and precious herb in Traditional Chinese Medicine. The high biodiversity of Dendrobium and the therapeutic needs require tools for the correct and fast discrimination of different Dendrobium species. This study investigates Fourier transform infrared spectroscopy followed by cluster analysis for discrimination and chemical phylogenetic study of seven Dendrobium species. Despite the general pattern of the IR spectra, different intensities, shapes, peak positions were found in the IR spectra of these samples, especially in the range of 1800-800 cm-1. The second derivative transformation and alcoholic extracting procedure obviously enlarged the tiny spectral differences among these samples. The results indicated each Dendrobium species had a characteristic IR spectra profile, which could be used to discriminate them. The similarity coefficients among the samples were analyzed based on their second derivative IR spectra, which ranged from 0.7632 to 0.9700, among the seven Dendrobium species, and from 0.5163 to 0.9615, among the ethanol extracts. A dendrogram was constructed based on cluster analysis the IR spectra for studying the chemical phylogenetic relationships among the samples. The results indicated that D. denneanum and D. crepidatum could be the alternative resources to substitute D. chrysotoxum, D. officinale and D. nobile which were officially recorded in Chinese Pharmacopoeia. In conclusion, with the advantages of high resolution, speediness and convenience, the experimental approach can successfully discriminate and construct the chemical phylogenetic relationships of the seven Dendrobium species.

[Discriminating power of socio-demographic and psychological variables on addictive use of cellular phones among middle school students].

PubMed

Lee, Haejung; Kim, Myoung Soo; Son, Hyun Kyung; Ahn, Sukhee; Kim, Jung Soon; Kim, Young Hae

2007-10-01

The purpose of this study was to examine the degrees of cellular phone usage among middle school students and to identify discriminating factors of addictive use of cellular phones among sociodemographic and psychological variables. From 123 middle schools in Busan, potential participants were identified through stratified random sampling and 747 middle school students participated in the study. The data was collected from December 1, 2004 to December 30, 2004. Descriptive and discriminant analyses were used. Fifty seven percent of the participants were male and 89.7% used cellular phones at school. The participants were grouped into three groups depending on the levels of the cellular phone usage: addicted (n=117), dependent (n=418), non-addicted (n=212). Within the three groups, two functions were produced and only one function was significant, discriminating the addiction group from non-addiction group. Additional discriminant analysis with only two groups produced one function that classified 81.2% of the participants correctly into the two groups. Impulsiveness, anxiety, and stress were significant discriminating factors. Based on the findings of this study, developing intervention programs focusing on impulsiveness, anxiety and stress to reduce the possible addictive use of cellular phones is suggested.

Rapid discrimination and determination of antibiotics drugs in plastic syringes using near infrared spectroscopy with chemometric analysis: Application to amoxicillin and penicillin.

PubMed

Lê, Laetitia Minh Mai; Eveleigh, Luc; Hasnaoui, Ikram; Prognon, Patrice; Baillet-Guffroy, Arlette; Caudron, Eric

2017-05-10

The aim of this study was to investigate near infrared spectroscopy (NIRS) combined to chemometric analysis to discriminate and quantify three antibiotics by direct measurement in plastic syringes.Solutions of benzylpenicillin (PENI), amoxicillin (AMOX) and amoxicillin/clavulanic acid (AMOX/CLAV) were analyzed at therapeutic concentrations in glass vials and plastic syringes with NIR spectrometer by direct measurement. Chemometric analysis using partial least squares regression and discriminative analysis was conducted to develop qualitative and quantitative calibration models. Discrimination of the three antibiotics was optimal for concentrated solutions with 100% of accuracy. For quantitative analysis, the three antibiotics furnished a linear response (R²>0.9994) for concentrations ranging from 0.05 to 0.2 g/mL for AMOX, 0.1 to 1.0 MUI/mL for PENI and 0.005 to 0.05 g/mL for AMOX/CLAV with excellent repeatability (maximum 1.3%) and intermediate precision (maximum of 3.2%). Based on proposed models, 94.4% of analyzed AMOX syringes, 80.0% of AMOX/CLAV syringes and 85.7% of PENI syringes were compliant with a relative error including the limit of ± 15%.NIRS as rapid, non-invasive and non-destructive analytical method represents a potentially powerful tool to further develop for securing the drug administration circuit of healthcare institutions to ensure that patients receive the correct product at the right dose. Copyright © 2017 Elsevier B.V. All rights reserved.

Infrasound Signals as Basis for Event Discriminants

DTIC Science & Technology

2007-09-01

tests ( UGT ) at the NTS, some work was done on finding discriminants between UGTs and earthquakes. Plots of wind-corrected infrasound pressure amplitude...probably due to the longer duration of earthquake motion compared to the Figure 1. These figure illustrate the initial comparisons for UGTs and...earthquakes for signal duration (left) and wind corrected amplitude (right) as functions of Mb. relatively short duration for a UGT . On the other hand

Application of Fourier transform infrared spectroscopy and chemometrics for differentiation of Salmonella enterica serovar Enteritidis phage types.

PubMed

Preisner, Ornella; Guiomar, Raquel; Machado, Jorge; Menezes, José Cardoso; Lopes, João Almeida

2010-06-01

Fourier transform infrared (FT-IR) spectroscopy and chemometric techniques were used to discriminate five closely related Salmonella enterica serotype Enteritidis phage types, phage type 1 (PT1), PT1b, PT4b, PT6, and PT6a. Intact cells and outer membrane protein (OMP) extracts from bacterial cell membranes were subjected to FT-IR analysis in transmittance mode. Spectra were collected over a wavenumber range from 4,000 to 600 cm(-1). Partial least-squares discriminant analysis (PLS-DA) was used to develop calibration models based on preprocessed FT-IR spectra. The analysis based on OMP extracts provided greater separation between the Salmonella Enteritidis PT1-PT1b, PT4b, and PT6-PT6a groups than the intact cell analysis. When these three phage type groups were considered, the method based on OMP extract FT-IR spectra was 100% accurate. Moreover, complementary local models that considered only the PT1-PT1b and PT6-PT6a groups were developed, and the level of discrimination increased. PT1 and PT1b isolates were differentiated successfully with the local model using the entire OMP extract spectrum (98.3% correct predictions), whereas the accuracy of discrimination between PT6 and PT6a isolates was 86.0%. Isolates belonging to different phage types (PT19, PT20, and PT21) were used with the model to test its robustness. For the first time it was demonstrated that FT-IR analysis of OMP extracts can be used for construction of robust models that allow fast and accurate discrimination of different Salmonella Enteritidis phage types.

Geographical identification of saffron (Crocus sativus L.) by linear discriminant analysis applied to the UV-visible spectra of aqueous extracts.

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna

2017-03-15

We attempted geographical classification of saffron using UV-visible spectroscopy, conventionally adopted for quality grading according to the ISO Normative 3632. We investigated 81 saffron samples produced in L'Aquila, Città della Pieve, Cascia, and Sardinia (Italy) and commercial products purchased in various supermarkets. Exploratory principal component analysis applied to the UV-vis spectra of saffron aqueous extracts revealed a clear differentiation of the samples belonging to different quality categories, but a poor separation according to the geographical origin of the spices. On the other hand, linear discriminant analysis based on 8 selected absorbance values, concentrated near 279, 305 and 328nm, allowed a good distinction of the spices coming from different sites. Under severe validation conditions (30% and 50% of saffron samples in the evaluation set), correct predictions were 85 and 83%, respectively. Copyright © 2016 Elsevier Ltd. All rights reserved.

Predicting plantar fasciitis in runners.

PubMed

Warren, B L; Jones, C J

1987-02-01

Ninety-one runners were studied to determine whether specific variables were indicative of runners who had suffered with plantar fasciitis either presently or formerly vs runners who had never suffered with plantar fasciitis. Each runner was asked to complete a running history, was subjected to several anatomical measurements, and was asked to run on a treadmill in both a barefoot and shoe condition at a speed of 3.35 mps (8 min mile pace). Factor coefficients were used in a discriminant function analysis which revealed that, when group membership was predicted, 63% of the runners could be correctly assigned to their group. Considering that 76% of the control group was correctly predicted, it was concluded that the predictor variables were able to correctly predict membership of the control group, but not able to correctly predict the presently or formerly injured sufferers of plantar fasciitis.

Role of internal marketing, organizational commitment, and job stress in discerning the turnover intention of Korean nurses.

PubMed

Lee, Haejung; Kim, Myoung-Soo; Yoon, Jung-A

2011-06-01

The purpose of this study was to examine the discriminating factors of Korean nurses' turnover intention (TI) among internal marketing (IM), organizational commitment (OC), and job stress (JS). Nurses (n = 185) who had worked for 1-10 years were surveyed from six general hospitals in South Korea. The data were collected by using questionnaires and were analyzed with descriptive statistics and discriminant analysis. The participants were grouped into three groups, depending on the level of their TI: "low TI group" (n = 58), "moderate TI group" (n = 96), and "high TI group" (n = 31). One function significantly discriminated between the high TI and low TI groups. The function correctly classified 84.3% of the participants into the two groups and 75.3% were correctly classified in the cross-validation. Organizational commitment was the most important factor. Job stress and the IM components of staffing-promotion, reward, management philosophy, working environment, and segmentation were significant discriminant factors of TI. Based on the findings of this study, we could conclude that OC, JS, and IM play important roles in the TI of nurses. Implying a career development system as an OC management strategy, an innovative promotion policy to change conservative organizational climates and a balance of effort-reward can be considered as managerial interventions to reduce nurses' TI. © 2010 The Authors. Japan Journal of Nursing Science © 2010 Japan Academy of Nursing Science.

Discriminating talent-identified junior Australian football players using a video decision-making task.

PubMed

Woods, Carl T; Raynor, Annette J; Bruce, Lyndell; McDonald, Zane

2016-01-01

This study examined if a video decision-making task could discriminate talent-identified junior Australian football players from their non-talent-identified counterparts. Participants were recruited from the 2013 under 18 (U18) West Australian Football League competition and classified into two groups: talent-identified (State U18 Academy representatives; n = 25; 17.8 ± 0.5 years) and non-talent-identified (non-State U18 Academy selection; n = 25; 17.3 ± 0.6 years). Participants completed a video decision-making task consisting of 26 clips sourced from the Australian Football League game-day footage, recording responses on a sheet provided. A score of "1" was given for correct and "0" for incorrect responses, with the participants total score used as the criterion value. One-way analysis of variance tested the main effect of "status" on the task criterion, whilst a bootstrapped receiver operating characteristic (ROC) curve assessed the discriminant ability of the task. An area under the curve (AUC) of 1 (100%) represented perfect discrimination. Between-group differences were evident (P < 0.05) and the ROC curve was maximised with a score of 15.5/26 (60%) (AUC = 89.0%), correctly classifying 92% and 76% of the talent-identified and non-talent-identified participants, respectively. Future research should investigate the mechanisms leading to the superior decision-making observed in the talent-identified group.

A retrieval-based approach to eliminating hindsight bias.

PubMed

Van Boekel, Martin; Varma, Keisha; Varma, Sashank

2017-03-01

Individuals exhibit hindsight bias when they are unable to recall their original responses to novel questions after correct answers are provided to them. Prior studies have eliminated hindsight bias by modifying the conditions under which original judgments or correct answers are encoded. Here, we explored whether hindsight bias can be eliminated by manipulating the conditions that hold at retrieval. Our retrieval-based approach predicts that if the conditions at retrieval enable sufficient discrimination of memory representations of original judgments from memory representations of correct answers, then hindsight bias will be reduced or eliminated. Experiment 1 used the standard memory design to replicate the hindsight bias effect in middle-school students. Experiments 2 and 3 modified the retrieval phase of this design, instructing participants beforehand that they would be recalling both their original judgments and the correct answers. As predicted, this enabled participants to form compound retrieval cues that discriminated original judgment traces from correct answer traces, and eliminated hindsight bias. Experiment 4 found that when participants were not instructed beforehand that they would be making both recalls, they did not form discriminating retrieval cues, and hindsight bias returned. These experiments delineate the retrieval conditions that produce-and fail to produce-hindsight bias.

The relationship between perceived discrimination and patient experiences with health care.

PubMed

Weech-Maldonado, Robert; Hall, Allyson; Bryant, Thomas; Jenkins, Kevin A; Elliott, Marc N

2012-09-01

Prior studies have shown that racial/ethnic minorities have lower Consumer Assessments of Healthcare Providers and Systems (CAHPS) scores. Perceived discrimination may mediate the relationship between race/ethnicity and patient experiences with care. To examine the relationship between perceived discrimination based on race/ethnicity and Medicaid insurance and CAHPS reports and ratings of care. The study analyzed 2007 survey data from 1509 Florida Medicaid beneficiaries. CAHPS reports (getting needed care, timeliness of care, communication with doctor, and health plan customer service) and ratings (personal doctor, specialist care, overall health care, and health plan) of care were the primary outcome variables. Patient perceptions of discrimination based on their race/ethnicity and having Medicaid insurance were the primary independent variables. Regression analysis modeled the effect of perceptions of discrimination on CAHPS reports and ratings controlling for age, sex, education, self-rated health status, race/ethnicity, survey language, and fee-for-service enrollment. SEs were corrected for correlation within plans. Medicaid beneficiaries reporting discrimination based on race/ethnicity had lower CAHPS scores, ranging from 15 points lower (on a 0-100 scale) for getting needed care to 6 points lower for specialist rating, compared with those who never experienced discrimination. Similar results were obtained for perceived discrimination based on Medicaid insurance. Perceptions of discrimination based on race/ethnicity and Medicaid insurance are prevalent and are associated with substantially lower CAHPS reports and ratings of care. Practices must develop and implement strategies to reduce perceived discrimination among patients.

Theoretical vs. empirical discriminability: the application of ROC methods to eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2018-01-01

Receiver operating characteristic (ROC) analysis was introduced to the field of eyewitness identification 5 years ago. Since that time, it has been both influential and controversial, and the debate has raised an issue about measuring discriminability that is rarely considered. The issue concerns the distinction between empirical discriminability (measured by area under the ROC curve) vs. underlying/theoretical discriminability (measured by d' or variants of it). Under most circumstances, the two measures will agree about a difference between two conditions in terms of discriminability. However, it is possible for them to disagree, and that fact can lead to confusion about which condition actually yields higher discriminability. For example, if the two conditions have implications for real-world practice (e.g., a comparison of competing lineup formats), should a policymaker rely on the area-under-the-curve measure or the theory-based measure? Here, we illustrate the fact that a given empirical ROC yields as many underlying discriminability measures as there are theories that one is willing to take seriously. No matter which theory is correct, for practical purposes, the singular area-under-the-curve measure best identifies the diagnostically superior procedure. For that reason, area under the ROC curve informs policy in a way that underlying theoretical discriminability never can. At the same time, theoretical measures of discriminability are equally important, but for a different reason. Without an adequate theoretical understanding of the relevant task, the field will be in no position to enhance empirical discriminability.

Classification of edible oils by employing 31P and 1H NMR spectroscopy in combination with multivariate statistical analysis. A proposal for the detection of seed oil adulteration in virgin olive oils.

PubMed

Vigli, Georgia; Philippidis, Angelos; Spyros, Apostolos; Dais, Photis

2003-09-10

A combination of (1)H NMR and (31)P NMR spectroscopy and multivariate statistical analysis was used to classify 192 samples from 13 types of vegetable oils, namely, hazelnut, sunflower, corn, soybean, sesame, walnut, rapeseed, almond, palm, groundnut, safflower, coconut, and virgin olive oils from various regions of Greece. 1,2-Diglycerides, 1,3-diglycerides, the ratio of 1,2-diglycerides to total diglycerides, acidity, iodine value, and fatty acid composition determined upon analysis of the respective (1)H NMR and (31)P NMR spectra were selected as variables to establish a classification/prediction model by employing discriminant analysis. This model, obtained from the training set of 128 samples, resulted in a significant discrimination among the different classes of oils, whereas 100% of correct validated assignments for 64 samples were obtained. Different artificial mixtures of olive-hazelnut, olive-corn, olive-sunflower, and olive-soybean oils were prepared and analyzed by (1)H NMR and (31)P NMR spectroscopy. Subsequent discriminant analysis of the data allowed detection of adulteration as low as 5% w/w, provided that fresh virgin olive oil samples were used, as reflected by their high 1,2-diglycerides to total diglycerides ratio (D > or = 0.90).

Prediction of Nonalcoholic Fatty Liver Disease Via a Novel Panel of Serum Adipokines

PubMed Central

Jamali, Raika; Arj, Abbas; Razavizade, Mohsen; Aarabi, Mohammad Hossein

2016-01-01

Abstract Considering limitations of liver biopsy for diagnosis of nonalcoholic liver disease (NAFLD), biomarkers’ panels were proposed. The aims of this study were to establish models based on serum adipokines for discriminating NAFLD from healthy individuals and nonalcoholic steatohepatitis (NASH) from simple steatosis. This case-control study was conducted in patients with persistent elevated serum aminotransferase levels and fatty liver on ultrasound. Individuals with evidence of alcohol consumption, hepatotoxic medication, viral hepatitis, and known liver disease were excluded. Liver biopsy was performed in the remaining patients to distinguish NAFLD/NASH. Histologic findings were interpreted using “nonalcoholic fatty liver activity score.” Control group consisted of healthy volunteers with normal physical examination, liver function tests, and liver ultrasound. Binary logistic regression analysis was applied to ascertain the effects of independent variables on the likelihood that participants have NAFLD/NASH. Decreased serum adiponectin and elevated serum visfatin, IL-6, TNF-a were associated with an increased likelihood of exhibiting NAFLD. NAFLD discriminant score was developed as the following: [(−0.298 × adiponectin) + (0.022 × TNF-a) + (1.021 × Log visfatin) + (0.709 × Log IL-6) + 1.154]. In NAFLD discriminant score, 86.4% of original grouped cases were correctly classified. Discriminant score threshold value of (−0.29) yielded a sensitivity and specificity of 91% and 83% respectively, for discriminating NAFLD from healthy controls. Decreased serum adiponectin and elevated serum visfatin, IL-8, TNF-a were correlated with an increased probability of NASH. NASH discriminant score was proposed as the following: [(−0.091 × adiponectin) + (0.044 × TNF-a) + (1.017 × Log visfatin) + (0.028 × Log IL-8) − 1.787] In NASH model, 84% of original cases were correctly classified. Discriminant score threshold value of (−0.22) yielded a sensitivity and specificity of 90% and 66% respectively, for separating NASH from simple steatosis. New discriminant scores were introduced for differentiating NAFLD/NASH patients with a high accuracy. If verified by future studies, application of suggested models for screening of NAFLD/NASH seems reasonable. PMID:26844476

"Perceived age discrimination across age in Europe: From an ageing society to a society for all ages": Correction to Bratt et al. (2018).

PubMed

2018-03-01

Reports an error in "Perceived age discrimination across age in Europe: From an ageing society to a society for all ages" by Christopher Bratt, Dominic Abrams, Hannah J. Swift, Christin-Melanie Vauclair and Sibila Marques ( Developmental Psychology , 2018[Jan], Vol 54[1], 167-180). In the article, the copyright license has been changed to the Creative Commons CC-BY Attribution License. The online version of this article has been corrected. (The following abstract of the original article appeared in record 2017-47508-001.) Ageism is recognized as a significant obstacle to older people's well-being, but age discrimination against younger people has attracted less attention. We investigate levels of perceived age discrimination across early to late adulthood, using data from the European Social Survey (ESS), collected in 29 countries (N = 56,272). We test for approximate measurement invariance across countries. We use local structural equation modeling as well as moderated nonlinear factor analysis to test for measurement invariance across age as a continuous variable. Using models that account for the moderate degree of noninvariance, we find that younger people report experiencing the highest levels of age discrimination. We also find that national context substantially affects levels of ageism experienced among older respondents. The evidence highlights that more research is needed to address ageism in youth and across the life span, not just old adulthood. It also highlights the need to consider factors that differently contribute to forms of ageism experienced by people at different life stages and ages. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

45 CFR 1225.10 - Corrective action.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 4 2011-10-01 2011-10-01 false Corrective action. 1225.10 Section 1225.10 Public... Corrective action. When it has been determined by Final Agency Decision that the aggrieved party has been subjected to illegal discrimination, the following corrective actions may be taken: (a) Selection as a...

45 CFR 1225.10 - Corrective action.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 4 2010-10-01 2010-10-01 false Corrective action. 1225.10 Section 1225.10 Public... Corrective action. When it has been determined by Final Agency Decision that the aggrieved party has been subjected to illegal discrimination, the following corrective actions may be taken: (a) Selection as a...

[Two cases of fluent aphasia with selective difficulty of syllable identification].

PubMed

Endo, K; Suzuki, K; Yamadori, A; Fujii, T; Tobita, M; Ohtake, H

1999-10-01

We report two aphasic patients who could discriminate Japanese syllables but could not identify them. Case 1 was a 51-year-old right handed woman with 12-year education. Case 2 was a 50-year-old right handed man with 9-year education. They developed fluent aphasia after a cerebral infarction. Brain MRI of case 1 revealed widely distributed lesions including inferior frontal, superior temporal, angular and supramarginal gyri. Lesions revealed by Brain CT in case 2 included the left superior and middle temporal, angular and supramarginal gyri. Both showed severe impairment of repetition and confrontation naming. No difference of performance was present between repetition of single syllables and polysyllabic words. On the contrary, oral reading of Kana characters were preserved. We examined their ability to perceive syllables in detail. In the discrimination task, they judged whether a pair of heard syllables was same or different. Case 1 was correct in 85% of the tasks and case 2 in 98%. In an identification task, they heard a syllable and chose a corresponding Kana, Kanji, or picture out of 10 respective candidates. Case 1 was correct only in 30% and case 2 in 50% of these tasks. On the other hand, selection of a correct target in response to a polysyllabic word was much better, i.e. 70% in case 1 and 90% in case 2. Based on these data we concluded that (1) syllabic identification is a different process from syllabic discrimination, and (2) comprehension of a polysyllabic word can be achieved even when the precise phonological analysis of continuent syllables are impaired.

Sex estimation from measurements of the first rib in a contemporary Polish population.

PubMed

Kubicka, Anna Maria; Piontek, Janusz

2016-01-01

The aim of this study was to evaluate the accuracy of sex assessment using measurements of the first rib from computed tomography (CT) to develop a discriminant formula. Four discriminant formulae were derived based on CT imaging of the right first rib of 85 female and 91 male Polish patients of known age and sex. In direct discriminant analysis, the first equation consisted of all first rib variables; the second included measurements of the rib body; the third comprised only two measurements of the sternal end of the first rib. The stepwise method selected the four best variables from all measurements. The discriminant function equation was then tested on a cross-validated group consisting of 23 females and 24 males. The direct discriminant analysis showed that sex assessment was possible in 81.5% of cases in the first group and in 91.5% in the cross-validated group when all variables for the first rib were included. The average accuracy for the original group for rib body and sternal end was 80.9 and 67.9%, respectively. The percentages of correctly assigned individuals for the functions based on the rib body and sternal end in the cross-validated group were 76.6 and 85.0%, respectively. Higher average accuracies were obtained for stepwise discriminant analysis: 83.1% for the original group and 91.2% for the cross-validated group. The exterior edge, anterior-posterior of the sternal end, and depth of the arc were the most reliable parameters. Our results suggest that the first rib is dimorphic and that the described method can be used for sex assessment.

Comparison of diverse methods for the correction of atmospheric effects on LANDSAT and SKYLAB images. [radiometric correction in Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Camara, G.; Dias, L. A. V.; Mascarenhas, N. D. D.; Desouza, R. C. M.; Pereira, A. E. C.

1982-01-01

Earth's atmosphere reduces a sensors ability in currently discriminating targets. Using radiometric correction to reduce the atmospheric effects may improve considerably the performance of an automatic image interpreter. Several methods for radiometric correction from the open literature are compared leading to the development of an atmospheric correction system.

A Pilot Study Combining a GC-Sensor Device with a Statistical Model for the Identification of Bladder Cancer from Urine Headspace

PubMed Central

Khalid, Tanzeela; White, Paul; De Lacy Costello, Ben; Persad, Raj; Ewen, Richard; Johnson, Emmanuel; Probert, Chris S.; Ratcliffe, Norman

2013-01-01

There is a need to reduce the number of cystoscopies on patients with haematuria. Presently there are no reliable biomarkers to screen for bladder cancer. In this paper, we evaluate a new simple in–house fabricated, GC-sensor device in the diagnosis of bladder cancer based on volatiles. Sensor outputs from 98 urine samples were used to build and test diagnostic models. Samples were taken from 24 patients with transitional (urothelial) cell carcinoma (age 27-91 years, median 71 years) and 74 controls presenting with urological symptoms, but without a urological malignancy (age 29-86 years, median 64 years); results were analysed using two statistical approaches to assess the robustness of the methodology. A two-group linear discriminant analysis method using a total of 9 time points (which equates to 9 biomarkers) correctly assigned 24/24 (100%) of cancer cases and 70/74 (94.6%) controls. Under leave-one-out cross-validation 23/24 (95.8%) of cancer cases were correctly predicted with 69/74 (93.2%) of controls. For partial least squares discriminant analysis, the correct leave-one-out cross-validation prediction values were 95.8% (cancer cases) and 94.6% (controls). These data are an improvement on those reported by other groups studying headspace gases and also superior to current clinical techniques. This new device shows potential for the diagnosis of bladder cancer, but the data must be reproduced in a larger study. PMID:23861976

Characterization and detection of Anopheles vestitipennis and Anopheles punctimacula (Diptera: Culicidae) larval habitats in Belize with field survey and SPOT satellite imagery

NASA Technical Reports Server (NTRS)

Rejmankova, E.; Pope, K. O.; Roberts, D. R.; Lege, M. G.; Andre, R.; Greico, J.; Alonzo, Y.

1998-01-01

Surveys of larval habitats of Anopheles vestitipennis and Anopheles punctimacula were conducted in Belize, Central America. Habitat analysis and classification resulted in delineation of eight habitat types defined by dominant life forms and hydrology. Percent cover of tall dense macrophytes, shrubs, open water, and pH were significantly different between sites with and without An. vestitipennis. For An. punctimacula, percent cover of tall dense macrophytes, trees, detritus, open water, and water depth were significantly different between larvae positive and negative sites. The discriminant function for An. vestitipennis correctly predicted the presence of larvae in 65% of sites and correctly predicted the absence of larvae in 88% of sites. The discriminant function for An. punctimacula correctly predicted 81% of sites for the presence of larvae and 45% for the absence of larvae. Canonical discriminant analysis of the three groups of habitats (An. vestitipennis positive; An. punctimacula positive; all negative) confirmed that while larval habitats of An. punctimacula are clustered in the tree dominated area, larval habitats of An. vestitipennis were found in both tree dominated and tall dense macrophyte dominated environments. The forest larval habitats of An. vestitipennis and An. punctimacula seem to be randomly distributed among different forest types. Both species tend to occur in denser forests with more detritus, shallower water, and slightly higher pH. Classification of dry season (February) SPOT multispectral satellite imagery produced 10 land cover types with the swamp forest and tall dense marsh classes being of particular interest. The accuracy assessment showed that commission errors for the tall, dense marsh and swamp forest appeared to be minor; but omission errors were significant, especially for the swamp forest (perhaps because no swamp forests are flooded in February). This means that where the classification indicates there are An. vestitipennis breeding sites, they probably do exist; but breeding sites in many locations are not identified and could be more abundant than indicated.

Inter- and intraspecific diversity in Cistus L. (Cistaceae) seeds, analysed with computer vision techniques.

PubMed

Lo Bianco, M; Grillo, O; Cañadas, E; Venora, G; Bacchetta, G

2017-03-01

This work aims to discriminate among different species of the genus Cistus, using seed parameters and following the scientific plant names included as accepted in The Plant List. Also, the intraspecific phenotypic differentiation of C. creticus, through comparison with three subspecies (C. creticus subsp. creticus, C. c. subsp. eriocephalus and C. c. subsp. corsicus), as well as the interpopulation variability among five C. creticus subsp. eriocephalus populations was evaluated. Seed mean weight and 137 morphocolorimetric quantitative variables, describing shape, size, colour and textural seed traits, were measured using image analysis techniques. Measured data were analysed applying step-wise linear discriminant analysis. An overall cross-validated classification performance of 80.6% was recorded at species level. With regard to C. creticus, as case study, percentages of correct discrimination of 96.7% and 99.6% were achieved at intraspecific and interpopulation levels, respectively. In this classification model, the relevance of the colorimetric and textural descriptive features was highlighted, as well as the seed mean weight, which was the most discriminant feature at specific and intraspecific level. These achievements proved the ability of the image analysis system as highly diagnostic for systematic purposes and confirm that seeds in the genus Cistus have important diagnostic value. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.

Aroma volatiles obtained at harvest by HS-SPME/GC-MS and INDEX/MS-E-nose fingerprint discriminate climacteric behaviour in melon fruit.

PubMed

Chaparro-Torres, Libia A; Bueso, María C; Fernández-Trujillo, Juan P

2016-05-01

Melon aroma volatiles were extracted at harvest from juice of a climacteric near-isogenic line (NIL) SC3-5-1 with two quantitative trait loci (QTLs) introgressed which produced climacteric behaviour and its non-climacteric parental (PS) using two methodologies of analysis: static headspace solid phase micro-extraction (HS-SPME) by gas chromatography-mass spectrometry (GC-MS) and inside needle dynamic extraction (INDEX) by MS-based electronic nose (MS-E-nose). Of the 137 volatiles compounds identified, most were found at significantly higher concentrations in SC3-5-1 than in PS in both seasons. These volatiles were mostly esters, alcohols, sulfur-derived esters and even some aldehydes and others. The number of variables with high correlation values was reduced by using correlation network analysis. Partial least squares-discriminant analysis (PLS-DA) achieved the correct classification of PS and SC3-5-1. The ions m/z 74, 91, 104, 105, 106 and 108, mainly volatile derivatives precursor phenylalanine, were the most discriminant in SC3-5-1 and PS. As many as 104 QTLs were mapped in season 1 and at least 78 QTLs in each season with an effect above the PS mean. GC-MS gave better discrimination than E-nose. Most of the QTLs that mapped in both seasons enhanced aroma volatiles associated with climacteric behaviour. © 2015 Society of Chemical Industry.

The contribution of cluster and discriminant analysis to the classification of complex aquifer systems.

PubMed

Panagopoulos, G P; Angelopoulou, D; Tzirtzilakis, E E; Giannoulopoulos, P

2016-10-01

This paper presents an innovated method for the discrimination of groundwater samples in common groups representing the hydrogeological units from where they have been pumped. This method proved very efficient even in areas with complex hydrogeological regimes. The proposed method requires chemical analyses of water samples only for major ions, meaning that it is applicable to most of cases worldwide. Another benefit of the method is that it gives a further insight of the aquifer hydrogeochemistry as it provides the ions that are responsible for the discrimination of the group. The procedure begins with cluster analysis of the dataset in order to classify the samples in the corresponding hydrogeological unit. The feasibility of the method is proven from the fact that the samples of volcanic origin were separated into two different clusters, namely the lava units and the pyroclastic-ignimbritic aquifer. The second step is the discriminant analysis of the data which provides the functions that distinguish the groups from each other and the most significant variables that define the hydrochemical composition of the aquifer. The whole procedure was highly successful as the 94.7 % of the samples were classified to the correct aquifer system. Finally, the resulted functions can be safely used to categorize samples of either unknown or doubtful origin improving thus the quality and the size of existing hydrochemical databases.

Artificial nose, NIR and UV-visible spectroscopy for the characterisation of the PDO Chianti Classico olive oil.

PubMed

Forina, M; Oliveri, P; Bagnasco, L; Simonetti, R; Casolino, M C; Nizzi Grifi, F; Casale, M

2015-11-01

An authentication study of the Italian PDO (Protected Designation of Origin) olive oil Chianti Classico, based on artificial nose, near-infrared and UV-visible spectroscopy, with a set of samples representative of the whole Chianti Classico production area and a considerable number of samples from other Italian PDO regions was performed. The signals provided by the three analytical techniques were used both individually and jointly, after fusion of the respective variables, in order to build a model for the Chianti Classico PDO olive oil. Different signal pre-treatments were performed in order to investigate their importance and their effects in enhancing and extracting information from experimental data, correcting backgrounds or removing baseline variations. Stepwise-Linear Discriminant Analysis (STEP-LDA) was used as a feature selection technique and, afterward, Linear Discriminant Analysis (LDA) and the class-modelling technique Quadratic Discriminant Analysis-UNEQual dispersed classes (QDA-UNEQ) were applied to sub-sets of selected variables, in order to obtain efficient models capable of characterising the extra virgin olive oils produced in the Chianti Classico PDO area. Copyright © 2015 Elsevier B.V. All rights reserved.

Temporal stability of otolith elemental fingerprints discriminates among lagoon nursery habitats

NASA Astrophysics Data System (ADS)

Tournois, Jennifer; Ferraton, Franck; Velez, Laure; McKenzie, David J.; Aliaume, Catherine; Mercier, Lény; Darnaude, Audrey M.

2013-10-01

The chemical composition of fish otoliths reflects that of the water masses that they inhabit. Otolith elemental compositions can, therefore, be used as natural tags to discriminate among habitats. However, for retrospective habitat identification to be valid and reliable for any adult, irrespective of its age, significant differences in environmental conditions, and therefore otolith signatures, must be temporally stable within each habitat, otherwise connectivity studies have to be carried out by matching year-classes to the corresponding annual fingerprints. This study investigated how various different combinations of chemical elements in otoliths could distinguish, over three separate years, between four coastal lagoon habitats used annually as nurseries by gilthead sea bream (Sparus aurata L.) in the Gulf of Lions (NW Mediterranean). A series of nine elements were measured in otoliths of 301 S. aurata juveniles collected in the four lagoons in 2008, 2010 and 2011. Percentages of correct re-assignment of juveniles to their lagoon of origin were calculated with the Random Forest classification method, considering every possible combination of elements. This revealed both spatial and temporal variations in accuracy of habitat identification, with correct re-assignment to each lagoon ranging from 44 to 99% depending on the year and the lagoon. There were also annual differences in the combination of elements that provided the best discrimination among the lagoons. Despite this, when the data from the three years were pooled, a combination of eight elements (B, Ba, Cu, Li, Mg, Rb, Sr and Y) provided greater than 70% correct re-assignment to each single lagoon, with a multi-annual global accuracy of 79%. When considering the years separately, discrimination accuracy with these elemental fingerprints was above 90% for 2008 and 2010. It decreased to 61% in 2011, when unusually heavy rainfall occurred, which presumably reduced chemical differences among several of the lagoons. This study highlights the need for multi-annual sampling, and multi-elemental analysis, when developing otolith microchemical fingerprints to explore nursery habitat use in coastal fishes.

Proteomics-Derived Cerebrospinal Fluid Markers of Autopsy-Confirmed Alzheimer’s Disease

PubMed Central

Roher, Alex E.; Maarouf, Chera L.; Sue, Lucia I.; Hu, Yiran; Wilson, Jeffrey; Beach, Thomas G.

2010-01-01

The diagnostic performance of several candidate cerebrospinal fluid (CSF) protein biomarkers of neuropathologically-confirmed Alzheimer’s disease (AD), non-demented (ND) elderly controls and non-AD dementias (NADD) was assessed. Candidate markers were selected on the basis of initial 2-dimensional gel electrophoresis studies or by literature review. Markers selected by the former method included apolipoprotein A-1 (ApoA1), hemopexin (HPX), transthyretin (TTR) and pigment epithelium-derived factor (PEDF) while markers identified from the literature included Aβ1–40, Aβ1–42, total tau, phosphorylated tau, α-1 acid glycoprotein (A1GP), haptoglobin, zinc α-2 glycoprotein (Z2GP) and apolipoprotein E (ApoE). Ventricular CSF concentrations of the markers were measured by ELISA. The concentrations of Aβ1–42, ApoA1, A1GP, ApoE, HPX and Z2GP differed significantly among AD, ND and NADD subjects. Logistic regression analysis for the diagnostic discrimination of AD from ND found that Aβ1–42, ApoA1 and HPX each had significant and independent associations with diagnosis. The CSF concentrations of these three markers distinguished AD from ND subjects with 84% sensitivity and 72% specificity, with 78% of subjects correctly classified. By comparison, using Aβ1–42 alone gave 79% sensitivity and 61% specificity, with 68% of subjects correctly classified. For the diagnostic discrimination of AD from NADD, only the concentration of Aβ1–42 was significantly related to diagnosis, with a sensitivity of 58%, specificity of 86% and 86% correctly classified. The results indicate that for the discrimination of AD from ND control subjects, measurement of a set of markers including Aβ1–42, ApoA1 and HPX improved diagnostic performance over that obtained by measurement of Aβ1–42 alone. For the discrimination of AD from NADD subjects, measurement of Aβ1–42 alone was superior. PMID:19863188

The effects of errors on children's performance on a circle-ellipse discrimination.

PubMed

Stoddard, L T; Sidman, M

1967-05-01

Children first learned by means of a teaching program to discriminate a circle from relatively flat ellipses. Children in the control group then proceeded into a program which gradually reduced the difference between the circle and the ellipses. They advanced to a finer discrimination when they made a correct choice, and reversed to an easier discrimination after making errors ("backup" procedure). The children made relatively few errors until they approached the region of their difference threshold (empirically determined under the conditions described). When they could no longer discriminate the forms, they learned other bases for responding that could be classified as specifiable error patterns. Children in the experimental group, having learned the preliminary circle-ellipse discrimination, were started at the upper end of the ellipse series, where it was impossible for them to discriminate the forms. The backup procedure returned them to an easier discrimination after they made errors. They made many errors and reversed down through the ellipse series. Eventually, most of the children reached a point in the ellipse series where they abandoned their systematic errors and began to make correct first choices; then they advanced upward through the program. All of the children advanced to ellipse sizes that were much larger than the ellipse size at the point of their furthest descent.

Persistent topographic quantitative EEG sequelae of chronic marihuana use: a replication study and initial discriminant function analysis.

PubMed

Struve, F A; Straumanis, J J; Patrick, G

1994-04-01

In a previous pilot study using psychiatric patients we reported that daily marihuana users had significant elevations of (1) Absolute Alpha Power, (2) Relative Alpha Power, and (3) Interhemispheric Alpha Coherence over both frontal and frontal-central areas when contrasted with subjects who did not use marihuana. We referred to this phenomenon as Hyperfrontality of Alpha. The study presented here is a successful replication of our previous findings using new samples of subjects and identical methods. Post hoc analyses based on the combined sample from both studies suggest that variables of psychiatric diagnoses and medication did not bias our results. In addition, a discriminant function analysis using quantitative EEG variables as candidate predictors generated a 95% correct THC user versus nonuser classification accuracy which received a successful jackknife replication.

Prediction of the space adaptation syndrome

NASA Technical Reports Server (NTRS)

Reschke, M. F.; Homick, J. L.; Ryan, P.; Moseley, E. C.

1984-01-01

The univariate and multivariate relationships of provocative measures used to produce motion sickness symptoms were described. Normative subjects were used to develop and cross-validate sets of linear equations that optimally predict motion sickness in parabolic flights. The possibility of reducing the number of measurements required for prediction was assessed. After describing the variables verbally and statistically for 159 subjects, a factor analysis of 27 variables was completed to improve understanding of the relationships between variables and to reduce the number of measures for prediction purposes. The results of this analysis show that none of variables are significantly related to the responses to parabolic flights. A set of variables was selected to predict responses to KC-135 flights. A series of discriminant analyses were completed. Results indicate that low, moderate, or severe susceptibility could be correctly predicted 64 percent and 53 percent of the time on original and cross-validation samples, respectively. Both the factor analysis and the discriminant analysis provided no basis for reducing the number of tests.

Provenance Establishment of Stingless Bee Honey Using Multi-element Analysis in Combination with Chemometrics Techniques.

PubMed

Shadan, Aidil Fahmi; Mahat, Naji A; Wan Ibrahim, Wan Aini; Ariffin, Zaiton; Ismail, Dzulkiflee

2018-01-01

As consumption of stingless bee honey has been gaining popularity in many countries including Malaysia, ability to identify accurately its geographical origin proves pertinent for investigating fraudulent activities for consumer protection. Because a chemical signature can be location-specific, multi-element distribution patterns may prove useful for provenancing such product. Using the inductively coupled-plasma optical emission spectrometer as well as principal component analysis (PCA) and linear discriminant analysis (LDA), the distributions of multi-elements in stingless bee honey collected at four different geographical locations (North, West, East, and South) in Johor, Malaysia, were investigated. While cross-validation using PCA demonstrated 87.0% correct classification rate, the same was improved (96.2%) with the use of LDA, indicating that discrimination was possible for the different geographical regions. Therefore, utilization of multi-element analysis coupled with chemometrics techniques for assigning the provenance of stingless bee honeys for forensic applications is supported. © 2017 American Academy of Forensic Sciences.

Progress toward the determination of correct classification rates in fire debris analysis.

PubMed

Waddell, Erin E; Song, Emma T; Rinke, Caitlin N; Williams, Mary R; Sigman, Michael E

2013-07-01

Principal components analysis (PCA), linear discriminant analysis (LDA), and quadratic discriminant analysis (QDA) were used to develop a multistep classification procedure for determining the presence of ignitable liquid residue in fire debris and assigning any ignitable liquid residue present into the classes defined under the American Society for Testing and Materials (ASTM) E 1618-10 standard method. A multistep classification procedure was tested by cross-validation based on model data sets comprised of the time-averaged mass spectra (also referred to as total ion spectra) of commercial ignitable liquids and pyrolysis products from common building materials and household furnishings (referred to simply as substrates). Fire debris samples from laboratory-scale and field test burns were also used to test the model. The optimal model's true-positive rate was 81.3% for cross-validation samples and 70.9% for fire debris samples. The false-positive rate was 9.9% for cross-validation samples and 8.9% for fire debris samples. © 2013 American Academy of Forensic Sciences.

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

PubMed

Blasco, H; Błaszczyński, J; Billaut, J C; Nadal-Desbarats, L; Pradat, P F; Devos, D; Moreau, C; Andres, C R; Emond, P; Corcia, P; Słowiński, R

2015-02-01

Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data. Copyright © 2014 Elsevier Inc. All rights reserved.

Sexing California gulls using morphometrics and discriminant function analysis

USGS Publications Warehouse

Herring, Garth; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Takekawa, John Y.

2010-01-01

A discriminant function analysis (DFA) model was developed with DNA sex verification so that external morphology could be used to sex 203 adult California Gulls (Larus californicus) in San Francisco Bay (SFB). The best model was 97% accurate and included head-to-bill length, culmen depth at the gonys, and wing length. Using an iterative process, the model was simplified to a single measurement (head-to-bill length) that still assigned sex correctly 94% of the time. A previous California Gull sex determination model developed for a population in Wyoming was then assessed by fitting SFB California Gull measurement data to the Wyoming model; this new model failed to converge on the same measurements as those originally used by the Wyoming model. Results from the SFB discriminant function model were compared to the Wyoming model results (by using SFB data with the Wyoming model); the SFB model was 7% more accurate for SFB California gulls. The simplified DFA model (head-to-bill length only) provided highly accurate results (94%) and minimized the measurements and time required to accurately sex California Gulls.

The classification of almonds (Prunus dulcis) by country and variety using UHPLC-HRMS-based untargeted metabolomics.

PubMed

Gil Solsona, R; Boix, C; Ibáñez, M; Sancho, J V

2018-03-01

The aim of this study was to use an untargeted UHPLC-HRMS-based metabolomics approach allowing discrimination between almonds based on their origin and variety. Samples were homogenised, extracted with ACN:H 2 O (80:20) containing 0.1% HCOOH and injected in a UHPLC-QTOF instrument in both positive and negative ionisation modes. Principal component analysis (PCA) was performed to ensure the absence of outliers. Partial least squares - discriminant analysis (PLS-DA) was employed to create and validate the models for country (with five different compounds) and variety (with 20 features), showing more than 95% accuracy. Additional samples were injected and the model was evaluated with blind samples, with more than 95% of samples being correctly classified using both models. MS/MS experiments were carried out to tentatively elucidate the highlighted marker compounds (pyranosides, peptides or amino acids, among others). This study has shown the potential of high-resolution mass spectrometry to perform and validate classification models, also providing information concerning the identification of the unexpected biomarkers which showed the highest discriminant power.

Prediction of villages at risk for filariasis transmission in the Nile Delta using remote sensing and geographic information system technologies.

PubMed

Hassan, A N; Beck, L R; Dister, S

1998-04-01

Remote sensing and geographic information system (GIS) technologies were used to discriminate between 130 villages, in the Nile Delta, at high and low risk for filariasis, as defined by microfilarial prevalence. Landsat Thematic Mapper (TM) data were digitally processed to generate a map of landcover as well as spectral indices such as NDVI and moisture index. A Tasseled Cap transformation was also carried out on the TM data which produced three more indices: brightness, greenness and wetness. GIS functions were used to extract information on landcover and spectral indices within one km buffers around the study villages. The relationship between satellite data and prevalence was investigated using discriminant analysis. The analysis indicated that the most important landscape elements associated with prevalence were water and marginal vegetation, while wetness and moisture index were the most important indices. Discriminant functions generated for these variables were able to correctly predict 80% and 74% of high and low prevalence villages, respectively, with an overall accuracy of 77%. The present approach provides a promising tool for regional filariasis surveillance and helps direct control efforts.

Study of the method of water-injected meat identifying based on low-field nuclear magnetic resonance

NASA Astrophysics Data System (ADS)

Xu, Jianmei; Lin, Qing; Yang, Fang; Zheng, Zheng; Ai, Zhujun

2018-01-01

The aim of this study to apply low-field nuclear magnetic resonance technique was to study regular variation of the transverse relaxation spectral parameters of water-injected meat with the proportion of water injection. Based on this, the method of one-way ANOVA and discriminant analysis was used to analyse the differences between these parameters in the capacity of distinguishing water-injected proportion, and established a model for identifying water-injected meat. The results show that, except for T 21b, T 22e and T 23b, the other parameters of the T 2 relaxation spectrum changed regularly with the change of water-injected proportion. The ability of different parameters to distinguish water-injected proportion was different. Based on S, P 22 and T 23m as the prediction variable, the Fisher model and the Bayes model were established by discriminant analysis method, qualitative and quantitative classification of water-injected meat can be realized. The rate of correct discrimination of distinguished validation and cross validation were 88%, the model was stable.

The identification of credit card encoders by hierarchical cluster analysis of the jitters of magnetic stripes.

PubMed

Leung, S C; Fung, W K; Wong, K H

1999-01-01

The relative bit density variation graphs of 207 specimen credit cards processed by 12 encoding machines were examined first visually, and then classified by means of hierarchical cluster analysis. Twenty-nine credit cards being treated as 'questioned' samples were tested by way of cluster analysis against 'controls' derived from known encoders. It was found that hierarchical cluster analysis provided a high accuracy of identification with all 29 'questioned' samples classified correctly. On the other hand, although visual comparison of jitter graphs was less discriminating, it was nevertheless capable of giving a reasonably accurate result.

Discrimination of irradiated MOX fuel from UOX fuel by multivariate statistical analysis of simulated activities of gamma-emitting isotopes

NASA Astrophysics Data System (ADS)

Åberg Lindell, M.; Andersson, P.; Grape, S.; Hellesen, C.; Håkansson, A.; Thulin, M.

2018-03-01

This paper investigates how concentrations of certain fission products and their related gamma-ray emissions can be used to discriminate between uranium oxide (UOX) and mixed oxide (MOX) type fuel. Discrimination of irradiated MOX fuel from irradiated UOX fuel is important in nuclear facilities and for transport of nuclear fuel, for purposes of both criticality safety and nuclear safeguards. Although facility operators keep records on the identity and properties of each fuel, tools for nuclear safeguards inspectors that enable independent verification of the fuel are critical in the recovery of continuity of knowledge, should it be lost. A discrimination methodology for classification of UOX and MOX fuel, based on passive gamma-ray spectroscopy data and multivariate analysis methods, is presented. Nuclear fuels and their gamma-ray emissions were simulated in the Monte Carlo code Serpent, and the resulting data was used as input to train seven different multivariate classification techniques. The trained classifiers were subsequently implemented and evaluated with respect to their capabilities to correctly predict the classes of unknown fuel items. The best results concerning successful discrimination of UOX and MOX-fuel were acquired when using non-linear classification techniques, such as the k nearest neighbors method and the Gaussian kernel support vector machine. For fuel with cooling times up to 20 years, when it is considered that gamma-rays from the isotope 134Cs can still be efficiently measured, success rates of 100% were obtained. A sensitivity analysis indicated that these methods were also robust.

45 CFR 1225.19 - Corrective action.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 45 Public Welfare 4 2011-10-01 2011-10-01 false Corrective action. 1225.19 Section 1225.19 Public... Corrective action. (a) When discrimination is found, Peace Corps or ACTION must take appropriate action to... corrective action to the agent and other class members in accordance with § 1225.10 of this part. (b) When...

45 CFR 1225.19 - Corrective action.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 45 Public Welfare 4 2010-10-01 2010-10-01 false Corrective action. 1225.19 Section 1225.19 Public... Corrective action. (a) When discrimination is found, Peace Corps or ACTION must take appropriate action to... corrective action to the agent and other class members in accordance with § 1225.10 of this part. (b) When...

Shape Coding for Daymarks

DOT National Transportation Integrated Search

1974-03-01

Three experiments were conducted on form discrimination to select and evaluate forms for shape coding of daymarks. The discriminability of the forms was measured by the frequency with which each form was identified correctly and the frequency with wh...

Temporal patterns and source apportionment of nitrate-nitrogen leaching in a paddy field at Kelantan, Malaysia.

PubMed

Hussain, Hazilia; Yusoff, Mohd Kamil; Ramli, Mohd Firuz; Abd Latif, Puziah; Juahir, Hafizan; Zawawi, Mohamed Azwan Mohammed

2013-11-15

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.

Phylogenetic comparative methods complement discriminant function analysis in ecomorphology.

PubMed

Barr, W Andrew; Scott, Robert S

2014-04-01

In ecomorphology, Discriminant Function Analysis (DFA) has been used as evidence for the presence of functional links between morphometric variables and ecological categories. Here we conduct simulations of characters containing phylogenetic signal to explore the performance of DFA under a variety of conditions. Characters were simulated using a phylogeny of extant antelope species from known habitats. Characters were modeled with no biomechanical relationship to the habitat category; the only sources of variation were body mass, phylogenetic signal, or random "noise." DFA on the discriminability of habitat categories was performed using subsets of the simulated characters, and Phylogenetic Generalized Least Squares (PGLS) was performed for each character. Analyses were repeated with randomized habitat assignments. When simulated characters lacked phylogenetic signal and/or habitat assignments were random, <5.6% of DFAs and <8.26% of PGLS analyses were significant. When characters contained phylogenetic signal and actual habitats were used, 33.27 to 45.07% of DFAs and <13.09% of PGLS analyses were significant. False Discovery Rate (FDR) corrections for multiple PGLS analyses reduced the rate of significance to <4.64%. In all cases using actual habitats and characters with phylogenetic signal, correct classification rates of DFAs exceeded random chance. In simulations involving phylogenetic signal in both predictor variables and predicted categories, PGLS with FDR was rarely significant, while DFA often was. In short, DFA offered no indication that differences between categories might be explained by phylogenetic signal, while PGLS did. As such, PGLS provides a valuable tool for testing the functional hypotheses at the heart of ecomorphology. Copyright © 2013 Wiley Periodicals, Inc.

Effective Identification of Low-Gliadin Wheat Lines by Near Infrared Spectroscopy (NIRS): Implications for the Development and Analysis of Foodstuffs Suitable for Celiac Patients.

PubMed

García-Molina, María Dolores; García-Olmo, Juan; Barro, Francisco

2016-01-01

The aim of this work was to assess the ability of Near Infrared Spectroscopy (NIRS) to distinguish wheat lines with low gliadin content, obtained by RNA interference (RNAi), from non-transgenic wheat lines. The discriminant analysis was performed using both whole grain and flour. The transgenic sample set included 409 samples for whole grain sorting and 414 samples for flour experiments, while the non-transgenic set consisted of 126 and 156 samples for whole grain and flour, respectively. Samples were scanned using a Foss-NIR Systems 6500 System II instrument. Discrimination models were developed using the entire spectral range (400-2500 nm) and ranges of 400-780 nm, 800-1098 nm and 1100-2500 nm, followed by analysis of means of partial least square (PLS). Two external validations were made, using samples from the years 2013 and 2014 and a minimum of 99% of the flour samples and 96% of the whole grain samples were classified correctly. The results demonstrate the ability of NIRS to successfully discriminate between wheat samples with low-gliadin content and wild types. These findings are important for the development and analysis of foodstuff for celiac disease (CD) patients to achieve better dietary composition and a reduction in disease incidence.

Laser-Induced Breakdown Spectroscopy Coupled with Multivariate Chemometrics for Variety Discrimination of Soil

PubMed Central

Yu, Ke-Qiang; Zhao, Yan-Ru; Liu, Fei; He, Yong

2016-01-01

The aim of this work was to analyze the variety of soil by laser-induced breakdown spectroscopy (LIBS) coupled with chemometrics methods. 6 certified reference materials (CRMs) of soil samples were selected and their LIBS spectra were captured. Characteristic emission lines of main elements were identified based on the LIBS curves and corresponding contents. From the identified emission lines, LIBS spectra in 7 lines with high signal-to-noise ratio (SNR) were chosen for further analysis. Principal component analysis (PCA) was carried out using the LIBS spectra at 7 selected lines and an obvious cluster of 6 soils was observed. Soft independent modeling of class analogy (SIMCA) and least-squares support vector machine (LS-SVM) were introduced to establish discriminant models for classifying the 6 types of soils, and they offered the correct discrimination rates of 90% and 100%, respectively. Receiver operating characteristic (ROC) curve was used to evaluate the performance of models and the results demonstrated that the LS-SVM model was promising. Lastly, 8 types of soils from different places were gathered to conduct the same experiments for verifying the selected 7 emission lines and LS-SVM model. The research revealed that LIBS technology coupled with chemometrics could conduct the variety discrimination of soil. PMID:27279284

Using near infrared spectroscopy to classify soybean oil according to expiration date.

PubMed

da Costa, Gean Bezerra; Fernandes, David Douglas Sousa; Gomes, Adriano A; de Almeida, Valber Elias; Veras, Germano

2016-04-01

A rapid and non-destructive methodology is proposed for the screening of edible vegetable oils according to conservation state expiration date employing near infrared (NIR) spectroscopy and chemometric tools. A total of fifty samples of soybean vegetable oil, of different brands andlots, were used in this study; these included thirty expired and twenty non-expired samples. The oil oxidation was measured by peroxide index. NIR spectra were employed in raw form and preprocessed by offset baseline correction and Savitzky-Golay derivative procedure, followed by PCA exploratory analysis, which showed that NIR spectra would be suitable for the classification task of soybean oil samples. The classification models were based in SPA-LDA (Linear Discriminant Analysis coupled with Successive Projection Algorithm) and PLS-DA (Discriminant Analysis by Partial Least Squares). The set of samples (50) was partitioned into two groups of training (35 samples: 15 non-expired and 20 expired) and test samples (15 samples 5 non-expired and 10 expired) using sample-selection approaches: (i) Kennard-Stone, (ii) Duplex, and (iii) Random, in order to evaluate the robustness of the models. The obtained results for the independent test set (in terms of correct classification rate) were 96% and 98% for SPA-LDA and PLS-DA, respectively, indicating that the NIR spectra can be used as an alternative to evaluate the degree of oxidation of soybean oil samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Sex estimation in a modern American osteological sample using a discriminant function analysis from the calcaneus.

PubMed

DiMichele, Daniel L; Spradley, M Katherine

2012-09-10

Reliable methods for sex estimation during the development of a biological profile are important to the forensic community in instances when the common skeletal elements used to assess sex are absent or damaged. Sex estimation from the calcaneus has potentially significant importance for the forensic community. Specifically, measurements of the calcaneus provide an additional reliable method for sex estimation via discriminant function analysis based on a North American forensic population. Research on a modern American sample was chosen in order to develop up-to-date population specific discriminant functions for sex estimation. The current study addresses this matter, building upon previous research and introduces a new measurement, posterior circumference that promises to advance the accuracy of use of this single, highly resistant bone in future instances of sex determination from partial skeletal remains. Data were collected from The William Bass Skeletal Collection, housed at The University of Tennessee. Sample size includes 320 adult individuals born between the years 1900 and 1985. The sample was comprised of 136 females and 184 males. Skeletons used for measurements were confined to those with fused diaphyses showing no signs of pathology or damage that may have altered measurements, and that also had accompanying records that included information on ancestry, age, and sex. Measurements collected and analyzed include maximum length, load-arm length, load-arm width, and posterior circumference. The sample was used to compute a discriminant function, based on all four variables, and was performed in SAS 9.1.3. The discriminant function obtained an overall cross-validated classification rate of 86.69%. Females were classified correctly in 88.64% of the cases and males were correctly classified in 84.75% of the cases. Due to the increasing heterogeneity of current populations further discussion on this topic will include the importance that the re-evaluation of past studies has on modern forensic populations. Due to secular and micro evolutionary changes among populations, the near future must include additional methods being updated, and new methods being examined, both which should cover a wide population spectrum. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Perception of coarticulated tones by non-native listeners

NASA Astrophysics Data System (ADS)

Bent, Tessa

2005-04-01

Mandarin lexical tones vary in their acoustic realization depending on the surrounding context. Native listeners compensate for this tonal coarticulation when identifying tones in context. This study investigated how native English listeners handle tonal coarticulation by testing native English and Mandarin listeners discrimination of the four Mandarin lexical tones in tri-syllabic sequences in which the middle tone varied while the first and last tones were held constant. Three different such frames were tested. As expected, Mandarin listeners discriminated all pairs in all contexts with a high degree of accuracy. English listeners exhibited poorer discrimination than Mandarin listeners and their discrimination accuracy showed a high degree of context dependency. In addition to assessing accuracy, reactions times to correctly discriminated different trials were entered into a multidimensional scaling analysis. For both listener groups, the arrangement of tones in perceptual space varied depending on the surrounding context suggesting that listeners attend to different acoustic attributes of the target tone depending on the surrounding tones. These results demonstrate the importance for models of cross-language speech perception of including contextual variation when characterizing the perception of non-native prosodic categories. [Work supported by NIH/NIDCD

Color vision in the giant panda (Ailuropoda melanoleuca).

PubMed

Kelling, Angela S; Snyder, Rebecca J; Marr, M Jackson; Bloomsmith, Mollie A; Gardner, Wendy; Maple, Terry L

2006-05-01

Hue discrimination abilities of giant pandas were tested, controlling for brightness. Subjects were 2 adult giant pandas (1 male and 1 female). A simultaneous discrimination procedure without correction was used. In five tasks, white, black, and five saturations each of green, blue, and red served as positive stimuli that were paired with one or two comparison stimuli consisting of 16 saturations of gray. To demonstrate discrimination, the subjects were required to choose the positive stimulus in 16 of 20 trials (80% correct) for three consecutivesessions. Both subjects reached criterion forgreen and red. The female subject also reached criterion for blue. The male was not tested for blue. This study is a systematic replication of Bacon and Burghardt's (1976) color discrimination experiment on black bears. The results suggest that color vision in the giant panda is comparable to that of black bears and other carnivores that are not strictly nocturnal.

Short-Term Intra-Subject Variation in Exhaled Volatile Organic Compounds (VOCs) in COPD Patients and Healthy Controls and Its Effect on Disease Classification

PubMed Central

Phillips, Christopher; Mac Parthaláin, Neil; Syed, Yasir; Deganello, Davide; Claypole, Timothy; Lewis, Keir

2014-01-01

Exhaled volatile organic compounds (VOCs) are of interest for their potential to diagnose disease non-invasively. However, most breath VOC studies have analyzed single breath samples from an individual and assumed them to be wholly consistent representative of the person. This provided the motivation for an investigation of the variability of breath profiles when three breath samples are taken over a short time period (two minute intervals between samples) for 118 stable patients with Chronic Obstructive Pulmonary Disease (COPD) and 63 healthy controls and analyzed by gas chromatography and mass spectroscopy (GC/MS). The extent of the variation in VOC levels differed between COPD and healthy subjects and the patterns of variation differed for isoprene versus the bulk of other VOCs. In addition, machine learning approaches were applied to the breath data to establish whether these samples differed in their ability to discriminate COPD from healthy states and whether aggregation of multiple samples, into single data sets, could offer improved discrimination. The three breath samples gave similar classification accuracy to one another when evaluated separately (66.5% to 68.3% subjects classified correctly depending on the breath repetition used). Combining multiple breath samples into single data sets gave better discrimination (73.4% subjects classified correctly). Although accuracy is not sufficient for COPD diagnosis in a clinical setting, enhanced sampling and analysis may improve accuracy further. Variability in samples, and short-term effects of practice or exertion, need to be considered in any breath testing program to improve reliability and optimize discrimination. PMID:24957028

Short-Term Intra-Subject Variation in Exhaled Volatile Organic Compounds (VOCs) in COPD Patients and Healthy Controls and Its Effect on Disease Classification.

PubMed

Phillips, Christopher; Mac Parthaláin, Neil; Syed, Yasir; Deganello, Davide; Claypole, Timothy; Lewis, Keir

2014-05-09

Exhaled volatile organic compounds (VOCs) are of interest for their potential to diagnose disease non-invasively. However, most breath VOC studies have analyzed single breath samples from an individual and assumed them to be wholly consistent representative of the person. This provided the motivation for an investigation of the variability of breath profiles when three breath samples are taken over a short time period (two minute intervals between samples) for 118 stable patients with Chronic Obstructive Pulmonary Disease (COPD) and 63 healthy controls and analyzed by gas chromatography and mass spectroscopy (GC/MS). The extent of the variation in VOC levels differed between COPD and healthy subjects and the patterns of variation differed for isoprene versus the bulk of other VOCs. In addition, machine learning approaches were applied to the breath data to establish whether these samples differed in their ability to discriminate COPD from healthy states and whether aggregation of multiple samples, into single data sets, could offer improved discrimination. The three breath samples gave similar classification accuracy to one another when evaluated separately (66.5% to 68.3% subjects classified correctly depending on the breath repetition used). Combining multiple breath samples into single data sets gave better discrimination (73.4% subjects classified correctly). Although accuracy is not sufficient for COPD diagnosis in a clinical setting, enhanced sampling and analysis may improve accuracy further. Variability in samples, and short-term effects of practice or exertion, need to be considered in any breath testing program to improve reliability and optimize discrimination.

Olfactory discrimination training up-regulates and reorganizes expression of microRNAs in adult mouse hippocampus.

PubMed

Smalheiser, Neil R; Lugli, Giovanni; Lenon, Angela L; Davis, John M; Torvik, Vetle I; Larson, John

2010-02-26

Adult male mice (strain C57Bl/6J) were trained to execute nose-poke responses for water reinforcement; then they were randomly assigned to either of two groups: olfactory discrimination training (exposed to two odours with reward contingent upon correctly responding to one odour) or pseudo-training (exposed to two odours with reward not contingent upon response). These were run in yoked fashion and killed when the discrimination-trained mouse reached a learning criterion of 70% correct responses in 20 trials, occurring after three sessions (a total of approximately 40 min of training). The hippocampus was dissected bilaterally from each mouse (N = 7 in each group) and profiling of 585 miRNAs (microRNAs) was carried out using multiplex RT-PCR (reverse transcription-PCR) plates. A significant global up-regulation of miRNA expression was observed in the discrimination training versus pseudo-training comparison; when tested individually, 29 miRNAs achieved significance at P = 0.05. miR-10a showed a 2.7-fold increase with training, and is predicted to target several learning-related mRNAs including BDNF (brain-derived neurotrophic factor), CAMK2b (calcium/calmodulin-dependent protein kinase IIβ), CREB1 (cAMP-response-element-binding protein 1) and ELAVL2 [ELAV (embryonic lethal, abnormal vision, Drosophila)-like; Hu B]. Analysis of miRNA pairwise correlations revealed the existence of several miRNA co-expression modules that were specific to the training group. These in vivo results indicate that significant, dynamic and co-ordinated changes in miRNA expression accompany early stages of learning.

Regional Seismic Amplitude Modeling and Tomography for Earthquake-Explosion Discrimination

NASA Astrophysics Data System (ADS)

Walter, W. R.; Pasyanos, M. E.; Matzel, E.; Gok, R.; Sweeney, J.; Ford, S. R.; Rodgers, A. J.

2008-12-01

Empirically explosions have been discriminated from natural earthquakes using regional amplitude ratio techniques such as P/S in a variety of frequency bands. We demonstrate that such ratios discriminate nuclear tests from earthquakes using closely located pairs of earthquakes and explosions recorded on common, publicly available stations at test sites around the world (e.g. Nevada, Novaya Zemlya, Semipalatinsk, Lop Nor, India, Pakistan, and North Korea). We are examining if there is any relationship between the observed P/S and the point source variability revealed by longer period full waveform modeling. For example, regional waveform modeling shows strong tectonic release from the May 1998 India test, in contrast with very little tectonic release in the October 2006 North Korea test, but the P/S discrimination behavior appears similar in both events using the limited regional data available. While regional amplitude ratios such as P/S can separate events in close proximity, it is also empirically well known that path effects can greatly distort observed amplitudes and make earthquakes appear very explosion-like. Previously we have shown that the MDAC (Magnitude Distance Amplitude Correction, Walter and Taylor, 2001) technique can account for simple 1-D attenuation and geometrical spreading corrections, as well as magnitude and site effects. However in some regions 1-D path corrections are a poor approximation and we need to develop 2-D path corrections. Here we demonstrate a new 2-D attenuation tomography technique using the MDAC earthquake source model applied to a set of events and stations in both the Middle East and the Yellow Sea Korean Peninsula regions. We believe this new 2-D MDAC tomography has the potential to greatly improve earthquake-explosion discrimination, particularly in tectonically complex regions such as the Middle East.

Detection of sunn pest-damaged wheat samples using visible/near-infrared spectroscopy based on pattern recognition.

PubMed

Basati, Zahra; Jamshidi, Bahareh; Rasekh, Mansour; Abbaspour-Gilandeh, Yousef

2018-05-30

The presence of sunn pest-damaged grains in wheat mass reduces the quality of flour and bread produced from it. Therefore, it is essential to assess the quality of the samples in collecting and storage centers of wheat and flour mills. In this research, the capability of visible/near-infrared (Vis/NIR) spectroscopy combined with pattern recognition methods was investigated for discrimination of wheat samples with different percentages of sunn pest-damaged. To this end, various samples belonging to five classes (healthy and 5%, 10%, 15% and 20% unhealthy) were analyzed using Vis/NIR spectroscopy (wavelength range of 350-1000 nm) based on both supervised and unsupervised pattern recognition methods. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) as the unsupervised techniques and soft independent modeling of class analogies (SIMCA) and partial least squares-discriminant analysis (PLS-DA) as supervised methods were used. The results showed that Vis/NIR spectra of healthy samples were correctly clustered using both PCA and HCA. Due to the high overlapping between the four unhealthy classes (5%, 10%, 15% and 20%), it was not possible to discriminate all the unhealthy samples in individual classes. However, when considering only the two main categories of healthy and unhealthy, an acceptable degree of separation between the classes can be obtained after classification with supervised pattern recognition methods of SIMCA and PLS-DA. SIMCA based on PCA modeling correctly classified samples in two classes of healthy and unhealthy with classification accuracy of 100%. Moreover, the power of the wavelengths of 839 nm, 918 nm and 995 nm were more than other wavelengths to discriminate two classes of healthy and unhealthy. It was also concluded that PLS-DA provides excellent classification results of healthy and unhealthy samples (R 2  = 0.973 and RMSECV = 0.057). Therefore, Vis/NIR spectroscopy based on pattern recognition techniques can be useful for rapid distinguishing the healthy wheat samples from those damaged by sunn pest in the maintenance and processing centers. Copyright © 2018 Elsevier B.V. All rights reserved.

Stable isotope ratio analysis for authentication of lamb meat.

PubMed

Piasentier, E; Valusso, R; Camin, F; Versini, G

2003-07-01

The effectiveness of the analysis of stable isotope ratios ((13)C/(12)C and (15)N/(14)N) in fractions of lamb meat, measured by isotope ratio mass spectrometry, was evaluated as a method of feeding and geographical origin authentication. Analyses were carried out on meat from 12 lamb types, produced in couples in six European countries (country of origin, CO) and divided in three groups according to the feeding regime during their finishing period: suckled milk only, pasture without any solid supplementation and supplementation containing maize grain (feeding regime, FR). These analyses were made on two samples of longissimus thoracis muscle, taken from the 13th rib section of the left side of two different lambs, randomly chosen between the 120 selected to represent each lamb type. δ(13)C values varied significantly in different meat fractions, the difference being higher in protein than in fat (average difference 5.0‰). However, the pairs δ(13)C values of crude fat and protein were highly correlated (r=0.976) and affected by lamb type in a similar fashion, mainly reflecting animals' feeding regime. Even δ(15)N values of meat protein fraction showed significant differences between lamb types, not dependant on the feeding regime. In fact, lambs fed on similar diets, but in different countries, gave meat with different (15)N relative abundances. These findings provide the possibility of discriminating lamb types within the same feeding regime. Canonical discriminant analysis was carried out to evaluate whether lamb meat from different CO or FR or CO×FR interaction could be mathematically distinguished by its stable isotope ratios. On the basis of CO, the corrected empirical allocation of 79.2% of the initial observations and the corrected cross-validation of two thirds of the individual meat samples was obtained. FR gave better results: 91.7% of the individual meat samples was both correctly allocated and cross-validated, indicating the high potential of stable isotope ratio analysis as a tool for lamb diet characterisation. The most satisfactory classification attained, using K-means clustering technique and canonical discriminant analysis, enabled a good resolution of six CO×FR groups of lamb types: Icelandic fed on pasture; British and French grazing; Italian; suckled and Karagouniko concentrates finished; French Lacaune; Ternasco de Aragon. It was concluded that multielement stable isotope analysis may be considered promising for the reliable evaluation of lamb meat authenticity, in the same way as for wine, fruit juice, honey and dairy products.

Spatially resolved bimodal spectroscopy for classification/evaluation of mouse skin inflammatory and pre-cancerous stages

NASA Astrophysics Data System (ADS)

Díaz-Ayil, Gilberto; Amouroux, Marine; Clanché, Fabien; Granjon, Yves; Blondel, Walter C. P. M.

2009-07-01

Spatially-resolved bimodal spectroscopy (multiple AutoFluorescence AF excitation and Diffuse Reflectance DR), was used in vivo to discriminate various healthy and precancerous skin stages in a pre-clinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A specific data preprocessing scheme was applied to intensity spectra (filtering, spectral correction and intensity normalization), and several sets of spectral characteristics were automatically extracted and selected based on their discrimination power, statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of Sensibility (Se) and Specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibres distances and of the numbers of principal components, such that: Se and Sp ~ 100% when discriminating CH vs. others; Sp ~ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ~ 74% and Se ~ 63% for AH vs. D.

Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process

PubMed Central

Ucchesu, Mariano; Orrù, Martino; Grillo, Oscar; Venora, Gianfranco; Paglietti, Giacomo; Ardu, Andrea; Bacchetta, Gianluigi

2016-01-01

The identification of archaeological charred grape seeds is a difficult task due to the alteration of the morphological seeds shape. In archaeobotanical studies, for the correct discrimination between Vitis vinifera subsp. sylvestris and Vitis vinifera subsp. vinifera grape seeds it is very important to understand the history and origin of the domesticated grapevine. In this work, different carbonisation experiments were carried out using a hearth to reproduce the same burning conditions that occurred in archaeological contexts. In addition, several carbonisation trials on modern wild and cultivated grape seeds were performed using a muffle furnace. For comparison with archaeological materials, modern grape seed samples were obtained using seven different temperatures of carbonisation ranging between 180 and 340ºC for 120 min. Analysing the grape seed size and shape by computer vision techniques, and applying the stepwise linear discriminant analysis (LDA) method, discrimination of the wild from the cultivated charred grape seeds was possible. An overall correct classification of 93.3% was achieved. Applying the same statistical procedure to compare modern charred with archaeological grape seeds, found in Sardinia and dating back to the Early Bronze Age (2017–1751 2σ cal. BC), allowed 75.0% of the cases to be identified as wild grape. The proposed method proved to be a useful and effective procedure in identifying, with high accuracy, the charred grape seeds found in archaeological sites. Moreover, it may be considered valid support for advances in the knowledge and comprehension of viticulture adoption and the grape domestication process. The same methodology may also be successful when applied to other plant remains, and provide important information about the history of domesticated plants. PMID:26901361

Predictive Method for Correct Identification of Archaeological Charred Grape Seeds: Support for Advances in Knowledge of Grape Domestication Process.

PubMed

Ucchesu, Mariano; Orrù, Martino; Grillo, Oscar; Venora, Gianfranco; Paglietti, Giacomo; Ardu, Andrea; Bacchetta, Gianluigi

2016-01-01

The identification of archaeological charred grape seeds is a difficult task due to the alteration of the morphological seeds shape. In archaeobotanical studies, for the correct discrimination between Vitis vinifera subsp. sylvestris and Vitis vinifera subsp. vinifera grape seeds it is very important to understand the history and origin of the domesticated grapevine. In this work, different carbonisation experiments were carried out using a hearth to reproduce the same burning conditions that occurred in archaeological contexts. In addition, several carbonisation trials on modern wild and cultivated grape seeds were performed using a muffle furnace. For comparison with archaeological materials, modern grape seed samples were obtained using seven different temperatures of carbonisation ranging between 180 and 340ºC for 120 min. Analysing the grape seed size and shape by computer vision techniques, and applying the stepwise linear discriminant analysis (LDA) method, discrimination of the wild from the cultivated charred grape seeds was possible. An overall correct classification of 93.3% was achieved. Applying the same statistical procedure to compare modern charred with archaeological grape seeds, found in Sardinia and dating back to the Early Bronze Age (2017-1751 2σ cal. BC), allowed 75.0% of the cases to be identified as wild grape. The proposed method proved to be a useful and effective procedure in identifying, with high accuracy, the charred grape seeds found in archaeological sites. Moreover, it may be considered valid support for advances in the knowledge and comprehension of viticulture adoption and the grape domestication process. The same methodology may also be successful when applied to other plant remains, and provide important information about the history of domesticated plants.

Comparison of visible and near infrared reflectance spectroscopy on fat to authenticate dietary history of lambs.

PubMed

Huang, Y; Andueza, D; de Oliveira, L; Zawadzki, F; Prache, S

2015-11-01

Since consumers are showing increased interest in the origin and method of production of their food, it is important to be able to authenticate dietary history of animals by rapid and robust methods used in the ruminant products. Promising breakthroughs have been made in the use of spectroscopic methods on fat to discriminate pasture-fed and concentrate-fed lambs. However, questions remained on their discriminatory ability in more complex feeding conditions, such as concentrate-finishing after pasture-feeding. We compared the ability of visible reflectance spectroscopy (Vis RS, wavelength range: 400 to 700 nm) with that of visible-near-infrared reflectance spectroscopy (Vis-NIR RS, wavelength range: 400 to 2500 nm) to differentiate between carcasses of lambs reared with three feeding regimes, using partial least square discriminant analysis (PLS-DA) as a classification method. The sample set comprised perirenal fat of Romane male lambs fattened at pasture (P, n = 69), stall-fattened indoors on commercial concentrate and straw (S, n = 55) and finished indoors with concentrate and straw for 28 days after pasture-feeding (PS, n = 65). The overall correct classification rate was better for Vis-NIR RS than for Vis RS (99.0% v. 95.1%, P < 0.05). Vis-NIR RS allowed a correct classification rate of 98.6%, 100.0% and 98.5% for P, S and PS lambs, respectively, whereas Vis RS allowed a correct classification rate of 98.6%, 94.5% and 92.3% for P, S and PS lambs, respectively. This study suggests the likely implication of molecules absorbing light in the non-visible part of the Vis-NIR spectra (possibly fatty acids), together with carotenoid and haem pigments, in the discrimination of the three feeding regimes.

Are psychological measures and actuarial data equally effective in discriminating among the prison population? Analysis by crimes

PubMed Central

Burneo-Garcés, Carlos; Marín-Morales, Agar; Pérez-García, Miguel

2018-01-01

The ability of a wide range of psychological and actuarial measures to characterize crimes in the prison population has not yet been compared in a single study. Our main objective was to determine if the discriminant capacity of psychological measures (PM) and actuarial data (AD) varies according to the crime. An Ecuadorian sample of 576 men convicted of Robbery, Murder, Rape and Drug Possession crimes was evaluated through an ad hoc questionnaire, prison files and the Spanish adaptation of the Personality Assessment Inventory. Discriminant analysis was used to establish, for each crime, the discriminant capacity and the classification accuracy of a model composed of AD (socio-demographic and judicial measures) and a second model incorporating PM. The AD showed a superior discriminant capacity, whilst the contribution of both types of measures varied according to the crime. The PM generated some increase in the correct classification percentages for Murder, Rape and Drug Possession, but their contribution was zero for the crime of Robbery. Specific profiles of each crime were obtained from the strongest significant correlations between the value of each explanatory variable and the probability of belonging to the crime. The AD model is more robust when these four crimes are characterized. The contribution of AD and PM depends on the crime, and the inclusion of PM in actuarial models moderately optimizes the classification accuracy of Murder, Rape, and Drug Possession crimes. PMID:29874264

Top-down and bottom-up modulation of brain structures involved in auditory discrimination.

PubMed

Diekhof, Esther K; Biedermann, Franziska; Ruebsamen, Rudolf; Gruber, Oliver

2009-11-10

Auditory deviancy detection comprises both automatic and voluntary processing. Here, we investigated the neural correlates of different components of the sensory discrimination process using functional magnetic resonance imaging. Subliminal auditory processing of deviant events that were not detected led to activation in left superior temporal gyrus. On the other hand, both correct detection of deviancy and false alarms activated a frontoparietal network of attentional processing and response selection, i.e. this network was activated regardless of the physical presence of deviant events. Finally, activation in the putamen, anterior cingulate and middle temporal cortex depended on factual stimulus representations and occurred only during correct deviancy detection. These results indicate that sensory discrimination may rely on dynamic bottom-up and top-down interactions.

Discrimination thresholds of normal and anomalous trichromats: Model of senescent changes in ocular media density on the Cambridge Colour Test

PubMed Central

Shinomori, Keizo; Panorgias, Athanasios; Werner, John S.

2017-01-01

Age-related changes in chromatic discrimination along dichromatic confusion lines were measured with the Cambridge Colour Test (CCT). One hundred and sixty-two individuals (16 to 88 years old) with normal Rayleigh matches were the major focus of this paper. An additional 32 anomalous trichromats classified by their Rayleigh matches were also tested. All subjects were screened to rule out abnormalities of the anterior and posterior segments. Thresholds on all three chromatic vectors measured with the CCT showed age-related increases. Protan and deutan vector thresholds increased linearly with age while the tritan vector threshold was described with a bilinear model. Analysis and modeling demonstrated that the nominal vectors of the CCT are shifted by senescent changes in ocular media density, and a method for correcting the CCT vectors is demonstrated. A correction for these shifts indicates that classification among individuals of different ages is unaffected. New vector thresholds for elderly observers and for all age groups are suggested based on calculated tolerance limits. PMID:26974943

Age determination of female redhead ducks

USGS Publications Warehouse

Dane, C.W.; Johnson, D.H.

1975-01-01

Eighty-seven fall-collected wings from female redhead ducks (Aythya americana) were assigned to the adult or juvenile group based on 'tertial' and 'tertial covert' shape and wear. To obtain spring age-related characters from these fall-collected groupings, we considered parameters of flight feathers retained until after the first breeding season. Parameters measured included: markings on and width of greater secondary coverts, and length, weight, and diameter of primary feathers. The best age categorization was obtained with discriminant analysis based on a combination of the most accurately measured parameters. This analysis, applied to 81 wings with complete measurements, resulted in only 1 being incorrectly aged and 3 placed in a questionable category. Discriminant functions used with covert markings and the three 5th primary parameters were applied to 30 known-age juvenile, hand-reared redhead females, 28 were correctly aged, none was incorrectly aged, and only 2 were placed in the questionable category.

Static Corrections to Improve Seismic Monitoring of the North Korean Nuclear Test Site with Regional Arrays

NASA Astrophysics Data System (ADS)

Wilkins, N.; Wookey, J. M.; Selby, N. D.

2017-12-01

Seismology is an important part of the International Monitoring System (IMS) installed to detect, identify, and locate nuclear detonations in breach of the Comprehensive nuclear Test Ban Treaty (CTBT) prior to and after its entry into force. Seismic arrays in particular provide not only a means of detecting and locating underground nuclear explosions, but in discriminating them from naturally occurring earthquakes of similar magnitude. One potential discriminant is the amplitude ratio of high frequency (> 2 Hz) P waves to S waves (P/S) measured at regional distances (3 - 17 °). Accurate measurement of such discriminants, and the ability to detect low-magnitude seismicity from a suspicious event relies on high signal-to-noise ratio (SNR) data. A correction to the slowness vector of the incident seismic wavefield, and static corrections applied to the waveforms recorded at each receiver within the array can be shown to improve the SNR. We apply codes we have developed to calculate slowness-azimuth station corrections (SASCs) and static corrections to the arrival time and amplitude of the seismic waveform to seismic arrays regional to the DPRK nuclear test site at Punggye-ri, North Korea. We use the F-statistic to demonstrate the SNR improvement to data from the nuclear tests and other seismic events in the vicinity of the test site. We also make new measurements of P/S with the corrected waveforms and compare these with existing measurements.

Landsat real-time processing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Davis, E.L.

A novel method for performing real-time acquisition and processing Landsat/EROS data covers all aspects including radiometric and geometric corrections of multispectral scanner or return-beam vidicon inputs, image enhancement, statistical analysis, feature extraction, and classification. Radiometric transformations include bias/gain adjustment, noise suppression, calibration, scan angle compensation, and illumination compensation, including topography and atmospheric effects. Correction or compensation for geometric distortion includes sensor-related distortions, such as centering, skew, size, scan nonlinearity, radial symmetry, and tangential symmetry. Also included are object image-related distortions such as aspect angle (altitude), scale distortion (altitude), terrain relief, and earth curvature. Ephemeral corrections are also applied to compensatemore » for satellite forward movement, earth rotation, altitude variations, satellite vibration, and mirror scan velocity. Image enhancement includes high-pass, low-pass, and Laplacian mask filtering and data restoration for intermittent losses. Resource classification is provided by statistical analysis including histograms, correlational analysis, matrix manipulations, and determination of spectral responses. Feature extraction includes spatial frequency analysis, which is used in parallel discriminant functions in each array processor for rapid determination. The technique uses integrated parallel array processors that decimate the tasks concurrently under supervision of a control processor. The operator-machine interface is optimized for programming ease and graphics image windowing.« less

REGIONAL SEISMIC AMPLITUDE MODELING AND TOMOGRAPHY FOR EARTHQUAKE-EXPLOSION DISCRIMINATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Walter, W R; Pasyanos, M E; Matzel, E

2008-07-08

We continue exploring methodologies to improve earthquake-explosion discrimination using regional amplitude ratios such as P/S in a variety of frequency bands. Empirically we demonstrate that such ratios separate explosions from earthquakes using closely located pairs of earthquakes and explosions recorded on common, publicly available stations at test sites around the world (e.g. Nevada, Novaya Zemlya, Semipalatinsk, Lop Nor, India, Pakistan, and North Korea). We are also examining if there is any relationship between the observed P/S and the point source variability revealed by longer period full waveform modeling (e. g. Ford et al 2008). For example, regional waveform modeling showsmore » strong tectonic release from the May 1998 India test, in contrast with very little tectonic release in the October 2006 North Korea test, but the P/S discrimination behavior appears similar in both events using the limited regional data available. While regional amplitude ratios such as P/S can separate events in close proximity, it is also empirically well known that path effects can greatly distort observed amplitudes and make earthquakes appear very explosion-like. Previously we have shown that the MDAC (Magnitude Distance Amplitude Correction, Walter and Taylor, 2001) technique can account for simple 1-D attenuation and geometrical spreading corrections, as well as magnitude and site effects. However in some regions 1-D path corrections are a poor approximation and we need to develop 2-D path corrections. Here we demonstrate a new 2-D attenuation tomography technique using the MDAC earthquake source model applied to a set of events and stations in both the Middle East and the Yellow Sea Korean Peninsula regions. We believe this new 2-D MDAC tomography has the potential to greatly improve earthquake-explosion discrimination, particularly in tectonically complex regions such as the Middle East. Monitoring the world for potential nuclear explosions requires characterizing seismic events and discriminating between natural and man-made seismic events, such as earthquakes and mining activities, and nuclear weapons testing. We continue developing, testing, and refining size-, distance-, and location-based regional seismic amplitude corrections to facilitate the comparison of all events that are recorded at a particular seismic station. These corrections, calibrated for each station, reduce amplitude measurement scatter and improve discrimination performance. We test the methods on well-known (ground truth) datasets in the U.S. and then apply them to the uncalibrated stations in Eurasia, Africa, and other regions of interest to improve underground nuclear test monitoring capability.« less

Aggression against Women by Men: Sexual and Spousal Assault.

ERIC Educational Resources Information Center

Dewhurst, Ann Marie; And Others

1992-01-01

Compared 19 sexual offenders, 22 batterers, 10 violent community comparison subjects, and 21 community comparison subjects on demographic, personality, and attitudinal variables. Discriminating variables correctly classified 75 percent of participants. Hostility toward women and depression were two best discriminating variables, suggesting that…

Distinction Between Recurrent Glioma and Radiation Injury Using Magnetic Resonance Spectroscopy in Combination With Diffusion-Weighted Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zeng, Q.-S.; Li, C.-F.; Liu Hong

2007-05-01

Purpose: The aim of this study was to explore the diagnostic effectiveness of magnetic resonance (MR) spectroscopy with diffusion-weighted imaging on the evaluation of the recurrent contrast-enhancing areas at the site of treated gliomas. Methods and Materials: In 55 patients who had new contrast-enhancing lesions in the vicinity of the previously resected and irradiated high-grade gliomas, two-dimensional MR spectroscopy and diffusion-weighted imaging were performed. Spectral data for N-acetylaspartate (NAA), choline (Cho), creatine (Cr), lipid (Lip), and lactate (Lac) were analyzed in conjunction with the apparent diffusion coefficient (ADC) in all patients. Diagnosis of these lesions was assigned by means ofmore » follow-up or histopathology. Results: The Cho/NAA and Cho/Cr ratios were significantly higher in recurrent tumor than in regions of radiation injury (p < 0.01). The ADC value and ADC ratios (ADC of contrast-enhancing lesion to matching structure in the contralateral hemisphere) were significantly higher in radiation injury regions than in recurrent tumor (p < 0.01). With MR spectroscopic data, two variables (Cho/NAA and Cho/Cr ratios) were shown to differentiate recurrent glioma from radiation injury, and 85.5% of total subjects were correctly classified into groups. However, with discriminant analysis of MR spectroscopy imaging plus diffusion-weighted imaging, three variables (Cho/NAA, Cho/Cr, and ADC ratio) were identified and 96.4% of total subjects were correctly classified. There was a significant difference between the diagnostic accuracy of the two discriminant analyses (Chi-square = 3.96, p = 0.046). Conclusion: Using discriminant analysis, this study found that MR spectroscopy in combination with ADC ratio, rather than ADC value, can improve the ability to differentiate recurrent glioma and radiation injury.« less

Early postoperative repair status after rotator cuff repair cannot be accurately classified using questionnaires of patient function and isokinetic strength evaluation.

PubMed

Colliver, Jessica; Wang, Allan; Joss, Brendan; Ebert, Jay; Koh, Eamon; Breidahl, William; Ackland, Timothy

2016-04-01

This study investigated if patients with an intact tendon repair or partial-thickness retear early after rotator cuff repair display differences in clinical evaluations and whether early tendon healing can be predicted using these assessments. We prospectively evaluated 60 patients at 16 weeks after arthroscopic supraspinatus repair. Evaluation included the Oxford Shoulder Score, 11-item version of the Disabilities of the Arm, Shoulder and Hand, visual analog scale for pain, 12-item Short Form Health Survey, isokinetic strength, and magnetic resonance imaging (MRI). Independent t tests investigated clinical differences in patients based on the Sugaya MRI rotator cuff classification system (grades 1, 2, or 3). Discriminant analysis determined whether intact repairs (Sugaya grade 1) and partial-thickness retears (Sugaya grades 2 and 3) could be predicted. No differences (P < .05) existed in the clinical or strength measures. Although discriminant analysis revealed the 11-item version of the Disabilities of the Arm, Shoulder and Hand produced a 97% true-positive rate for predicting partial thickness retears, it also produced a 90% false-positive rate whereby it incorrectly predicted a retear in 90% of patients whose repair was intact. The ability to discriminate between groups was enhanced with up to 5 variables entered; however, only 87% of the partial-retear group and 36% of the intact-repair group were correctly classified. No differences in clinical scores existed between patients stratified by the Sugaya MRI classification system at 16 weeks. An intact repair or partial-thickness retear could not be accurately predicted. Our results suggest that correct classification of healing in the early postoperative stages should involve imaging. Copyright © 2016 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

Identification of Medicinal Mugua Origin by Near Infrared Spectroscopy Combined with Partial Least-squares Discriminant Analysis.

PubMed

Han, Bangxing; Peng, Huasheng; Yan, Hui

2016-01-01

Mugua is a common Chinese herbal medicine. There are three main medicinal origin places in China, Xuancheng City Anhui Province, Qijiang District Chongqing City, Yichang City, Hubei Province, and suitable for food origin places Linyi City Shandong Province. To construct a qualitative analytical method to identify the origin of medicinal Mugua by near infrared spectroscopy (NIRS). Partial least squares discriminant analysis (PLSDA) model was established after the Mugua derived from five different origins were preprocessed by the original spectrum. Moreover, the hierarchical cluster analysis was performed. The result showed that PLSDA model was established. According to the relationship of the origins-related important score and wavenumber, and K-mean cluster analysis, the Muguas derived from different origins were effectively identified. NIRS technology can quickly and accurately identify the origin of Mugua, provide a new method and technology for the identification of Chinese medicinal materials. After preprocessed by D1+autoscale, more peaks were increased in the preprocessed Mugua in the near infrared spectrumFive latent variable scores could reflect the information related to the origin place of MuguaOrigins of Mugua were well-distinguished according to K. mean value clustering analysis. Abbreviations used: TCM: Traditional Chinese Medicine, NIRS: Near infrared spectroscopy, SG: Savitzky-Golay smoothness, D1: First derivative, D2: Second derivative, SNV: Standard normal variable transformation, MSC: Multiplicative scatter correction, PLSDA: Partial least squares discriminant analysis, LV: Latent variable, VIP scores: Important score.

An investigation of the use of discriminant analysis for the classification of blade edge type from cut marks made by metal and bamboo blades.

PubMed

Bonney, Heather

2014-08-01

Analysis of cut marks in bone is largely limited to two dimensional qualitative description. Development of morphological classification methods using measurements from cut mark cross sections could have multiple uses across palaeoanthropological and archaeological disciplines, where cutting edge types are used to investigate and reconstruct behavioral patterns. An experimental study was undertaken, using porcine bone, to determine the usefulness of discriminant function analysis in classifying cut marks by blade edge type, from a number of measurements taken from their cross-sectional profile. The discriminant analysis correctly classified 86.7% of the experimental cut marks into serrated, non-serrated and bamboo blade types. The technique was then used to investigate a series of cut marks of unknown origin from a collection of trophy skulls from the Torres Strait Islands, to investigate whether they were made by bamboo or metal blades. Nineteen out of twenty of the cut marks investigated were classified as bamboo which supports the non-contemporaneous ethnographic accounts of the knives used for trophy taking and defleshing remains. With further investigation across a variety of blade types, this technique could prove a valuable tool in the interpretation of cut mark evidence from a wide variety of contexts, particularly in forensic anthropology where the requirement for presentation of evidence in a statistical format is becoming increasingly important. © 2014 Wiley Periodicals, Inc.

Effective Identification of Low-Gliadin Wheat Lines by Near Infrared Spectroscopy (NIRS): Implications for the Development and Analysis of Foodstuffs Suitable for Celiac Patients

PubMed Central

García-Molina, María Dolores; García-Olmo, Juan; Barro, Francisco

2016-01-01

Scope The aim of this work was to assess the ability of Near Infrared Spectroscopy (NIRS) to distinguish wheat lines with low gliadin content, obtained by RNA interference (RNAi), from non-transgenic wheat lines. The discriminant analysis was performed using both whole grain and flour. The transgenic sample set included 409 samples for whole grain sorting and 414 samples for flour experiments, while the non-transgenic set consisted of 126 and 156 samples for whole grain and flour, respectively. Methods and Results Samples were scanned using a Foss-NIR Systems 6500 System II instrument. Discrimination models were developed using the entire spectral range (400–2500 nm) and ranges of 400–780 nm, 800–1098 nm and 1100–2500 nm, followed by analysis of means of partial least square (PLS). Two external validations were made, using samples from the years 2013 and 2014 and a minimum of 99% of the flour samples and 96% of the whole grain samples were classified correctly. Conclusions The results demonstrate the ability of NIRS to successfully discriminate between wheat samples with low-gliadin content and wild types. These findings are important for the development and analysis of foodstuff for celiac disease (CD) patients to achieve better dietary composition and a reduction in disease incidence. PMID:27018786

Classification of Antibiotic Resistance Patterns of Indicator Bacteria by Discriminant Analysis: Use in Predicting the Source of Fecal Contamination in Subtropical Waters

PubMed Central

Harwood, Valerie J.; Whitlock, John; Withington, Victoria

2000-01-01

The antibiotic resistance patterns of fecal streptococci and fecal coliforms isolated from domestic wastewater and animal feces were determined using a battery of antibiotics (amoxicillin, ampicillin, cephalothin, chlortetracycline, oxytetracycline, tetracycline, erythromycin, streptomycin, and vancomycin) at four concentrations each. The sources of animal feces included wild birds, cattle, chickens, dogs, pigs, and raccoons. Antibiotic resistance patterns of fecal streptococci and fecal coliforms from known sources were grouped into two separate databases, and discriminant analysis of these patterns was used to establish the relationship between the antibiotic resistance patterns and the bacterial source. The fecal streptococcus and fecal coliform databases classified isolates from known sources with similar accuracies. The average rate of correct classification for the fecal streptococcus database was 62.3%, and that for the fecal coliform database was 63.9%. The sources of fecal streptococci and fecal coliforms isolated from surface waters were identified by discriminant analysis of their antibiotic resistance patterns. Both databases identified the source of indicator bacteria isolated from surface waters directly impacted by septic tank discharges as human. At sample sites selected for relatively low anthropogenic impact, the dominant sources of indicator bacteria were identified as various animals. The antibiotic resistance analysis technique promises to be a useful tool in assessing sources of fecal contamination in subtropical waters, such as those in Florida. PMID:10966379

Discrimination of winter wheat on irrigated land in southern Finney County, Kansas

NASA Technical Reports Server (NTRS)

Morain, S. A. (Principal Investigator); Williams, D. L.; Barker, B.; Coiner, J. C.

1973-01-01

The author has identified the following significant results. Winter wheat in the large field irrigated landscape of southern Finney County, Kansas was successfully discriminated by use of 4 ERTS-1 images. These images were acquired 16 August 1972, 21 September 1972, and 2 December 1972. MSS-5 images from each date and the MSS-7 image from 2 December 1972 were used. Human interpretation of the four images resulted in a classification scheme which produced 98% correct estimation of the number of wheat fields in the training sample and 100% correct estimation in the test sample. Overall correct separation of wheat from non-wheat fields was 93% and 86%, respectively. Offsetting errors resulted in the estimation accuracy for wheat.

Pavlovian conditioning enhances resistance to disruption of dogs performing an odor discrimination.

PubMed

Hall, Nathaniel J; Smith, David W; Wynne, Clive D L

2015-05-01

Domestic dogs are used to aid in the detection of a variety of substances such as narcotics and explosives. Under real-world detection situations there are many variables that may disrupt the dog's performance. Prior research on behavioral momentum theory suggests that higher rates of reinforcement produce greater resistance to disruption, and that this is heavily influenced by the stimulus-reinforcer relationship. The present study tests the Pavlovian interpretation of resistance to change using dogs engaged in an odor discrimination task. Dogs were trained on two odor discriminations that alternated every six trials akin to a multiple schedule in which the reinforcement probability for a correct response was always 1. Dogs then received several sessions of either odor Pavlovian conditioning to the S+ of one odor discrimination (Pavlovian group) or explicitly unpaired exposure to the S+ of one odor discrimination (Unpaired group). The remaining odor discrimination pair for each dog always remained an unexposed control. Resistance to disruption was assessed under presession feeding, a food-odor disruptor condition, and extinction, with baseline sessions intervening between disruption conditions. Equivalent baseline detection rates were observed across experimental groups and odorant pairs. Under disruption conditions, Pavlovian conditioning led to enhanced resistance to disruption of detection performance compared to the unexposed control odor discrimination. Unpaired odor conditioning did not influence resistance to disruption. These results suggest that changes in Pavlovian contingencies are sufficient to influence resistance to change. © Society for the Experimental Analysis of Behavior.

NIR spectroscopy as a tool for discriminating between lichens exposed to air pollution.

PubMed

Casale, Monica; Bagnasco, Lucia; Giordani, Paolo; Mariotti, Mauro Giorgio; Malaspina, Paola

2015-09-01

Lichens are used as biomonitors of air pollution because they are extremely sensitive to the presence of substances that alter atmospheric composition. Fifty-one thalli of two different varieties of Pseudevernia furfuracea (var. furfuracea and var. ceratea) were collected far from local sources of air pollution. Twenty-six of these thalli were then exposed to the air for one month in the industrial port of Genoa, which has high levels of environmental pollution. The possibility of using Near-infrared spectroscopy (NIRS) for generating a 'fingerprint' of lichens was investigated. Chemometric methods were successfully applied to discriminate between samples from polluted and non-polluted areas. In particular, Principal Component Analysis (PCA) was applied as a multivariate display method on the NIR spectra to visualise the data structure. This showed that the difference between samples of different varieties was not significant in comparison to the difference between samples exposed to different levels of environmental pollution. Then Linear Discriminant Analysis (LDA) was carried out to discriminate between lichens based on their exposure to pollutants. The distinction between control samples (not exposed) and samples exposed to the air in the industrial port of Genoa was evaluated. On average, 95.2% of samples were correctly classified, 93.0% of total internal prediction (5 cross-validation groups) and 100.0% of external prediction (on the test set) was achieved. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Colorimetric Sensor for Qualitative Discrimination and Quantitative Detection of Volatile Amines

PubMed Central

Tang, Zhonglin; Yang, Jianhua; Yu, Junyun; Cui, Bo

2010-01-01

We have developed a novel colorimetric sensor based on a digital camera and white LED illumination. Colorimetric sensor arrays (CSAs) were made from a set of six chemically responsive dyes impregnated on an inert substrate plate by solution casting. Six common amine aqueous solutions, including dimethylamine, triethylamine, diisopropylamine, aniline, cyclohexylamine, and pyridine vaporized at 25 °C and six health-related trimethylamine (TMA) concentrations including 170 ppm, 51 ppm, 8 ppm, 2 ppm, 125 ppb and 50 ppb were analyzed by the sensor to test its ability for the qualitative discrimination and quantitative detection of volatile amines. We extracted the feature vectors of the CSA's response to the analytes from a fusional color space, which was obtained by conducting a joint search algorithm of sequential forward selection and sequential backward selection (SFS&SBS) based on the linear discriminant criteria (LDC) in a mixed color space composed of six common color spaces. The principle component analysis (PCA) followed by the hierarchical cluser analysis (HCA) were utilized to discriminate 12 analytes. Results showed that the colorimetric sensor grouped the six amine vapors and five TMA concentrations correctly, while TMA concentrations of 125 ppb and 50 ppb were indiscriminable from each other. The limitation of detection (LOD) of the sensor for TMA was found to be lower than 50 ppb. The CSAs were reusable for TMA concentrations below 8 ppm. PMID:22163560

Wave Mode Discrimination of Coded Ultrasonic Guided Waves Using Two-Dimensional Compressed Pulse Analysis.

PubMed

Malo, Sergio; Fateri, Sina; Livadas, Makis; Mares, Cristinel; Gan, Tat-Hean

2017-07-01

Ultrasonic guided waves testing is a technique successfully used in many industrial scenarios worldwide. For many complex applications, the dispersive nature and multimode behavior of the technique still poses a challenge for correct defect detection capabilities. In order to improve the performance of the guided waves, a 2-D compressed pulse analysis is presented in this paper. This novel technique combines the use of pulse compression and dispersion compensation in order to improve the signal-to-noise ratio (SNR) and temporal-spatial resolution of the signals. The ability of the technique to discriminate different wave modes is also highlighted. In addition, an iterative algorithm is developed to identify the wave modes of interest using adaptive peak detection to enable automatic wave mode discrimination. The employed algorithm is developed in order to pave the way for further in situ applications. The performance of Barker-coded and chirp waveforms is studied in a multimodal scenario where longitudinal and flexural wave packets are superposed. The technique is tested in both synthetic and experimental conditions. The enhancements in SNR and temporal resolution are quantified as well as their ability to accurately calculate the propagation distance for different wave modes.

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis

PubMed Central

Ferrand, Claude; Audiffren, Michel

2018-01-01

Background Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Methods Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. Results A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. Conclusions This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging. PMID:29850247

Cognitive Strategies and Physical Activity in Older Adults: A Discriminant Analysis.

PubMed

André, Nathalie; Ferrand, Claude; Albinet, Cédric; Audiffren, Michel

2018-01-01

Although a number of studies have examined sociodemographic, psychosocial, and environmental determinants of the level of physical activity (PA) for older people, little attention has been paid to the predictive power of cognitive strategies for independently living older adults. However, cognitive strategies have recently been considered to be critical in the management of day-to-day living. Data were collected from 243 men and women aged 55 years and older living in France using face-to-face interviews between 2011 and 2013. A stepwise discriminant analysis selected five predictor variables (age, perceived health status, barriers' self-efficacy, internal memory, and attentional control strategies) of the level of PA. The function showed that the rate of correct prediction was 73% for the level of PA. The calculated discriminant function based on the five predictor variables is useful for detecting individuals at high risk of lapses once engaged in regular PA. This study highlighted the need to consider cognitive functions as a determinant of the level of PA and, more specifically, those cognitive functions related to executive functions (internal memory and attentional control), to facilitate the maintenance of regular PA. These results are discussed in relation to successful aging.

Classification of lung cancer patients and controls by chromatography of modified nucleosides in serum

USGS Publications Warehouse

McEntire, John E.; Kuo, Kenneth C.; Smith, Mark E.; Stalling, David L.; Richens, Jack W.; Zumwalt, Robert W.; Gehrke, Charles W.; Papermaster, Ben W.

1989-01-01

A wide spectrum of modified nucleosides has been quantified by high-performance liquid chromatography in serum of 49 male lung cancer patients, 35 patients with other cancers, and 48 patients hospitalized for nonneoplastic diseases. Data for 29 modified nucleoside peaks were normalized to an internal standard and analyzed by discriminant analysis and stepwise discriminant analysis. A model based on peaks selected by a stepwise discriminant procedure correctly classified 79% of the cancer and 75% of the noncancer subjects. It also demonstrated 84% sensitivity and 79% specificity when comparing lung cancer to noncancer subjects, and 80% sensitivity and 55% specificity in comparing lung cancer to other cancers. The nucleoside peaks having the greatest influence on the models varied dependent on the subgroups compared, confirming the importance of quantifying a wide array of nucleosides. These data support and expand previous studies which reported the utility of measuring modified nucleoside levels in serum and show that precise measurement of an array of 29 modified nucleosides in serum by high-performance liquid chromatography with UV scanning with subsequent data modeling may provide a clinically useful approach to patient classification in diagnosis and subsequent therapeutic monitoring.

Normal peer models and autistic children's learning.

PubMed Central

Egel, A L; Richman, G S; Koegel, R L

1981-01-01

Present research and legislation regarding mainstreaming autistic children into normal classrooms have raised the importance of studying whether autistic children can benefit from observing normal peer models. The present investigation systematically assessed whether autistic children's learning of discrimination tasks could be improved if they observed normal children perform the tasks correctly. In the context of a multiple baseline design, four autistic children worked on five discrimination tasks that their teachers reported were posing difficulty. Throughout the baseline condition the children evidenced very low levels of correct responding on all five tasks. In the subsequent treatment condition, when normal peers modeled correct responses, the autistic children's correct responding increased dramatically. In each case, the peer modeling procedure produced rapid achievement of the acquisition which was maintained after the peer models were removed. These results are discussed in relation to issues concerning observational learning and in relation to the implications for mainstreaming autistic children into normal classrooms. PMID:7216930

HIV Stigma in Prisons and Jails: Results from a Staff Survey

PubMed Central

Dembo, Richard; Copenhaver, Michael; Hiller, Matthew; Swan, Holly; Garcia, Carmen Albizu; O’Connell, Daniel; Oser, Carrie; Pearson, Frank; Pankow, Jennifer

2015-01-01

With numerous HIV service gaps in prisons and jails, there has been little research on HIV stigma attitudes among correctional staff. Such attitudes may undermine HIV services for inmates at risk of or infected with HIV. This HIV stigma attitudes survey among 218 correctional staff in 32 US facilities (1) provides an overview of staff’s stigma attitudes, (2) reports psychometric analyses of domains in Earnshaw and Chaudoir’s HIV Stigma Framework (HSF), and (3) explores differences in stigma attitudes among different staff types. Overall, correctional and medical staff expressed non stigmatizing attitudes toward people living with HIV/AIDS, but perceived that stigma and discrimination exist in others. Factor analyses revealed a three factor structure capturing two mechanisms of the HSF (prejudice, discrimination). Few factor score differences were found by staff type or setting. Implications for correctional HIV services and future research on HIV stigma attitudes are discussed. PMID:26036464

HIV Stigma in Prisons and Jails: Results from a Staff Survey.

PubMed

Belenko, Steven; Dembo, Richard; Copenhaver, Michael; Hiller, Matthew; Swan, Holly; Albizu Garcia, Carmen; O'Connell, Daniel; Oser, Carrie; Pearson, Frank; Pankow, Jennifer

2016-01-01

With numerous HIV service gaps in prisons and jails, there has been little research on HIV stigma attitudes among correctional staff. Such attitudes may undermine HIV services for inmates at risk of or infected with HIV. This HIV stigma attitudes survey among 218 correctional staff in 32 US facilities (1) provides an overview of staff's stigma attitudes, (2) reports psychometric analyses of domains in Earnshaw and Chaudoir's HIV Stigma Framework (HSF), and (3) explores differences in stigma attitudes among different staff types. Overall, correctional and medical staff expressed non stigmatizing attitudes toward people living with HIV/AIDS, but perceived that stigma and discrimination exist in others. Factor analyses revealed a three factor structure capturing two mechanisms of the HSF (prejudice, discrimination). Few factor score differences were found by staff type or setting. Implications for correctional HIV services and future research on HIV stigma attitudes are discussed.

Cross-modal cueing effects of visuospatial attention on conscious somatosensory perception.

PubMed

Doruk, Deniz; Chanes, Lorena; Malavera, Alejandra; Merabet, Lotfi B; Valero-Cabré, Antoni; Fregni, Felipe

2018-04-01

The impact of visuospatial attention on perception with supraliminal stimuli and stimuli at the threshold of conscious perception has been previously investigated. In this study, we assess the cross-modal effects of visuospatial attention on conscious perception for near-threshold somatosensory stimuli applied to the face. Fifteen healthy participants completed two sessions of a near-threshold cross-modality cue-target discrimination/conscious detection paradigm. Each trial began with an endogenous visuospatial cue that predicted the location of a weak near-threshold electrical pulse delivered to the right or left cheek with high probability (∼75%). Participants then completed two tasks: first, a forced-choice somatosensory discrimination task (felt once or twice?) and then, a somatosensory conscious detection task (did you feel the stimulus and, if yes, where (left/right)?). Somatosensory discrimination was evaluated with the response reaction times of correctly detected targets, whereas the somatosensory conscious detection was quantified using perceptual sensitivity (d') and response bias (beta). A 2 × 2 repeated measures ANOVA was used for statistical analysis. In the somatosensory discrimination task (1 st task), participants were significantly faster in responding to correctly detected targets (p < 0.001). In the somatosensory conscious detection task (2 nd task), a significant effect of visuospatial attention on response bias (p = 0.008) was observed, suggesting that participants had a less strict criterion for stimuli preceded by spatially valid than invalid visuospatial cues. We showed that spatial attention has the potential to modulate the discrimination and the conscious detection of near-threshold somatosensory stimuli as measured, respectively, by a reduction of reaction times and a shift in response bias toward less conservative responses when the cue predicted stimulus location. A shift in response bias indicates possible effects of spatial attention on internal decision processes. The lack of significant results in perceptual sensitivity (d') could be due to weaker effects of endogenous attention on perception.

Neural indices of phonemic discrimination and sentence-level speech intelligibility in quiet and noise: A P3 study.

PubMed

Koerner, Tess K; Zhang, Yang; Nelson, Peggy B; Wang, Boxiang; Zou, Hui

2017-07-01

This study examined how speech babble noise differentially affected the auditory P3 responses and the associated neural oscillatory activities for consonant and vowel discrimination in relation to segmental- and sentence-level speech perception in noise. The data were collected from 16 normal-hearing participants in a double-oddball paradigm that contained a consonant (/ba/ to /da/) and vowel (/ba/ to /bu/) change in quiet and noise (speech-babble background at a -3 dB signal-to-noise ratio) conditions. Time-frequency analysis was applied to obtain inter-trial phase coherence (ITPC) and event-related spectral perturbation (ERSP) measures in delta, theta, and alpha frequency bands for the P3 response. Behavioral measures included percent correct phoneme detection and reaction time as well as percent correct IEEE sentence recognition in quiet and in noise. Linear mixed-effects models were applied to determine possible brain-behavior correlates. A significant noise-induced reduction in P3 amplitude was found, accompanied by significantly longer P3 latency and decreases in ITPC across all frequency bands of interest. There was a differential effect of noise on consonant discrimination and vowel discrimination in both ERP and behavioral measures, such that noise impacted the detection of the consonant change more than the vowel change. The P3 amplitude and some of the ITPC and ERSP measures were significant predictors of speech perception at segmental- and sentence-levels across listening conditions and stimuli. These data demonstrate that the P3 response with its associated cortical oscillations represents a potential neurophysiological marker for speech perception in noise. Copyright © 2017 Elsevier B.V. All rights reserved.

45 CFR 1151.34 - Preemployment inquiries.

Code of Federal Regulations, 2014 CFR

2014-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... handicapped person, or inquire as to the nature or severity of a handicap. A recipient may, however, make... taking remedial action to correct the effects of past discrimination, when a recipient is taking...

45 CFR 1151.34 - Preemployment inquiries.

Code of Federal Regulations, 2012 CFR

2012-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... handicapped person, or inquire as to the nature or severity of a handicap. A recipient may, however, make... taking remedial action to correct the effects of past discrimination, when a recipient is taking...

45 CFR 1151.34 - Preemployment inquiries.

Code of Federal Regulations, 2011 CFR

2011-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... handicapped person, or inquire as to the nature or severity of a handicap. A recipient may, however, make... taking remedial action to correct the effects of past discrimination, when a recipient is taking...

45 CFR 1151.34 - Preemployment inquiries.

Code of Federal Regulations, 2010 CFR

2010-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... handicapped person, or inquire as to the nature or severity of a handicap. A recipient may, however, make... taking remedial action to correct the effects of past discrimination, when a recipient is taking...

45 CFR 1151.34 - Preemployment inquiries.

Code of Federal Regulations, 2013 CFR

2013-10-01

... HUMANITIES NATIONAL ENDOWMENT FOR THE ARTS NONDISCRIMINATION ON THE BASIS OF HANDICAP Discrimination... handicapped person, or inquire as to the nature or severity of a handicap. A recipient may, however, make... taking remedial action to correct the effects of past discrimination, when a recipient is taking...

Assessment of forward head posture in females: observational and photogrammetry methods.

PubMed

Salahzadeh, Zahra; Maroufi, Nader; Ahmadi, Amir; Behtash, Hamid; Razmjoo, Arash; Gohari, Mahmoud; Parnianpour, Mohamad

2014-01-01

There are different methods to assess forward head posture (FHP) but the accuracy and discrimination ability of these methods are not clear. Here, we want to compare three postural angles for FHP assessment and also study the discrimination accuracy of three photogrammetric methods to differentiate groups categorized based on observational method. All Seventy-eight healthy female participants (23 ± 2.63 years), were classified into three groups: moderate-severe FHP, slight FHP and non FHP based on observational postural assessment rules. Applying three photogrammetric methods - craniovertebral angle, head title angle and head position angle - to measure FHP objectively. One - way ANOVA test showed a significant difference in three categorized group's craniovertebral angle (P< 0.05, F=83.07). There was no dramatic difference in head tilt angle and head position angle methods in three groups. According to Linear Discriminate Analysis (LDA) results, the canonical discriminant function (Wilks'Lambda) was 0.311 for craniovertebral angle with 79.5% of cross-validated grouped cases correctly classified. Our results showed that, craniovertebral angle method may discriminate the females with moderate-severe and non FHP more accurate than head position angle and head tilt angle. The photogrammetric method had excellent inter and intra rater reliability to assess the head and cervical posture.

Fourier transform near-infrared spectroscopy application for sea salt quality evaluation.

PubMed

Galvis-Sánchez, Andrea C; Lopes, João Almeida; Delgadillo, Ivonne; Rangel, António O S S

2011-10-26

Near-infrared (NIR) spectroscopy in diffuse reflectance mode was explored with the objective of discriminating sea salts according to their quality type (traditional salt vs "flower of salt") and geographical origin (Atlantic vs Mediterranean). Sea salts were also analyzed in terms of Ca(2+), Mg(2+), K(+), alkalinity, and sulfate concentrations to support spectroscopic results. High concentrations of Mg(2+) and K(+) characterized Atlantic samples, while a high Ca(2+) content was observed in traditional sea salts. A partial least-squares discriminant analysis model considering the 8500-7500 cm(-1) region permitted the discrimination of salts by quality types. The regions 4650-4350 and 5900-5500 cm(-1) allowed salts classification according to their geographical origin. It was possible to classify correctly 85.3 and 94.8% of the analyzed samples according to the salt type and to the geographical origin, respectively. These results demonstrated that NIR spectroscopy is a suitable and very efficient tool for sea salt quality evaluation.

Discrimination of hydrothermal alteration mineral assemblages at Virginia City, Nevada, using the airborne imaging spectrometer

NASA Technical Reports Server (NTRS)

Hutsinpiller, Amy

1988-01-01

The purpose of this study is to use airborne imaging spectrometer data to discriminate hydrothermal alteration mineral assemblages associated with silver and gold mineralization at Virginia City, NV. The data is corrected for vertical striping and sample gradients, and converted to flat-field logarithmic residuals. Log residual spectra from areas known to be altered are compared to field spectra for kaolinitic, illitic, sericitic, and propylitic alteration types. The areal distributions of these alteration types are estimated using a spectral matching technique. Both visual examination of spectra and the matching techniques are effective in distinguishing kaolinitic, illitic, and propylitic alteration types from each other. However, illitic and sericitic alteration cannot be separated using these techniques because the spectra of illite and sericite are very similar. A principal components analysis of 14 channels in the 2.14-2.38 micron wavelength region is also successful in discriminating and mapping illitic, kaolinitic, and propylitic alteration types.

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

Temple, E. C.; Shipman, J. R.

1981-01-01

Fisher's sample linear discriminant function is modified through an appropriate alteration of the common sample variance-covariance matrix. The alteration consists of adding nonnegative values to the eigenvalues of the sample variance covariance matrix. The desired results of this modification is to increase the number of correct classifications by the new linear discriminant function over Fisher's function. This study is limited to the two-group discriminant problem.

Gait characterization in golden retriever muscular dystrophy dogs using linear discriminant analysis.

PubMed

Fraysse, Bodvaël; Barthélémy, Inès; Qannari, El Mostafa; Rouger, Karl; Thorin, Chantal; Blot, Stéphane; Le Guiner, Caroline; Chérel, Yan; Hogrel, Jean-Yves

2017-04-12

Accelerometric analysis of gait abnormalities in golden retriever muscular dystrophy (GRMD) dogs is of limited sensitivity, and produces highly complex data. The use of discriminant analysis may enable simpler and more sensitive evaluation of treatment benefits in this important preclinical model. Accelerometry was performed twice monthly between the ages of 2 and 12 months on 8 healthy and 20 GRMD dogs. Seven accelerometric parameters were analysed using linear discriminant analysis (LDA). Manipulation of the dependent and independent variables produced three distinct models. The ability of each model to detect gait alterations and their pattern change with age was tested using a leave-one-out cross-validation approach. Selecting genotype (healthy or GRMD) as the dependent variable resulted in a model (Model 1) allowing a good discrimination between the gait phenotype of GRMD and healthy dogs. However, this model was not sufficiently representative of the disease progression. In Model 2, age in months was added as a supplementary dependent variable (GRMD_2 to GRMD_12 and Healthy_2 to Healthy_9.5), resulting in a high overall misclassification rate (83.2%). To improve accuracy, a third model (Model 3) was created in which age was also included as an explanatory variable. This resulted in an overall misclassification rate lower than 12%. Model 3 was evaluated using blinded data pertaining to 81 healthy and GRMD dogs. In all but one case, the model correctly matched gait phenotype to the actual genotype. Finally, we used Model 3 to reanalyse data from a previous study regarding the effects of immunosuppressive treatments on muscular dystrophy in GRMD dogs. Our model identified significant effect of immunosuppressive treatments on gait quality, corroborating the original findings, with the added advantages of direct statistical analysis with greater sensitivity and more comprehensible data representation. Gait analysis using LDA allows for improved analysis of accelerometry data by applying a decision-making analysis approach to the evaluation of preclinical treatment benefits in GRMD dogs.

Elemental source attribution signatures for calcium ammonium nitrate (CAN) fertilizers used in homemade explosives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fraga, Carlos G.; Mitroshkov, Alexander V.; Mirjankar, Nikhil S.

Calcium ammonium nitrate (CAN) is a widely available fertilizer composed of ammonium nitrate mixed with some form of calcium carbonate such as limestone or dolomite. CAN is also frequently used to make homemade explosives. The potential of using elemental profiling and chemometrics to match both pristine and reprocessed CAN fertilizers to their factories for use in future forensic investigations was examined. Inductively coupled plasma-mass spectrometry (ICP-MS) analysis was performed on 64 elements in 125 samples from 11 CAN stocks from 6 different CAN factories. Fisher ratio, degree-of-class-separation, and partial least squares discriminant analysis (PLSDA) were used to develop a modelmore » using the concentrations of Na, V, Mn, Cu, Ga, Sr, Ba and U to classify a validation set of CAN samples into 5 factory groups; one group was two factories from the same fertilizer company. In terms of the pristine CAN samples, i.e., unadulterated prills, 64% of the test samples were matched to their correct factory group with zero false positives. The same PLSDA model was used to correctly match 100% of the CAN samples that were reprocessed by crushing and mixing the CAN with powdered sugar. In the case of crushed CAN samples mixed with aluminum powder, correct matches were made for zero to 100% of the samples depending on the factory the CAN originated. Remarkably, for one factory, 100% of the ammonium nitrate samples that were extracted from CAN using tap or bottled water were matched to the correct CAN factory group. Lastly, the water-insoluble (calcium carbonate) portions of CAN provided a greater degree of discrimination between factories than the water-soluble portions of CAN. In summary, this work illustrates that sourcing unadulterated CAN fertilizer can potentially be done with high frequency and high confidence using elemental profiling and chemometrics while the sourcing of reprocessed CAN is dependent on how much an adulterant alters the recovered elemental profile of CAN.« less

Carbon isotope discrimination of arctic and boreal biomes inferred from remote atmospheric measurements and a biosphere-atmosphere model

NASA Astrophysics Data System (ADS)

Randerson, J. T.; Still, C. J.; Ballé, J. J.; Fung, I. Y.; Doney, S. C.; Tans, P. P.; Conway, T. J.; White, J. W. C.; Vaughn, B.; Suits, N.; Denning, A. S.

2002-07-01

Estimating discrimination against 13C during photosynthesis at landscape, regional, and biome scales is difficult because of large-scale variability in plant stress, vegetation composition, and photosynthetic pathway. Here we present estimates of 13C discrimination for northern biomes based on a biosphere-atmosphere model and on National Oceanic and Atmospheric Administration Climate Monitoring and Diagnostics Laboratory and Institute of Arctic and Alpine Research remote flask measurements. With our inversion approach, we solved for three ecophysiological parameters of the northern biosphere (13C discrimination, a net primary production light use efficiency, and a temperature sensitivity of heterotrophic respiration (a Q10 factor)) that provided a best fit between modeled and observed δ13C and CO2. In our analysis we attempted to explicitly correct for fossil fuel emissions, remote C4 ecosystem fluxes, ocean exchange, and isotopic disequilibria of terrestrial heterotrophic respiration caused by the Suess effect. We obtained a photosynthetic discrimination for arctic and boreal biomes between 19.0 and 19.6‰. Our inversion analysis suggests that Q10 and light use efficiency values that minimize the cost function covary. The optimal light use efficiency was 0.47 gC MJ-1 photosynthetically active radiation, and the optimal Q10 value was 1.52. Fossil fuel and ocean exchange contributed proportionally more to month-to-month changes in the atmospheric growth rate of δ13C and CO2 during winter months, suggesting that remote atmospheric observations during the summer may yield more precise estimates of the isotopic composition of the biosphere.

Signal peptide discrimination and cleavage site identification using SVM and NN.

PubMed

Kazemian, H B; Yusuf, S A; White, K

2014-02-01

About 15% of all proteins in a genome contain a signal peptide (SP) sequence, at the N-terminus, that targets the protein to intracellular secretory pathways. Once the protein is targeted correctly in the cell, the SP is cleaved, releasing the mature protein. Accurate prediction of the presence of these short amino-acid SP chains is crucial for modelling the topology of membrane proteins, since SP sequences can be confused with transmembrane domains due to similar composition of hydrophobic amino acids. This paper presents a cascaded Support Vector Machine (SVM)-Neural Network (NN) classification methodology for SP discrimination and cleavage site identification. The proposed method utilises a dual phase classification approach using SVM as a primary classifier to discriminate SP sequences from Non-SP. The methodology further employs NNs to predict the most suitable cleavage site candidates. In phase one, a SVM classification utilises hydrophobic propensities as a primary feature vector extraction using symmetric sliding window amino-acid sequence analysis for discrimination of SP and Non-SP. In phase two, a NN classification uses asymmetric sliding window sequence analysis for prediction of cleavage site identification. The proposed SVM-NN method was tested using Uni-Prot non-redundant datasets of eukaryotic and prokaryotic proteins with SP and Non-SP N-termini. Computer simulation results demonstrate an overall accuracy of 0.90 for SP and Non-SP discrimination based on Matthews Correlation Coefficient (MCC) tests using SVM. For SP cleavage site prediction, the overall accuracy is 91.5% based on cross-validation tests using the novel SVM-NN model. © 2013 Published by Elsevier Ltd.

[State Recognition of Solid Fermentation Process Based on Near Infrared Spectroscopy with Adaboost and Spectral Regression Discriminant Analysis].

PubMed

Yu, Shuang; Liu, Guo-hai; Xia, Rong-sheng; Jiang, Hui

2016-01-01

In order to achieve the rapid monitoring of process state of solid state fermentation (SSF), this study attempted to qualitative identification of process state of SSF of feed protein by use of Fourier transform near infrared (FT-NIR) spectroscopy analysis technique. Even more specifically, the FT-NIR spectroscopy combined with Adaboost-SRDA-NN integrated learning algorithm as an ideal analysis tool was used to accurately and rapidly monitor chemical and physical changes in SSF of feed protein without the need for chemical analysis. Firstly, the raw spectra of all the 140 fermentation samples obtained were collected by use of Fourier transform near infrared spectrometer (Antaris II), and the raw spectra obtained were preprocessed by use of standard normal variate transformation (SNV) spectral preprocessing algorithm. Thereafter, the characteristic information of the preprocessed spectra was extracted by use of spectral regression discriminant analysis (SRDA). Finally, nearest neighbors (NN) algorithm as a basic classifier was selected and building state recognition model to identify different fermentation samples in the validation set. Experimental results showed as follows: the SRDA-NN model revealed its superior performance by compared with other two different NN models, which were developed by use of the feature information form principal component analysis (PCA) and linear discriminant analysis (LDA), and the correct recognition rate of SRDA-NN model achieved 94.28% in the validation set. In this work, in order to further improve the recognition accuracy of the final model, Adaboost-SRDA-NN ensemble learning algorithm was proposed by integrated the Adaboost and SRDA-NN methods, and the presented algorithm was used to construct the online monitoring model of process state of SSF of feed protein. Experimental results showed as follows: the prediction performance of SRDA-NN model has been further enhanced by use of Adaboost lifting algorithm, and the correct recognition rate of the Adaboost-SRDA-NN model achieved 100% in the validation set. The overall results demonstrate that SRDA algorithm can effectively achieve the spectral feature information extraction to the spectral dimension reduction in model calibration process of qualitative analysis of NIR spectroscopy. In addition, the Adaboost lifting algorithm can improve the classification accuracy of the final model. The results obtained in this work can provide research foundation for developing online monitoring instruments for the monitoring of SSF process.

Exploring the Stability of Ligand Binding Modes to Proteins by Molecular Dynamics Simulations: A Cross-docking Study.

PubMed

Liu, Kai; Kokubo, Hironori

2017-10-23

Docking has become an indispensable approach in drug discovery research to predict the binding mode of a ligand. One great challenge in docking is to efficiently refine the correct pose from various putative docking poses through scoring functions. We recently examined the stability of self-docking poses under molecular dynamics (MD) simulations and showed that equilibrium MD simulations have some capability to discriminate between correct and decoy poses. Here, we have extended our previous work to cross-docking studies for practical applications. Three target proteins (thrombin, heat shock protein 90-alpha, and cyclin-dependent kinase 2) of pharmaceutical interest were selected. Three comparable poses (one correct pose and two decoys) for each ligand were then selected from the docking poses. To obtain the docking poses for the three target proteins, we used three different protocols, namely: normal docking, induced fit docking (IFD), and IFD against the homology model. Finally, five parallel MD equilibrium runs were performed on each pose for the statistical analysis. The results showed that the correct poses were generally more stable than the decoy poses under MD. The discrimination capability of MD depends on the strategy. The safest way was to judge a pose as being stable if any one run among five parallel runs was stable under MD. In this case, 95% of the correct poses were retained under MD, and about 25-44% of the decoys could be excluded by the simulations for all cases. On the other hand, if we judge a pose as being stable when any two or three runs were stable, with the risk of incorrectly excluding some correct poses, approximately 31-53% or 39-56% of the two decoys could be excluded by MD, respectively. Our results suggest that simple equilibrium simulations can serve as an effective filter to exclude decoy poses that cannot be distinguished by docking scores from the computationally expensive free-energy calculations.

Correction of the data generated by mass spectrometry analyses of biological tissues: application to food authentication.

PubMed

Engel, Erwan; Ratel, Jérémy

2007-06-22

The objective of the work was to assess the relevance for the authentication of food of a novel chemometric method developed to correct mass spectrometry (MS) data from instrumental drifts, namely, the comprehensive combinatory standard correction (CCSC). Applied to gas chromatography (GC)-MS data, the method consists in analyzing a liquid sample with a mixture of n internal standards and in using the best combination of standards to correct the MS signal provided by each compound. The paper focuses on the authentication of the type of feeding in farm animals based on the composition in volatile constituents of their adipose tissues. The first step of the work enabled on one hand to ensure the feasibility of the conversion of the adipose tissue sample into a liquid phase required for the use of the CCSC method and on the other hand, to determine the key parameters of the extraction of the volatile fraction from this liquid phase by dynamic headspace. The second step showed the relevance of the CCSC pre-processing of the MS fingerprints generated by dynamic headspace-MS analysis of lamb tissues, for the discrimination of animals fed exclusively with pasture (n=8) or concentrate (n=8). When compared with filtering of raw data, internal normalization and correction by a single standard, the CCSC method increased by 17.1-, 3.3- and 1.3-fold, respectively, the number of mass fragments which discriminated the type of feeding. The final step confirmed the advantage of the CCSC pre-processing of dynamic headspace-gas chromatography-MS data for revealing molecular tracers of the type of feeding those number (n=72) was greater when compared to the number of tracers obtained with raw data (n=42), internal normalization (n=63) and correction by a single standard (n=57). The relevance of the information gained by using the CCSC method is discussed.

Olfactory discrimination and generalization of ammonium nitrate and structurally related odorants in Labrador retrievers.

PubMed

Lazarowski, Lucia; Foster, Melanie L; Gruen, Margaret E; Sherman, Barbara L; Fish, Richard E; Milgram, Norton W; Dorman, David C

2015-11-01

A critical aspect of canine explosive detection involves the animal's ability respond to novel, untrained odors based on prior experience with training odors. In the current study, adult Labrador retrievers (N = 15) were initially trained to discriminate between a rewarded odor (vanillin) and an unrewarded odor (ethanol) by manipulating scented objects with their nose in order to receive a food reward using a canine-adapted discrimination training apparatus. All dogs successfully learned this olfactory discrimination task (≥80 % correct in a mean of 296 trials). Next, dogs were trained on an ammonium nitrate (AN, NH4NO3) olfactory discrimination task [acquired in 60-240 trials, with a mean (±SEM) number of trials to criterion of 120.0 ± 15.6] and then tested for their ability to respond to untrained ammonium- and/or nitrate-containing chemicals as well as variants of AN compounds. Dogs did not respond to sodium nitrate or ammonium sulfate compounds at rates significantly higher than chance (58.8 ± 4.5 and 57.7 ± 3.3 % correct, respectively). Transfer performance to fertilizer-grade AN, AN mixed in Iraqi soil, and AN and flaked aluminum was significantly higher than chance (66.7 ± 3.2, 73.3 ± 4.0, 68.9 ± 4.0 % correct, respectively); however, substantial individual differences were observed. Only 53, 60, and 64 % of dogs had a correct response rate with fertilizer-grade AN, AN and Iraqi soil, and AN and flaked aluminum, respectively, that were greater than chance. Our results suggest that dogs do not readily generalize from AN to similar AN-based odorants at reliable levels desired for explosive detection dogs and that performance varies significantly within Labrador retrievers selected for an explosive detection program.

Analysis of Stomata Distribution Patterns for Quantification of the Foliar Plasticity of Tradescantia Zebrina

NASA Astrophysics Data System (ADS)

Batista Florindo, Joao; Landini, Gabriel; Almeida Filho, Humberto; Martinez Bruno, Odemir

2015-09-01

Here we propose a method for the analysis of the stomata distribution patterns on the surface of plant leaves. We also investigate how light exposure during growth can affect stomata distribution and the plasticity of leaves. Understanding foliar plasticity (the ability of leaves to modify their structural organization to adapt to changing environmental resources) is a fundamental problem in Agricultural and Environmental Sciences. Most published work on quantification of stomata has concentrated on descriptions of their density per unit of leaf area, however density alone does not provide a complete description of the problem and leaves several unanswered questions (e.g. whether the stomata patterns change across various areas of the leaf, or how the patterns change under varying observational scales). We used two approaches here, to know, multiscale fractal dimension and complex networks, as a means to provide a description of the complexity of these distributions. In the experiments, we used 18 samples from the plant Tradescantia Zebrina grown under three different conditions (4 hours of artificial light each day, 24 hours of artificial light each day, and sunlight) for a total of 69 days. The network descriptors were capable of correctly discriminating the different conditions in 88% of cases, while the fractal descriptors discriminated 83% of the samples. This is a significant improvement over the correct classification rates achieved when using only stomata density (56% of the samples).

Rapid discrimination of bergamot essential oil by paper spray mass spectrometry and chemometric analysis.

PubMed

Taverna, Domenico; Di Donna, Leonardo; Mazzotti, Fabio; Tagarelli, Antonio; Napoli, Anna; Furia, Emilia; Sindona, Giovanni

2016-09-01

A novel approach for the rapid discrimination of bergamot essential oil from other citrus fruits oils is presented. The method was developed using paper spray mass spectrometry (PS-MS) allowing for a rapid molecular profiling coupled with a statistic tool for a precise and reliable discrimination between the bergamot complex matrix and other similar matrices, commonly used for its reconstitution. Ambient mass spectrometry possesses the ability to record mass spectra of ordinary samples, in their native environment, without sample preparation or pre-separation by creating ions outside the instrument. The present study reports a PS-MS method for the determination of oxygen heterocyclic compounds such as furocoumarins, psoralens and flavonoids present in the non-volatile fraction of citrus fruits essential oils followed by chemometric analysis. The volatile fraction of Bergamot is one of the most known and fashionable natural products, which found applications in flavoring industry as ingredient in beverages and flavored foodstuff. The development of the presented method employed bergamot, sweet orange, orange, cedar, grapefruit and mandarin essential oils. PS-MS measurements were carried out in full scan mode for a total run time of 2 min. The capability of PS-MS profiling to act as marker for the classification of bergamot essential oils was evaluated by using multivariate statistical analysis. Two pattern recognition techniques, linear discriminant analysis and soft independent modeling of class analogy, were applied to MS data. The cross-validation procedure has shown excellent results in terms of the prediction ability because both models have correctly classified all samples for each category. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

A discriminant analysis prediction model of non-syndromic cleft lip with or without cleft palate based on risk factors.

PubMed

Li, Huixia; Luo, Miyang; Luo, Jiayou; Zheng, Jianfei; Zeng, Rong; Du, Qiyun; Fang, Junqun; Ouyang, Na

2016-11-23

A risk prediction model of non-syndromic cleft lip with or without cleft palate (NSCL/P) was established by a discriminant analysis to predict the individual risk of NSCL/P in pregnant women. A hospital-based case-control study was conducted with 113 cases of NSCL/P and 226 controls without NSCL/P. The cases and the controls were obtained from 52 birth defects' surveillance hospitals in Hunan Province, China. A questionnaire was administered in person to collect the variables relevant to NSCL/P by face to face interviews. Logistic regression models were used to analyze the influencing factors of NSCL/P, and a stepwise Fisher discriminant analysis was subsequently used to construct the prediction model. In the univariate analysis, 13 influencing factors were related to NSCL/P, of which the following 8 influencing factors as predictors determined the discriminant prediction model: family income, maternal occupational hazards exposure, premarital medical examination, housing renovation, milk/soymilk intake in the first trimester of pregnancy, paternal occupational hazards exposure, paternal strong tea drinking, and family history of NSCL/P. The model had statistical significance (lambda = 0.772, chi-square = 86.044, df = 8, P < 0.001). Self-verification showed that 83.8 % of the participants were correctly predicted to be NSCL/P cases or controls with a sensitivity of 74.3 % and a specificity of 88.5 %. The area under the receiver operating characteristic curve (AUC) was 0.846. The prediction model that was established using the risk factors of NSCL/P can be useful for predicting the risk of NSCL/P. Further research is needed to improve the model, and confirm the validity and reliability of the model.

Are you positive? Electric dipole polarity discrimination in the yellow stingray, Urobatis jamaicensis.

PubMed

Siciliano, Avery M; Kajiura, Stephen M; Long, John H; Porter, Marianne E

2013-10-01

It is well established that elasmobranchs can detect dipole electric fields. However, it is unclear whether they can discriminate between the anode and cathode. To investigate this subject, we employed a behavioral assay to determine the discriminatory ability of the yellow stingray, Urobatis jamaicensis. We conditioned stingrays with food rewards to bite either the anode (n=5) or the cathode (n=6) of a direct-current dipole located on the floor of an experimental tank. All individuals successfully performed the task after 18 to 22 days. Stingrays were then tested in experimental sessions when they were rewarded only after they identified the correct pole. Stingrays successfully discriminated between the poles at a rate greater than chance, ranging among individuals from a mean of 66% to 93% correct. During experimental sessions, stingrays conditioned to distinguish the anode performed similarly to those conditioned to distinguish the cathode. We hypothesize that the ability to discriminate anode from cathode is physiologically encoded, but its utility in providing spatial information under natural conditions remains to be demonstrated. The ability to discriminate polarity may eliminate ambiguity in induction-based magnetoreception and facilitate navigation with respect to the geomagnetic field.

Development of a speaker discrimination test for cochlear implant users based on the Oldenburg Logatome corpus.

PubMed

Mühler, Roland; Ziese, Michael; Rostalski, Dorothea

2009-01-01

The purpose of the study was to develop a speaker discrimination test for cochlear implant (CI) users. The speech material was drawn from the Oldenburg Logatome (OLLO) corpus, which contains 150 different logatomes read by 40 German and 10 French native speakers. The prototype test battery included 120 logatome pairs spoken by 5 male and 5 female speakers with balanced representations of the conditions 'same speaker' and 'different speaker'. Ten adult normal-hearing listeners and 12 adult postlingually deafened CI users were included in a study to evaluate the suitability of the test. The mean speaker discrimination score for the CI users was 67.3% correct and for the normal-hearing listeners 92.2% correct. A significant influence of voice gender and fundamental frequency difference on the speaker discrimination score was found in CI users as well as in normal-hearing listeners. Since the test results of the CI users were significantly above chance level and no ceiling effect was observed, we conclude that subsets of the OLLO corpus are very well suited to speaker discrimination experiments in CI users. Copyright 2008 S. Karger AG, Basel.

Differences in Perception of Musical Stimuli among Acoustic, Electric, and Combined Modality Listeners.

PubMed

Prentiss, Sandra M; Friedland, David R; Nash, John J; Runge, Christina L

2015-05-01

Cochlear implants have shown vast improvements in speech understanding for those with severe to profound hearing loss; however, music perception remains a challenge for electric hearing. It is unclear whether the difficulties arise from limitations of sound processing, the nature of a damaged auditory system, or a combination of both. To examine music perception performance with different acoustic and electric hearing configurations. Chord discrimination and timbre perception were tested in subjects representing four daily-use listening configurations: unilateral cochlear implant (CI), contralateral bimodal (CIHA), bilateral hearing aid (HAHA) and normal-hearing (NH) listeners. A same-different task was used for discrimination of two chords played on piano. Timbre perception was assessed using a 10-instrument forced-choice identification task. Fourteen adults were included in each group, none of whom were professional musicians. The number of correct responses was divided by the total number of presentations to calculate scores in percent correct. Data analyses were performed with Kruskal-Wallis one-way analysis of variance and linear regression. Chord discrimination showed a narrow range of performance across groups, with mean scores ranging between 72.5% (CI) and 88.9% (NH). Significant differences were seen between the NH and all hearing-impaired groups. Both the HAHA and CIHA groups performed significantly better than the CI groups, and no significant differences were observed between the HAHA and CIHA groups. Timbre perception was significantly poorer for the hearing-impaired groups (mean scores ranged from 50.3-73.9%) compared to NH (95.2%). Significantly better performance was observed in the HAHA group as compared to both groups with electric hearing (CI and CIHA). There was no significant difference in performance between the CIHA and CI groups. Timbre perception was a significantly more difficult task than chord discrimination for both the CI and CIHA groups, yet the easier task for the NH group. A significant difference between the two tasks was not seen in the HAHA group. Having impaired hearing decreases performance compared to NH across both chord discrimination and timbre perception tasks. For chord discrimination, having acoustic hearing improved performance compared to electric hearing only. Timbre perception distinguished those with acoustic hearing from those with electric hearing. Those with bilateral acoustic hearing, even if damaged, performed significantly better on this task than those requiring electrical stimulation, which may indicate that CI sound processing fails to capture and deliver the necessary acoustic cues for timbre perception. Further analysis of timbre characteristics in electric hearing may contribute to advancements in programming strategies to obtain optimal hearing outcomes. American Academy of Audiology.

"Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling": Correction to Park et al. (2016).

PubMed

2017-02-01

Reports an error in "Does Anger Regulation Mediate the Discrimination-Mental Health Link Among Mexican-Origin Adolescents? A Longitudinal Mediation Analysis Using Multilevel Modeling" by Irene J. K. Park, Lijuan Wang, David R. Williams and Margarita Alegría ( Developmental Psychology , Advanced Online Publication, Nov 28, 2016, np). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n=246 . Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n= 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2016-57671-001.) Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn, more frequent outward anger expression was associated with higher levels of anxiety and depression at a given time point. Gender, age, and nativity status were not significant moderators of the hypothesized mediation models. By identifying outward anger expression as an explanatory mechanism in the discrimination-distress link among Latino youths, this study points to a malleable target for prevention and intervention efforts aimed at mitigating the detrimental impact of racism on Latino youths' mental health during the developmentally critical period of adolescence. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

[Social self-positioning as indicator of socioeconomic status].

PubMed

Fernández, E; Alonso, R M; Quer, A; Borrell, C; Benach, J; Alonso, J; Gómez, G

2000-01-01

Self-perceived class results from directly questioning subjects about his or her social class. The aim of this investigation was to analyse self-perceived class in relation to other indicator variables of socioeconomic level. Data from the 1994 Catalan Health Interview Survey, a cross-sectional survey of a representative sample of the non-institutionalised population of Catalonia was used. We conducted a discriminant analysis to compute the degree of right classification when different socioeconomic variables potentially related to self-perceived class were considered. All subjects who directly answered the questionnaire were included (N = 12,245). With the aim of obtaining the discriminant functions in a group of subjects and to validate it in another one, the subjects were divided into two random samples, containing approximately 75% and 25% of subjects (analysis sample, n = 9,248; and validation sample, n = 2,997). The final function for men and women included level of education, social class (based in occupation) and equivalent income. This function correctly classified 40.9% of the subjects in the analysis sample and 39.2% in the validation sample. Two other functions were selected for men and women separately. In men, the function included level of education, professional category, and family income (39.2% of classification in analysis sample and 37.2% in validation sample). In women, the function (level of education, working status, and equivalent income) correctly classified 40.3% of women in analysis sample whereas the percentage was 38.9% in validation sample. The percentages of right classification were higher for the highest and lowest classes. These results show the utility of a simple variable to self-position within the social scale. Self-perceived class is related to education, income, and working determinants.

Local classification: Locally weighted-partial least squares-discriminant analysis (LW-PLS-DA).

PubMed

Bevilacqua, Marta; Marini, Federico

2014-08-01

The possibility of devising a simple, flexible and accurate non-linear classification method, by extending the locally weighted partial least squares (LW-PLS) approach to the cases where the algorithm is used in a discriminant way (partial least squares discriminant analysis, PLS-DA), is presented. In particular, to assess which category an unknown sample belongs to, the proposed algorithm operates by identifying which training objects are most similar to the one to be predicted and building a PLS-DA model using these calibration samples only. Moreover, the influence of the selected training samples on the local model can be further modulated by adopting a not uniform distance-based weighting scheme which allows the farthest calibration objects to have less impact than the closest ones. The performances of the proposed locally weighted-partial least squares-discriminant analysis (LW-PLS-DA) algorithm have been tested on three simulated data sets characterized by a varying degree of non-linearity: in all cases, a classification accuracy higher than 99% on external validation samples was achieved. Moreover, when also applied to a real data set (classification of rice varieties), characterized by a high extent of non-linearity, the proposed method provided an average correct classification rate of about 93% on the test set. By the preliminary results, showed in this paper, the performances of the proposed LW-PLS-DA approach have proved to be comparable and in some cases better than those obtained by other non-linear methods (k nearest neighbors, kernel-PLS-DA and, in the case of rice, counterpropagation neural networks). Copyright © 2014 Elsevier B.V. All rights reserved.

Sex discrimination from the acetabulum in a twentieth-century skeletal sample from France using digital photogrammetry.

PubMed

Macaluso, P J

2011-02-01

Digital photogrammetric methods were used to collect diameter, area, and perimeter data of the acetabulum for a twentieth-century skeletal sample from France (Georges Olivier Collection, Musée de l'Homme, Paris) consisting of 46 males and 36 females. The measurements were then subjected to both discriminant function and logistic regression analyses in order to develop osteometric standards for sex assessment. Univariate discriminant functions and logistic regression equations yielded overall correct classification accuracy rates for both the left and the right acetabula ranging from 84.1% to 89.6%. The multivariate models developed in this study did not provide increased accuracy over those using only a single variable. Classification sex bias ratios ranged between 1.1% and 7.3% for the majority of models. The results of this study, therefore, demonstrate that metric analysis of acetabular size provides a highly accurate, and easily replicable, method of discriminating sex in this documented skeletal collection. The results further suggest that the addition of area and perimeter data derived from digital images may provide a more effective method of sex assessment than that offered by traditional linear measurements alone. Copyright © 2010 Elsevier GmbH. All rights reserved.

Botanical traceability of commercial tannins using the mineral profile and stable isotopes.

PubMed

Bertoldi, Daniela; Santato, Alessandro; Paolini, Mauro; Barbero, Alice; Camin, Federica; Nicolini, Giorgio; Larcher, Roberto

2014-09-01

Commercial tannins are natural polyphenolic compounds extracted from different plant tissues such as gall, the wood of different species and fruit. In the food industry they are mainly used as flavourings and food ingredients, whereas in winemaking they are classified as clarification agents for wine protein stabilisation, although colour stabilisation, metal removal, unpleasant thiol removal and rheological correction are also well-known and desired effects. Due to their particular technical properties and very different costs, the possibility of correct identification of the real botanical origin of tannins can be considered a primary target in oenology research and in fulfilling the technical and economic requirements of the wine industry. For some categories of tannins encouraging results have already been achieved by considering sugar or polyphenolic composition. For the first time this work verifies the possibility of determining the botanical origin of tannins on the basis of the mineral element profile and analysis of the (13) C/(12) C isotopic ratio. One hundred two commercial tannins originating from 10 different botanical sources (grapes, oak, gall, chestnut, fruit trees, quebracho, tea, acacia, officinal plants and tara) were analysed to determine 57 elements and the (13) C/(12) C isotopic ratio, using inductively coupled plasma mass spectrometry and isotope-ratio mass spectrometry, respectively. Forward stepwise discriminant analysis provided good discrimination between the 8 most abundant groups, with 100% correct re-classification. The model was then validated five times on subsets of 10% of the overall samples, randomly extracted, achieving satisfactory results. With a similar approach it was also possible to distinguish toasted and untoasted oak tannins as well as tannins from grape skin and grape seeds. Copyright © 2014 John Wiley & Sons, Ltd.

41 CFR 101-8.308 - Preemployment inquiries.

Code of Federal Regulations, 2013 CFR

2013-07-01

... FEDERAL FINANCIAL ASSISTANCE 8.3-Discrimination Prohibited on the Basis of Handicap § 101-8.308... whether the applicant is a handicapped person or as to the nature or severity of a handicap. A recipient... functions. (b) When a recipient is taking remedial action to correct the effects of past discrimination, or...

41 CFR 101-8.308 - Preemployment inquiries.

Code of Federal Regulations, 2012 CFR

2012-07-01

... FEDERAL FINANCIAL ASSISTANCE 8.3-Discrimination Prohibited on the Basis of Handicap § 101-8.308... whether the applicant is a handicapped person or as to the nature or severity of a handicap. A recipient... functions. (b) When a recipient is taking remedial action to correct the effects of past discrimination, or...

41 CFR 101-8.308 - Preemployment inquiries.

Code of Federal Regulations, 2011 CFR

2011-07-01

... FEDERAL FINANCIAL ASSISTANCE 8.3-Discrimination Prohibited on the Basis of Handicap § 101-8.308... whether the applicant is a handicapped person or as to the nature or severity of a handicap. A recipient... functions. (b) When a recipient is taking remedial action to correct the effects of past discrimination, or...

41 CFR 101-8.308 - Preemployment inquiries.

Code of Federal Regulations, 2014 CFR

2014-07-01

... FEDERAL FINANCIAL ASSISTANCE 8.3-Discrimination Prohibited on the Basis of Handicap § 101-8.308... whether the applicant is a handicapped person or as to the nature or severity of a handicap. A recipient... functions. (b) When a recipient is taking remedial action to correct the effects of past discrimination, or...

Provenance establishment of coffee using solution ICP-MS and ICP-AES.

PubMed

Valentin, Jenna L; Watling, R John

2013-11-01

Statistical interpretation of the concentrations of 59 elements, determined using solution based inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma emission spectroscopy (ICP-AES), was used to establish the provenance of coffee samples from 15 countries across five continents. Data confirmed that the harvest year, degree of ripeness and whether the coffees were green or roasted had little effect on the elemental composition of the coffees. The application of linear discriminant analysis and principal component analysis of the elemental concentrations permitted up to 96.9% correct classification of the coffee samples according to their continent of origin. When samples from each continent were considered separately, up to 100% correct classification of coffee samples into their countries, and plantations of origin was achieved. This research demonstrates the potential of using elemental composition, in combination with statistical classification methods, for accurate provenance establishment of coffee. Copyright © 2013 Elsevier Ltd. All rights reserved.

Memory as discrimination: what distraction reveals.

PubMed

Beaman, C Philip; Hanczakowski, Maciej; Hodgetts, Helen M; Marsh, John E; Jones, Dylan M

2013-11-01

Recalling information involves the process of discriminating between relevant and irrelevant information stored in memory. Not infrequently, the relevant information needs to be selected from among a series of related possibilities. This is likely to be particularly problematic when the irrelevant possibilities not only are temporally or contextually appropriate, but also overlap semantically with the target or targets. Here, we investigate the extent to which purely perceptual features that discriminate between irrelevant and target material can be used to overcome the negative impact of contextual and semantic relatedness. Adopting a distraction paradigm, it is demonstrated that when distractors are interleaved with targets presented either visually (Experiment 1) or auditorily (Experiment 2), a within-modality semantic distraction effect occurs; semantically related distractors impact upon recall more than do unrelated distractors. In the semantically related condition, the number of intrusions in recall is reduced, while the number of correctly recalled targets is simultaneously increased by the presence of perceptual cues to relevance (color features in Experiment 1 or speaker's gender in Experiment 2). However, as is demonstrated in Experiment 3, even presenting semantically related distractors in a language and a sensory modality (spoken Welsh) distinct from that of the targets (visual English) is insufficient to eliminate false recalls completely or to restore correct recall to levels seen with unrelated distractors . Together, the study shows how semantic and nonsemantic discriminability shape patterns of both erroneous and correct recall.

Classification of white wine aromas with an electronic nose.

PubMed

Lozano, J; Santos, J P; Horrillo, M C

2005-09-15

This paper reports the use of a tin dioxide multisensor array based electronic nose for recognition of 29 typical aromas in white wine. Headspace technique has been used to extract aroma of the wine. Multivariate analysis, including principal component analysis (PCA) as well as probabilistic neural networks (PNNs), has been used to identify the main aroma added to the wine. The results showed that in spite of the strong influence of ethanol and other majority compounds of wine, the system could discriminate correctly the aromatic compounds added to the wine with a minimum accuracy of 97.2%.

NCLEX-RN performance: predicting success on the computerized examination.

PubMed

Beeman, P B; Waterhouse, J K

2001-01-01

Since the adoption of the Computerized Adaptive Testing (CAT) format of the National Certification Licensure Examination for Registered Nurses (NCLEX-RN), no studies have been reported in the literature on predictors of successful performance by baccalaureate nursing graduates on the licensure examination. In this study, a discriminant analysis was used to identify which of 21 variables can be significant predictors of success on the CAT NCLEX-RN. The convenience sample consisted of 289 individuals who graduated from a baccalaureate nursing program between 1995 and 1998. Seven significant predictor variables were identified. The total number of C+ or lower grades earned in nursing theory courses was the best predictor, followed by grades in several individual nursing courses. More than 93 per cent of graduates were correctly classified. Ninety-four per cent of NCLEX "passes" were correctly classified, as were 92 per cent of NCLEX failures. This degree of accuracy in classifying CAT NCLEX-RN failures represents a marked improvement over results reported in previous studies of licensure examinations, and suggests the discriminant function will be helpful in identifying future students in danger of failure. J Prof Nurs 17:158-165, 2001. Copyright 2001 by W.B. Saunders Company

Application of wavelet multi-resolution analysis for correction of seismic acceleration records

NASA Astrophysics Data System (ADS)

Ansari, Anooshiravan; Noorzad, Assadollah; Zare, Mehdi

2007-12-01

During an earthquake, many stations record the ground motion, but only a few of them could be corrected using conventional high-pass and low-pass filtering methods and the others were identified as highly contaminated by noise and as a result useless. There are two major problems associated with these noisy records. First, since the signal to noise ratio (S/N) is low, it is not possible to discriminate between the original signal and noise either in the frequency domain or in the time domain. Consequently, it is not possible to cancel out noise using conventional filtering methods. The second problem is the non-stationary characteristics of the noise. In other words, in many cases the characteristics of the noise are varied over time and in these situations, it is not possible to apply frequency domain correction schemes. When correcting acceleration signals contaminated with high-level non-stationary noise, there is an important question whether it is possible to estimate the state of the noise in different bands of time and frequency. Wavelet multi-resolution analysis decomposes a signal into different time-frequency components, and besides introducing a suitable criterion for identification of the noise among each component, also provides the required mathematical tool for correction of highly noisy acceleration records. In this paper, the characteristics of the wavelet de-noising procedures are examined through the correction of selected real and synthetic acceleration time histories. It is concluded that this method provides a very flexible and efficient tool for the correction of very noisy and non-stationary records of ground acceleration. In addition, a two-step correction scheme is proposed for long period correction of the acceleration records. This method has the advantage of stable results in displacement time history and response spectrum.

Using Balance Tests to Discriminate Between Participants With a Recent Index Lateral Ankle Sprain and Healthy Control Participants: A Cross-Sectional Study

PubMed Central

Pourkazemi, Fereshteh; Hiller, Claire; Raymond, Jacqueline; Black, Deborah; Nightingale, Elizabeth; Refshauge, Kathryn

2016-01-01

Context:  The first step to identifying factors that increase the risk of recurrent ankle sprains is to identify impairments after a first sprain and compare performance with individuals who have never sustained a sprain. Few researchers have restricted recruitment to a homogeneous group of patients with first sprains, thereby introducing the potential for confounding. Objective:  To identify impairments that differ in participants with a recent index lateral ankle sprain versus participants with no history of ankle sprain. Design:  Cross-sectional study. Patients or Other Participants:  We recruited a sample of convenience from May 2010 to April 2013 that included 70 volunteers (age = 27.4 ± 8.3 years, height = 168.7 ± 9.5 cm, mass = 65.0 ± 12.5 kg) serving as controls and 30 volunteers (age = 31.1 ± 13.3 years, height = 168.3 ± 9.1 cm, mass = 67.3 ± 13.7 kg) with index ankle sprains. Main Outcome Measure(s):  We collected demographic and physical performance variables, including ankle-joint range of motion, balance (time to balance after perturbation, Star Excursion Balance Test, foot lifts during single-legged stance, demi-pointe balance test), proprioception, motor planning, inversion-eversion peak power, and timed stair tests. Discriminant analysis was conducted to determine the relationship between explanatory variables and sprain status. Sequential discriminant analysis was performed to identify the most relevant variables that explained the greatest variance. Results:  The average time since the sprain was 3.5 ± 1.5 months. The model, including all variables, correctly predicted a sprain status of 77% (n = 23) of the sprain group and 80% (n = 56) of the control group and explained 40% of the variance between groups ( = 42.16, P = .03). Backward stepwise discriminant analysis revealed associations between sprain status and only 2 tests: Star Excursion Balance Test in the anterior direction and foot lifts during single-legged stance ( = 15.2, P = .001). These 2 tests explained 15% of the between-groups variance and correctly predicted group membership of 63% (n = 19) of the sprain group and 69% (n = 48) of the control group. Conclusions:  Balance impairments were associated with a recent first ankle sprain, but proprioception, motor control, power, and function were not. PMID:26967374

Using Balance Tests to Discriminate Between Participants With a Recent Index Lateral Ankle Sprain and Healthy Control Participants: A Cross-Sectional Study.

PubMed

Pourkazemi, Fereshteh; Hiller, Claire; Raymond, Jacqueline; Black, Deborah; Nightingale, Elizabeth; Refshauge, Kathryn

2016-03-01

The first step to identifying factors that increase the risk of recurrent ankle sprains is to identify impairments after a first sprain and compare performance with individuals who have never sustained a sprain. Few researchers have restricted recruitment to a homogeneous group of patients with first sprains, thereby introducing the potential for confounding. To identify impairments that differ in participants with a recent index lateral ankle sprain versus participants with no history of ankle sprain. Cross-sectional study. We recruited a sample of convenience from May 2010 to April 2013 that included 70 volunteers (age = 27.4 ± 8.3 years, height = 168.7 ± 9.5 cm, mass = 65.0 ± 12.5 kg) serving as controls and 30 volunteers (age = 31.1 ± 13.3 years, height = 168.3 ± 9.1 cm, mass = 67.3 ± 13.7 kg) with index ankle sprains. We collected demographic and physical performance variables, including ankle-joint range of motion, balance (time to balance after perturbation, Star Excursion Balance Test, foot lifts during single-legged stance, demi-pointe balance test), proprioception, motor planning, inversion-eversion peak power, and timed stair tests. Discriminant analysis was conducted to determine the relationship between explanatory variables and sprain status. Sequential discriminant analysis was performed to identify the most relevant variables that explained the greatest variance. The average time since the sprain was 3.5 ± 1.5 months. The model, including all variables, correctly predicted a sprain status of 77% (n = 23) of the sprain group and 80% (n = 56) of the control group and explained 40% of the variance between groups ([Formula: see text] = 42.16, P = .03). Backward stepwise discriminant analysis revealed associations between sprain status and only 2 tests: Star Excursion Balance Test in the anterior direction and foot lifts during single-legged stance ([Formula: see text] = 15.2, P = .001). These 2 tests explained 15% of the between-groups variance and correctly predicted group membership of 63% (n = 19) of the sprain group and 69% (n = 48) of the control group. Balance impairments were associated with a recent first ankle sprain, but proprioception, motor control, power, and function were not.

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis

PubMed Central

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Background: Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. Methods: In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. Results: The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Conclusion: Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended. PMID:26793655

Prediction of unwanted pregnancies using logistic regression, probit regression and discriminant analysis.

PubMed

Ebrahimzadeh, Farzad; Hajizadeh, Ebrahim; Vahabi, Nasim; Almasian, Mohammad; Bakhteyar, Katayoon

2015-01-01

Unwanted pregnancy not intended by at least one of the parents has undesirable consequences for the family and the society. In the present study, three classification models were used and compared to predict unwanted pregnancies in an urban population. In this cross-sectional study, 887 pregnant mothers referring to health centers in Khorramabad, Iran, in 2012 were selected by the stratified and cluster sampling; relevant variables were measured and for prediction of unwanted pregnancy, logistic regression, discriminant analysis, and probit regression models and SPSS software version 21 were used. To compare these models, indicators such as sensitivity, specificity, the area under the ROC curve, and the percentage of correct predictions were used. The prevalence of unwanted pregnancies was 25.3%. The logistic and probit regression models indicated that parity and pregnancy spacing, contraceptive methods, household income and number of living male children were related to unwanted pregnancy. The performance of the models based on the area under the ROC curve was 0.735, 0.733, and 0.680 for logistic regression, probit regression, and linear discriminant analysis, respectively. Given the relatively high prevalence of unwanted pregnancies in Khorramabad, it seems necessary to revise family planning programs. Despite the similar accuracy of the models, if the researcher is interested in the interpretability of the results, the use of the logistic regression model is recommended.

Wage differences according to health status in France.

PubMed

Ben Halima, Mohamed Ali; Rococo, Emeline

2014-11-01

Many OECD countries have implemented anti-discrimination laws in recent decades. However, according to the annual report published in 2010 by the French High Authority for the Fight against Discrimination and for Equality, the second most commonly cited factor in discrimination claims since 2005 is a handicap or health status. The aim of this research is to estimate the level of unexplained components in the wage gap that can be attributed to wage discrimination based on health status in France in 2010 utilizing data from the Health, Healthcare and Insurance survey among 1594 individuals. Three health indicators are used: self-perceived health status, activity limitations and long-term chronic illness. To measure the wage gap according to an individual's health status, the analysis considers the endogenous selection of health status and unobserved differences in productivity. The results demonstrate that wage discrimination is experienced by individuals in poor health regardless of the health indicator utilized. The hourly wage rate among individuals with poor self-assessed health status is on average 14.2% lower than among individuals with good self-assessed health status. However, for individuals suffering from a long-term chronic illness or an activity limitation, the gap is 6.3% and 4.5%, respectively. The decomposition performed on wage differences according to health status by correcting for health status selection bias and controlling for unobserved differences in productivity indicates that the 'unexplained component' that can be attributed to wage discrimination is equal to 50%. Copyright © 2014 Elsevier Ltd. All rights reserved.

Near Infrared Spectroscopy Facilitates Rapid Identification of Both Young and Mature Amazonian Tree Species.

PubMed

Lang, Carla; Costa, Flávia Regina Capellotto; Camargo, José Luís Campana; Durgante, Flávia Machado; Vicentini, Alberto

2015-01-01

Precise identification of plant species requires a high level of knowledge by taxonomists and presence of reproductive material. This represents a major limitation for those working with seedlings and juveniles, which differ morphologically from adults and do not bear reproductive structures. Near-infrared spectroscopy (FT-NIR) has previously been shown to be effective in species discrimination of adult plants, so if young and adults have a similar spectral signature, discriminant functions based on FT-NIR spectra of adults can be used to identify leaves from young plants. We tested this with a sample of 419 plants in 13 Amazonian species from the genera Protium and Crepidospermum (Burseraceae). We obtained 12 spectral readings per plant, from adaxial and abaxial surfaces of dried leaves, and compared the rate of correct predictions of species with discriminant functions for different combinations of readings. We showed that the best models for predicting species in early developmental stages are those containing spectral data from both young and adult plants (98% correct predictions of external samples), but even using only adult spectra it is still possible to attain good levels of identification of young. We obtained an average of 75% correct identifications of young plants by discriminant equations based only on adults, when the most informative wavelengths were selected. Most species were accurately predicted (75-100% correct identifications), and only three had poor predictions (27-60%). These results were obtained despite the fact that spectra of young individuals were distinct from those of adults when species were analyzed individually. We concluded that FT-NIR has a high potential in the identification of species even at different ontogenetic stages, and that young plants can be identified based on spectra of adults with reasonable confidence.

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: A comparative study between different modeling methods

NASA Astrophysics Data System (ADS)

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm-1. Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity.

Controlling protected designation of origin of wine by Raman spectroscopy.

PubMed

Mandrile, Luisa; Zeppa, Giuseppe; Giovannozzi, Andrea Mario; Rossi, Andrea Mario

2016-11-15

In this paper, a Fourier Transform Raman spectroscopy method, to authenticate the provenience of wine, for food traceability applications was developed. In particular, due to the specific chemical fingerprint of the Raman spectrum, it was possible to discriminate different wines produced in the Piedmont area (North West Italy) in accordance with i) grape varieties, ii) production area and iii) ageing time. In order to create a consistent training set, more than 300 samples from tens of different producers were analyzed, and a chemometric treatment of raw spectra was applied. A discriminant analysis method was employed in the classification procedures, providing a classification capability (percentage of correct answers) of 90% for validation of grape analysis and geographical area provenance, and a classification capability of 84% for ageing time classification. The present methodology was applied successfully to raw materials without any preliminary treatment of the sample, providing a response in a very short time. Copyright © 2016 Elsevier Ltd. All rights reserved.

Rejection of randomly coinciding 2ν2β events in ZnMoO4 scintillating bolometers

NASA Astrophysics Data System (ADS)

Chernyak, D. M.; Danevich, F. A.; Giuliani, A.; Mancuso, M.; Nones, C.; Olivieri, E.; Tenconi, M.; Tretyak, V. I.

2014-01-01

Random coincidence of 2ν2β decay events could be one of the main sources of background for 0ν2β decay in cryogenic bolometers due to their poor time resolution. Pulse-shape discrimination by using front edge analysis, the mean-time and χ2 methods was applied to discriminate randomly coinciding 2ν2β events in ZnMoO4 cryogenic scintillating bolometers. The background can be effectively rejected on the level of 99% by the mean-time analysis of heat signals with the rise time about 14 ms and the signal-to-noise ratio 900, and on the level of 98% for the light signals with 3 ms rise time and signal-to-noise ratio of 30 (under a requirement to detect 95% of single events). Importance of the signal-to-noise ratio, correct finding of the signal start and choice of an appropriate sampling frequency are discussed.

Performance of brain-damaged and non-brain-damaged institutionalized children on the Minnesota Percepto-Diagnostic Test.

PubMed

Holland, J M; Fuller, G B; Barth, C E

1982-01-01

Examined the performance of 64 children on the Minnesota Percepto-Diagnostic test (MPD) who were diagnosed as either Brain-Damaged (BD) or emotionally impaired Non-Brain-Damaged (NBD). There were 31 children in the NBD group and 33 in the BD group. The MPD T-score and Actuarial Table significantly differentiated between the two groups. Seventy-four percent of the combined BD-NBD groups were identified correctly. Additional discriminant analysis on this sample yielded combined BD-NBD groups classification rates that ranged from 77% with the MPD variables Separation of Circle-Diamond (SPCD), Distortion of Circle-Diamond (DCD) and Distortion of Dots (DD) to 83% with the WISC-R three IQ scores plus the MPD T-score, SPCD and DD. The MPD T-score and Actuarial Table (MPD Two-Step Diagnosis) appeared to generalize to other populations more readily than discriminant analysis formulae, which tend to be sensitive to the samples from which they are derived.

An item response theory analysis of the Psychological Inventory of Criminal Thinking Styles: comparing male and female probationers and prisoners.

PubMed

Walters, Glenn D

2014-09-01

An item response theory (IRT) analysis of the Psychological Inventory of Criminal Thinking Styles (PICTS) was performed on 26,831 (19,067 male and 7,764 female) federal probationers and compared with results obtained on 3,266 (3,039 male and 227 female) prisoners from previous research. Despite the fact male and female federal probationers scored significantly lower on the PICTS thinking style scales than male and female prisoners, discrimination and location parameter estimates for the individual PICTS items were comparable across sex and setting. Consistent with the results of a previous IRT analysis conducted on the PICTS, the current results did not support sentimentality as a component of general criminal thinking. Findings from this study indicate that the discriminative power of the individual PICTS items is relatively stable across sex (male, female) and correctional setting (probation, prison) and that the PICTS may be measuring the same criminal thinking construct in male and female probationers and prisoners. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Characterization of oils and fats by 1H NMR and GC/MS fingerprinting: classification, prediction and detection of adulteration.

PubMed

Fang, Guihua; Goh, Jing Yeen; Tay, Manjun; Lau, Hiu Fung; Li, Sam Fong Yau

2013-06-01

The correct identification of oils and fats is important to consumers from both commercial and health perspectives. Proton nuclear magnetic resonance ((1)H NMR) spectroscopy, gas chromatography-mass spectrometry (GC/MS) fingerprinting and chemometrics were employed successfully for the quality control of oils and fats. Principal component analysis (PCA) of both techniques showed group clustering of 14 types of oils and fats. Partial least squares discriminant analysis (PLS-DA) and orthogonal projections to latent structures discriminant analysis (OPLS-DA) using GC/MS data had excellent classification sensitivity and specificity compared to models using NMR data. Depending on the availability of the instruments, data from either technique can effectively be applied for the establishment of an oils and fats database to identify unknown samples. Partial least squares (PLS) models were successfully established for the detection of as low as 5% of lard and beef tallow spiked into canola oil, thus illustrating possible applications in Islamic and Jewish countries. Copyright © 2012 Elsevier Ltd. All rights reserved.

Determination of sex from the hyoid bone in a contemporary White population.

PubMed

Logar, Ciara J; Peckmann, Tanya R; Meek, Susan; Walls, Stephen G

2016-04-01

Six discriminant functions, developed from an historic White population, were tested on a contemporary White population for determination of sex from the hyoid. One hundred and thirty four fused and unfused hyoids from a contemporary White population were used. Individuals ranged between 20 and 49 years old. Six historic White discriminant functions were applied to the fused and unfused hyoids of the pooled contemporary White population, i.e. all males and females and all age ranges combined. The overall accuracy rates were between 72.1% and 92.3%. Correct sex determination for contemporary White males ranged between 88.2% and 96.3%, while correct sex determination for contemporary White females ranged between 31.3% and 92.0%. Discriminant functions were created for the contemporary White population with overall mean accuracy rates between 67.0% and 93.0%. The multivariate discriminant function overall accuracy rates were between 89.0% and 93.0% and the univariate discriminant function overall accuracy rates were between 67.0% and 86.8%. The contemporary White population data were compared to other populations and showed significant differences between many of the variables measured. This study illustrated the need for population-specific and temporally-specific discriminant functions for determination of sex from the hyoid bone. Copyright © 2016 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Movement Correction Method for Human Brain PET Images: Application to Quantitative Analysis of Dynamic [18F]-FDDNP Scans

PubMed Central

Wardak, Mirwais; Wong, Koon-Pong; Shao, Weber; Dahlbom, Magnus; Kepe, Vladimir; Satyamurthy, Nagichettiar; Small, Gary W.; Barrio, Jorge R.; Huang, Sung-Cheng

2010-01-01

Head movement during a PET scan (especially, dynamic scan) can affect both the qualitative and quantitative aspects of an image, making it difficult to accurately interpret the results. The primary objective of this study was to develop a retrospective image-based movement correction (MC) method and evaluate its implementation on dynamic [18F]-FDDNP PET images of cognitively intact controls and patients with Alzheimer’s disease (AD). Methods Dynamic [18F]-FDDNP PET images, used for in vivo imaging of beta-amyloid plaques and neurofibrillary tangles, were obtained from 12 AD and 9 age-matched controls. For each study, a transmission scan was first acquired for attenuation correction. An accurate retrospective MC method that corrected for transmission-emission misalignment as well as emission-emission misalignment was applied to all studies. No restriction was assumed for zero movement between the transmission scan and first emission scan. Logan analysis with cerebellum as the reference region was used to estimate various regional distribution volume ratio (DVR) values in the brain before and after MC. Discriminant analysis was used to build a predictive model for group membership, using data with and without MC. Results MC improved the image quality and quantitative values in [18F]-FDDNP PET images. In this subject population, medial temporal (MTL) did not show a significant difference between controls and AD before MC. However, after MC, significant differences in DVR values were seen in frontal, parietal, posterior cingulate (PCG), MTL, lateral temporal (LTL), and global between the two groups (P < 0.05). In controls and AD, the variability of regional DVR values (as measured by the coefficient of variation) decreased on average by >18% after MC. Mean DVR separation between controls and ADs was higher in frontal, MTL, LTL and global after MC. Group classification by discriminant analysis based on [18F]-FDDNP DVR values was markedly improved after MC. Conclusion The streamlined and easy to use MC method presented in this work significantly improves the image quality and the measured tracer kinetics of [18F]-FDDNP PET images. The proposed MC method has the potential to be applied to PET studies on patients having other disorders (e.g., Down syndrome and Parkinson’s disease) and to brain PET scans with other molecular imaging probes. PMID:20080894

Spatial and temporal air quality pattern recognition using environmetric techniques: a case study in Malaysia.

PubMed

Syed Abdul Mutalib, Sharifah Norsukhairin; Juahir, Hafizan; Azid, Azman; Mohd Sharif, Sharifah; Latif, Mohd Talib; Aris, Ahmad Zaharin; Zain, Sharifuddin M; Dominick, Doreena

2013-09-01

The objective of this study is to identify spatial and temporal patterns in the air quality at three selected Malaysian air monitoring stations based on an eleven-year database (January 2000-December 2010). Four statistical methods, Discriminant Analysis (DA), Hierarchical Agglomerative Cluster Analysis (HACA), Principal Component Analysis (PCA) and Artificial Neural Networks (ANNs), were selected to analyze the datasets of five air quality parameters, namely: SO2, NO2, O3, CO and particulate matter with a diameter size of below 10 μm (PM10). The three selected air monitoring stations share the characteristic of being located in highly urbanized areas and are surrounded by a number of industries. The DA results show that spatial characterizations allow successful discrimination between the three stations, while HACA shows the temporal pattern from the monthly and yearly factor analysis which correlates with severe haze episodes that have happened in this country at certain periods of time. The PCA results show that the major source of air pollution is mostly due to the combustion of fossil fuel in motor vehicles and industrial activities. The spatial pattern recognition (S-ANN) results show a better prediction performance in discriminating between the regions, with an excellent percentage of correct classification compared to DA. This study presents the necessity and usefulness of environmetric techniques for the interpretation of large datasets aiming to obtain better information about air quality patterns based on spatial and temporal characterizations at the selected air monitoring stations.

Neuropsychological performance of sexual assaulters and pedophiles.

PubMed

Scott, M L; Cole, J K; McKay, S E; Golden, C J; Liggett, K R

1984-10-01

Persons who had been arrested for sexual assault were administered the Luria-Nebraska Neuropsychological Battery and the results compared to a group of normal controls. The sexual assaulters performed significantly worse on 7 of the 14 scales of the battery. The data were then broken down into three groups: (1) those who had forcibly assaulted postpubescent victims, (2) those subjects who had sexually molested a prepubescent child, and (3) normal controls. A discriminant analysis correctly classified 68% of the subjects on the basis of their neuropsychological performance alone.

Morphometric classification of Spanish thoroughbred stallion sperm heads.

PubMed

Hidalgo, Manuel; Rodríguez, Inmaculada; Dorado, Jesús; Soler, Carles

2008-01-30

This work used semen samples collected from 12 stallions and assessed for sperm morphometry by the Sperm Class Analyzer (SCA) computer-assisted system. A discriminant analysis was performed on the morphometric data from that sperm to obtain a classification matrix for sperm head shape. Thereafter, we defined six types of sperm head shape. Classification of sperm head by this method obtained a globally correct assignment of 90.1%. Moreover, significant differences (p<0.05) were found between animals for all the sperm head morphometric parameters assessed.

Sex determination using discriminant function analysis in Indigenous (Kurubas) children and adolescents of Coorg, Karnataka, India: A lateral cephalometric study.

PubMed

Devang Divakar, Darshan; John, Jacob; Al Kheraif, Abdulaziz Abdullah; Mavinapalla, Seema; Ramakrishnaiah, Ravikumar; Vellappally, Sajith; Hashem, Mohamed Ibrahim; Dalati, M H N; Durgesh, B H; Safadi, Rima A; Anil, Sukumaran

2016-11-01

Aim: To test the validity of sex discrimination using lateral cephalometric radiograph and discriminant function analysis in Indigenous (Kuruba) children and adolescents of Coorg, Karnataka, India. Methods and materials: Six hundred and sixteen lateral cephalograms of 380 male and 236 females of age ranging from 6.5 to 18 years of Indigenous population of Coorg, Karnataka, India called Kurubas having a normal occlusion were included in the study. Lateral cephalograms were obtained in a standard position with teeth in centric occlusion and lips relaxed. Each radiograph was traced and cephalometric landmarks were measured using digital calliper. Calculations of 24 cephalometric measurements were performed. Results: Males exhibited significantly greater mean angular and linear cephalometric measurements as compared to females ( p  < 0.05) (Table 5). Also, significant differences ( p  < 0.05) were observed in all the variables according to age (Table 6). Out of 24 variables, only ULTc predicts the gender. The reliability of the derived discriminant function was assessed among study subjects; 100% of males and females were recognized correctly. Conclusion: The final outcome of this study validates the existence of sexual dimorphism in the skeleton as early as 6.5 years of age. There is a need for further research to determine other landmarks that can help in sex determination and norms for Indigenous (Kuruba) population and also other Indigenous population of Coorg, Karnataka, India.

Measurements of the talus in the assessment of population affinity.

PubMed

Bidmos, Mubarak A; Dayal, Manisha R; Adegboye, Oyelola A

2018-06-01

As part of their routine work, forensic anthropologists are expected to report population affinity as part of the biological profile of an individual. The skull is the most widely used bone for the estimation of population affinity but it is not always present in a forensic case. Thus, other bones that preserve well have been shown to give a good indication of either the sex or population affinity of an individual. In this study, the potential of measurements of the talus was investigated for the purpose of estimating population affinity in South Africans. Nine measurements from two hundred and twenty tali of South African Africans (SAA) and South African Whites (SAW) from the Raymond A. Dart Collection of Human Skeletons were used. Direct and step-wise discriminant function and logistic regression analyses were carried out using SPSS and SAS. Talar length was the best single variable for discriminating between these two groups for males while in females the head height was the best single predictor. Average accuracies for correct population affinity classification using logistic regression analysis were higher than those obtained from discriminant function analysis. This study was the first of its type to employ discriminant function analyses and logistic regression analyses to estimate the population affinity of an individual from the talus. Thus these equations can now be used by South African anthropologists when estimating the population affinity of dismembered or damaged or incomplete skeletal remains of SAA and SAW. Copyright © 2018 Elsevier B.V. All rights reserved.

Incarceration as a Mechanism of Social Discrimination.

ERIC Educational Resources Information Center

French, Laurence A.

This paper addresses itself to the use of judicial discrimination as a vehicle of imposing and maintaining superordinate controls on society, especially in the white, male-dominated South. The study, using the North Carolina correctional system as an indicator of fair and equal justice, as manifested by our judicial ideals, shows that this is not…

Sex and race determination of crania by calipers and computer : a test of the Giles and Elliot discriminant functions in 52 forensic cases.

DOT National Transportation Integrated Search

1979-01-01

The Giles and Elliot discriminant functions diagnosing sex and race from cranial measurements were tested on a series of forensically examined crania of known sex and race. Of 52 crania of known sex, 46 (88%) were correctly diagnosed. Racial diagnose...

Immunological discrimination of Atlantic striped bass stocks

USGS Publications Warehouse

Schill, W.B.; Dorazio, R.M.

1990-01-01

Stocks of Atlantic striped bass Morone saxatilis that were assumed to be geographically isolated during spawning showed strong antigenic differences in blood serum albumin. A discriminant function was estimated from the immunologic responses of northern (Canadian and Hudson River) and southern (Chesapeake Bay and Roanoke River) stocks to two reference antisera. The function correctly classified 92% of the northern and 95% of the southern fish in the training set. Cross-validation revealed similar percentages of correct classification for fish that were of known origin but not used to estimate the discriminant function. Monte Carlo experiments were used to evaluate the ability of the discriminant function to predict the relative contribution of northern fish in samples of various size and stock composition. Averages of predicted proportions of northern fish in the samples agreed well with actual proportions. Coefficients of variation (100 × SD/mean) in the predicted proportions ranged from 1.5 to 36% for samples of 50–400 fish that contained at least 10% northern stock. In samples that contained only 2% northern stock, however, at least 1,600 fish were required to achieve similar levels of precision.

Boronlectin/Polyelectrolyte Ensembles as Artificial Tongue: Design, Construction, and Application for Discriminative Sensing of Complex Glycoconjugates from Panax ginseng.

PubMed

Zhang, Xiao-Tai; Wang, Shu; Xing, Guo-Wen

2017-02-01

Ginsenoside is a large family of triterpenoid saponins from Panax ginseng, which possesses various important biological functions. Due to the very similar structures of these complex glycoconjugates, it is crucial to develop a powerful analytic method to identify ginsenosides qualitatively or quantitatively. We herein report an eight-channel fluorescent sensor array as artificial tongue to achieve the discriminative sensing of ginsenosides. The fluorescent cross-responsive array was constructed by four boronlectins bearing flexible boronic acid moieties (FBAs) with multiple reactive sites and two linear poly(phenylene-ethynylene) (PPEs). An "on-off-on" response pattern was afforded on the basis of superquenching of fluorescent indicator PPEs and an analyte-induced allosteric indicator displacement (AID) process. Most importantly, it was found that the canonical distribution of ginsenoside data points analyzed by linear discriminant analysis (LDA) was highly correlated with the inherent molecular structures of the analytes, and the absence of overlaps among the five point groups reflected the effectiveness of the sensor array in the discrimination process. Almost all of the unknown ginsenoside samples at different concentrations were correctly identified on the basis of the established mathematical model. Our current work provided a general and constructive method to improve the quality assessment and control of ginseng and its extracts, which are useful and helpful for further discriminating other complex glycoconjugate families.

Sensitivity and Specificity of Eustachian Tube Function Tests in Adults

PubMed Central

Doyle, William J.; Swarts, J. Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M.

2013-01-01

Objective Determine if Eustachian Tube (ET) function (ETF) tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and define the inter-relatedness of ETF test parameters. Methods ETF was evaluated using the Forced-Response, Inflation-Deflation, Valsalva and Sniffing tests in 15 control ears of adult subjects after unilateral myringotomy (Group I) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (Group II). Data were analyzed using logistic regression including each parameter independently and then a step-down Discriminant Analysis including all ETF test parameters to predict group assignment. Factor Analysis operating over all parameters was used to explore relatedness. Results The Discriminant Analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency and % positive pressure equilibrated) that together correctly assigned ears to Group II at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters, the first had negative loadings of the ETF structural parameters, the second had positive loadings of the muscle-assisted ET opening parameters and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. Discussion These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories. PMID:23868429

Nomogram Prediction of Overall Survival After Curative Irradiation for Uterine Cervical Cancer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seo, YoungSeok; Yoo, Seong Yul; Kim, Mi-Sook

Purpose: The purpose of this study was to develop a nomogram capable of predicting the probability of 5-year survival after radical radiotherapy (RT) without chemotherapy for uterine cervical cancer. Methods and Materials: We retrospectively analyzed 549 patients that underwent radical RT for uterine cervical cancer between March 1994 and April 2002 at our institution. Multivariate analysis using Cox proportional hazards regression was performed and this Cox model was used as the basis for the devised nomogram. The model was internally validated for discrimination and calibration by bootstrap resampling. Results: By multivariate regression analysis, the model showed that age, hemoglobin levelmore » before RT, Federation Internationale de Gynecologie Obstetrique (FIGO) stage, maximal tumor diameter, lymph node status, and RT dose at Point A significantly predicted overall survival. The survival prediction model demonstrated good calibration and discrimination. The bootstrap-corrected concordance index was 0.67. The predictive ability of the nomogram proved to be superior to FIGO stage (p = 0.01). Conclusions: The devised nomogram offers a significantly better level of discrimination than the FIGO staging system. In particular, it improves predictions of survival probability and could be useful for counseling patients, choosing treatment modalities and schedules, and designing clinical trials. However, before this nomogram is used clinically, it should be externally validated.« less

Sex determination from the talus in a contemporary Greek population using discriminant function analysis.

PubMed

Peckmann, Tanya R; Orr, Kayla; Meek, Susan; Manolis, Sotiris K

2015-07-01

The determination of sex is an important part of building the biological profile for unknown human remains. Many of the bones traditionally used for the determination of sex are often found fragmented or incomplete in forensic and archaeological cases. The goal of the present research was to derive discriminant function equations from the talus, a preservationally favoured bone, for sexing skeletons from a contemporary Greek population. Nine parameters were measured on 182 individuals (96 males and 86 females) from the University of Athens Human Skeletal Reference Collection. The individuals ranged in age from 20 to 99 years old. The statistical analyses showed that all measured parameters were sexually dimorphic. Discriminant function score equations were generated for use in sex determination. The average accuracy of sex classification ranged from 65.2% to 93.4% for the univariate analysis, 90%-96.5% for the direct method and 86.7% for the stepwise method. Comparisons to other populations were made. Overall, the cross-validated accuracies ranged from 65.5% to 83.2% and males were most often correctly identified. The talus was shown to be useful for sex determination in the modern Greek population. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Acoustic discrimination of Southern Ocean zooplankton

NASA Astrophysics Data System (ADS)

Brierley, Andrew S.; Ward, Peter; Watkins, Jonathan L.; Goss, Catherine

Acoustic surveys in the vicinity of the sub-Antarctic island of South Georgia during a period of exceptionally calm weather revealed the existence of a number of horizontally extensive yet vertically discrete scattering layers in the upper 250 m of the water column. These layers were fished with a Longhurst-Hardy plankton recorder (LHPR) and a multiple-opening 8 m 2 rectangular mid-water trawl (RMT8). Analysis of catches suggested that each scattering layer was composed predominantly of a single species (biovolume>95%) of either the euphausiids Euphausia frigida or Thysanöessa macrura, the hyperiid amphipod Themisto gaudichaudii, or the eucalaniid copepod Rhincalanus gigas. Instrumentation on the nets allowed their trajectories to be reconstructed precisely, and thus catch data to be related directly to the corresponding acoustic signals. Discriminant function analysis of differences between mean volume backscattering strength at 38, 120 and 200 kHz separated echoes originating from each of the dominant scattering layers, and other signals identified as originating from Antarctic krill ( Euphausia superba), with an overall correct classification rate of 77%. Using echo intensity data alone, gathered using hardware commonly employed for fishery acoustics, it is therefore possible to discriminate in situ between several zooplanktonic taxa, taxa which in some instances exhibit similar gross morphological characteristics and have overlapping length- frequency distributions. Acoustic signals from the mysid Antarctomysis maxima could also be discriminated once information on target distribution was considered, highlighting the value of incorporating multiple descriptors of echo characteristics into signal identification procedures. The ability to discriminate acoustically between zooplankton taxa could be applied to provide improved acoustic estimates of species abundance, and to enhance field studies of zooplankton ecology, distribution and species interactions.

Elemental analysis of cotton by laser-induced breakdown spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schenk, Emily R.; Almirall, Jose R.

Laser-induced breakdown spectroscopy (LIBS) has been applied to the elemental characterization of unprocessed cotton. This research is important in forensic and fraud detection applications to establish an elemental fingerprint of U.S. cotton by region, which can be used to determine the source of the cotton. To the best of our knowledge, this is the first report of a LIBS method for the elemental analysis of cotton. The experimental setup consists of a Nd:YAG laser that operates at the fundamental wavelength as the LIBS excitation source and an echelle spectrometer equipped with an intensified CCD camera. The relative concentrations of elementsmore » Al, Ba, Ca, Cr, Cu, Fe, Mg, and Sr from both nutrients and environmental contributions were determined by LIBS. Principal component analysis was used to visualize the differences between cotton samples based on the elemental composition by region in the U.S. Linear discriminant analysis of the LIBS data resulted in the correct classification of >97% of the cotton samples by U.S. region and >81% correct classification by state of origin.« less

[Applications of three-dimensional fluorescence spectrum of dissolved organic matter to identification of red tide algae].

PubMed

Lü, Gui-Cai; Zhao, Wei-Hong; Wang, Jiang-Tao

2011-01-01

The identification techniques for 10 species of red tide algae often found in the coastal areas of China were developed by combining the three-dimensional fluorescence spectra of fluorescence dissolved organic matter (FDOM) from the cultured red tide algae with principal component analysis. Based on the results of principal component analysis, the first principal component loading spectrum of three-dimensional fluorescence spectrum was chosen as the identification characteristic spectrum for red tide algae, and the phytoplankton fluorescence characteristic spectrum band was established. Then the 10 algae species were tested using Bayesian discriminant analysis with a correct identification rate of more than 92% for Pyrrophyta on the level of species, and that of more than 75% for Bacillariophyta on the level of genus in which the correct identification rates were more than 90% for the phaeodactylum and chaetoceros. The results showed that the identification techniques for 10 species of red tide algae based on the three-dimensional fluorescence spectra of FDOM from the cultured red tide algae and principal component analysis could work well.

Development of a Meiosis Concept Inventory

PubMed Central

Kalas, Pamela; O’Neill, Angie; Pollock, Carol; Birol, Gülnur

2013-01-01

We have designed, developed, and validated a 17-question Meiosis Concept Inventory (Meiosis CI) to diagnose student misconceptions on meiosis, which is a fundamental concept in genetics. We targeted large introductory biology and genetics courses and used published methodology for question development, which included the validation of questions by student interviews (n = 28), in-class testing of the questions by students (n = 193), and expert (n = 8) consensus on the correct answers. Our item analysis showed that the questions’ difficulty and discrimination indices were in agreement with published recommended standards and discriminated effectively between high- and low-scoring students. We foresee other institutions using the Meiosis CI as both a diagnostic tool and an instrument to assess teaching effectiveness and student progress, and invite instructors to visit http://q4b.biology.ubc.ca for more information. PMID:24297292

Factors associated with cane use among community dwelling older adults.

PubMed

Aminzadeh, F; Edwards, N

2000-01-01

Guided by the Theory of Planned Behavior (TPB), this study examined factors associated with cane use among community dwelling older adults. Data were collected in a cross-sectional survey of a convenience sample of 106 community residing older adults in Ottawa, Canada. Using a stepwise discriminant analysis, subjective norms, attitudes, and age surfaced as the key variables associated with cane use in this sample. The discriminant function accounted for 67% of the variance in cane use and correctly classified 91% of cases (Wilks's lambda = 0.33, lambda2 = 110.12, df = 3, p < 0.0001). The findings provide evidence for the utility of the TPB in its application to understanding cane use behaviors of older persons and have important implications for the design of theory-based fall prevention interventions to enhance the acceptance and effective use of mobility aids.

Race, biology, and health care: reassessing a relationship.

PubMed

Byrd, W M

1990-01-01

Recent reports reaffirm huge disparities in the health of blacks compared to other Americans. These disparities persist in part because of the current attempt by health policy makers to frame racially based health differences in non-racial terms. Yet an historical analysis shows that since ancient times, blacks have been the victims of racism in the biomedical sciences; health-system discrimination and deprivation; and later, medical and scientific exploitation. Race- and class-based structuring of the health delivery system has combined with other factors, including physicians' attitudes conditioned by their participation in slavery, and the scientific myth of black biological and intellectual inferiority, to establish a "slave health deficit" that has never been corrected. Until the persistent institutional racism and racial discrimination in health policy, health delivery, and medical educational systems are eradicated, African-Americans will continue to experience poor health outcome.

Using sperm morphometry and multivariate analysis to differentiate species of gray Mazama

PubMed Central

Duarte, José Maurício Barbanti

2016-01-01

There is genetic evidence that the two species of Brazilian gray Mazama, Mazama gouazoubira and Mazama nemorivaga, belong to different genera. This study identified significant differences that separated them into distinct groups, based on characteristics of the spermatozoa and ejaculate of both species. The characteristics that most clearly differentiated between the species were ejaculate colour, white for M. gouazoubira and reddish for M. nemorivaga, and sperm head dimensions. Multivariate analysis of sperm head dimension and format data accurately discriminated three groups for species with total percentage of misclassified of 0.71. The individual analysis, by animal, and the multivariate analysis have also discriminated correctly all five animals (total percentage of misclassified of 13.95%), and the canonical plot has shown three different clusters: Cluster 1, including individuals of M. nemorivaga; Cluster 2, including two individuals of M. gouazoubira; and Cluster 3, including a single individual of M. gouazoubira. The results obtained in this work corroborate the hypothesis of the formation of new genera and species for gray Mazama. Moreover, the easily applied method described herein can be used as an auxiliary tool to identify sibling species of other taxonomic groups. PMID:28018612

Understanding Laterally Varying Path Effects on P/S Ratios and their Effectiveness for Event Discrimination at Local Distances

NASA Astrophysics Data System (ADS)

Pyle, M. L.; Walter, W. R.

2017-12-01

Discrimination between underground explosions and naturally occurring earthquakes is an important endeavor for global security and test-ban treaty monitoring, and ratios of seismic P to S-wave amplitudes at regional distances have proven to be an effective discriminant. The use of the P/S ratio is rooted in the idea that explosive sources should theoretically only generate compressional energy. While, in practice, shear energy is observed from explosions, generally when corrections are made for magnitude and distance, P/S ratios from explosions are higher than those from surrounding earthquakes. At local distances (< 200 km) that might be needed to detect smaller events, however, this discriminant becomes less reliable. While ratios at some stations still show separation between earthquake and explosion populations, at other stations the populations are indistinguishable. There is no clear distance or azimuthal trend for which stations show discriminating abilities and which do not. A number of factors may play a role in differences we see between regional and local discrimination, including source effects such as depth and radiation pattern, and path effects such as laterally varying attenuation and focusing/defocusing from layers and scattering. We use data from the Source Physics Experiment (SPE) to investigate some of these effects. SPE is a series of chemical explosions at the Nevada National Security Site (NNSS) designed to improve our understanding and modeling capabilities of shear waves generated by explosions. Phase I consisted of 5 explosions in granite and Phase II will move to a contrasting dry alluvium geology. We apply a high-resolution 2D attenuation model to events near the NNSS to examine what effect path plays in local P/S ratios, and how well an earthquake-derived model can account for shallower explosion paths. The model incorporates both intrinsic attenuation and scattering effects and extends to 16 Hz, allowing us to make lateral path corrections and consider high-frequency ratios. Preliminary work suggests that while 2D path corrections modestly improve earthquake amplitude predictions, explosion amplitudes are not well matched, and so P/S ratios do not necessarily improve. Further work is needed to better understand the uses and limitation of 2D path corrections for local P/S ratios.

Sounds Activate Visual Cortex and Improve Visual Discrimination

PubMed Central

Störmer, Viola S.; Martinez, Antigona; McDonald, John J.; Hillyard, Steven A.

2014-01-01

A recent study in humans (McDonald et al., 2013) found that peripheral, task-irrelevant sounds activated contralateral visual cortex automatically as revealed by an auditory-evoked contralateral occipital positivity (ACOP) recorded from the scalp. The present study investigated the functional significance of this cross-modal activation of visual cortex, in particular whether the sound-evoked ACOP is predictive of improved perceptual processing of a subsequent visual target. A trial-by-trial analysis showed that the ACOP amplitude was markedly larger preceding correct than incorrect pattern discriminations of visual targets that were colocalized with the preceding sound. Dipole modeling of the scalp topography of the ACOP localized its neural generators to the ventrolateral extrastriate visual cortex. These results provide direct evidence that the cross-modal activation of contralateral visual cortex by a spatially nonpredictive but salient sound facilitates the discriminative processing of a subsequent visual target event at the location of the sound. Recordings of event-related potentials to the targets support the hypothesis that the ACOP is a neural consequence of the automatic orienting of visual attention to the location of the sound. PMID:25031419

Discrimination of trait-based characteristics by trace element bioaccumulation in riverine fishes

USGS Publications Warehouse

Short, T.M.; DeWeese, L.R.; Dubrovsky, N.M.

2008-01-01

Relations between tissue trace element concentrations and species traits were examined for 45 fish species to determine the extent to which trait-based characteristics accounted for relative differences among species in trace element bioaccumulation. Percentages of fish species correctly classified by discriminant analysis according to traits predicted by tissue trace element concentrations ranged from 72% to 87%. Tissue concentrations of copper, mercury, selenium, and zinc appeared to have the greatest overall influence on differentiating species according to trait characteristics. Discrimination of trait characteristics did not appear to be strongly influenced by local sources of trace elements in the streambed sediment. Bioaccumulation was greatest for those species classified as primarily detritivores, having relatively large adult body size, considered nonmigratory with respect to reproductive strategy, occurring mostly in large or variable size streams and rivers, preferring depositional areas within the stream channel, and preferring benthic rather than open-water habitats. Our findings provide evidence of the strong relationship between bioaccumulation of environmental trace elements and trait-based factors that influence contaminant exposure. ?? 2008 NRC.

Fitting the Rasch Model to Account for Variation in Item Discrimination

ERIC Educational Resources Information Center

Weitzman, R. A.

2009-01-01

Building on the Kelley and Gulliksen versions of classical test theory, this article shows that a logistic model having only a single item parameter can account for varying item discrimination, as well as difficulty, by using item-test correlations to adjust incorrect-correct (0-1) item responses prior to an initial model fit. The fit occurs…

Teaching Children with Autism to Discriminate the Reinforced and Nonreinforced Responses of Others: Implications for Observational Learning

ERIC Educational Resources Information Center

DeQuinzio, Jaime Ann; Taylor, Bridget A.

2015-01-01

We taught 4 participants with autism to discriminate between the reinforced and nonreinforced responses of an adult model and evaluated the effectiveness of this intervention using a multiple baseline design. During baseline, participants were simply exposed to adult models' correct and incorrect responses and the respective consequences of each.…

Identifying and Correctly Labeling Sexual Prejudice, Discrimination, and Oppression

ERIC Educational Resources Information Center

Dermer, Shannon B.; Smith, Shannon D.; Barto, Korenna K.

2010-01-01

To effectively work with and advocate for lesbians, gay men, and their families, one has to be aware of the individual, relational, and societal forces that may negatively affect them. The focus of this article is to familiarize the reader with terminology used to identify and label sexual prejudice, discrimination, and oppression. The pros and…

Luck and Learning: Feedback Contingencies and Initial Success in Verbal Discrimination Learning.

ERIC Educational Resources Information Center

Schneider, H. G.; Ferrante, A. P.

1983-01-01

A total of 90 undergraduate volunteers learned a 12-pair, low-frequency verbal discrimination list. Independent variables were feedback (positive only, negative only, or both) and initial success (17, 50, or 83 percent correct on the first trial). While the main effect of feedback was not significant, that of initial success was. (Author/RH)

78 FR 22361 - Social Security Ruling, SSR 13-1p; Titles II and XVI: Agency Processes for Addressing Allegations...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-15

... SOCIAL SECURITY ADMINISTRATION [Docket No. SSA-2012-0071] Social Security Ruling, SSR 13-1p..., Misconduct, or Discrimination by Administrative Law Judges (ALJs); Correction AGENCY: Social Security Administration. ACTION: Notice of Social Security Ruling; Correction. SUMMARY: The Social Security Administration...

78 FR 8217 - Social Security Ruling, SSR 13-1p; Titles II and XVI: Agency Processes for Addressing Allegations...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-02-05

... SOCIAL SECURITY ADMINISTRATION [Docket No. SSA-2012-0071] Social Security Ruling, SSR 13-1p..., Misconduct, or Discrimination by Administrative Law Judges (ALJs); Correction AGENCY: Social Security Administration. ACTION: Notice of Social Security Ruling; Correction. SUMMARY: The Social Security Administration...

Raman Spectroscopy an Option for the Early Detection of Citrus Huanglongbing.

PubMed

Pérez, Moisés Roberto Vallejo; Mendoza, María Guadalupe Galindo; Elías, Miguel Ghebre Ramírez; González, Francisco Javier; Contreras, Hugo Ricardo Navarro; Servín, Carlos Contreras

2016-05-01

This research describes the application of portable field Raman spectroscopy combined with a statistical analysis of the resulting spectra, employing principal component analysis (PCA) and linear discriminant analysis (LDA), in which we determine that this method provides a high degree of reliability in the early detection of Huanglongbing (HLB) on Sweet Orange, disease caused by the bacteria Candidatus Liberibacter asiaticus. Symptomatic and asymptomatic plant samples of Sweet Orange (Citrus sinensis), Persian Lime (C. latifolia), and Mexican Lime (C. aurantifolia) trees were collected from several municipalities, three at Colima State and three at Jalisco State (HLB presence). In addition, Sweet Orange samples were taken from two other Mexican municipalities, one at San Luis Potosí and the other at Veracruz (HLB absent). All samples were analyzed by real-time PCR to determine its phytosanitary condition, and its spectral signatures were obtained with an ID-Raman mini. Spectral anomalies in orange trees HLB-positive, were identified in bands related to carbohydrates (905 cm(-1), 1043 cm(-1), 1127 cm(-1), 1208 cm(-1), 1370 cm(-1), 1272 cm(-1), 1340 cm(-1), and 1260-1280 cm(-1)), amino acids, proteins (815 cm(-1), 830 cm(-1), 852 cm(-1), 918 cm(-1), 926 cm(-1), 970 cm(-1), 1002 cm(-1), 1053 cm(-1), and 1446 cm(-1)), and lipids (1734 cm(-1), 1736 cm(-1), 1738 cm(-1), 1745 cm(-1), and 1746 cm(-1)). Moreover, PCA-LDA showed a sensitivity of 86.9 % (percentage of positives, which are correctly identified), a specificity of 91.4 % (percentage of negatives, which are correctly identified), and a precision of 89.2 % (the proportion of all tests that are correct) in discriminating between orange plants HLB-positive and healthy plants. The Raman spectroscopy technique permitted rapid diagnoses, was low-cost, simple, and practical to administer, and produced immediate results. These are essential features for phytosanitary epidemiological surveillance activities that may conduct a targeted selection of highly suspicious trees to undergo molecular DNA analysis. © The Author(s) 2016.

Predicting malignant and tuberculous pleural effusions through demographics and pleural fluid analysis of patients.

PubMed

Valdés, Luis; San-José, Esther; Ferreiro, Lucía; Golpe, Antonio; González-Barcala, Francisco-Javier; Toubes, María E; Rodríguez-Álvarez, María X; Álvarez-Dobaño, José M; Rodríguez-Núñez, Nuria; Rábade, Carlos; Gude, Francisco

2015-04-01

The differential diagnosis of malignant and tuberculous pleural effusion is frequently difficult. The aim of our study is to determine the discrimination value of demographic parameters and different biological markers in pleural fluid. In pleural fluid obtained from 106 patients with tuberculous, 250 with malignant and 218 with miscellaneous pleural effusion, clinical and analytical parameters were analysed, applying polytomous regression analysis and the receiver operating characteristic (ROC) curves. The three groups could be differentiated using the measured markers. Age, tumour necrosing factor-alpha, lactate dehydrogenase (LDH), adenosine deaminase (ADA), C-reactive protein (CRP) and carcinoembryonic antigen (CEA) were significant predictors for discriminating tuberculous from malignant pleural effusions; nucleated cells, lymphocytes, cholesterol, LDH, ADA, CRP, CEA and CA15.3 distinguish between malignant and miscellaneous pleural effusions. The ROC areas (95% confidence interval) were, 0.973 (0.953, 0.992) for tuberculous, 0.922 (0.900, 0.943) for miscellaneous, and 0.927 (0.907, 0.948) for malignant pleural effusion. The polytomous model correctly classified a significantly high proportion of patients with tuberculosis (85.8%) and cancer (81.6%). The incorrect classification rate was 17.8%, which increased to 19.5% in the correction using bootstrap. The results obtained to estimate the probability of tuberculous and malignant pleural effusion confirm that this model achieves a high diagnostic accuracy. This model should be applied to determine which patients with a pleural effusion of unknown origin would not benefit from further invasive procedures. © 2014 John Wiley & Sons Ltd.

Determination of Sex from Footprint Dimensions in a Ghanaian Population.

PubMed

Abledu, Jubilant Kwame; Abledu, Godfred Kwame; Offei, Eric Bekoe; Antwi, Emmanuel Mensah

2015-01-01

The present study sought to verify the utility and reliability of footprint dimensions in sex determination in a Ghanaian population. Bilateral footprints were obtained from 126 Ghanaian students (66 males and 60 females) aged 18-30 years at Koforidua Polytechnic using an ink pad and white papers. Seven dimensions-length of each toe (designated T1-T5) from the most anterior point of the toe to the mid-rear heel point, breadth at ball (BAB) and breadth at heel (BAH)--and the heel-ball (HB) index were obtained from each footprint. Some footprint dimensions (i.e. T2, T3, T4 and T5) showed statistically significant bilateral asymmetry in males only. All the footprint dimensions, except HB index, were significantly greater in males than females (p<0.001). Applied singly in discriminant function analysis, the footprint dimensions allowed 69.8%-80.3% of cases to be correctly classified into their sex groups; the accuracy of sex classification was higher using left footprints than right footprints. With all dimensions subjected to stepwise discriminant function analysis 80.3% and 77% of cases could be correctly classified, combining both T5 and BAH for left footprints and T1, BAB and BAH for left footprints respectively. The present study has demonstrated, for the first time among Ghanaian subjects, the utility and reliability of sex determination standards developed from footprint dimensions. The results thus provide the baseline for elaborated studies in the future.

A morphometric system to distinguish sheep and goat postcranial bones

PubMed Central

2017-01-01

Distinguishing between the bones of sheep and goat is a notorious challenge in zooarchaeology. Several methodological contributions have been published at different times and by various people to facilitate this task, largely relying on a macro-morphological approach. This is now routinely adopted by zooarchaeologists but, although it certainly has its value, has also been shown to have limitations. Morphological discriminant criteria can vary in different populations and correct identification is highly dependent upon a researcher’s experience, availability of appropriate reference collections, and many other factors that are difficult to quantify. There is therefore a need to establish a more objective system, susceptible to scrutiny. In order to fulfil such a requirement, this paper offers a comprehensive morphometric method for the identification of sheep and goat postcranial bones, using a sample of more than 150 modern skeletons as a basis, and building on previous pioneering work. The proposed method is based on measurements—some newly created, others previously published–and its use is recommended in combination with the more traditional morphological approach. Measurement ratios, used to translate morphological traits into biometrical attributes, are demonstrated to have substantial diagnostic potential, with the vast majority of specimens correctly assigned to species. The efficacy of the new method is also tested with Discriminant Analysis, which provides a successful verification of the biometrical indices, a statistical means to select the most promising measurements, and an additional line of analysis to be used in conjunction with the others. PMID:28594831

A morphometric system to distinguish sheep and goat postcranial bones.

PubMed

Salvagno, Lenny; Albarella, Umberto

2017-01-01

Distinguishing between the bones of sheep and goat is a notorious challenge in zooarchaeology. Several methodological contributions have been published at different times and by various people to facilitate this task, largely relying on a macro-morphological approach. This is now routinely adopted by zooarchaeologists but, although it certainly has its value, has also been shown to have limitations. Morphological discriminant criteria can vary in different populations and correct identification is highly dependent upon a researcher's experience, availability of appropriate reference collections, and many other factors that are difficult to quantify. There is therefore a need to establish a more objective system, susceptible to scrutiny. In order to fulfil such a requirement, this paper offers a comprehensive morphometric method for the identification of sheep and goat postcranial bones, using a sample of more than 150 modern skeletons as a basis, and building on previous pioneering work. The proposed method is based on measurements-some newly created, others previously published-and its use is recommended in combination with the more traditional morphological approach. Measurement ratios, used to translate morphological traits into biometrical attributes, are demonstrated to have substantial diagnostic potential, with the vast majority of specimens correctly assigned to species. The efficacy of the new method is also tested with Discriminant Analysis, which provides a successful verification of the biometrical indices, a statistical means to select the most promising measurements, and an additional line of analysis to be used in conjunction with the others.

Measurement of residual chemical shift anisotropies in compressed polymethylmethacrylate gels. Automatic compensation of gel isotropic shift contribution.

PubMed

Hallwass, Fernando; Teles, Rubens R; Hellemann, Erich; Griesinger, Christian; Gil, Roberto R; Navarro-Vázquez, Armando

2018-05-01

Mechanical compression of polymer gels provides a simple way for the measurement of residual chemical shift anisotropies, which then can be employed, on its own, or in combination with residual dipolar couplings, for structural elucidation purposes. Residual chemical shift anisotropies measured using compression devices needed a posteriori correction to account for the increase of the polymer to solvent ratio inside the swollen gel. This correction has been cast before in terms of a single-free parameter which, as shown here, can be simultaneously optimized along with the components of the alignment tensor while still retaining discriminating power of the different relative configurations as illustrated in the stereochemical analysis of α-santonin and 10-epi-8-deoxycumambrin B. Copyright © 2018 John Wiley & Sons, Ltd.

Moment Tensor Analysis of Shallow Sources

NASA Astrophysics Data System (ADS)

Chiang, A.; Dreger, D. S.; Ford, S. R.; Walter, W. R.; Yoo, S. H.

2015-12-01

A potential issue for moment tensor inversion of shallow seismic sources is that some moment tensor components have vanishing amplitudes at the free surface, which can result in bias in the moment tensor solution. The effects of the free-surface on the stability of the moment tensor method becomes important as we continue to investigate and improve the capabilities of regional full moment tensor inversion for source-type identification and discrimination. It is important to understand these free surface effects on discriminating shallow explosive sources for nuclear monitoring purposes. It may also be important in natural systems that have shallow seismicity such as volcanoes and geothermal systems. In this study, we apply the moment tensor based discrimination method to the HUMMING ALBATROSS quarry blasts. These shallow chemical explosions at approximately 10 m depth and recorded up to several kilometers distance represent rather severe source-station geometry in terms of vanishing traction issues. We show that the method is capable of recovering a predominantly explosive source mechanism, and the combined waveform and first motion method enables the unique discrimination of these events. Recovering the correct yield using seismic moment estimates from moment tensor inversion remains challenging but we can begin to put error bounds on our moment estimates using the NSS technique.

Discriminating features of echolocation clicks of melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus), and Gray's spinner dolphins (Stenella longirostris longirostris).

PubMed

Baumann-Pickering, Simone; Wiggins, Sean M; Hildebrand, John A; Roch, Marie A; Schnitzler, Hans-Ulrich

2010-10-01

Spectral parameters were used to discriminate between echolocation clicks produced by three dolphin species at Palmyra Atoll: melon-headed whales (Peponocephala electra), bottlenose dolphins (Tursiops truncatus) and Gray's spinner dolphins (Stenella longirostris longirostris). Single species acoustic behavior during daytime observations was recorded with a towed hydrophone array sampling at 192 and 480 kHz. Additionally, an autonomous, bottom moored High-frequency Acoustic Recording Package (HARP) collected acoustic data with a sampling rate of 200 kHz. Melon-headed whale echolocation clicks had the lowest peak and center frequencies, spinner dolphins had the highest frequencies and bottlenose dolphins were nested in between these two species. Frequency differences were significant. Temporal parameters were not well suited for classification. Feature differences were enhanced by reducing variability within a set of single clicks by calculating mean spectra for groups of clicks. Median peak frequencies of averaged clicks (group size 50) of melon-headed whales ranged between 24.4 and 29.7 kHz, of bottlenose dolphins between 26.7 and 36.7 kHz, and of spinner dolphins between 33.8 and 36.0 kHz. Discriminant function analysis showed the ability to correctly discriminate between 93% of melon-headed whales, 75% of spinner dolphins and 54% of bottlenose dolphins.

Effect of musical training on static and dynamic measures of spectral-pattern discrimination.

PubMed

Sheft, Stanley; Smayda, Kirsten; Shafiro, Valeriy; Maddox, W Todd; Chandrasekaran, Bharath

2013-06-01

Both behavioral and physiological studies have demonstrated enhanced processing of speech in challenging listening environments attributable to musical training. The relationship, however, of this benefit to auditory abilities as assessed by psychoacoustic measures remains unclear. Using tasks previously shown to relate to speech-in-noise perception, the present study evaluated discrimination ability for static and dynamic spectral patterns by 49 listeners grouped as either musicians or nonmusicians. The two static conditions measured the ability to detect a change in the phase of a logarithmic sinusoidal spectral ripple of wideband noise with ripple densities of 1.5 and 3.0 cycles per octave chosen to emphasize either timbre or pitch distinctions, respectively. The dynamic conditions assessed temporal-pattern discrimination of 1-kHz pure tones frequency modulated by different lowpass noise samples with thresholds estimated in terms of either stimulus duration or signal-to-noise ratio. Musicians performed significantly better than nonmusicians on all four tasks. Discriminant analysis showed that group membership was correctly predicted for 88% of the listeners with the structure coefficient of each measure greater than 0.51. Results suggest that enhanced processing of static and dynamic spectral patterns defined by low-rate modulation may contribute to the relationship between musical training and speech-in-noise perception. [Supported by NIH.].

Neuromyths in Music Education: Prevalence and Predictors of Misconceptions among Teachers and Students

PubMed Central

Düvel, Nina; Wolf, Anna; Kopiez, Reinhard

2017-01-01

In the last decade, educational neuroscience has become increasingly important in the context of instruction, and its applications have been transformed into new teaching methods. Although teachers are interested in educational neuroscience, communication between scientists and teachers is not always straightforward. Thus, misunderstandings of neuroscientific research results can evolve into so-called neuromyths. The aim of the present study was to investigate the prevalence of such music-related neuromyths among music teachers and music students. Based on an extensive literature research, 26 theses were compiled and subsequently evaluated by four experts. Fourteen theses were selected, of which seven were designated as scientifically substantiated and seven as scientifically unsubstantiated (hereafter labeled as “neuromyths”). One group of adult music teachers (n = 91) and one group of music education students (n = 125) evaluated the theses (forced-choice discrimination task) in two separate online surveys. Additionally, in both surveys person-characteristic variables were gathered to determine possible predictors for the discrimination performance. As a result, identification rates of the seven scientifically substantiated theses were similar for teachers (76%) and students (78%). Teachers and students correctly rejected 60 and 59%, respectively, of the seven neuromyths as scientifically unsubstantiated statements. Sensitivity analysis by signal detection theory revealed a discrimination performance of d' = 1.25 (SD = 1.12) for the group of teachers and d' = 1.48 (SD = 1.22) for the students. Both groups showed a general tendency to evaluate the theses as scientifically substantiated (teachers: c = −0.35, students: c = −0.41). Specifically, buzz words such as “brain hemisphere” or “cognitive enhancement” were often classified as correct. For the group of teachers, the best predictor of discrimination performance was having read a large number of media about educational neuroscience and related topics (R2 = 0.06). For the group of students, the best predictors for discrimination performance were a high number of read media and the hitherto completed number of semesters (R2 = 0.14). Our findings make clear that both teachers and students are far from being experts on topics related to educational neuroscience in music and would therefore benefit from current education-related research in psychology and neuroscience. PMID:28484416

Neuromyths in Music Education: Prevalence and Predictors of Misconceptions among Teachers and Students.

PubMed

Düvel, Nina; Wolf, Anna; Kopiez, Reinhard

2017-01-01

In the last decade, educational neuroscience has become increasingly important in the context of instruction, and its applications have been transformed into new teaching methods. Although teachers are interested in educational neuroscience, communication between scientists and teachers is not always straightforward. Thus, misunderstandings of neuroscientific research results can evolve into so-called neuromyths . The aim of the present study was to investigate the prevalence of such music-related neuromyths among music teachers and music students. Based on an extensive literature research, 26 theses were compiled and subsequently evaluated by four experts. Fourteen theses were selected, of which seven were designated as scientifically substantiated and seven as scientifically unsubstantiated (hereafter labeled as "neuromyths"). One group of adult music teachers ( n = 91) and one group of music education students ( n = 125) evaluated the theses (forced-choice discrimination task) in two separate online surveys. Additionally, in both surveys person-characteristic variables were gathered to determine possible predictors for the discrimination performance. As a result, identification rates of the seven scientifically substantiated theses were similar for teachers (76%) and students (78%). Teachers and students correctly rejected 60 and 59%, respectively, of the seven neuromyths as scientifically unsubstantiated statements. Sensitivity analysis by signal detection theory revealed a discrimination performance of d' = 1.25 ( SD = 1.12) for the group of teachers and d' = 1.48 ( SD = 1.22) for the students. Both groups showed a general tendency to evaluate the theses as scientifically substantiated (teachers: c = -0.35, students: c = -0.41). Specifically, buzz words such as "brain hemisphere" or "cognitive enhancement" were often classified as correct. For the group of teachers, the best predictor of discrimination performance was having read a large number of media about educational neuroscience and related topics ( R 2 = 0.06). For the group of students, the best predictors for discrimination performance were a high number of read media and the hitherto completed number of semesters ( R 2 = 0.14). Our findings make clear that both teachers and students are far from being experts on topics related to educational neuroscience in music and would therefore benefit from current education-related research in psychology and neuroscience.

Discrimination accuracy between real and sham press needles in the hands.

PubMed

Kim, Sungha; Lee, Sanghun; Choi, Sunmi; Park, Jeonghwan; Kim, Sungchul

2015-08-01

To evaluate the blinding effectiveness of a modified blunt sham press needle on the basis of the ability of subjects to discriminate between real and sham acupuncture needles compared with their discrimination ability based on pure guessing, and to define differences between senses (touch and vision) in the rates of correctly identified needles. Sixty-three healthy students and staff members were recruited through convenience sampling. First, real or sham acupuncture was randomly administered to the left LI4 point while subjects could not observe the needle tip. A real or sham needle tip was then shown to the subjects. Finally, a random combination of real or sham acupuncture needles were randomly administered to the left and right LI4 points, this time with the subjects observing the procedure. In all conditions the subjects gave their judgement as Yes or No in response to questions asking them to identify the needle type. The proportion of correct judgements (P(C)) was computed for the last part of the trial in left and right LI4 points, and the rates of correctly identified needles for each trial were obtained. The subjects' accuracy of discrimination between the real and sham acupuncture needles in left and right LI4 points was not significantly different from that based on pure guess (P(C)=0.50 (chance level)), which indicates complete inability to discriminate between needles. The rates of correctly identified needles using touch, vision and a combination of both senses were not significantly different (p=0.807). The findings from this study show that this sham acupuncture device successfully blinded subjects to real and sham press needles, suggesting that it is effective for subject blinding in studies on acupuncture using press needles, and facilitating evaluation of the effects of acupuncture in placebo-controlled trials using a rigorous scientific research methodology. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Investigating the Predictive Value of Functional MRI to Appetitive and Aversive Stimuli: A Pattern Classification Approach.

PubMed

McCabe, Ciara; Rocha-Rego, Vanessa

2016-01-01

Dysfunctional neural responses to appetitive and aversive stimuli have been investigated as possible biomarkers for psychiatric disorders. However it is not clear to what degree these are separate processes across the brain or in fact overlapping systems. To help clarify this issue we used Gaussian process classifier (GPC) analysis to examine appetitive and aversive processing in the brain. 25 healthy controls underwent functional MRI whilst seeing pictures and receiving tastes of pleasant and unpleasant food. We applied GPCs to discriminate between the appetitive and aversive sights and tastes using functional activity patterns. The diagnostic accuracy of the GPC for the accuracy to discriminate appetitive taste from neutral condition was 86.5% (specificity = 81%, sensitivity = 92%, p = 0.001). If a participant experienced neutral taste stimuli the probability of correct classification was 92. The accuracy to discriminate aversive from neutral taste stimuli was 82.5% (specificity = 73%, sensitivity = 92%, p = 0.001) and appetitive from aversive taste stimuli was 73% (specificity = 77%, sensitivity = 69%, p = 0.001). In the sight modality, the accuracy to discriminate appetitive from neutral condition was 88.5% (specificity = 85%, sensitivity = 92%, p = 0.001), to discriminate aversive from neutral sight stimuli was 92% (specificity = 92%, sensitivity = 92%, p = 0.001), and to discriminate aversive from appetitive sight stimuli was 63.5% (specificity = 73%, sensitivity = 54%, p = 0.009). Our results demonstrate the predictive value of neurofunctional data in discriminating emotional and neutral networks of activity in the healthy human brain. It would be of interest to use pattern recognition techniques and fMRI to examine network dysfunction in the processing of appetitive, aversive and neutral stimuli in psychiatric disorders. Especially where problems with reward and punishment processing have been implicated in the pathophysiology of the disorder.

Classification and discrimination of pediatric patients undergoing open heart surgery with and without methylprednisolone treatment by cytomics

NASA Astrophysics Data System (ADS)

Bocsi, Jozsef; Mittag, Anja; Pierzchalski, Arkadiusz; Osmancik, Pavel; Dähnert, Ingo; Tárnok, Attila

2011-02-01

Introduction: Methylprednisolone (MP) is frequently preoperatively administered in children undergoing open heart surgery. The aim of this medication is to inhibit overshooting immune responses. Earlier studies demonstrated cellular and humoral immunological changes in pediatric patients undergoing heart surgeries with and without MP administration. Here in a retrospective study we investigated the modulation of the cellular immune response by MP. The aim was to identify suitable parameters characterizing MP effects by cluster analysis. Methods: Blood samples were analysed from two aged matched groups with surgical correction of septum defects. Group without MP treatment consisted of 10 patients; MP was administered on 21 patients (median dose: 11mg/kg) before cardiopulmonary bypass (CPB). EDTA anticoagulated blood was obtained 24 h preoperatively, after anesthesia, at CPB begin and end (CPB2), 4h, 24h, 48h after surgery, at discharge and at out-patient followup (8.2; 3.3-12.2 month after surgery; median and IQR). Flow cytometry showed the biggest MP relevant changes at CPB2 and 4h postoperatively. They were used for clustering analysis. Classification was made by discriminant analysis and cluster analysis by means of Genes@work software. Results & conclusion: 146 parameters were obtained from analysis. Cross-validation revealed several parameters being able to discriminate between MP groups and to identify immune modulation. MP administration resulted in a delayed activation of monocytes, increased ratio of neutrophils, reduced T-lymphocytes counts. Cluster analysis demonstrated that classification of patients is possible based on the identified cytomics parameters. Further investigation of these parameters might help to understand the MP effects in pediatric open heart surgery.

Speech perception task with pseudowords.

PubMed

Appezzato, Mariana Martins; Hackerott, Maria Mercedes Saraiva; Avila, Clara Regina Brandão de

2018-01-01

Purpose Prepare a list of pseudowords in Brazilian Portuguese to assess the auditory discrimination ability of schoolchildren and investigate the internal consistency of test items and the effect of school grade on discrimination performance. Methods Study participants were 60 schoolchildren (60% female) enrolled in the 3rd (n=14), 4th (n=24) and 5th (n=22) grades of an elementary school in the city of Sao Paulo, Brazil, aged between eight years and two months and 11 years and eight months (99 to 136 months; mean=120.05; SD=10.26), with average school performance score of 7.21 (minimum 5.0; maximum 10; SD=1.23). Forty-eight minimal pairs of Brazilian Portuguese pseudowords distinguished by a single phoneme were prepared. The participants' responses (whether the elements of the pairs were the same or different) were noted and analyzed. The data were analyzed using the Cronbach's Alpha Coefficient, Spearman's Correlation Coefficient, and Bonferroni Post-hoc Test at significance level of 0.05. Results Internal consistency analysis indicated the deletion of 20 pairs. The 28 items with results showed good internal consistency (α=0.84). The maximum and minimum scores of correct discrimination responses were 34 and 16, respectively (mean=30.79; SD=3.68). No correlation was observed between age, school performance, and discrimination performance, and no difference between school grades was found. Conclusion Most of the items proposed for assessing the auditory discrimination of speech sounds showed good internal consistency in relation to the task. Age and school grade did not improve the auditory discrimination of speech sounds.

Retrieval of high-spectral-resolution lidar for atmospheric aerosol optical properties profiling

NASA Astrophysics Data System (ADS)

Liu, Dong; Luo, Jing; Yang, Yongying; Cheng, Zhongtao; Zhang, Yupeng; Zhou, Yudi; Duan, Lulin; Su, Lin

2015-10-01

High-spectral-resolution lidars (HSRLs) are increasingly being developed for atmospheric aerosol remote sensing applications due to the straightforward and independent retrieval of aerosol optical properties without reliance on assumptions about lidar ratio. In HSRL technique, spectral discrimination between scattering from molecules and aerosol particles is one of the most critical processes, which needs to be accomplished by means of a narrowband spectroscopic filter. To ensure a high retrieval accuracy of an HSRL system, the high-quality design of its spectral discrimination filter should be made. This paper reviews the available algorithms that were proposed for HSRLs and makes a general accuracy analysis of the HSRL technique focused on the spectral discrimination, in order to provide heuristic guidelines for the reasonable design of the spectral discrimination filter. We introduce a theoretical model for retrieval error evaluation of an HSRL instrument with general three-channel configuration. Monte Carlo (MC) simulations are performed to validate the correctness of the theoretical model. Results from both the model and MC simulations agree very well, and they illustrate one important, although not well realized fact: a large molecular transmittance and a large spectral discrimination ratio (SDR, i.e., ratio of the molecular transmittance to the aerosol transmittance) are beneficial t o promote the retrieval accuracy. The application of the conclusions obtained in this paper in the designing of a new type of spectroscopic filter, that is, the field-widened Michelson interferometer, is illustrated in detail. These works are with certain universality and expected to be useful guidelines for HSRL community, especially when choosing or designing the spectral discrimination filter.

Authentication of the botanical origin of honey by front-face fluorescence spectroscopy. A preliminary study.

PubMed

Ruoff, Kaspar; Karoui, Romdhane; Dufour, Eric; Luginbühl, Werner; Bosset, Jacques-Olivier; Bogdanov, Stefan; Amado, Renato

2005-03-09

The potential of front-face fluorescence spectroscopy for the authentication of unifloral and polyfloral honey types (n = 57 samples) previously classified using traditional methods such as chemical, pollen, and sensory analysis was evaluated. Emission spectra were recorded between 280 and 480 nm (excit: 250 nm), 305 and 500 nm (excit: 290 nm), and 380 and 600 nm (excit: 373 nm) directly on honey samples. In addition, excitation spectra (290-440 nm) were recorded with the emission measured at 450 nm. A total of four different spectral data sets were considered for data analysis. After normalization of the spectra, chemometric evaluation of the spectral data was carried out using principal component analysis (PCA) and linear discriminant analysis (LDA). The rate of correct classification ranged from 36% to 100% by using single spectral data sets (250, 290, 373, 450 nm) and from 73% to 100% by combining these four data sets. For alpine polyfloral honey and the unifloral varieties investigated (acacia, alpine rose, honeydew, chestnut, and rape), correct classification ranged from 96% to 100%. This preliminary study indicates that front-face fluorescence spectroscopy is a promising technique for the authentication of the botanical origin of honey. It is nondestructive, rapid, easy to use, and inexpensive. The use of additional excitation wavelengths between 320 and 440 nm could increase the correct classification of the less characteristic fluorescent varieties.

High-throughput microarray technology in diagnostics of enterobacteria based on genome-wide probe selection and regression analysis.

PubMed

Friedrich, Torben; Rahmann, Sven; Weigel, Wilfried; Rabsch, Wolfgang; Fruth, Angelika; Ron, Eliora; Gunzer, Florian; Dandekar, Thomas; Hacker, Jörg; Müller, Tobias; Dobrindt, Ulrich

2010-10-21

The Enterobacteriaceae comprise a large number of clinically relevant species with several individual subspecies. Overlapping virulence-associated gene pools and the high overall genome plasticity often interferes with correct enterobacterial strain typing and risk assessment. Array technology offers a fast, reproducible and standardisable means for bacterial typing and thus provides many advantages for bacterial diagnostics, risk assessment and surveillance. The development of highly discriminative broad-range microbial diagnostic microarrays remains a challenge, because of marked genome plasticity of many bacterial pathogens. We developed a DNA microarray for strain typing and detection of major antimicrobial resistance genes of clinically relevant enterobacteria. For this purpose, we applied a global genome-wide probe selection strategy on 32 available complete enterobacterial genomes combined with a regression model for pathogen classification. The discriminative power of the probe set was further tested in silico on 15 additional complete enterobacterial genome sequences. DNA microarrays based on the selected probes were used to type 92 clinical enterobacterial isolates. Phenotypic tests confirmed the array-based typing results and corroborate that the selected probes allowed correct typing and prediction of major antibiotic resistances of clinically relevant Enterobacteriaceae, including the subspecies level, e.g. the reliable distinction of different E. coli pathotypes. Our results demonstrate that the global probe selection approach based on longest common factor statistics as well as the design of a DNA microarray with a restricted set of discriminative probes enables robust discrimination of different enterobacterial variants and represents a proof of concept that can be adopted for diagnostics of a wide range of microbial pathogens. Our approach circumvents misclassifications arising from the application of virulence markers, which are highly affected by horizontal gene transfer. Moreover, a broad range of pathogens have been covered by an efficient probe set size enabling the design of high-throughput diagnostics.

Classification of plum spirit drinks by synchronous fluorescence spectroscopy.

PubMed

Sádecká, J; Jakubíková, M; Májek, P; Kleinová, A

2016-04-01

Synchronous fluorescence spectroscopy was used in combination with principal component analysis (PCA) and linear discriminant analysis (LDA) for the differentiation of plum spirits according to their geographical origin. A total of 14 Czech, 12 Hungarian and 18 Slovak plum spirit samples were used. The samples were divided in two categories: colorless (22 samples) and colored (22 samples). Synchronous fluorescence spectra (SFS) obtained at a wavelength difference of 60 nm provided the best results. Considering the PCA-LDA applied to the SFS of all samples, Czech, Hungarian and Slovak colorless samples were properly classified in both the calibration and prediction sets. 100% of correct classification was also obtained for Czech and Hungarian colored samples. However, one group of Slovak colored samples was classified as belonging to the Hungarian group in the calibration set. Thus, the total correct classifications obtained were 94% and 100% for the calibration and prediction steps, respectively. The results were compared with those obtained using near-infrared (NIR) spectroscopy. Applying PCA-LDA to NIR spectra (5500-6000 cm(-1)), the total correct classifications were 91% and 92% for the calibration and prediction steps, respectively, which were slightly lower than those obtained using SFS. Copyright © 2015 Elsevier Ltd. All rights reserved.

Metabolomics for organic food authentication: Results from a long-term field study in carrots.

PubMed

Cubero-Leon, Elena; De Rudder, Olivier; Maquet, Alain

2018-01-15

Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

[Application of ICP-MS to Identify the Botanic Source of Characteristic Honey in South Yunnan].

PubMed

Wei, Yue; Chen, Fang; Wang, Yong; Chen, Lan-zhen; Zhang, Xue-wen; Wang, Yan-hui; Wu, Li-ming; Zhou, Qun

2016-01-01

By adopting inductively coupled plasma mass spectrometry (ICP-MS) combined with chemometric analysis technology, 23 kinds of minerals in four kinds of characteristic honey derived from Yunnan province were analyzed. The result showed that 21 kinds of mineral elements, namely Na, Mg, K, Ca, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Se, Sr, Mo, Cd, Sb, Ba, Tl and Pb, have significant differences among different varieties of honey. The results of principal component analysis (PCA) showed that the cumulative variance contribution rate of the first four main components reached 77.74%, seven kinds of elements (Mg, Ca, Mn, Co, Sr, Cd, Ba) from the first main component contained most of the honey information. Through the stepwise discriminant analysis, seven kinds of elements (Mg, K, Ca, Cr, Mn, Sr, Pb) were filtered. out and used to establish the discriminant function model, and the correct classification rates of the proposed model reached 90% and 86.7%, respectively, which showed elements contents could be effectively indicators to discriminate the four kinds characteristic honey in southern Yunnan Province. In view of all the honey samples were harvested from apiaries located at south Yunnan Province where have similar climate, soil and other environment conditions, the differences of the mineral elements contents for the honey samples mainly due to their corresponding nectariferous plant. Therefore, it is feasible to identify honey botanical source through the differences of mineral elements.

Analysis of discriminative control by social behavioral stimuli

PubMed Central

Hake, Don F.; Donaldson, Tom; Hyten, Cloyd

1983-01-01

Visual discriminative control of the behavior of one rat by the behavior of another was studied in a two-compartment chamber. Each rat's compartment had a food cup and two response keys arranged vertically next to the clear partition that separated the two rats. Illumination of the leader's key lights signaled a “search” period when a response by the leader on the unsignaled and randomly selected correct key for that trial illuminated the follower's keys. Then, a response by the follower on the corresponding key was reinforced, or a response on the incorrect key terminated the trial without reinforcement. Accuracy of following the leader increased to 85% within 15 sessions. Blocking the view of the leader reduced accuracy but not to chance levels. Apparent control by visual behavioral stimuli was also affected by auditory stimuli and a correction procedure. When white noise eliminated auditory cues, social learning was not acquired as fast nor as completely. A reductionistic position holds that behavioral stimuli are the same as nonsocial stimuli; however, that does not mean that they do not require any separate treatment. Behavioral stimuli are usually more variable than nonsocial stimuli, and further study is required to disentangle behavioral and nonsocial contributions to the stimulus control of social interactions. PMID:16812313

Potential use of ionic species for identifying source land-uses of stormwater runoff.

PubMed

Lee, Dong Hoon; Kim, Jin Hwi; Mendoza, Joseph A; Lee, Chang-Hee; Kang, Joo-Hyon

2017-02-01

Identifying critical land-uses or source areas is important to prioritize resources for cost-effective stormwater management. This study investigated the use of information on ionic composition as a fingerprint to identify the source land-use of stormwater runoff. We used 12 ionic species in stormwater runoff monitored for a total of 20 storm events at five sites with different land-use compositions during the 2012-2014 wet seasons. A stepwise forward discriminant function analysis (DFA) with the jack-knifed cross validation approach was used to select ionic species that better discriminate the land-use of its source. Of the 12 ionic species, 9 species (K + , Mg 2+ , Na + , NH 4 + , Br - , Cl - , F - , NO 2 - , and SO 4 2- ) were selected for better performance of the DFA. The DFA successfully differentiated stormwater samples from urban, rural, and construction sites using concentrations of the ionic species (70%, 95%, and 91% of correct classification, respectively). Over 80% of the new data cases were correctly classified by the trained DFA model. When applied to data cases from a mixed land-use catchment and downstream, the DFA model showed the greater impact of urban areas and rural areas respectively in the earlier and later parts of a storm event.

Morphological differences in parr of Atlantic salmon Salmo salar from three regions in Norway.

PubMed

Solem, O; Berg, O K

2011-05-01

Morphological characters were compared in parr (total length 33-166 mm) of Atlantic salmon Salmo salar sampled from eight wild populations in three regions, three in northern, two in the middle and three in southern Norway, covering a distance of 1700 km (from 70° N to 58° N). On the basis of morphological characters 94·6% of the individuals were correctly classified into the three regions. Discrimination between populations within these three regions also had a high degree of correct classification (89·0-95·8%). Principle component analysis identified largest differences to be in head characters, notably eye diameter and jawbone, with the smallest diameter and head size among the northernmost populations. Fish from the southern rivers had a deeper body form whereas fish from the middle region had larger heads and pectoral fins. This illustrates that S. salar already in the early parr stage has morphological traits, which can be used in discrimination between regions and populations and that these differences are discernible in spite of the volume of escaped farmed fish spawning in Norwegian rivers during the past 30 years. © 2011 The Authors. Journal of Fish Biology © 2011 The Fisheries Society of the British Isles.

Testing alternative ground water models using cross-validation and other methods

USGS Publications Warehouse

Foglia, L.; Mehl, S.W.; Hill, M.C.; Perona, P.; Burlando, P.

2007-01-01

Many methods can be used to test alternative ground water models. Of concern in this work are methods able to (1) rank alternative models (also called model discrimination) and (2) identify observations important to parameter estimates and predictions (equivalent to the purpose served by some types of sensitivity analysis). Some of the measures investigated are computationally efficient; others are computationally demanding. The latter are generally needed to account for model nonlinearity. The efficient model discrimination methods investigated include the information criteria: the corrected Akaike information criterion, Bayesian information criterion, and generalized cross-validation. The efficient sensitivity analysis measures used are dimensionless scaled sensitivity (DSS), composite scaled sensitivity, and parameter correlation coefficient (PCC); the other statistics are DFBETAS, Cook's D, and observation-prediction statistic. Acronyms are explained in the introduction. Cross-validation (CV) is a computationally intensive nonlinear method that is used for both model discrimination and sensitivity analysis. The methods are tested using up to five alternative parsimoniously constructed models of the ground water system of the Maggia Valley in southern Switzerland. The alternative models differ in their representation of hydraulic conductivity. A new method for graphically representing CV and sensitivity analysis results for complex models is presented and used to evaluate the utility of the efficient statistics. The results indicate that for model selection, the information criteria produce similar results at much smaller computational cost than CV. For identifying important observations, the only obviously inferior linear measure is DSS; the poor performance was expected because DSS does not include the effects of parameter correlation and PCC reveals large parameter correlations. ?? 2007 National Ground Water Association.

Assessment of phytoplankton class abundance using fluorescence excitation-emission matrix by parallel factor analysis and nonnegative least squares

NASA Astrophysics Data System (ADS)

Su, Rongguo; Chen, Xiaona; Wu, Zhenzhen; Yao, Peng; Shi, Xiaoyong

2015-07-01

The feasibility of using fluorescence excitation-emission matrix (EEM) along with parallel factor analysis (PARAFAC) and nonnegative least squares (NNLS) method for the differentiation of phytoplankton taxonomic groups was investigated. Forty-one phytoplankton species belonging to 28 genera of five divisions were studied. First, the PARAFAC model was applied to EEMs, and 15 fluorescence components were generated. Second, 15 fluorescence components were found to have a strong discriminating capability based on Bayesian discriminant analysis (BDA). Third, all spectra of the fluorescence component compositions for the 41 phytoplankton species were spectrographically sorted into 61 reference spectra using hierarchical cluster analysis (HCA), and then, the reference spectra were used to establish a database. Finally, the phytoplankton taxonomic groups was differentiated by the reference spectra database using the NNLS method. The five phytoplankton groups were differentiated with the correct discrimination ratios (CDRs) of 100% for single-species samples at the division level. The CDRs for the mixtures were above 91% for the dominant phytoplankton species and above 73% for the subdominant phytoplankton species. Sixteen of the 85 field samples collected from the Changjiang River estuary were analyzed by both HPLC-CHEMTAX and the fluorometric technique developed. The results of both methods reveal that Bacillariophyta was the dominant algal group in these 16 samples and that the subdominant algal groups comprised Dinophyta, Chlorophyta and Cryptophyta. The differentiation results by the fluorometric technique were in good agreement with those from HPLC-CHEMTAX. The results indicate that the fluorometric technique could differentiate algal taxonomic groups accurately at the division level.

Differentiation of cumin seeds using a metal-oxide based gas sensor array in tandem with chemometric tools.

PubMed

Ghasemi-Varnamkhasti, Mahdi; Amiri, Zahra Safari; Tohidi, Mojtaba; Dowlati, Majid; Mohtasebi, Seyed Saeid; Silva, Adenilton C; Fernandes, David D S; Araujo, Mário C U

2018-01-01

Cumin is a plant of the Apiaceae family (umbelliferae) which has been used since ancient times as a medicinal plant and as a spice. The difference in the percentage of aromatic compounds in cumin obtained from different locations has led to differentiation of some species of cumin from other species. The quality and price of cumin vary according to the specie and may be an incentive for the adulteration of high value samples with low quality cultivars. An electronic nose simulates the human olfactory sense by using an array of sensors to distinguish complex smells. This makes it an alternative for the identification and classification of cumin species. The data, however, may have a complex structure, difficult to interpret. Given this, chemometric tools can be used to manipulate data with two-dimensional structure (sensor responses in time) obtained by using electronic nose sensors. In this study, an electronic nose based on eight metal oxide semiconductor sensors (MOS) and 2D-LDA (two-dimensional linear discriminant analysis), U-PLS-DA (Partial least square discriminant analysis applied to the unfolded data) and PARAFAC-LDA (Parallel factor analysis with linear discriminant analysis) algorithms were used in order to identify and classify different varieties of both cultivated and wild black caraway and cumin. The proposed methodology presented a correct classification rate of 87.1% for PARAFAC-LDA and 100% for 2D-LDA and U-PLS-DA, indicating a promising strategy for the classification different varieties of cumin, caraway and other seeds. Copyright © 2017 Elsevier B.V. All rights reserved.

Solution identification and quantitative analysis of fiber-capacitive drop analyzer based on multivariate statistical methods

NASA Astrophysics Data System (ADS)

Chen, Zhe; Qiu, Zurong; Huo, Xinming; Fan, Yuming; Li, Xinghua

2017-03-01

A fiber-capacitive drop analyzer is an instrument which monitors a growing droplet to produce a capacitive opto-tensiotrace (COT). Each COT is an integration of fiber light intensity signals and capacitance signals and can reflect the unique physicochemical property of a liquid. In this study, we propose a solution analytical and concentration quantitative method based on multivariate statistical methods. Eight characteristic values are extracted from each COT. A series of COT characteristic values of training solutions at different concentrations compose a data library of this kind of solution. A two-stage linear discriminant analysis is applied to analyze different solution libraries and establish discriminant functions. Test solutions can be discriminated by these functions. After determining the variety of test solutions, Spearman correlation test and principal components analysis are used to filter and reduce dimensions of eight characteristic values, producing a new representative parameter. A cubic spline interpolation function is built between the parameters and concentrations, based on which we can calculate the concentration of the test solution. Methanol, ethanol, n-propanol, and saline solutions are taken as experimental subjects in this paper. For each solution, nine or ten different concentrations are chosen to be the standard library, and the other two concentrations compose the test group. By using the methods mentioned above, all eight test solutions are correctly identified and the average relative error of quantitative analysis is 1.11%. The method proposed is feasible which enlarges the applicable scope of recognizing liquids based on the COT and improves the concentration quantitative precision, as well.

In vivo diagnosis of mammary adenocarcinoma using Raman spectroscopy: an animal model study

NASA Astrophysics Data System (ADS)

Bitar, R. A.; Ribeiro, D. G.; dos Santos, E. A. P.; Ramalho, L. N. Z.; Ramalho, F. S.; Martin, A. A.; Martinho, H. S.

2010-02-01

Breast cancer is the most frequent cancer type in women Worldwide. Sensitivity and specificity of clinical breast examinations have been estimated from clinical trials to be approximately 54 % and 94 %, respectively. Further, approximately 95 % of all positive breast cancer screenings turn out to be false-positive. The optimal method for early detection should be both highly sensitive to ensure that all cancers are detected, and also highly specific to avoid the humanistic and economic costs associated with false-positive results. In vivo optical spectroscopy techniques, Raman in particular, have been pointed out as promising tools to improve the accuracy of screening mammography. The aim of the present study was to apply FT-Raman spectroscopy to discriminate normal and adenocarcinoma breast tissues of Sprague-Dawley female rats. The study was performed on 32 rats divided in the control (N=5) and experimental (N=27) groups. Histological analysis indicated that mammary hyperplasia, cribriform, papillary and solid adenocarcinomas were found in the experimental group subjects. The spectral collection was made using a commercial FT-Raman Spectrometer (Bruker RFS100) equipped with fiber-optic probe (RamProbe) and the spectral region between 900 and 1800 cm-1 was analyzed. Principal Components Analysis, Cluster Analysis, and Linear Discriminant Analysis with cross-validation were applied as spectral classification algorithm. As concluding remarks it is show that normal and adenocarcinoma tissues discriminations was possible (correct proportion for Transcutaneous collection mode was 80.80% and for "Open Sky" mode was 91.70%); however, a conclusive diagnosis among the four lesion subtypes was not possible.

Emergent, untrained stimulus relations in many-to-one matching-to-sample discriminations in rats.

PubMed

Nakagawa, Esho

2005-03-01

The present experiment investigated whether rats formed emergent, untrained stimulus relations in many-to-one matching-to-sample discriminations. In Phase 1, rats were trained to match two samples (triangle and horizontal stripes) to a common comparison (horizontal stripes) and two additional samples (circle or vertical stripes) to another comparison (vertical stripes). Then, in Phase 2, the rats were trained to match the one sample (triangle) to a new comparison (black) and the other sample (circle) to another comparison (white). In the Phase 3 test, half the rats (consistent group) were given two new tasks in which the sample-correct comparison relation was consistent with any emergent stimulus relations that previously may have been learned. The remaining 6 rats (inconsistent group) were given two new tasks in which the sample-correct comparison relation was not consistent with any previously learned emergent stimulus relations. Rats in the consistent group showed more accurate performance at the start of Phase 3, and faster learning to criterion in this phase, as compared with rats in the inconsistent group. This finding suggests that rats may form emergent, untrained stimulus relations between the discriminative stimuli in many-to-one matching-to-sample discriminations.

Morphometric sexing of Northwest Atlantic Roseate Terns

USGS Publications Warehouse

Palestis, Brian G.; Nisbet, Ian C.T.; Hatch, Jeremy J.; Szczys, Patricia; Spendelow, Jeffrey A.

2012-01-01

A difficulty in the study of monomorphic species is the inability of observers to visually distinguish females from males. Based on a sample of 745 known-sex birds nesting at Bird Island, MA, USA, a discriminant function analysis (DFA) was used to sex Roseate Terns (Sterna dougallii) of the Northwest Atlantic population using morphological measurements. DFA using only the total length of the head (including the bill) correctly identified the sex of approximately 86% of the terns, which increased to 88% if both members of a pair were measured. Including additional measurements increased these percentages slightly, to 87% and 90%, respectively. These levels of accuracy are generally higher than those reported for other species of terns. Because female-female pairs are frequent in this population, one cannot assume that the member of a pair with the larger head is a male, and additional discriminant functions were developed to help separate female-female from male-female pairs.

Evaluation of wavelength groups for discrimination of agricultural cover types. [remote sensing of environment in INDIANA

NASA Technical Reports Server (NTRS)

Kumar, R.

1978-01-01

Multispectral scanner data in twelve spectral channels, in the wavelength range 0.46 to 11.7 mm, acquired in July 1971 for three flightlines, were analyzed by applying automatic pattern recognition techniques. These twelve spectral channels were divided into four wavelength groups (W1, W2, W3 and W4), each consisting of three wavelength channels -- with respect to their estimated probability of correct classification (P sub c) in discriminating agricultural cover types. The same analysis was also done for the data acquired in August, to investigate the effect of time on these results. The effect of deletion of each of the wavelength groups on P sub C in the subsets of one to nine channels, is given. Values of P sub C for all possible combinations of wavelength groups, in the subsets of one to eleven channels are also given.

Quantification of chemical elements in blood of patients affected by multiple sclerosis.

PubMed

Forte, Giovanni; Visconti, Andrea; Santucci, Simone; Ghazaryan, Anna; Figà-Talamanca, Lorenzo; Cannoni, Stefania; Bocca, Beatrice; Pino, Anna; Violante, Nicola; Alimonti, Alessandro; Salvetti, Marco; Ristori, Giovanni

2005-01-01

Although some studies suggested a link between exposure to trace elements and development of multiple sclerosis (MS), clear information on their role in the aetiology of MS is still lacking. In this study the concentrations of Al, Ba, Be, Bi, Ca, Cd, Co, Cr, Cu, Fe, Hg, Li, Mg, Mn, Mo, Ni, Pb, Sb, Si, Sn, Sr, Tl, V, W, Zn and Zr were determined in the blood of 60 patients with MS and 60 controls. Quantifications were performed by inductively coupled plasma (ICP) atomic emission spectrometry and sector field ICP mass spectrometry. When the two groups were compared, an increased level of Co, Cu and Ni and a decrement of Be, Fe, Hg, Mg, Mo, Pb and Zn in blood of patients were observed. In addition, the discriminant analysis pointed out that Cu, Be, Hg, Co and Mo were able to discriminate between MS patients and controls (92.5% of cases correctly classified).

Evaluation of forensic genetic parameters of 12 STR loci in the Korean population using the InvestigatorⓇ HDplex kit.

PubMed

Jung, Ju Yeon; Kim, Eun Hye; Oh, Yu-Li; Park, Hyun-Chul; Hwang, Jung Ho; Lim, Si-Keun

2017-09-01

We genotyped and calculated the forensic parameters of 10 non-CODIS loci and 2 CODIS loci of 990 Korean individuals using the Investigator Ⓡ HDplex kit. No significant deviations from Hardy-Weinberg equilibrium (after Bonferroni correction for multiple testing) or genetic linkage disequilibrium were observed. The calculated matching probability and power of discrimination ranged from 0.0080 to 0.2014, and 0.7986 to 0.9920, respectively. We conclude that the markers of the kit are highly informative corroborative tools for forensic DNA analysis.

Multiple directed graph large-class multi-spectral processor

NASA Technical Reports Server (NTRS)

Casasent, David; Liu, Shiaw-Dong; Yoneyama, Hideyuki

1988-01-01

Numerical analysis techniques for the interpretation of high-resolution imaging-spectrometer data are described and demonstrated. The method proposed involves the use of (1) a hierarchical classifier with a tree structure generated automatically by a Fisher linear-discriminant-function algorithm and (2) a novel multiple-directed-graph scheme which reduces the local maxima and the number of perturbations required. Results for a 500-class test problem involving simulated imaging-spectrometer data are presented in tables and graphs; 100-percent-correct classification is achieved with an improvement factor of 5.

Distinguishing fibromyalgia from rheumatoid arthritis and systemic lupus in clinical questionnaires: an analysis of the revised Fibromyalgia Impact Questionnaire (FIQR) and its variant, the Symptom Impact Questionnaire (SIQR), along with pain locations

PubMed Central

2011-01-01

Introduction The purpose of this study was to explore a data set of patients with fibromyalgia (FM), rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) who completed the Revised Fibromyalgia Impact Questionnaire (FIQR) and its variant, the Symptom Impact Questionnaire (SIQR), for discriminating features that could be used to differentiate FM from RA and SLE in clinical surveys. Methods The frequency and means of comparing FM, RA and SLE patients on all pain sites and SIQR variables were calculated. Multiple regression analysis was then conducted to identify the significant pain sites and SIQR predictors of group membership. Thereafter stepwise multiple regression analysis was performed to identify the order of variables in predicting their maximal statistical contribution to group membership. Partial correlations assessed their unique contribution, and, last, two-group discriminant analysis provided a classification table. Results The data set contained information on the SIQR and also pain locations in 202 FM, 31 RA and 20 SLE patients. As the SIQR and pain locations did not differ much between the RA and SLE patients, they were grouped together (RA/SLE) to provide a more robust analysis. The combination of eight SIQR items and seven pain sites correctly classified 99% of FM and 90% of RA/SLE patients in a two-group discriminant analysis. The largest reported SIQR differences (FM minus RA/SLE) were seen for the parameters "tenderness to touch," "difficulty cleaning floors" and "discomfort on sitting for 45 minutes." Combining the SIQR and pain locations in a stepwise multiple regression analysis revealed that the seven most important predictors of group membership were mid-lower back pain (29%; 79% vs. 16%), tenderness to touch (11.5%; 6.86 vs. 3.02), neck pain (6.8%; 91% vs. 39%), hand pain (5%; 64% vs. 77%), arm pain (3%; 69% vs. 18%), outer lower back pain (1.7%; 80% vs. 22%) and sitting for 45 minutes (1.4%; 5.56 vs. 1.49). Conclusions A combination of two SIQR questions ("tenderness to touch" and "difficulty sitting for 45 minutes") plus pain in the lower back, neck, hands and arms may be useful in the construction of clinical questionnaires designed for patients with musculoskeletal pain. This combination provided the correct diagnosis in 97% of patients, with only 7 of 253 patients misclassified. PMID:21477308

The radiographic trabecular pattern of hips in patients with hip fractures and in elderly control subjects.

PubMed

Geraets, W G; Van der Stelt, P F; Lips, P; Van Ginkel, F C

1998-02-01

Due to the increasing number of osteoporotic fractures of hip, spine, and wrist there is a growing need for methods to track down the subjects with inferior bone structure and to monitor the effects of therapeutic measures. This study aims at a noninvasive diagnostic tool, deriving architectural properties of trabecular bone from in vivo measurements on plane radiographic films. Pelvic radiographs of the nonfractured hips of 81 patients with hip fractures and of the right hips of 74 controls were studied. The regions of interest, 2 x 2 cm2, located in the femoral neck, were sampled and digitized with a video camera connected to an image analysis system. Several geometrical and directional measurements were made. The measurements were evaluated by statistical comparison with fracture risk, gender, and Singh index. By discriminant analysis, type of fracture, as well as gender and Singh index could be predicted correctly for 58% of the subjects, whereas guessing would be correct in only 8%. It was found that the geometrical parameters discriminate between hips of controls and patients. With respect to the directional measurements associations were found with gender and Singh index. Although the new parameters assess fracture risk less accurately than bone density measurements, some parameters suggest by their behavior that they are relevant with respect to femoral bone architecture and its mechanical behavior. Although interpretation of the measurements in histological concepts requires methods that have been reported in literature only recently, it is concluded that digital analysis of the radiographic trabecular pattern is an interesting option to increase the diagnostic yield of plane film radiographs and to study the structure of bone in vivo.

Delineation of sympatric morphotypes of lake trout in Lake Superior

USGS Publications Warehouse

Moore, Seth A.; Bronte, Charles R.

2001-01-01

Three morphotypes of lake trout Salvelinus namaycush are recognized in Lake Superior: lean, siscowet, and humper. Absolute morphotype assignment can be difficult. We used a size-free, whole-body morphometric analysis (truss protocol) to determine whether differences in body shape existed among lake trout morphotypes. Our results showed discrimination where traditional morphometric characters and meristic measurements failed to detect differences. Principal components analysis revealed some separation of all three morphotypes based on head and caudal peduncle shape, but it also indicated considerable overlap in score values. Humper lake trout have smaller caudal peduncle widths to head length and depth characters than do lean or siscowet lake trout. Lean lake trout had larger head measures to caudal widths, whereas siscowet had higher caudal peduncle to head measures. Backward stepwise discriminant function analysis retained two head measures, three midbody measures, and four caudal peduncle measures; correct classification rates when using these variables were 83% for leans, 80% for siscowets, and 83% for humpers, which suggests the measures we used for initial classification were consistent. Although clear ecological reasons for these differences are not readily apparent, patterns in misclassification rates may be consistent with evolutionary hypotheses for lake trout within the Laurentian Great Lakes.

Discriminating anisometropic amblyopia from myopia based on interocular inhibition

PubMed Central

Jia, Wuli; Zhou, Jiawei; Lu, Zhong-Lin; Lesmes, Luis A.; Huang, Chang-Bing

2016-01-01

Amblyopia screening during childhood is critical for early detection and successful treatment. In the current study, we develop and evaluate a screening method that exploits the imbalanced interocular inhibition between amblyopic and fellow eyes. In nineteen subjects with anisometropic amblyopia and twenty-two age-matched subjects with myopia, we measured the area under the contrast sensitivity functions (AUCSFs) in eight monocular conditions defined by tested eye (left, right), patching of the untested eye (translucent, opaque), and refractive status (corrected, uncorrected). For each test eye, we defined the inhibition index as the ratio between AUCSF values obtained in the translucent and opaque patching conditions of the untested eye. To evaluate the screening potential of the inhibition index, we compared results from patients with amblyopia and myopia. With and without optical correction, the index was significantly lower in the amblyopic eye than in the fellow eye of the amblyopic subjects and both eyes of the myopic subjects. No significant difference was found among the two eyes of the myopic subjects and the fellow eyes of the amblyopic subjects. With the inhibition index as the predictor, a logistic regression model successfully discriminated amblyopic eyes from myopic eyes with 100% accuracy in the uncorrected condition. In the corrected condition, with the inhibition index and interocular visual acuity difference as predictors, amblyopic eyes were likewise discriminated from myopic eyes with 100% accuracy. This pattern of CSF changes, caused by the different patching modes of the untested eye, provides a potential CSF signature to discriminate anisometropic amblyopia from myopia. PMID:25701741

The 48-Pictures Test: a two-alternative forced-choice recognition test for the detection of malingering.

PubMed

Chouinard, M J; Rouleau, I

1997-11-01

We tested the validity of the 48-Pictures Test, a 2-alternative forced-choice recognition test, in detecting exaggerated memory impairments. This test maximizes subjective difficulty, through a large number of stimuli and shows minimal objective difficulty. We compared 17 suspected malingerers to 39 patients with memory impairments (6 amnesic, 15 frontal lobe dysfunctions, 18 other etiologies), and 17 normal adults instructed to simulate malingering on three memory tests: the 48-Pictures Test, the Rey Auditory Verbal Learning Test (RAVLT), and the Rey Complex Figure Test (RCFT). On the 48-Pictures Test, the clinical groups showed good recognition performance (amnesics: 85%; frontal dysfunction: 94%; other memory impairments: 97%), whereas the two simulator groups showed a poor performance (suspected malingerers: 62% correct; volunteer simulators 68% correct). The two other tests did not show a high degree of discrimination between the clinical groups and the simulator groups, except in 2 measures: the 2 simulator groups tended to show a performance decrement from the last recall trial to immediate recognition of the RAVLT and also performed better than the clinical groups on the immediate recall of the RCFT. A discriminant analysis with the latter 2 measures and the 48-Pictures Test correctly classified 96% of the participants. These results suggest that the 48-Pictures Test is a useful tool for the detection of possible simulated memory impairment and that when combined to the RAVLT recall-recognition difference score and to the immediate recall score on the RCFT can provide strong evidence of exaggerated memory impairment.

Radiological Evaluation of Strategic Structures in Patients with Mild Cognitive Impairment and Early Alzheimer's Disease.

PubMed

Nesteruk, Tomasz; Nesteruk, Marta; Styczyńska, Maria; Barcikowska-Kotowicz, Maria; Walecki, Jerzy

2016-01-01

The aim of the study was to evaluate the diagnostic value of two measurement techniques in patients with cognitive impairment - automated volumetry of the hippocampus, entorhinal cortex, parahippocampal gyrus, posterior cingulate gyrus, cortex of the temporal lobes and corpus callosum, and fractional anisotropy (FA) index measurement of the corpus callosum using diffusion tensor imaging. A total number of 96 patients underwent magnetic resonance imaging study of the brain - 33 healthy controls (HC), 33 patients with diagnosed mild cognitive impairment (MCI) and 30 patients with Alzheimer's disease (AD) in early stage. The severity of the dementia was evaluated with neuropsychological test battery. The volumetric measurements were performed automatically using FreeSurfer imaging software. The measurements of FA index were performed manually using ROI (region of interest) tool. The volumetric measurement of the temporal lobe cortex had the highest correct classification rate (68.7%), whereas the lowest was achieved with FA index measurement of the corpus callosum (51%). The highest sensitivity and specificity in discriminating between the patients with MCI vs. early AD was achieved with the volumetric measurement of the corpus callosum - the values were 73% and 71%, respectively, and the correct classification rate was 72%. The highest sensitivity and specificity in discriminating between HC and the patients with early AD was achieved with the volumetric measurement of the entorhinal cortex - the values were 94% and 100%, respectively, and the correct classification rate was 97%. The highest sensitivity and specificity in discriminating between HC and the patients with MCI was achieved with the volumetric measurement of the temporal lobe cortex - the values were 90% and 93%, respectively, and the correct classification rate was 92%. The diagnostic value varied depending on the measurement technique. The volumetric measurement of the atrophy proved to be the best imaging biomarker, which allowed the distinction between the groups of patients. The volumetric assessment of the corpus callosum proved to be a useful tool in discriminating between the patients with MCI vs. early AD.

Enzyme class identification in cleaning products by hydrolysis followed by derivatization with o-phthaldialdehyde, HPLC and linear discriminant analysis.

PubMed

Beneito-Cambra, M; Bernabé-Zafón, V; Herrero-Martínez, J M; Simó-Alfonso, E F; Ramis-Ramos, G

2009-07-15

The enzymes present in raw materials of the cleaning industry (enzyme industrial concentrates) and in household cleaners were isolated by precipitation with acetone and hydrolyzed with HCl. The resulting amino acids were derivatized with o-phthaldialdehyde, and the derivatives were separated by HPLC. The peaks of 14 amino acids were observed using a C18 column and a multi-segmented gradient of acetonitrile-water in the presence of a 5 mM citric/citrate buffer of pH 6.5. Using either normalized peak areas (divided by the sum of the peak areas of the chromatogram) or ratios of pairs of peak areas as predictor variables, linear discriminant analysis models, capable of predicting the enzyme class, including proteases, lipases, amylases and cellulases, were constructed. For this purpose, both enzyme industrial concentrates and detergent bases spiked with them were included in the training set. In all cases, the enzymes of the evaluation set, including industrial concentrates, spiked detergent bases and commercial cleaners were correctly classified with assignment probabilities higher than 99%.

Space sickness predictors suggest fluid shift involvement and possible countermeasures

NASA Technical Reports Server (NTRS)

Simanonok, K. E.; Moseley, E. C.; Charles, J. B.

1992-01-01

Preflight data from 64 first time Shuttle crew members were examined retrospectively to predict space sickness severity (NONE, MILD, MODERATE, or SEVERE) by discriminant analysis. From 9 input variables relating to fluid, electrolyte, and cardiovascular status, 8 variables were chosen by discriminant analysis that correctly predicted space sickness severity with 59 pct. success by one method of cross validation on the original sample and 67 pct. by another method. The 8 variables in order of their importance for predicting space sickness severity are sitting systolic blood pressure, serum uric acid, calculated blood volume, serum phosphate, urine osmolality, environmental temperature at the launch site, red cell count, and serum chloride. These results suggest the presence of predisposing physiologic factors to space sickness that implicate a fluid shift etiology. Addition of a 10th input variable, hours spent in the Weightless Environment Training Facility (WETF), improved the prediction of space sickness severity to 66 pct. success by the first method of cross validation on the original sample and to 71 pct. by the second method. The data suggest that WETF training may reduce space sickness severity.

Item response theory analysis of the mechanics baseline test

NASA Astrophysics Data System (ADS)

Cardamone, Caroline N.; Abbott, Jonathan E.; Rayyan, Saif; Seaton, Daniel T.; Pawl, Andrew; Pritchard, David E.

2012-02-01

Item response theory is useful in both the development and evaluation of assessments and in computing standardized measures of student performance. In item response theory, individual parameters (difficulty, discrimination) for each item or question are fit by item response models. These parameters provide a means for evaluating a test and offer a better measure of student skill than a raw test score, because each skill calculation considers not only the number of questions answered correctly, but the individual properties of all questions answered. Here, we present the results from an analysis of the Mechanics Baseline Test given at MIT during 2005-2010. Using the item parameters, we identify questions on the Mechanics Baseline Test that are not effective in discriminating between MIT students of different abilities. We show that a limited subset of the highest quality questions on the Mechanics Baseline Test returns accurate measures of student skill. We compare student skills as determined by item response theory to the more traditional measurement of the raw score and show that a comparable measure of learning gain can be computed.

A metabonomic strategy for the detection of the metabolic effects of chamomile (Matricaria recutita L.) ingestion.

PubMed

Wang, Yulan; Tang, Huiru; Nicholson, Jeremy K; Hylands, Peter J; Sampson, J; Holmes, Elaine

2005-01-26

A metabonomic strategy, utilizing high-resolution 1H NMR spectroscopy in conjunction with chemometric methods (discriminant analysis with orthogonal signal correction), has been applied to the study of human biological responses to chamomile tea ingestion. Daily urine samples were collected from volunteers during a 6-week period incorporating a 2-week baseline period, 2 weeks of daily chamomile tea ingestion, and a 2-week post-treatment phase. Although strong intersubject variation in metabolite profiles was observed, clear differentiation between the samples obtained before and after chamomile ingestion was achieved on the basis of increased urinary excretion of hippurate and glycine with depleted creatinine concentration. Samples obtained up to 2 weeks after daily chamomile intake formed an isolated cluster in the discriminant analysis map, from which it was inferred that the metabolic effects of chamomile ingestion were prolonged during the 2-week postdosing period. This study highlights the potential for metabonomic technology in the assessment of nutritional interventions, despite the high degree of variation from genetic and environmental sources.

LED-based near infrared sensor for cancer diagnostics

NASA Astrophysics Data System (ADS)

Bogomolov, Andrey; Ageev, Vladimir; Zabarylo, Urszula; Usenov, Iskander; Schulte, Franziska; Kirsanov, Dmitry; Belikova, Valeria; Minet, Olaf; Feliksberger, E.; Meshkovsky, I.; Artyushenko, Viacheslav

2016-03-01

Optical spectroscopic technologies are increasingly used for cancer diagnostics. Feasibility of differentiation between malignant and healthy samples of human kidney using Fluorescence, Raman, MIR and NIR spectroscopy has been recently reported . In the present work, a simplification of NIR spectroscopy method has been studied. Traditional high-resolution NIR spectrometry was replaced by an optical sensor based on a set of light-emitting diodes at selected wavelengths as light sources and a photodiode. Two prototypes of the sensor have been developed and tested using 14 in-vitro samples of seven kidney tumor patients. Statistical evaluation of results using principal component analysis and partial least-squares discriminant analysis has been performed. Despite only partial discrimination between tumor and healthy tissue achieved by the presented new technique, the results evidence benefits of LED-based near-infrared sensing used for oncological diagnostics. Publisher's Note: This paper, originally published on 4 March, 2016, was replaced with a corrected/revised version on 7 April, 2016. If you downloaded the original PDF but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance.

Rapid differentiation among bacteria that cause gastroenteritis by use of low-resolution Raman spectroscopy and PLS discriminant analysis.

PubMed

Mello, Cesar; Ribeiro, Diórginis; Novaes, Fábio; Poppi, Ronei J

2005-10-01

Use of classical microbiological methods to differentiate bacteria that cause gastroenteritis is cumbersome but usually very efficient. The high cost of reagents and the time required for such identifications, approximately four days, could have serious consequences, however, mainly when the patients are children, the elderly, or adults with low resistance. The search for new methods enabling rapid and reagentless differentiation of these microorganisms is, therefore, extremely relevant. In this work the main microorganisms responsible for gastroenteritis, Escherichia coli, Salmonella choleraesuis, and Shigella flexneri, were studied. For each microorganism sixty different dispersions were prepared in physiological solution. The Raman spectra of these dispersions were recorded using a diode laser operating in the near infrared region. Partial least-squares (PLS) discriminant analysis was used to differentiate among the bacteria by use of their respective Raman spectra. This approach enabled correct classification of 100% of the bacteria evaluated and unknown samples from the clinical environment, in less time ( approximately 10 h), by use of a low-cost, portable Raman spectrometer, which can be easily used in intensive care units and clinical environments.

Discrimination of edible oils and fats by combination of multivariate pattern recognition and FT-IR spectroscopy: a comparative study between different modeling methods.

PubMed

Javidnia, Katayoun; Parish, Maryam; Karimi, Sadegh; Hemmateenejad, Bahram

2013-03-01

By using FT-IR spectroscopy, many researchers from different disciplines enrich the experimental complexity of their research for obtaining more precise information. Moreover chemometrics techniques have boosted the use of IR instruments. In the present study we aimed to emphasize on the power of FT-IR spectroscopy for discrimination between different oil samples (especially fat from vegetable oils). Also our data were used to compare the performance of different classification methods. FT-IR transmittance spectra of oil samples (Corn, Colona, Sunflower, Soya, Olive, and Butter) were measured in the wave-number interval of 450-4000 cm(-1). Classification analysis was performed utilizing PLS-DA, interval PLS-DA, extended canonical variate analysis (ECVA) and interval ECVA methods. The effect of data preprocessing by extended multiplicative signal correction was investigated. Whilst all employed method could distinguish butter from vegetable oils, iECVA resulted in the best performances for calibration and external test set with 100% sensitivity and specificity. Copyright © 2012 Elsevier B.V. All rights reserved.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Characterization of porcine eyes based on autofluorescence lifetime imaging

NASA Astrophysics Data System (ADS)

Batista, Ana; Breunig, Hans Georg; Uchugonova, Aisada; Morgado, António Miguel; König, Karsten

2015-03-01

Multiphoton microscopy is a non-invasive imaging technique with ideal characteristics for biological applications. In this study, we propose to characterize three major structures of the porcine eye, the cornea, crystalline lens, and retina using two-photon excitation fluorescence lifetime imaging microscopy (2PE-FLIM). Samples were imaged using a laser-scanning microscope, consisting of a broadband sub-15 femtosecond (fs) near-infrared laser. Signal detection was performed using a 16-channel photomultiplier tube (PMT) detector (PML-16PMT). Therefore, spectral analysis of the fluorescence lifetime data was possible. To ensure a correct spectral analysis of the autofluorescence lifetime data, the spectra of the individual endogenous fluorophores were acquired with the 16-channel PMT and with a spectrometer. All experiments were performed within 12h of the porcine eye enucleation. We were able to image the cornea, crystalline lens, and retina at multiple depths. Discrimination of each structure based on their autofluorescence intensity and lifetimes was possible. Furthermore, discrimination between different layers of the same structure was also possible. To the best of our knowledge, this was the first time that 2PE-FLIM was used for porcine lens imaging and layer discrimination. With this study we further demonstrated the feasibility of 2PE-FLIM to image and differentiate three of the main components of the eye and its potential as an ophthalmologic technique.

Sex determination from the calcaneus in a 20th century Greek population using discriminant function analysis.

PubMed

Peckmann, Tanya R; Orr, Kayla; Meek, Susan; Manolis, Sotiris K

2015-12-01

The skull and post-cranium have been used for the determination of sex for unknown human remains. However, in forensic cases where skeletal remains often exhibit postmortem damage and taphonomic changes the calcaneus may be used for the determination of sex as it is a preservationally favored bone. The goal of the present research was to derive discriminant function equations from the calcaneus for estimation of sex from a contemporary Greek population. Nine parameters were measured on 198 individuals (103 males and 95 females), ranging in age from 20 to 99 years old, from the University of Athens Human Skeletal Reference Collection. The statistical analyses showed that all variables were sexually dimorphic. Discriminant function score equations were generated for use in sex determination. The average accuracy of sex classification ranged from 70% to 90% for the univariate analysis, 82.9% to 87.5% for the direct method, and 86.2% for the stepwise method. Comparisons to other populations were made. Overall, the cross-validated accuracies ranged from 48.6% to 56.1% with males most often identified correctly and females most often misidentified. The calcaneus was shown to be useful for sex determination in the twentieth century Greek population. Copyright © 2015 The Chartered Society of Forensic Sciences. Published by Elsevier Ireland Ltd. All rights reserved.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-01

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms.

Geographic identification of Boletus mushrooms by data fusion of FT-IR and UV spectroscopies combined with multivariate statistical analysis.

PubMed

Yao, Sen; Li, Tao; Li, JieQing; Liu, HongGao; Wang, YuanZhong

2018-06-05

Boletus griseus and Boletus edulis are two well-known wild-grown edible mushrooms which have high nutrition, delicious flavor and high economic value distributing in Yunnan Province. In this study, a rapid method using Fourier transform infrared (FT-IR) and ultraviolet (UV) spectroscopies coupled with data fusion was established for the discrimination of Boletus mushrooms from seven different geographical origins with pattern recognition method. Initially, the spectra of 332 mushroom samples obtained from the two spectroscopic techniques were analyzed individually and then the classification performance based on data fusion strategy was investigated. Meanwhile, the latent variables (LVs) of FT-IR and UV spectra were extracted by partial least square discriminant analysis (PLS-DA) and two datasets were concatenated into a new matrix for data fusion. Then, the fusion matrix was further analyzed by support vector machine (SVM). Compared with single spectroscopic technique, data fusion strategy can improve the classification performance effectively. In particular, the accuracy of correct classification of SVM model in training and test sets were 99.10% and 100.00%, respectively. The results demonstrated that data fusion of FT-IR and UV spectra can provide higher synergic effect for the discrimination of different geographical origins of Boletus mushrooms, which may be benefit for further authentication and quality assessment of edible mushrooms. Copyright © 2018 Elsevier B.V. All rights reserved.

Discrimination of biological and chemical threat simulants in residue mixtures on multiple substrates.

PubMed

Gottfried, Jennifer L

2011-07-01

The potential of laser-induced breakdown spectroscopy (LIBS) to discriminate biological and chemical threat simulant residues prepared on multiple substrates and in the presence of interferents has been explored. The simulant samples tested include Bacillus atrophaeus spores, Escherichia coli, MS-2 bacteriophage, α-hemolysin from Staphylococcus aureus, 2-chloroethyl ethyl sulfide, and dimethyl methylphosphonate. The residue samples were prepared on polycarbonate, stainless steel and aluminum foil substrates by Battelle Eastern Science and Technology Center. LIBS spectra were collected by Battelle on a portable LIBS instrument developed by A3 Technologies. This paper presents the chemometric analysis of the LIBS spectra using partial least-squares discriminant analysis (PLS-DA). The performance of PLS-DA models developed based on the full LIBS spectra, and selected emission intensities and ratios have been compared. The full-spectra models generally provided better classification results based on the inclusion of substrate emission features; however, the intensity/ratio models were able to correctly identify more types of simulant residues in the presence of interferents. The fusion of the two types of PLS-DA models resulted in a significant improvement in classification performance for models built using multiple substrates. In addition to identifying the major components of residue mixtures, minor components such as growth media and solvents can be identified with an appropriately designed PLS-DA model.

Seismic Source Scaling and Discrimination in Diverse Tectonic Environments

DTIC Science & Technology

2009-09-30

3349-3352. Imanishi, K., W. L. Ellsworth, and S. G. Prejean (2004). Earthquake source parameters determined by the SAFOD Pilot Hole seismic array ... seismic discrimination by performing a thorough investigation of* earthquake source scaling using diverse, high-quality datascts from varied tectonic...these corrections has a direct impact on our ability to identify clandestine explosions in the broad regional areas characterized by low seismicity

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-07-01

In this paper we present improved methods for discriminating and quantifying Primary Biological Aerosol Particles (PBAP) by applying hierarchical agglomerative cluster analysis to multi-parameter ultra violet-light induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1×106 points on a desktop computer, allowing for each fluorescent particle in a dataset to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient dataset. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best performing methods were applied to the BEACHON-RoMBAS ambient dataset where it was found that the z-score and range normalisation methods yield similar results with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misatrribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed yielding an explict cluster attribution for each particle, improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

Time course of discrimination between emotional facial expressions: the role of visual saliency.

PubMed

Calvo, Manuel G; Nummenmaa, Lauri

2011-08-01

Saccadic and manual responses were used to investigate the speed of discrimination between happy and non-happy facial expressions in two-alternative-forced-choice tasks. The minimum latencies of correct saccadic responses indicated that the earliest time point at which discrimination occurred ranged between 200 and 280ms, depending on type of expression. Corresponding minimum latencies for manual responses ranged between 440 and 500ms. For both response modalities, visual saliency of the mouth region was a critical factor in facilitating discrimination: The more salient the mouth was in happy face targets in comparison with non-happy distracters, the faster discrimination was. Global image characteristics (e.g., luminance) and semantic factors (i.e., categorical similarity and affective valence of expression) made minor or no contribution to discrimination efficiency. This suggests that visual saliency of distinctive facial features, rather than the significance of expression, is used to make both early and later expression discrimination decisions. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multicopy programmable discrimination of general qubit states

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sentis, G.; Bagan, E.; Calsamiglia, J.

2010-10-15

Quantum state discrimination is a fundamental primitive in quantum statistics where one has to correctly identify the state of a system that is in one of two possible known states. A programmable discrimination machine performs this task when the pair of possible states is not a priori known but instead the two possible states are provided through two respective program ports. We study optimal programmable discrimination machines for general qubit states when several copies of states are available in the data or program ports. Two scenarios are considered: One in which the purity of the possible states is a priorimore » known, and the fully universal one where the machine operates over generic mixed states of unknown purity. We find analytical results for both the unambiguous and minimum error discrimination strategies. This allows us to calculate the asymptotic performance of programmable discrimination machines when a large number of copies are provided and to recover the standard state discrimination and state comparison values as different limiting cases.« less

Refining Stimulus Parameters in Assessing Infant Speech Perception Using Visual Reinforcement Infant Speech Discrimination: Sensation Level.

PubMed

Uhler, Kristin M; Baca, Rosalinda; Dudas, Emily; Fredrickson, Tammy

2015-01-01

Speech perception measures have long been considered an integral piece of the audiological assessment battery. Currently, a prelinguistic, standardized measure of speech perception is missing in the clinical assessment battery for infants and young toddlers. Such a measure would allow systematic assessment of speech perception abilities of infants as well as the potential to investigate the impact early identification of hearing loss and early fitting of amplification have on the auditory pathways. To investigate the impact of sensation level (SL) on the ability of infants with normal hearing (NH) to discriminate /a-i/ and /ba-da/ and to determine if performance on the two contrasts are significantly different in predicting the discrimination criterion. The design was based on a survival analysis model for event occurrence and a repeated measures logistic model for binary outcomes. The outcome for survival analysis was the minimum SL for criterion and the outcome for the logistic regression model was the presence/absence of achieving the criterion. Criterion achievement was designated when an infant's proportion correct score was >0.75 on the discrimination performance task. Twenty-two infants with NH sensitivity participated in this study. There were 9 males and 13 females, aged 6-14 mo. Testing took place over two to three sessions. The first session consisted of a hearing test, threshold assessment of the two speech sounds (/a/ and /i/), and if time and attention allowed, visual reinforcement infant speech discrimination (VRISD). The second session consisted of VRISD assessment for the two test contrasts (/a-i/ and /ba-da/). The presentation level started at 50 dBA. If the infant was unable to successfully achieve criterion (>0.75) at 50 dBA, the presentation level was increased to 70 dBA followed by 60 dBA. Data examination included an event analysis, which provided the probability of criterion distribution across SL. The second stage of the analysis was a repeated measures logistic regression where SL and contrast were used to predict the likelihood of speech discrimination criterion. Infants were able to reach criterion for the /a-i/ contrast at statistically lower SLs when compared to /ba-da/. There were six infants who never reached criterion for /ba-da/ and one never reached criterion for /a-i/. The conditional probability of not reaching criterion by 70 dB SL was 0% for /a-i/ and 21% for /ba-da/. The predictive logistic regression model showed that children were more likely to discriminate the /a-i/ even when controlling for SL. Nearly all normal-hearing infants can demonstrate discrimination criterion of a vowel contrast at 60 dB SL, while a level of ≥70 dB SL may be needed to allow all infants to demonstrate discrimination criterion of a difficult consonant contrast. American Academy of Audiology.

Skin injury model classification based on shape vector analysis

PubMed Central

2012-01-01

Background: Skin injuries can be crucial in judicial decision making. Forensic experts base their classification on subjective opinions. This study investigates whether known classes of simulated skin injuries are correctly classified statistically based on 3D surface models and derived numerical shape descriptors. Methods: Skin injury surface characteristics are simulated with plasticine. Six injury classes – abrasions, incised wounds, gunshot entry wounds, smooth and textured strangulation marks as well as patterned injuries - with 18 instances each are used for a k-fold cross validation with six partitions. Deformed plasticine models are captured with a 3D surface scanner. Mean curvature is estimated for each polygon surface vertex. Subsequently, distance distributions and derived aspect ratios, convex hulls, concentric spheres, hyperbolic points and Fourier transforms are used to generate 1284-dimensional shape vectors. Subsequent descriptor reduction maximizing SNR (signal-to-noise ratio) result in an average of 41 descriptors (varying across k-folds). With non-normal multivariate distribution of heteroskedastic data, requirements for LDA (linear discriminant analysis) are not met. Thus, shrinkage parameters of RDA (regularized discriminant analysis) are optimized yielding a best performance with λ = 0.99 and γ = 0.001. Results: Receiver Operating Characteristic of a descriptive RDA yields an ideal Area Under the Curve of 1.0for all six categories. Predictive RDA results in an average CRR (correct recognition rate) of 97,22% under a 6 partition k-fold. Adding uniform noise within the range of one standard deviation degrades the average CRR to 71,3%. Conclusions: Digitized 3D surface shape data can be used to automatically classify idealized shape models of simulated skin injuries. Deriving some well established descriptors such as histograms, saddle shape of hyperbolic points or convex hulls with subsequent reduction of dimensionality while maximizing SNR seem to work well for the data at hand, as predictive RDA results in CRR of 97,22%. Objective basis for discrimination of non-overlapping hypotheses or categories are a major issue in medicolegal skin injury analysis and that is where this method appears to be strong. Technical surface quality is important in that adding noise clearly degrades CRR. Trial registration: This study does not cover the results of a controlled health care intervention as only plasticine was used. Thus, there was no trial registration. PMID:23497357

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis.

PubMed

Li, Zihui; Du, Boping; Li, Jing; Zhang, Jinli; Zheng, Xiaojing; Jia, Hongyan; Xing, Aiying; Sun, Qi; Liu, Fei; Zhang, Zongde

2017-03-01

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM. We used 1 H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0. The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM. Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

A New Clinical Pain Knowledge Test for Nurses: Development and Psychometric Evaluation.

PubMed

Bernhofer, Esther I; St Marie, Barbara; Bena, James F

2017-08-01

All nurses care for patients with pain, and pain management knowledge and attitude surveys for nurses have been around since 1987. However, no validated knowledge test exists to measure postlicensure clinicians' knowledge of the core competencies of pain management in current complex patient populations. To develop and test the psychometric properties of an instrument designed to measure pain management knowledge of postlicensure nurses. Psychometric instrument validation. Four large Midwestern U.S. hospitals. Registered nurses employed full time and part time August 2015 to April 2016, aged M = 43.25 years; time as RN, M = 16.13 years. Prospective survey design using e-mail to invite nurses to take an electronic multiple choice pain knowledge test. Content validity of initial 36-item test "very good" (95.1% agreement). Completed tests that met analysis criteria, N = 747. Mean initial test score, 69.4% correct (range 27.8-97.2). After revision/removal of 13 unacceptable questions, mean test score was 50.4% correct (range 8.7-82.6). Initial test item percent difficulty range was 15.2%-98.1%; discrimination values range, 0.03-0.50; final test item percent difficulty range, 17.6%-91.1%, discrimination values range, -0.04 to 1.04. Split-half reliability final test was 0.66. A high decision consistency reliability was identified, with test cut-score of 75%. The final 23-item Clinical Pain Knowledge Test has acceptable discrimination, difficulty, decision consistency, reliability, and validity in the general clinical inpatient nurse population. This instrument will be useful in assessing pain management knowledge of clinical nurses to determine gaps in education, evaluate knowledge after pain management education, and measure research outcomes. Copyright © 2017 American Society for Pain Management Nursing. Published by Elsevier Inc. All rights reserved.

Lung Cancer Risk Prediction Model Incorporating Lung Function: Development and Validation in the UK Biobank Prospective Cohort Study.

PubMed

Muller, David C; Johansson, Mattias; Brennan, Paul

2017-03-10

Purpose Several lung cancer risk prediction models have been developed, but none to date have assessed the predictive ability of lung function in a population-based cohort. We sought to develop and internally validate a model incorporating lung function using data from the UK Biobank prospective cohort study. Methods This analysis included 502,321 participants without a previous diagnosis of lung cancer, predominantly between 40 and 70 years of age. We used flexible parametric survival models to estimate the 2-year probability of lung cancer, accounting for the competing risk of death. Models included predictors previously shown to be associated with lung cancer risk, including sex, variables related to smoking history and nicotine addiction, medical history, family history of lung cancer, and lung function (forced expiratory volume in 1 second [FEV1]). Results During accumulated follow-up of 1,469,518 person-years, there were 738 lung cancer diagnoses. A model incorporating all predictors had excellent discrimination (concordance (c)-statistic [95% CI] = 0.85 [0.82 to 0.87]). Internal validation suggested that the model will discriminate well when applied to new data (optimism-corrected c-statistic = 0.84). The full model, including FEV1, also had modestly superior discriminatory power than one that was designed solely on the basis of questionnaire variables (c-statistic = 0.84 [0.82 to 0.86]; optimism-corrected c-statistic = 0.83; p FEV1 = 3.4 × 10 -13 ). The full model had better discrimination than standard lung cancer screening eligibility criteria (c-statistic = 0.66 [0.64 to 0.69]). Conclusion A risk prediction model that includes lung function has strong predictive ability, which could improve eligibility criteria for lung cancer screening programs.

Rapid on-line detection and grading of wooden breast myopathy in chicken fillets by near-infrared spectroscopy.

PubMed

Wold, Jens Petter; Veiseth-Kent, Eva; Høst, Vibeke; Løvland, Atle

2017-01-01

The main objective of this work was to develop a method for rapid and non-destructive detection and grading of wooden breast (WB) syndrome in chicken breast fillets. Near-infrared (NIR) spectroscopy was chosen as detection method, and an industrial NIR scanner was applied and tested for large scale on-line detection of the syndrome. Two approaches were evaluated for discrimination of WB fillets: 1) Linear discriminant analysis based on NIR spectra only, and 2) a regression model for protein was made based on NIR spectra and the estimated concentrations of protein were used for discrimination. A sample set of 197 fillets was used for training and calibration. A test set was recorded under industrial conditions and contained spectra from 79 fillets. The classification methods obtained 99.5-100% correct classification of the calibration set and 100% correct classification of the test set. The NIR scanner was then installed in a commercial chicken processing plant and could detect incidence rates of WB in large batches of fillets. Examples of incidence are shown for three broiler flocks where a high number of fillets (9063, 6330 and 10483) were effectively measured. Prevalence of WB of 0.1%, 6.6% and 8.5% were estimated for these flocks based on the complete sample volumes. Such an on-line system can be used to alleviate the challenges WB represents to the poultry meat industry. It enables automatic quality sorting of chicken fillets to different product categories. Manual laborious grading can be avoided. Incidences of WB from different farms and flocks can be tracked and information can be used to understand and point out main causes for WB in the chicken production. This knowledge can be used to improve the production procedures and reduce today's extensive occurrence of WB.

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

PubMed

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

Comparison of learning ability and memory retention in altricial (Bengalese finch, Lonchura striata var. domestica) and precocial (blue-breasted quail, Coturnix chinensis) birds using a color discrimination task.

PubMed

Ueno, Aki; Suzuki, Kaoru

2014-02-01

The present study sought to assess the potential application of avian models with different developmental modes to studies on cognition and neuroscience. Six altricial Bengalese finches (Lonchura striata var. domestica), and eight precocial blue-breasted quails (Coturnix chinensis) were presented with color discrimination tasks to compare their respective faculties for learning and memory retention within the context of the two developmental modes. Tasks consisted of presenting birds with discriminative cues in the form of colored feeder lids, and birds were considered to have learned a task when 80% of their attempts at selecting the correctly colored lid in two consecutive blocks of 10 trials were successful. All of the finches successfully performed the required experimental tasks, whereas only half of the quails were able to execute the same tasks. In the learning test, finches required significantly fewer trials than quails to learn the task (finches: 13.5 ± 9.14 trials, quails: 45.8 ± 4.35 trials, P < 0.05), with finches scoring significantly more correct responses than quails (finches: 98.3 ± 4.08%, quails: 85.0 ± 5.77% at the peak of the learning curve). In the memory retention tests, which were conducted 45 days after the learning test, finches retained the ability to discriminate between colors correctly (95.0 ± 4.47%), whereas quails did not retain any memory of the experimental procedure and so could not be tested. These results suggested that altricial and precocial birds both possess the faculty for learning and retaining discrimination-type tasks, but that altricial birds perform better than precocial birds in both faculties. The present findings imply that developmental mode is an important consideration for assessing the suitability of bird species for particular experiments. © 2013 Japanese Society of Animal Science.

The development and cross-validation of an MMPI typology of murderers.

PubMed

Holcomb, W R; Adams, N A; Ponder, H M

1985-06-01

A sample of 80 male offenders charged with premeditated murder were divided into five personality types using MMPI scores. A hierarchical clustering procedure was used with a subsequent internal cross-validation analysis using a second sample of 80 premeditated murderers. A Discriminant Analysis resulted in a 96.25% correct classification of subjects from the second sample into the five types. Clinical data from a mental status interview schedule supported the external validity of these types. There were significant differences among the five types in hallucinations, disorientation, hostility, depression, and paranoid thinking. Both similarities and differences of the present typology with prior research was discussed. Additional research questions were suggested.

Multiresolution Wavelet Analysis of Heartbeat Intervals Discriminates Healthy Patients from Those with Cardiac Pathology

NASA Astrophysics Data System (ADS)

Thurner, Stefan; Feurstein, Markus C.; Teich, Malvin C.

1998-02-01

We applied multiresolution wavelet analysis to the sequence of times between human heartbeats ( R-R intervals) and have found a scale window, between 16 and 32 heartbeat intervals, over which the widths of the R-R wavelet coefficients fall into disjoint sets for normal and heart-failure patients. This has enabled us to correctly classify every patient in a standard data set as belonging either to the heart-failure or normal group with 100% accuracy, thereby providing a clinically significant measure of the presence of heart failure from the R-R intervals alone. Comparison is made with previous approaches, which have provided only statistically significant measures.

Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach

NASA Astrophysics Data System (ADS)

Samulski, Maurice; Karssemeijer, Nico

2008-03-01

Most of the current CAD systems detect suspicious mass regions independently in single views. In this paper we present a method to match corresponding regions in mediolateral oblique (MLO) and craniocaudal (CC) mammographic views of the breast. For every possible combination of mass regions in the MLO view and CC view, a number of features are computed, such as the difference in distance of a region to the nipple, a texture similarity measure, the gray scale correlation and the likelihood of malignancy of both regions computed by single-view analysis. In previous research, Linear Discriminant Analysis was used to discriminate between correct and incorrect links. In this paper we investigate if the performance can be improved by employing a statistical method in which four classes are distinguished. These four classes are defined by the combinations of view (MLO/CC) and pathology (TP/FP) labels. We use distance-weighted k-Nearest Neighbor density estimation to estimate the likelihood of a region combination. Next, a correspondence score is calculated as the likelihood that the region combination is a TP-TP link. The method was tested on 412 cases with a malignant lesion visible in at least one of the views. In 82.4% of the cases a correct link could be established between the TP detections in both views. In future work, we will use the framework presented here to develop a context dependent region matching scheme, which takes the number and likelihood of possible alternatives into account. It is expected that more accurate determination of matching probabilities will lead to improved CAD performance.

Identification of pesticide varieties by detecting characteristics of Chlorella pyrenoidosa using Visible/Near infrared hyperspectral imaging and Raman microspectroscopy technology.

PubMed

Shao, Yongni; Li, Yuan; Jiang, Linjun; Pan, Jian; He, Yong; Dou, Xiaoming

2016-11-01

The main goal of this research is to examine the feasibility of applying Visible/Near-infrared hyperspectral imaging (Vis/NIR-HSI) and Raman microspectroscopy technology for non-destructive identification of pesticide varieties (glyphosate and butachlor). Both mentioned technologies were explored to investigate how internal elements or characteristics of Chlorella pyrenoidosa change when pesticides are applied, and in the meantime, to identify varieties of the pesticides during this procedure. Successive projections algorithm (SPA) was introduced to our study to identify seven most effective wavelengths. With those wavelengths suggested by SPA, a model of the linear discriminant analysis (LDA) was established to classify the pesticide varieties, and the correct classification rate of the SPA-LDA model reached as high as 100%. For the Raman technique, a few partial least squares discriminant analysis models were established with different preprocessing methods from which we also identified one processing approach that achieved the most optimal result. The sensitive wavelengths (SWs) which are related to algae's pigment were chosen, and a model of LDA was established with the correct identification reached a high level of 90.0%. The results showed that both Vis/NIR-HSI and Raman microspectroscopy techniques are capable to identify pesticide varieties in an indirect but effective way, and SPA is an effective wavelength extracting method. The SWs corresponding to microalgae pigments, which were influenced by pesticides, could also help to characterize different pesticide varieties and benefit the variety identification. Copyright © 2016 Elsevier Ltd. All rights reserved.

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 1

NASA Technical Reports Server (NTRS)

Schlosser, E. H.

1980-01-01

A generalized four channel hyperplane to discriminate water from nonwater was developed using LANDSAT-3 multispectral scaner (MSS) scenes and matching same/next day color infrared aerial photography. The MSS scenes varied in sun elevation angle from 40 to 58 deg. The 28 matching air photo frames contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant, was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. A linear discriminant was iteratively fitted to the labelled pixels. This discriminant correctly classified 98.7% of the water pixels and 98.6% of the nonwater pixels. The discriminant detected 91.3% of the 414 water bodies over 10 acres in surface area, and misclassified as water 36 groups of contiguous nonwater pixels.

Mapping Discrimination Experienced by Indonesian Trans* FtM Persons.

PubMed

Gordon, Danny; Pratama, Mario Prajna

2017-01-01

This work sought to document how Indonesian trans* FtM persons experienced discrimination across the interlinked domains of social networks, religious and educational institutions, employment and the workplace, and health care institutions. Objectives were (1) to map the discrimination experienced by trans* FtM individuals in Indonesia, and (2) to establish the specific priorities of the Indonesian trans* FtM community. In-depth interviews, focus groups, and participant observation was used involving 14 respondents. Findings revealed that respondents experienced othering through rejection, misidentification, harassment, "correction," and bureaucratic discrimination across the five preestablished domains. Health care and a lack of information emerged as areas of particular concern for respondents. This work calls for health care that is sensitive to the needs of trans* FtM people coupled with high-quality information to alleviate the cycles through which discrimination is sustained.

A signal-detection-based diagnostic-feature-detection model of eyewitness identification.

PubMed

Wixted, John T; Mickes, Laura

2014-04-01

The theoretical understanding of eyewitness identifications made from a police lineup has long been guided by the distinction between absolute and relative decision strategies. In addition, the accuracy of identifications associated with different eyewitness memory procedures has long been evaluated using measures like the diagnosticity ratio (the correct identification rate divided by the false identification rate). Framed in terms of signal-detection theory, both the absolute/relative distinction and the diagnosticity ratio are mainly relevant to response bias while remaining silent about the key issue of diagnostic accuracy, or discriminability (i.e., the ability to tell the difference between innocent and guilty suspects in a lineup). Here, we propose a signal-detection-based model of eyewitness identification, one that encourages the use of (and helps to conceptualize) receiver operating characteristic (ROC) analysis to measure discriminability. Recent ROC analyses indicate that the simultaneous presentation of faces in a lineup yields higher discriminability than the presentation of faces in isolation, and we propose a diagnostic feature-detection hypothesis to account for that result. According to this hypothesis, the simultaneous presentation of faces allows the eyewitness to appreciate that certain facial features (viz., those that are shared by everyone in the lineup) are non-diagnostic of guilt. To the extent that those non-diagnostic features are discounted in favor of potentially more diagnostic features, the ability to discriminate innocent from guilty suspects will be enhanced.

Bimodal spectroscopic evaluation of ultra violet-irradiated mouse skin inflammatory and precancerous stages: instrumentation, spectral feature extraction/selection and classification (k-NN, LDA and SVM)

NASA Astrophysics Data System (ADS)

Díaz-Ayil, G.; Amouroux, M.; Blondel, W. C. P. M.; Bourg-Heckly, G.; Leroux, A.; Guillemin, F.; Granjon, Y.

2009-07-01

This paper deals with the development and application of in vivo spatially-resolved bimodal spectroscopy (AutoFluorescence AF and Diffuse Reflectance DR), to discriminate various stages of skin precancer in a preclinical model (UV-irradiated mouse): Compensatory Hyperplasia CH, Atypical Hyperplasia AH and Dysplasia D. A programmable instrumentation was developed for acquiring AF emission spectra using 7 excitation wavelengths: 360, 368, 390, 400, 410, 420 and 430 nm, and DR spectra in the 390-720 nm wavelength range. After various steps of intensity spectra preprocessing (filtering, spectral correction and intensity normalization), several sets of spectral characteristics were extracted and selected based on their discrimination power statistically tested for every pair-wise comparison of histological classes. Data reduction with Principal Components Analysis (PCA) was performed and 3 classification methods were implemented (k-NN, LDA and SVM), in order to compare diagnostic performance of each method. Diagnostic performance was studied and assessed in terms of sensitivity (Se) and specificity (Sp) as a function of the selected features, of the combinations of 3 different inter-fibers distances and of the numbers of principal components, such that: Se and Sp ≈ 100% when discriminating CH vs. others; Sp ≈ 100% and Se > 95% when discriminating Healthy vs. AH or D; Sp ≈ 74% and Se ≈ 63%for AH vs. D.

Ex post facto assessment of diffusion tensor imaging metrics from different MRI protocols: preparing for multicentre studies in ALS.

PubMed

Rosskopf, Johannes; Müller, Hans-Peter; Dreyhaupt, Jens; Gorges, Martin; Ludolph, Albert C; Kassubek, Jan

2015-03-01

Diffusion tensor imaging (DTI) for assessing ALS-associated white matter alterations has still not reached the level of a neuroimaging biomarker. Since large-scale multicentre DTI studies in ALS may be hampered by differences in scanning protocols, an approach for pooling of DTI data acquired with different protocols was investigated. Three hundred and nine datasets from 170 ALS patients and 139 controls were collected ex post facto from a monocentric database reflecting different scanning protocols. A 3D correction algorithm was introduced for a combined analysis of DTI metrics despite different acquisition protocols, with the focus on the CST as the tract correlate of ALS neuropathological stage 1. A homogenous set of data was obtained by application of 3D correction matrices. Results showed that a fractional anisotropy (FA) threshold of 0.41 could be defined to discriminate ALS patients from controls (sensitivity/specificity, 74%/72%). For the remaining test sample, sensitivity/specificity values of 68%/74% were obtained. In conclusion, the objective was to merge data recorded with different DTI protocols with 3D correction matrices for analyses at group level. These post processing tools might facilitate analysis of large study samples in a multicentre setting for DTI analysis at group level to aid in establishing DTI as a non-invasive biomarker for ALS.

Custom-made foot orthoses: an analysis of prescription characteristics from an Australian commercial orthotic laboratory.

PubMed

Menz, Hylton B; Allan, Jamie J; Bonanno, Daniel R; Landorf, Karl B; Murley, George S

2017-01-01

Foot orthoses are widely used in the prevention and treatment of foot disorders. The aim of this study was to describe characteristics of custom-made foot orthosis prescriptions from a Australian podiatric orthotic laboratory. One thousand consecutive foot orthosis prescription forms were obtained from a commercial prescription foot orthosis laboratory located in Melbourne, Victoria, Australia (Footwork Podiatric Laboratory). Each item from the prescription form was documented in relation to orthosis type, cast correction, arch fill technique, cast modifications, shell material, shell modifications and cover material. Cluster analysis and discriminant function analysis were applied to identify patterns in the prescription data. Prescriptions were obtained from 178 clinical practices across Australia and Hong Kong, with patients ranging in age from 5 to 92 years. Three broad categories ('clusters') were observed that were indicative of increasing 'control' of rearfoot pronation. A combination of five variables (rearfoot cast correction, cover shape, orthosis type, forefoot cast correction and plantar fascial accommodation) was able to identify these clusters with an accuracy of 70%. Significant differences between clusters were observed in relation to age and sex of the patient and the geographic location of the prescribing clinician. Foot orthosis prescriptions are complex, but can be broadly classified into three categories. Selection of these prescription subtypes appears to be influenced by both patient factors (age and sex) and clinician factors (clinic location).

Harvest locations of goose barnacles can be successfully discriminated using trace elemental signatures

NASA Astrophysics Data System (ADS)

Albuquerque, Rui; Queiroga, Henrique; Swearer, Stephen E.; Calado, Ricardo; Leandro, Sérgio M.

2016-06-01

European Union regulations state that consumers must be rightfully informed about the provenance of fishery products to prevent fraudulent practices. However, mislabeling of the geographical origin is a common practice. It is therefore paramount to develop forensic methods that allow all players involved in the supply chain to accurately trace the origin of seafood. In this study, trace elemental signatures (TES) of the goose barnacle Pollicipes pollicipes, collected from ten sites along the Portuguese coast, were employed to discriminate individual’s origin. Barium (Ba), boron (B), cadmium (Cd), chromium (Cr), lithium (Li), magnesium (Mg), manganese (Mn), phosphorous (P), lead (Pb), strontium (Sr) and zinc (Zn) - were quantified using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Significant differences were recorded among locations for all elements. A regularized discriminant analysis (RDA) revealed that 83% of all individuals were correctly assigned. This study shows TES can be a reliable tool to confirm the geographic origin of goose barnacles at fine spatial resolution. Although additional studies are required to ascertain the reliability of TES on cooked specimens and the temporal stability of the signature, the approach holds great promise for the management of goose barnacles fisheries, enforcement of conservation policies and assurance in accurate labeling.

Talent identification and selection in elite youth football: An Australian context.

PubMed

O'Connor, Donna; Larkin, Paul; Mark Williams, A

2016-10-01

We identified the perceptual-cognitive skills and player history variables that differentiate players selected or not selected into an elite youth football (i.e. soccer) programme in Australia. A sample of elite youth male football players (n = 127) completed an adapted participation history questionnaire and video-based assessments of perceptual-cognitive skills. Following data collection, 22 of these players were offered a full-time scholarship for enrolment at an elite player residential programme. Participants selected for the scholarship programme recorded superior performance on the combined perceptual-cognitive skills tests compared to the non-selected group. There were no significant between group differences on the player history variables. Stepwise discriminant function analysis identified four predictor variables that resulted in the best categorization of selected and non-selected players (i.e. recent match-play performance, region, number of other sports participated, combined perceptual-cognitive performance). The effectiveness of the discriminant function is reflected by 93.7% of players being correctly classified, with the four variables accounting for 57.6% of the variance. Our discriminating model for selection may provide a greater understanding of the factors that influence elite youth talent selection and identification.

Sounds activate visual cortex and improve visual discrimination.

PubMed

Feng, Wenfeng; Störmer, Viola S; Martinez, Antigona; McDonald, John J; Hillyard, Steven A

2014-07-16

A recent study in humans (McDonald et al., 2013) found that peripheral, task-irrelevant sounds activated contralateral visual cortex automatically as revealed by an auditory-evoked contralateral occipital positivity (ACOP) recorded from the scalp. The present study investigated the functional significance of this cross-modal activation of visual cortex, in particular whether the sound-evoked ACOP is predictive of improved perceptual processing of a subsequent visual target. A trial-by-trial analysis showed that the ACOP amplitude was markedly larger preceding correct than incorrect pattern discriminations of visual targets that were colocalized with the preceding sound. Dipole modeling of the scalp topography of the ACOP localized its neural generators to the ventrolateral extrastriate visual cortex. These results provide direct evidence that the cross-modal activation of contralateral visual cortex by a spatially nonpredictive but salient sound facilitates the discriminative processing of a subsequent visual target event at the location of the sound. Recordings of event-related potentials to the targets support the hypothesis that the ACOP is a neural consequence of the automatic orienting of visual attention to the location of the sound. Copyright © 2014 the authors 0270-6474/14/349817-08$15.00/0.

Discriminant cognitive factors in responder and non-responder patients with schizophrenia.

PubMed

Stip, E; Lussier, I; Ngan, E; Mendrek, A; Liddle, P

1999-12-01

To identify which improvements in cognitive function are associated with symptom resolution in schizophrenic patients treated with atypical antipsychotics. a prospective open trial with atypical neuroleptics (risperidone, clozapine, quetiapine). Inpatient and outpatient units, Institute of Psychiatry. Thirty-nine patients with schizophrenia according to DSM-IV criteria were included. Clinical and cognitive assessment were done at baseline (T0) and again after six months of treatment (T2). Twenty-five patients completed the trial. New-generation antipsychotics during six months. Patients were considered as responders if their PANSS score decreased at least 20% (n = 15) and non-responders if it did not (n = 10). a computerized cognitive assessment comprised tests of short-term-memory (digit span), explicit long-term memory (word pair learning), divided attention, selective attention and verbal fluency (orthographic and semantic). Clinical assessment included PANSS and ESRS. A discriminant function analysis was performed to determine which changes in cognitive performance predicted symptomatic response status. Semantic fluency and orthographic fluency were significant predictors. Together they correctly predicted responder status in 88% of cases. Memory was not a significant predictor of symptomatic response. Verbal fluency discriminated the responder from the non-responder group during a pharmacological treatment.

Assessment of statistical methods used in library-based approaches to microbial source tracking.

PubMed

Ritter, Kerry J; Carruthers, Ethan; Carson, C Andrew; Ellender, R D; Harwood, Valerie J; Kingsley, Kyle; Nakatsu, Cindy; Sadowsky, Michael; Shear, Brian; West, Brian; Whitlock, John E; Wiggins, Bruce A; Wilbur, Jayson D

2003-12-01

Several commonly used statistical methods for fingerprint identification in microbial source tracking (MST) were examined to assess the effectiveness of pattern-matching algorithms to correctly identify sources. Although numerous statistical methods have been employed for source identification, no widespread consensus exists as to which is most appropriate. A large-scale comparison of several MST methods, using identical fecal sources, presented a unique opportunity to assess the utility of several popular statistical methods. These included discriminant analysis, nearest neighbour analysis, maximum similarity and average similarity, along with several measures of distance or similarity. Threshold criteria for excluding uncertain or poorly matched isolates from final analysis were also examined for their ability to reduce false positives and increase prediction success. Six independent libraries used in the study were constructed from indicator bacteria isolated from fecal materials of humans, seagulls, cows and dogs. Three of these libraries were constructed using the rep-PCR technique and three relied on antibiotic resistance analysis (ARA). Five of the libraries were constructed using Escherichia coli and one using Enterococcus spp. (ARA). Overall, the outcome of this study suggests a high degree of variability across statistical methods. Despite large differences in correct classification rates among the statistical methods, no single statistical approach emerged as superior. Thresholds failed to consistently increase rates of correct classification and improvement was often associated with substantial effective sample size reduction. Recommendations are provided to aid in selecting appropriate analyses for these types of data.

Almost equivalence of combinatorial and distance processes for discrimination in multielement images.

PubMed

Ferraro, M; Foster, D H

1991-01-01

Under certain experimental conditions, visual discrimination performance in multielement images is closely related to visual identification performance: elements of the image are distinguished only insofar as they appear to have distinct, discrete, internal characterizations. This report is concerned with the detailed relationship between such internal characterizations and observable discrimination performance. Two types of general processes that might underline discrimination are considered. The first is based on computing all possible internal image characterizations that could allow a correct decision, each characterization weighted by the probability of its occurrence and of a correct decision being made. The second process is based on computing the difference between the probabilities associated with the internal characterizations of the individual image elements, the difference quantified naturally with an l(p) norm. The relationship between the two processes was investigated analytically and by Monte Carlo simulations over a plausible range of numbers n of the internal characterizations of each of the m elements in the image. The predictions of the two processes were found to be closely similar. The relationship was precisely one-to-one, however, only for n = 2, m = 3, 4, 6, and for n greater than 2, m = 3, 4, p = 2. For all other cases tested, a one-to-one relationship was shown to be impossible.

Individual variability in visual discrimination and reversal learning performance in common marmosets.

PubMed

Takemoto, Atsushi; Miwa, Miki; Koba, Reiko; Yamaguchi, Chieko; Suzuki, Hiromi; Nakamura, Katsuki

2015-04-01

Detailed information about the characteristics of learning behavior in marmosets is useful for future marmoset research. We trained 42 marmosets in visual discrimination and reversal learning. All marmosets could learn visual discrimination, and all but one could complete reversal learning, though some marmosets failed to touch the visual stimuli and were screened out. In 87% of measurements, the final percentage of correct responses was over 95%. We quantified performance with two measures: onset trial and dynamic interval. Onset trial represents the number of trials that elapsed before the marmoset started to learn. Dynamic interval represents the number of trials from the start before reaching the final percentage of correct responses. Both measures decreased drastically as a result of the formation of discrimination learning sets. In reversal learning, both measures worsened, but the effect on onset trial was far greater. The effects of age and sex were not significant as far as we used adolescent or young adult marmosets. Unexpectedly, experimental circumstance (in the colony or isolator) had only a subtle effect on performance. However, we found that marmosets from different families exhibited different learning process characteristics, suggesting some family effect on learning. Copyright © 2014 Elsevier Ireland Ltd and the Japan Neuroscience Society. All rights reserved.

Optimal sequential measurements for bipartite state discrimination

NASA Astrophysics Data System (ADS)

Croke, Sarah; Barnett, Stephen M.; Weir, Graeme

2017-05-01

State discrimination is a useful test problem with which to clarify the power and limitations of different classes of measurement. We consider the problem of discriminating between given states of a bipartite quantum system via sequential measurement of the subsystems, with classical feed-forward of measurement results. Our aim is to understand when sequential measurements, which are relatively easy to implement experimentally, perform as well, or almost as well, as optimal joint measurements, which are in general more technologically challenging. We construct conditions that the optimal sequential measurement must satisfy, analogous to the well-known Helstrom conditions for minimum error discrimination in the unrestricted case. We give several examples and compare the optimal probability of correctly identifying the state via global versus sequential measurement strategies.

Intertrial-interval effects on sensitivity (A') and response bias (B") in a temporal discrimination by rats.

PubMed Central

Raslear, T G; Shurtleff, D; Simmons, L

1992-01-01

Killeen and Fetterman's (1988) behavioral theory of animal timing predicts that decreases in the rate of reinforcement should produce decreases in the sensitivity (A') of temporal discriminations and a decrease in miss and correct rejection rates (decrease in bias toward "long" responses). Eight rats were trained on a 10- versus 0.1-s temporal discrimination with an intertrial interval of 5 s and were subsequently tested on probe days on the same discrimination with intertrial intervals of 1, 2.5, 5, 10, or 20 s. The rate of reinforcement declined for all animals as intertrial interval increased. Although sensitivity (A') decreased with increasing intertrial interval, all rats showed an increase in bias to make long responses. PMID:1447544

Disruption of amygdala-entorhinal-hippocampal network in late-life depression.

PubMed

Leal, Stephanie L; Noche, Jessica A; Murray, Elizabeth A; Yassa, Michael A

2017-04-01

Episodic memory deficits are evident in late-life depression (LLD) and are associated with subtle synaptic and neurochemical changes in the medial temporal lobes (MTL). However, the particular mechanisms by which memory impairment occurs in LLD are currently unknown. We tested older adults with (DS+) and without (DS-) depressive symptoms using high-resolution fMRI that is capable of discerning signals in hippocampal subfields and amygdala nuclei. Scanning was conducted during performance of an emotional discrimination task used previously to examine the relationship between depressive symptoms and amygdala-mediated emotional modulation of hippocampal pattern separation in young adults. We found that hippocampal dentate gyrus (DG)/CA3 activity was reduced during correct discrimination of negative stimuli and increased during correct discrimination of neutral items in DS+ compared to DS- adults. The extent of the latter increase was correlated with symptom severity. Furthermore, DG/CA3 and basolateral amygdala (BLA) activity predicted discrimination performance on negative trials, a relationship that depended on symptom severity. The impact of the BLA on depressive symptom severity was mediated by the DG/CA3 during discrimination of neutral items, and by the lateral entorhinal cortex (LEC) during false recognition of positive items. These results shed light on a novel mechanistic account for amygdala-hippocampal network changes and concurrent alterations in emotional episodic memory in LLD. The BLA-LEC-DG/CA3 network, which comprises a key pathway by which emotion modulates memory, is specifically implicated in LLD. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Superiority of artificial neural networks for a genetic classification procedure.

PubMed

Sant'Anna, I C; Tomaz, R S; Silva, G N; Nascimento, M; Bhering, L L; Cruz, C D

2015-08-19

The correct classification of individuals is extremely important for the preservation of genetic variability and for maximization of yield in breeding programs using phenotypic traits and genetic markers. The Fisher and Anderson discriminant functions are commonly used multivariate statistical techniques for these situations, which allow for the allocation of an initially unknown individual to predefined groups. However, for higher levels of similarity, such as those found in backcrossed populations, these methods have proven to be inefficient. Recently, much research has been devoted to developing a new paradigm of computing known as artificial neural networks (ANNs), which can be used to solve many statistical problems, including classification problems. The aim of this study was to evaluate the feasibility of ANNs as an evaluation technique of genetic diversity by comparing their performance with that of traditional methods. The discriminant functions were equally ineffective in discriminating the populations, with error rates of 23-82%, thereby preventing the correct discrimination of individuals between populations. The ANN was effective in classifying populations with low and high differentiation, such as those derived from a genetic design established from backcrosses, even in cases of low differentiation of the data sets. The ANN appears to be a promising technique to solve classification problems, since the number of individuals classified incorrectly by the ANN was always lower than that of the discriminant functions. We envisage the potential relevant application of this improved procedure in the genomic classification of markers to distinguish between breeds and accessions.

Multivariate pattern analysis reveals subtle brain anomalies relevant to the cognitive phenotype in neurofibromatosis type 1.

PubMed

Duarte, João V; Ribeiro, Maria J; Violante, Inês R; Cunha, Gil; Silva, Eduardo; Castelo-Branco, Miguel

2014-01-01

Neurofibromatosis Type 1 (NF1) is a common genetic condition associated with cognitive dysfunction. However, the pathophysiology of the NF1 cognitive deficits is not well understood. Abnormal brain structure, including increased total brain volume, white matter (WM) and grey matter (GM) abnormalities have been reported in the NF1 brain. These previous studies employed univariate model-driven methods preventing detection of subtle and spatially distributed differences in brain anatomy. Multivariate pattern analysis allows the combination of information from multiple spatial locations yielding a discriminative power beyond that of single voxels. Here we investigated for the first time subtle anomalies in the NF1 brain, using a multivariate data-driven classification approach. We used support vector machines (SVM) to classify whole-brain GM and WM segments of structural T1 -weighted MRI scans from 39 participants with NF1 and 60 non-affected individuals, divided in children/adolescents and adults groups. We also employed voxel-based morphometry (VBM) as a univariate gold standard to study brain structural differences. SVM classifiers correctly classified 94% of cases (sensitivity 92%; specificity 96%) revealing the existence of brain structural anomalies that discriminate NF1 individuals from controls. Accordingly, VBM analysis revealed structural differences in agreement with the SVM weight maps representing the most relevant brain regions for group discrimination. These included the hippocampus, basal ganglia, thalamus, and visual cortex. This multivariate data-driven analysis thus identified subtle anomalies in brain structure in the absence of visible pathology. Our results provide further insight into the neuroanatomical correlates of known features of the cognitive phenotype of NF1. Copyright © 2012 Wiley Periodicals, Inc.

Influence of microclimatic ammonia levels on productive performance of different broilers' breeds estimated with univariate and multivariate approaches.

PubMed

Soliman, Essam S; Moawed, Sherif A; Hassan, Rania A

2017-08-01

Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=-0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.

Influence of microclimatic ammonia levels on productive performance of different broilers’ breeds estimated with univariate and multivariate approaches

PubMed Central

Soliman, Essam S.; Moawed, Sherif A.; Hassan, Rania A.

2017-01-01

Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people’s health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Results: Ammonia levels were significantly higher (p< 0.01) in the Ross compared to the Hubbard breed farm, although no significant differences (p>0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (p< 0.01) during fall compared to winter irrespective of broiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p< 0.01), but not with the ambient temperature (r=−0.045; p>0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. Conclusion: The study revealed that broiler’s growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers’ growth performance parameters data using multivariate discriminant function analysis. PMID:28919677

Patterns of Circulating Inflammatory Biomarkers in Older Persons with Varying Levels of Physical Performance: A Partial Least Squares-Discriminant Analysis Approach

PubMed Central

Marzetti, Emanuele; Landi, Francesco; Marini, Federico; Cesari, Matteo; Buford, Thomas W.; Manini, Todd M.; Onder, Graziano; Pahor, Marco; Bernabei, Roberto; Leeuwenburgh, Christiaan; Calvani, Riccardo

2014-01-01

Background: Chronic, low-grade inflammation and declining physical function are hallmarks of the aging process. However, previous attempts to correlate individual inflammatory biomarkers with physical performance in older people have produced mixed results. Given the complexity of the inflammatory response, the simultaneous analysis of an array of inflammatory mediators may provide more insights into the relationship between inflammation and age-related physical function decline. This study was designed to explore the association between a panel of inflammatory markers and physical performance in older adults through a multivariate statistical approach. Methods: Community-dwelling older persons were categorized into “normal walkers” (NWs; n = 27) or “slow walkers” (SWs; n = 11) groups using 0.8 m s−1 as the 4-m gait speed cutoff. A panel of 14 circulating inflammatory biomarkers was assayed by multiplex analysis. Partial least squares-discriminant analysis (PLS-DA) was used to identify patterns of inflammatory mediators associated with gait speed categories. Results: The optimal complexity of the PLS-DA model was found to be five latent variables. The proportion of correct classification was 88.9% for NW subjects (74.1% in cross-validation) and 90.9% for SW individuals (81.8% in cross-validation). Discriminant biomarkers in the model were interleukin 8, myeloperoxidase, and tumor necrosis factor alpha (all higher in the SW group), and P-selectin, interferon gamma, and granulocyte–macrophage colony-stimulating factor (all higher in the NW group). Conclusion: Distinct profiles of circulating inflammatory biomarkers characterize older subjects with different levels of physical performance. The dissection of these patterns may provide novel insights into the role played by inflammation in the disabling cascade and possible new targets for interventions. PMID:25593902

Ribosomal subunit protein typing using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) for the identification and discrimination of Aspergillus species.

PubMed

Nakamura, Sayaka; Sato, Hiroaki; Tanaka, Reiko; Kusuya, Yoko; Takahashi, Hiroki; Yaguchi, Takashi

2017-04-26

Accurate identification of Aspergillus species is a very important subject. Mass spectral fingerprinting using matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is generally employed for the rapid identification of fungal isolates. However, the results are based on simple mass spectral pattern-matching, with no peak assignment and no taxonomic input. We propose here a ribosomal subunit protein (RSP) typing technique using MALDI-TOF MS for the identification and discrimination of Aspergillus species. The results are concluded to be phylogenetic in that they reflect the molecular evolution of housekeeping RSPs. The amino acid sequences of RSPs of genome-sequenced strains of Aspergillus species were first verified and compared to compile a reliable biomarker list for the identification of Aspergillus species. In this process, we revealed that many amino acid sequences of RSPs (about 10-60%, depending on strain) registered in the public protein databases needed to be corrected or newly added. The verified RSPs were allocated to RSP types based on their mass. Peak assignments of RSPs of each sample strain as observed by MALDI-TOF MS were then performed to set RSP type profiles, which were then further processed by means of cluster analysis. The resulting dendrogram based on RSP types showed a relatively good concordance with the tree based on β-tubulin gene sequences. RSP typing was able to further discriminate the strains belonging to Aspergillus section Fumigati. The RSP typing method could be applied to identify Aspergillus species, even for species within section Fumigati. The discrimination power of RSP typing appears to be comparable to conventional β-tubulin gene analysis. This method would therefore be suitable for species identification and discrimination at the strain to species level. Because RSP typing can characterize the strains within section Fumigati, this method has potential as a powerful and reliable tool in the field of clinical microbiology.

Memory Alteration Test to Detect Amnestic Mild Cognitive Impairment and Early Alzheimer's Dementia in Population with Low Educational Level.

PubMed

Custodio, Nilton; Lira, David; Herrera-Perez, Eder; Montesinos, Rosa; Castro-Suarez, Sheila; Cuenca-Alfaro, José; Valeriano-Lorenzo, Lucía

2017-01-01

Background/Aims : Short tests to early detection of the cognitive impairment are necessary in primary care setting, particularly in populations with low educational level. The aim of this study was to assess the performance of Memory Alteration Test (M@T) to discriminate controls, patients with amnestic Mild Cognitive Impairment (aMCI) and patients with early Alzheimer's Dementia (AD) in a sample of individuals with low level of education. Methods : Cross-sectional study to assess the performance of the M@T (study test), compared to the neuropsychological evaluation (gold standard test) scores in 247 elderly subjects with low education level from Lima-Peru. The cognitive evaluation included three sequential stages: (1) screening (to detect cases with cognitive impairment); (2) nosological diagnosis (to determinate specific disease); and (3) classification (to differentiate disease subtypes). The subjects with negative results for all stages were considered as cognitively normal (controls). The test performance was assessed by means of area under the receiver operating characteristic (ROC) curve. We calculated validity measures (sensitivity, specificity and correctly classified percentage), the internal consistency (Cronbach's alpha coefficient), and concurrent validity (Pearson's ratio coefficient between the M@T and Clinical Dementia Rating (CDR) scores). Results : The Cronbach's alpha coefficient was 0.79 and Pearson's ratio coefficient was 0.79 ( p < 0.01). The AUC of M@T to discriminate between early AD and aMCI was 99.60% (sensitivity = 100.00%, specificity = 97.53% and correctly classified = 98.41%) and to discriminate between aMCI and controls was 99.56% (sensitivity = 99.17%, specificity = 91.11%, and correctly classified = 96.99%). Conclusions : The M@T is a short test with a good performance to discriminate controls, aMCI and early AD in individuals with low level of education from urban settings.

Multivariate analysis of sexual size dimorphism in local turkeys (Meleagris gallopavo) in Nigeria.

PubMed

Ajayi, Oyeyemi O; Yakubu, Abdulmojeed; Jayeola, Oluwaseun O; Imumorin, Ikhide G; Takeet, Michael I; Ozoje, Michael O; Ikeobi, Christian O N; Peters, Sunday O

2012-06-01

Sexual size dimorphism is a key evolutionary feature that can lead to important biological insights. To improve methods of sexing live birds in the field, we assessed sexual size dimorphism in Nigerian local turkeys (Meleagris gallopavo) using multivariate techniques. Measurements were taken on 125 twenty-week-old birds reared under the intensive management system. The body parameters measured were body weight, body length, breast girth, thigh length, shank length, keel length, wing length and wing span. Univariate analysis revealed that toms (males) had significantly (P < 0.05) higher mean values than hens (females) in all the measured traits. Positive phenotypic correlations between body weight and body measurements ranged from 0.445 to 0.821 in toms and 0.053-0.660 in hens, respectively. Three principal components (PC1, PC2 and PC3) were extracted in toms, each accounting for 63.70%, 19.42% and 5.72% of the total variance, respectively. However, four principal components (PC1, PC2, PC3 and PC4) were extracted in hens, which explained 54.03%, 15.29%, 11.68% and 6.95%, respectively of the generalised variance. A stepwise discriminant function analysis of the eight morphological traits indicated that body weight, body length, tail length and wing span were the most discriminating variables in separating the sexes. The single discriminant function obtained was able to correctly classify 100% of the birds into their source population. The results obtained from the present study could aid future management decisions, ecological studies and conservation of local turkeys in a developing economy.

On the analysis of EEG power, frequency and asymmetry in Parkinson's disease during emotion processing.

PubMed

Yuvaraj, Rajamanickam; Murugappan, Murugappan; Mohamed Ibrahim, Norlinah; Iqbal, Mohd; Sundaraj, Kenneth; Mohamad, Khairiyah; Palaniappan, Ramaswamy; Mesquita, Edgar; Satiyan, Marimuthu

2014-04-09

While Parkinson's disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing. EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli. Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli. These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients.

Detection of Airway Colonization by Aspergillus fumigatus by Use of Electronic Nose Technology in Patients with Cystic Fibrosis.

PubMed

de Heer, K; Kok, M G M; Fens, N; Weersink, E J M; Zwinderman, A H; van der Schee, M P C; Visser, C E; van Oers, M H J; Sterk, P J

2016-03-01

Currently, there is no noninvasive test that can reliably diagnose early invasive pulmonary aspergillosis (IA). An electronic nose (eNose) can discriminate various lung diseases through an analysis of exhaled volatile organic compounds. We recently published a proof-of-principle study showing that patients with prolonged chemotherapy-induced neutropenia and IA have a distinct exhaled breath profile (or breathprint) that can be discriminated with an eNose. An eNose is cheap and noninvasive, and it yields results within minutes. We determined whether Aspergillus fumigatus colonization may also be detected with an eNose in cystic fibrosis (CF) patients. Exhaled breath samples of 27 CF patients were analyzed with a Cyranose 320. Culture of sputum samples defined the A. fumigatus colonization status. eNose data were classified using canonical discriminant analysis after principal component reduction. Our primary outcome was cross-validated accuracy, defined as the percentage of correctly classified subjects using the leave-one-out method. The P value was calculated by the generation of 100,000 random alternative classifications. Nine of the 27 subjects were colonized by A. fumigatus. In total, 3 subjects were misclassified, resulting in a cross-validated accuracy of the Cyranose detecting IA of 89% (P = 0.004; sensitivity, 78%; specificity, 94%). Receiver operating characteristic (ROC) curve analysis showed an area under the curve (AUC) of 0.89. The results indicate that A. fumigatus colonization leads to a distinctive breathprint in CF patients. The present proof-of-concept data merit external validation and monitoring studies. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Four Theorems on the Psychometric Function

PubMed Central

May, Keith A.; Solomon, Joshua A.

2013-01-01

In a 2-alternative forced-choice (2AFC) discrimination task, observers choose which of two stimuli has the higher value. The psychometric function for this task gives the probability of a correct response for a given stimulus difference, . This paper proves four theorems about the psychometric function. Assuming the observer applies a transducer and adds noise, Theorem 1 derives a convenient general expression for the psychometric function. Discrimination data are often fitted with a Weibull function. Theorem 2 proves that the Weibull “slope” parameter, , can be approximated by , where is the of the Weibull function that fits best to the cumulative noise distribution, and depends on the transducer. We derive general expressions for and , from which we derive expressions for specific cases. One case that follows naturally from our general analysis is Pelli's finding that, when , . We also consider two limiting cases. Theorem 3 proves that, as sensitivity improves, 2AFC performance will usually approach that for a linear transducer, whatever the actual transducer; we show that this does not apply at signal levels where the transducer gradient is zero, which explains why it does not apply to contrast detection. Theorem 4 proves that, when the exponent of a power-function transducer approaches zero, 2AFC performance approaches that of a logarithmic transducer. We show that the power-function exponents of 0.4–0.5 fitted to suprathreshold contrast discrimination data are close enough to zero for the fitted psychometric function to be practically indistinguishable from that of a log transducer. Finally, Weibull reflects the shape of the noise distribution, and we used our results to assess the recent claim that internal noise has higher kurtosis than a Gaussian. Our analysis of for contrast discrimination suggests that, if internal noise is stimulus-independent, it has lower kurtosis than a Gaussian. PMID:24124456

Assessing size and strength of the clavicle for its usefulness for sex estimation in a British medieval sample.

PubMed

Atterton, Thomas; De Groote, Isabelle; Eliopoulos, Constantine

2016-10-01

The construction of the biological profile from human skeletal remains is the foundation of anthropological examination. However, remains may be fragmentary and the elements usually employed, such as the pelvis and skull, are not available. The clavicle has been successfully used for sex estimation in samples from Iran and Greece. In the present study, the aim was to test the suitability of the measurements used in those previous studies on a British Medieval population. In addition, the project tested whether discrimination between sexes was due to size or clavicular strength. The sample consisted of 23 females and 25 males of pre-determined sex from two medieval collections: Poulton and Gloucester. Six measurements were taken using an osteometric board, sliding calipers and graduated tape. In addition, putty rings and bi-planar radiographs were made and robusticity measures calculated. The resulting variables were used in stepwise discriminant analyses. The linear measurements allowed correct sex classification in 89.6% of all individuals. This demonstrates the applicability of the clavicle for sex estimation in British populations. The most powerful discriminant factor was maximum clavicular length and the best combination of factors was maximum clavicular length and circumference. This result is similar to that obtained by other studies. To further investigate the extent of sexual dimorphism of the clavicle, the biomechanical properties of the polar second moment of area J and the ratio of maximum to minimum bending rigidity are included in the analysis. These were found to have little influence when entered into the discriminant function analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

Gain Shift Corrections at Chi-Nu

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brown, Tristan Brooks; Devlin, Matthew James

Ambient conditions have the potential to cause changes in liquid scintillator detector gain that vary with time and temperature. These gain shifts can lead to poor resolution in both energy as well as pulse shape discrimination. In order to correct for these shifts in the Chi-Nu high energy array, a laser system has been developed for calibration of the pulse height signals.

Age group estimation in free-ranging African elephants based on acoustic cues of low-frequency rumbles

PubMed Central

Stoeger, Angela S.; Zeppelzauer, Matthias; Baotic, Anton

2015-01-01

Animal vocal signals are increasingly used to monitor wildlife populations and to obtain estimates of species occurrence and abundance. In the future, acoustic monitoring should function not only to detect animals, but also to extract detailed information about populations by discriminating sexes, age groups, social or kin groups, and potentially individuals. Here we show that it is possible to estimate age groups of African elephants (Loxodonta africana) based on acoustic parameters extracted from rumbles recorded under field conditions in a National Park in South Africa. Statistical models reached up to 70 % correct classification to four age groups (infants, calves, juveniles, adults) and 95 % correct classification when categorising into two groups (infants/calves lumped into one group versus adults). The models revealed that parameters representing absolute frequency values have the most discriminative power. Comparable classification results were obtained by fully automated classification of rumbles by high-dimensional features that represent the entire spectral envelope, such as MFCC (75 % correct classification) and GFCC (74 % correct classification). The reported results and methods provide the scientific foundation for a future system that could potentially automatically estimate the demography of an acoustically monitored elephant group or population. PMID:25821348

Feasibility of use of fatty acid and triacylglycerol profiles for the authentication of commercial labelling in Iberian dry-cured sausages.

PubMed

Horcada, Alberto; Fernández-Cabanás, Víctor M; Polvillo, Oliva; Botella, Baltasar; Cubiles, M Dolores; Pino, Rafael; Narváez-Rivas, Mónica; León-Camacho, Manuel; Acuña, Rafael Rodríguez

2013-12-15

In the present study, fatty acid and triacylglycerol profiles were used to evaluate the possibility of authenticating Iberian dry-cured sausages according to their label specifications. 42 Commercial brand 'chorizo' and 39 commercial brand 'salchichón' sausages from Iberian pigs were purchased. 36 Samples were labelled Bellota and 45 bore the generic Ibérico label. In the market, Bellota is considered to be a better class than the generic Ibérico since products with the Bellota label are manufactured with high quality fat obtained from extensively reared pigs fed on acorns and pasture. Analyses of fatty acids and triacylglycerols were carried out by gas chromatography and a flame ion detector. A CP-SIL 88 column (highly substituted cyanopropyl phase; 50 m × 0.25 mm i.d., 0.2 µm film thickness) (Varian, Palo Alto, USA) was used for fatty acid analysis and a fused silica capillary DB-17HT column (50% phenyl-50% methylpolysiloxane; 30 m × 0.25 mm i.d., 0.15 µm film thickness) was used for triacylglycerols. Twelve fatty acids and 16 triacylglycerols were identified. Various discriminant models (linear quadratic discriminant analyses, logistic regression and support vector machines) were trained to predict the sample class (Bellota or Ibérico). These models included fatty acids and triacylglycerols separately and combined fatty acid and triacylglycerol profiles. The number of correctly classified samples according to discriminant analyses can be considered low (lower than 65%). The greatest discriminant rate was obtained when triacylglycerol profiles were included in the model, whilst using a combination of fatty acid and triacylglycerol profiles did not improve the rate of correct assignation. The values that represent the reliability of prediction of the samples according to the label specification were higher for the Ibérico class than for the Bellota class. In fact, quadratic and Support Vector Machine discriminate analyses were not able to assign the Bellota class (0%) when combined fatty acids and triacylglycerols were included in the model. The use of fatty acid and triacylglycerol profiles to discriminate Iberian dry-cured sausages in the market according to their labelling information is unclear. In order to ensure the genuineness of Iberian dry-cured sausages in the market, identification of fatty acid and triacylglycerol profiles should be combined with the application of quality standard traceability techniques. © 2013 Published by Elsevier B.V.

Two-Point Orientation Discrimination Versus the Traditional Two-Point Test for Tactile Spatial Acuity Assessment

PubMed Central

Tong, Jonathan; Mao, Oliver; Goldreich, Daniel

2013-01-01

Two-point discrimination is widely used to measure tactile spatial acuity. The validity of the two-point threshold as a spatial acuity measure rests on the assumption that two points can be distinguished from one only when the two points are sufficiently separated to evoke spatially distinguishable foci of neural activity. However, some previous research has challenged this view, suggesting instead that two-point task performance benefits from an unintended non-spatial cue, allowing spuriously good performance at small tip separations. We compared the traditional two-point task to an equally convenient alternative task in which participants attempt to discern the orientation (vertical or horizontal) of two points of contact. We used precision digital readout calipers to administer two-interval forced-choice versions of both tasks to 24 neurologically healthy adults, on the fingertip, finger base, palm, and forearm. We used Bayesian adaptive testing to estimate the participants’ psychometric functions on the two tasks. Traditional two-point performance remained significantly above chance levels even at zero point separation. In contrast, two-point orientation discrimination approached chance as point separation approached zero, as expected for a valid measure of tactile spatial acuity. Traditional two-point performance was so inflated at small point separations that 75%-correct thresholds could be determined on all tested sites for fewer than half of participants. The 95%-correct thresholds on the two tasks were similar, and correlated with receptive field spacing. In keeping with previous critiques, we conclude that the traditional two-point task provides an unintended non-spatial cue, resulting in spuriously good performance at small spatial separations. Unlike two-point discrimination, two-point orientation discrimination rigorously measures tactile spatial acuity. We recommend the use of two-point orientation discrimination for neurological assessment. PMID:24062677

Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling.

PubMed

Park, Irene J K; Wang, Lijuan; Williams, David R; Alegría, Margarita

2017-02-01

[Correction Notice: An Erratum for this article was reported in Vol 53(2) of Developmental Psychology (see record 2017-04475-001). In the article, there were several typographical errors in the Recruitment and Procedures section. The percentage of mothers who responded to survey items should have been 99.3%. Additionally, the youths surveyed at T2 and T3 should have been n 246. Accordingly, the percentage of youths surveyed in T2 and T3 should have been 91.4% and the percentage of mothers surveyed at T2 and T3 should have been 90.7%. Finally, the youths missing at T2 should have been n 23, and therefore the attrition rate for youth participants should have been 8.6. All versions of this article have been corrected.] Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin adolescents ( M age = 14.1 years, SD = 1.6; 57% girls), 12 to 17 years old. Three competing anger regulation variables were tested as potential mediators: outward anger expression, anger suppression, and anger control. Longitudinal mediation analyses were conducted using multilevel modeling that disaggregated within-person effects from between-person effects. Results indicated that outward anger expression was a significant mediator; anger suppression and anger control were not significant mediators. Within a given individual, greater racial/ethnic discrimination was associated with more frequent outward anger expression. In turn, more frequent outward anger expression was associated with higher levels of anxiety and depression at a given time point. Gender, age, and nativity status were not significant moderators of the hypothesized mediation models. By identifying outward anger expression as an explanatory mechanism in the discrimination-distress link among Latino youths, this study points to a malleable target for prevention and intervention efforts aimed at mitigating the detrimental impact of racism on Latino youths' mental health during the developmentally critical period of adolescence. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Open Microphone Speech Understanding: Correct Discrimination Of In Domain Speech

NASA Technical Reports Server (NTRS)

Hieronymus, James; Aist, Greg; Dowding, John

2006-01-01

An ideal spoken dialogue system listens continually and determines which utterances were spoken to it, understands them and responds appropriately while ignoring the rest This paper outlines a simple method for achieving this goal which involves trading a slightly higher false rejection rate of in domain utterances for a higher correct rejection rate of Out of Domain (OOD) utterances. The system recognizes semantic entities specified by a unification grammar which is specialized by Explanation Based Learning (EBL). so that it only uses rules which are seen in the training data. The resulting grammar has probabilities assigned to each construct so that overgeneralizations are not a problem. The resulting system only recognizes utterances which reduce to a valid logical form which has meaning for the system and rejects the rest. A class N-gram grammar has been trained on the same training data. This system gives good recognition performance and offers good Out of Domain discrimination when combined with the semantic analysis. The resulting systems were tested on a Space Station Robot Dialogue Speech Database and a subset of the OGI conversational speech database. Both systems run in real time on a PC laptop and the present performance allows continuous listening with an acceptably low false acceptance rate. This type of open microphone system has been used in the Clarissa procedure reading and navigation spoken dialogue system which is being tested on the International Space Station.

Neuroimaging evidence for a role of neural social stress processing in ethnic minority-associated environmental risk.

PubMed

Akdeniz, Ceren; Tost, Heike; Streit, Fabian; Haddad, Leila; Wüst, Stefan; Schäfer, Axel; Schneider, Michael; Rietschel, Marcella; Kirsch, Peter; Meyer-Lindenberg, Andreas

2014-06-01

Relative risk for the brain disorder schizophrenia is more than doubled in ethnic minorities, an effect that is evident across countries and linked to socially relevant cues such as skin color, making ethnic minority status a well-established social environmental risk factor. Pathoepidemiological models propose a role for chronic social stress and perceived discrimination for mental health risk in ethnic minorities, but the neurobiology is unexplored. To study neural social stress processing, using functional magnetic resonance imaging, and associations with perceived discrimination in ethnic minority individuals. Cross-sectional design in a university setting using 3 validated paradigms to challenge neural social stress processing and, to probe for specificity, emotional and cognitive brain functions. Healthy participants included those with German lineage (n = 40) and those of ethnic minority (n = 40) from different ethnic backgrounds matched for sociodemographic, psychological, and task performance characteristics. Control comparisons examined stress processing with matched ethnic background of investigators (23 Turkish vs 23 German participants) and basic emotional and cognitive tasks (24 Turkish vs 24 German participants). Blood oxygenation level-dependent response, functional connectivity, and psychological and physiological measures. There were significant increases in heart rate (P < .001), subjective emotional response (self-related emotions, P < .001; subjective anxiety, P = .006), and salivary cortisol level (P = .004) during functional magnetic resonance imaging stress induction. Ethnic minority individuals had significantly higher perceived chronic stress levels (P = .02) as well as increased activation (family-wise error-corrected [FWE] P = .005, region of interest corrected) and increased functional connectivity (PFWE = .01, region of interest corrected) of perigenual anterior cingulate cortex (ACC). The effects were specific to stress and not explained by a social distance effect. Ethnic minority individuals had significant correlations between perceived group discrimination and activation in perigenual ACC (PFWE = .001, region of interest corrected) and ventral striatum (PFWE = .02, whole brain corrected) and mediation of the relationship between perceived discrimination and perigenual ACC-dorsal ACC connectivity by chronic stress (P < .05). Epidemiologists proposed a causal role of social-evaluative stress, but the neural processes that could mediate this susceptibility effect were unknown. Our data demonstrate the potential of investigating associations from epidemiology with neuroimaging, suggest brain effects of social marginalization, and highlight a neural system in which environmental and genetic risk factors for mental illness may converge.

Discrimination of herbicide-resistant kochia with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Nugent, Paul W.; Shaw, Joseph A.; Jha, Prashant; Scherrer, Bryan; Donelick, Andrew; Kumar, Vipan

2018-01-01

A hyperspectral imager was used to differentiate herbicide-resistant versus herbicide-susceptible biotypes of the agronomic weed kochia, in different crops in the field at the Southern Agricultural Research Center in Huntley, Montana. Controlled greenhouse experiments showed that enough information was captured by the imager to classify plants as either a crop, herbicide-susceptible or herbicide-resistant kochia. The current analysis is developing an algorithm that will work in more uncontrolled outdoor situations. In overcast conditions, the algorithm correctly identified dicamba-resistant kochia, glyphosate-resistant kochia, and glyphosate- and dicamba-susceptible kochia with 67%, 76%, and 80% success rates, respectively.

Testing Event Discrimination over Broad Regions using the Historical Borovoye Observatory Explosion Dataset

NASA Astrophysics Data System (ADS)

Pasyanos, Michael E.; Ford, Sean R.; Walter, William R.

2014-03-01

We test the performance of high-frequency regional P/S discriminants to differentiate between earthquakes and explosions at test sites and over broad regions using a historical dataset of explosions recorded at the Borovoye Observatory in Kazakhstan. We compare these explosions to modern recordings of earthquakes at the same location. We then evaluate the separation of the two types of events using the raw measurements and those where the amplitudes are corrected for 1-D and 2-D attenuation structure. We find that high-frequency P/S amplitudes can reliably identify earthquakes and explosions, and that the discriminant is applicable over broad regions as long as propagation effects are properly accounted for. Lateral attenuation corrections provide the largest improvement in the 2-4 Hz band, the use of which may successfully enable the identification of smaller, distant events that have lower signal-to-noise at higher frequencies. We also find variations in P/S ratios among the three main nuclear testing locations within the Semipalatinsk Test Site which, due to their nearly identical paths to BRVK, must be a function of differing geology and emplacement conditions.

Application of inorganic element ratios to chemometrics for determination of the geographic origin of welsh onions.

PubMed

Ariyama, Kaoru; Horita, Hiroshi; Yasui, Akemi

2004-09-22

The composition of concentration ratios of 19 inorganic elements to Mg (hereinafter referred to as 19-element/Mg composition) was applied to chemometric techniques to determine the geographic origin (Japan or China) of Welsh onions (Allium fistulosum L.). Using a composition of element ratios has the advantage of simplified sample preparation, and it was possible to determine the geographic origin of a Welsh onion within 2 days. The classical technique based on 20 element concentrations was also used along with the new simpler one based on 19 elements/Mg in order to validate the new technique. Twenty elements, Na, P, K, Ca, Mg, Mn, Fe, Cu, Zn, Sr, Ba, Co, Ni, Rb, Mo, Cd, Cs, La, Ce, and Tl, in 244 Welsh onion samples were analyzed by flame atomic absorption spectroscopy, inductively coupled plasma atomic emission spectrometry, and inductively coupled plasma mass spectrometry. Linear discriminant analysis (LDA) on 20-element concentrations and 19-element/Mg composition was applied to these analytical data, and soft independent modeling of class analogy (SIMCA) on 19-element/Mg composition was applied to these analytical data. The results showed that techniques based on 19-element/Mg composition were effective. LDA, based on 19-element/Mg composition for classification of samples from Japan and from Shandong, Shanghai, and Fujian in China, classified 101 samples used for modeling 97% correctly and predicted another 119 samples excluding 24 nonauthentic samples 93% correctly. In discriminations by 10 times of SIMCA based on 19-element/Mg composition modeled using 101 samples, 220 samples from known production areas including samples used for modeling and excluding 24 nonauthentic samples were predicted 92% correctly.

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

PubMed Central

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Investigating the Predictive Value of Functional MRI to Appetitive and Aversive Stimuli: A Pattern Classification Approach

PubMed Central

McCabe, Ciara; Rocha-Rego, Vanessa

2016-01-01

Background Dysfunctional neural responses to appetitive and aversive stimuli have been investigated as possible biomarkers for psychiatric disorders. However it is not clear to what degree these are separate processes across the brain or in fact overlapping systems. To help clarify this issue we used Gaussian process classifier (GPC) analysis to examine appetitive and aversive processing in the brain. Method 25 healthy controls underwent functional MRI whilst seeing pictures and receiving tastes of pleasant and unpleasant food. We applied GPCs to discriminate between the appetitive and aversive sights and tastes using functional activity patterns. Results The diagnostic accuracy of the GPC for the accuracy to discriminate appetitive taste from neutral condition was 86.5% (specificity = 81%, sensitivity = 92%, p = 0.001). If a participant experienced neutral taste stimuli the probability of correct classification was 92. The accuracy to discriminate aversive from neutral taste stimuli was 82.5% (specificity = 73%, sensitivity = 92%, p = 0.001) and appetitive from aversive taste stimuli was 73% (specificity = 77%, sensitivity = 69%, p = 0.001). In the sight modality, the accuracy to discriminate appetitive from neutral condition was 88.5% (specificity = 85%, sensitivity = 92%, p = 0.001), to discriminate aversive from neutral sight stimuli was 92% (specificity = 92%, sensitivity = 92%, p = 0.001), and to discriminate aversive from appetitive sight stimuli was 63.5% (specificity = 73%, sensitivity = 54%, p = 0.009). Conclusions Our results demonstrate the predictive value of neurofunctional data in discriminating emotional and neutral networks of activity in the healthy human brain. It would be of interest to use pattern recognition techniques and fMRI to examine network dysfunction in the processing of appetitive, aversive and neutral stimuli in psychiatric disorders. Especially where problems with reward and punishment processing have been implicated in the pathophysiology of the disorder. PMID:27870866

Visible and near infrared spectroscopy as an authentication tool: Preliminary investigation of the prediction of the ageing time of beef steaks.

PubMed

Moran, Lara; Andres, Sonia; Allen, Paul; Moloney, Aidan P

2018-08-01

Visible-near infrared spectroscopy (Vis-NIRS) has been suggested to have potential for authentication of food products. The aim of the present preliminary study was to assess if this technology can be used to authenticate the ageing time (3, 7, 14 and 21 days post mortem) of beef steaks from three different muscles (M. Longissimus thoracis, M. Gluteus medius and M. Semitendinosus). Various mathematical pre-treatments were applied to the spectra to correct scattering and overlapping effects, and then partial least squares-discrimination analysis (PLS-DA) procedures applied. The best models were specific for each muscle, and the ability of prediction of ageing time was validated using full (leave-one-out) cross-validation, whereas authentication performance was evaluated using the parameters of sensitivity, specificity and overall correct classification. The results indicate that overall correct classification ranging from 94.2 to 100% was achieved, depending on the muscle. In conclusion, Vis-NIRS technology seems a valid tool for the authentication of ageing time of beef steaks. Copyright © 2018 Elsevier Ltd. All rights reserved.

Treatment in Borderline Class III Malocclusion: Orthodontic Camouflage (Extraction) Versus Orthognathic Surgery.

PubMed

Rabie, A-Bakr M; Wong, Ricky W K; Min, G U

2008-01-01

To investigate the differences in morphological characteristics of borderline class III patients who had undergone camouflage orthodontic treatment or orthognathic surgery, and to compare the treatment effects between these two modalities. Cephalograms of 25 patients (13 orthodontic, 12 surgical) with class III malocclusion were analyzed. All had a pretreatment ANB angle greater than -5 masculine. Using discriminant analysis, only Holdaway angle was selected to differentiate patients in the pretreatment stage. Seventy-two per cent patients were correctly classified. In the orthodontic group, reverse overjet was corrected by retraction of the lower incisors and downward and backward rotation of the mandible. The surgical group was corrected by setback of the lower anterior dentoalveolus and uprighting of the lower incisors. No difference was found in posttreatment soft tissue measurements between the two groups. Twelve degree for the Holdaway angle can be a guideline in determining the treatment modalities for borderline class III patients, but the preferences of operators and patients are also important. (2) Both therapeutic options should highlight changes in the lower dentoalveolus and lower incisors. (3) Both treatment modalities can achieve satisfactory improvements to the people.

Heuristics to Facilitate Understanding of Discriminant Analysis.

ERIC Educational Resources Information Center

Van Epps, Pamela D.

This paper discusses the principles underlying discriminant analysis and constructs a simulated data set to illustrate its methods. Discriminant analysis is a multivariate technique for identifying the best combination of variables to maximally discriminate between groups. Discriminant functions are established on existing groups and used to…

Statistical classification approach to discrimination between weak earthquakes and quarry blasts recorded by the Israel Seismic Network

NASA Astrophysics Data System (ADS)

Kushnir, A. F.; Troitsky, E. V.; Haikin, L. M.; Dainty, A.

1999-06-01

A semi-automatic procedure has been developed to achieve statistically optimum discrimination between earthquakes and explosions at local or regional distances based on a learning set specific to a given region. The method is used for step-by-step testing of candidate discrimination features to find the optimum (combination) subset of features, with the decision taken on a rigorous statistical basis. Linear (LDF) and Quadratic (QDF) Discriminant Functions based on Gaussian distributions of the discrimination features are implemented and statistically grounded; the features may be transformed by the Box-Cox transformation z=(1/ α)( yα-1) to make them more Gaussian. Tests of the method were successfully conducted on seismograms from the Israel Seismic Network using features consisting of spectral ratios between and within phases. Results showed that the QDF was more effective than the LDF and required five features out of 18 candidates for the optimum set. It was found that discrimination improved with increasing distance within the local range, and that eliminating transformation of the features and failing to correct for noise led to degradation of discrimination.

The effects of verbal descriptions on performance in lineups and showups.

PubMed

Wilson, Brent M; Seale-Carlisle, Travis M; Mickes, Laura

2018-01-01

Verbally describing a face has been found to impair subsequent recognition of that face from a photo lineup, a phenomenon known as the verbal overshadowing effect (Schooler & Engstler-Schooler, 1990). Recently, a large direct replication study successfully reproduced that original finding (Alogna et al., 2014). However, in both the original study and the replication studies, memory was tested using only target-present lineups (i.e., lineups containing the previously seen target face), making it possible to compute the correct identification rate (correct ID rate; i.e., the hit rate) but not the false identification rate (false ID rate; i.e., the false alarm rate). Thus, the lower correct ID rate for the verbal condition could reflect either reduced discriminability or a conservative criterion shift relative to the control condition. In four verbal overshadowing experiments reported here, we measured both correct ID rates and false ID rates using photo lineups (Experiments 1 and 2) or single-photo showups (Experiments 3 and 4). The experimental manipulation (verbally describing the face or not) occurred either immediately after encoding (Experiments 1 and 3) or 20-min after encoding (Experiments 2 and 4). In the immediate condition, discriminability did not differ between groups, but in the delayed condition, discriminability was lower in the verbal description group (i.e., a verbal overshadowing effect was observed). A fifth experiment found that the effect of the immediate-versus-delayed manipulation may be attributable to a change in the content of verbal descriptions, with the ratio of diagnostic to generic facial features in the descriptions decreasing as delay increases. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Tools based on multivariate statistical analysis for classification of soil and groundwater in Apulian agricultural sites.

PubMed

Ielpo, Pierina; Leardi, Riccardo; Pappagallo, Giuseppe; Uricchio, Vito Felice

2017-06-01

In this paper, the results obtained from multivariate statistical techniques such as PCA (Principal component analysis) and LDA (Linear discriminant analysis) applied to a wide soil data set are presented. The results have been compared with those obtained on a groundwater data set, whose samples were collected together with soil ones, within the project "Improvement of the Regional Agro-meteorological Monitoring Network (2004-2007)". LDA, applied to soil data, has allowed to distinguish the geographical origin of the sample from either one of the two macroaeras: Bari and Foggia provinces vs Brindisi, Lecce e Taranto provinces, with a percentage of correct prediction in cross validation of 87%. In the case of the groundwater data set, the best classification was obtained when the samples were grouped into three macroareas: Foggia province, Bari province and Brindisi, Lecce and Taranto provinces, by reaching a percentage of correct predictions in cross validation of 84%. The obtained information can be very useful in supporting soil and water resource management, such as the reduction of water consumption and the reduction of energy and chemical (nutrients and pesticides) inputs in agriculture.

Classification of different types of beer according to their colour characteristics

NASA Astrophysics Data System (ADS)

Nikolova, Kr T.; Gabrova, R.; Boyadzhiev, D.; Pisanova, E. S.; Ruseva, J.; Yanakiev, D.

2017-01-01

Twenty-two samples from different beers have been investigated in two colour systems - XYZ and SIELab - and have been characterised according to their colour parameters. The goals of the current study were to conduct correlation and discriminant analysis and to find the inner relation between the studied indices. K-means cluster has been used to compare and group the tested types of beer based on their similarity. To apply the K-Cluster analysis it is required that the number of clusters be determined in advance. The variant K = 4 was worked out. The first cluster unified all bright beers, the second one contained samples with fruits, the third one contained samples with addition of lemon, the fourth unified the samples of dark beers. By applying the discriminant analysis it is possible to help selections in the establishment of the type of beer. The proposed model correctly describes the types of beer on the Bulgarian market and it can be used for determining the affiliation of the beer which is not used in obtained model. One sample has been chosen from each cluster and the digital image has been obtained. It confirms the color parameters in the color system XYZ and SIELab. These facts can be used for elaboration for express estimation of beer by color.

Identification of Pulmonary Edema in Forensic Autopsy Cases of Sudden Cardiac Death Using Fourier Transform Infrared Microspectroscopy: A Pilot Study.

PubMed

Lin, Hancheng; Luo, Yiwen; Sun, Qiran; Zhang, Ji; Tuo, Ya; Zhang, Zhong; Wang, Lei; Deng, Kaifei; Chen, Yijiu; Huang, Ping; Wang, Zhenyuan

2018-02-20

Many studies have proven the usefulness of biofluid-based infrared spectroscopy in the clinical domain for diagnosis and monitoring the progression of diseases. Here we present a state-of-the-art study in the forensic field that employed Fourier transform infrared microspectroscopy for postmortem diagnosis of sudden cardiac death (SCD) by in situ biochemical investigation of alveolar edema fluid in lung tissue sections. The results of amide-related spectral absorbance analysis demonstrated that the pulmonary edema fluid of the SCD group was richer in protein components than that of the neurologic catastrophe (NC) and lethal multiple injuries (LMI) groups. The complementary results of unsupervised principle component analysis (PCA) and genetic algorithm-guided partial least-squares discriminant analysis (GA-PLS-DA) further indicated different global spectral band patterns of pulmonary edema fluids between these three groups. Ultimately, a random forest (RF) classification model for postmortem diagnosis of SCD was built and achieved good sensitivity and specificity scores of 97.3% and 95.5%, respectively. Classification predictions of unknown pulmonary edema fluid collected from 16 cases were also performed by the model, resulting in 100% correct discrimination. This pilot study demonstrates that FTIR microspectroscopy in combination with chemometrics has the potential to be an effective aid for postmortem diagnosis of SCD.

Rejection of randomly coinciding events in ZnMoO scintillating bolometers

NASA Astrophysics Data System (ADS)

Chernyak, D. M.; Danevich, F. A.; Giuliani, A.; Mancuso, M.; Nones, C.; Olivieri, E.; Tenconi, M.; Tretyak, V. I.

2014-06-01

Random coincidence of events (particularly from two neutrino double beta decay) could be one of the main sources of background in the search for neutrinoless double beta decay with cryogenic bolometers due to their poor time resolution. Pulse-shape discrimination by using front edge analysis, mean-time and methods were applied to discriminate randomly coinciding events in ZnMoO cryogenic scintillating bolometers. These events can be effectively rejected at the level of 99 % by the analysis of the heat signals with rise-time of about 14 ms and signal-to-noise ratio of 900, and at the level of 92 % by the analysis of the light signals with rise-time of about 3 ms and signal-to-noise ratio of 30, under the requirement to detect 95 % of single events. These rejection efficiencies are compatible with extremely low background levels in the region of interest of neutrinoless double beta decay of Mo for enriched ZnMoO detectors, of the order of counts/(y keV kg). Pulse-shape parameters have been chosen on the basis of the performance of a real massive ZnMoO scintillating bolometer. Importance of the signal-to-noise ratio, correct finding of the signal start and choice of an appropriate sampling frequency are discussed.

Topographic context of glaciers and perennial snowfields, Glacier National Park, Montana

NASA Astrophysics Data System (ADS)

Allen, Thomas R.

1998-01-01

Equilibrium-line altitudes (ELAs) of modem glaciers in the northern Rocky Mountains are known to correspond with regional climate, but strong subregional gradients such as across the Continental Divide in Glacier National Park, Montana, also exert topoclimatic influences on the ELA. This study analyzed the relationships between glacier and snowfield morphology, ELA, and surrounding topography. Glaciers and perennial snowfields were mapped using multitemporal satellite data from the Landsat Thematic Mapper and aerial photography within an integrated Geographic Information System (GIS). Relationships between glacier morphology and ELA were investigated using discriminant analysis. Four morphological categories of perennial snow and ice patches were identified: cirque glacier, niche glacier, ice cap, and snowfield. ELA was derived from overlaid glacier boundaries and Digital Elevation Models (DEMs) within the GIs. DEMs provided topographic variables and models of solar radiation and wind exposure/shelteredness. Regression analysis showed the effects of exposure; on snow accumulation, the strong influence of local topography through upslope zone morphology such as cirque backwalls, and the tendency for glaciers with high ELAs to exhibit compactness in morphology. Results highlight the relatively compact shape and larger area of glaciers adjacent to the Continental Divide. Discriminant analysis correctly predicted the type of glacier morphology in more than half the observations using factored variables of glacier shape, elevation range, and upslope area.

Thin-layer chromatographic identification of Chinese propolis using chemometric fingerprinting.

PubMed

Tang, Tie-xin; Guo, Wei-yan; Xu, Ye; Zhang, Si-ming; Xu, Xin-jun; Wang, Dong-mei; Zhao, Zhi-min; Zhu, Long-ping; Yang, De-po

2014-01-01

Poplar tree gum has a similar chemical composition and appearance to Chinese propolis (bee glue) and has been widely used as a counterfeit propolis because Chinese propolis is typically the poplar-type propolis, the chemical composition of which is determined mainly by the resin of poplar trees. The discrimination of Chinese propolis from poplar tree gum is a challenging task. To develop a rapid thin-layer chromatographic (TLC) identification method using chemometric fingerprinting to discriminate Chinese propolis from poplar tree gum. A new TLC method using a combination of ammonia and hydrogen peroxide vapours as the visualisation reagent was developed to characterise the chemical profile of Chinese propolis. Three separate people performed TLC on eight Chinese propolis samples and three poplar tree gum samples of varying origins. Five chemometric methods, including similarity analysis, hierarchical clustering, k-means clustering, neural network and support vector machine, were compared for use in classifying the samples based on their densitograms obtained from the TLC chromatograms via image analysis. Hierarchical clustering, neural network and support vector machine analyses achieved a correct classification rate of 100% in classifying the samples. A strategy for TLC identification of Chinese propolis using chemometric fingerprinting was proposed and it provided accurate sample classification. The study has shown that the TLC identification method using chemometric fingerprinting is a rapid, low-cost method for the discrimination of Chinese propolis from poplar tree gum and may be used for the quality control of Chinese propolis. Copyright © 2014 John Wiley & Sons, Ltd.

Assessment of a remote sensing-based model for predicting malaria transmission risk in villages of Chiapas, Mexico

NASA Technical Reports Server (NTRS)

Beck, L. R.; Rodriguez, M. H.; Dister, S. W.; Rodriguez, A. D.; Washino, R. K.; Roberts, D. R.; Spanner, M. A.

1997-01-01

A blind test of two remote sensing-based models for predicting adult populations of Anopheles albimanus in villages, an indicator of malaria transmission risk, was conducted in southern Chiapas, Mexico. One model was developed using a discriminant analysis approach, while the other was based on regression analysis. The models were developed in 1992 for an area around Tapachula, Chiapas, using Landsat Thematic Mapper (TM) satellite data and geographic information system functions. Using two remotely sensed landscape elements, the discriminant model was able to successfully distinguish between villages with high and low An. albimanus abundance with an overall accuracy of 90%. To test the predictive capability of the models, multitemporal TM data were used to generate a landscape map of the Huixtla area, northwest of Tapachula, where the models were used to predict risk for 40 villages. The resulting predictions were not disclosed until the end of the test. Independently, An. albimanus abundance data were collected in the 40 randomly selected villages for which the predictions had been made. These data were subsequently used to assess the models' accuracies. The discriminant model accurately predicted 79% of the high-abundance villages and 50% of the low-abundance villages, for an overall accuracy of 70%. The regression model correctly identified seven of the 10 villages with the highest mosquito abundance. This test demonstrated that remote sensing-based models generated for one area can be used successfully in another, comparable area.

Recognition Memory zROC Slopes for Items with Correct versus Incorrect Source Decisions Discriminate the Dual Process and Unequal Variance Signal Detection Models

ERIC Educational Resources Information Center

Starns, Jeffrey J.; Rotello, Caren M.; Hautus, Michael J.

2014-01-01

We tested the dual process and unequal variance signal detection models by jointly modeling recognition and source confidence ratings. The 2 approaches make unique predictions for the slope of the recognition memory zROC function for items with correct versus incorrect source decisions. The standard bivariate Gaussian version of the unequal…

WHODAS 2.0 as a Measure of Severity of Illness: Results of a FLDA Analysis

PubMed Central

Barahona, Igor; Aroca, Fuensanta; Peñuelas-Calvo, Inmaculada; Rodríguez-Jover, Alba; Amodeo-Escribano, Susana; González-Granado, Marta

2018-01-01

WHODAS 2.0 is the standard measure of disability promoted by World Health Organization whereas Clinical Global Impression (CGI) is a widely used scale for determining severity of mental illness. Although a close relationship between these two scales would be expected, there are no relevant studies on the topic. In this study, we explore if WHODAS 2.0 can be used for identifying severity of illness measured by CGI using the Fisher Linear Discriminant Analysis (FLDA) and for identifying which individual items of WHODAS 2.0 best predict CGI scores given by clinicians. One hundred and twenty-two patients were assessed with WHODAS 2.0 and CGI during three months in outpatient mental health facilities of four hospitals of Madrid, Spain. Compared with the traditional correction of WHODAS 2.0, FLDA improves accuracy in near 15%, and so, with FLDA WHODAS 2.0 classifying correctly 59.0% of the patients. Furthermore, FLDA identifies item 6.6 (illness effect on personal finances) and item 4.5 (damaged sexual life) as the most important items for clinicians to score the severity of illness. PMID:29770158

Comparing colour discrimination and proofreading performance under compact fluorescent and halogen lamp lighting.

PubMed

Mayr, Susanne; Köpper, Maja; Buchner, Axel

2013-01-01

Legislation in many countries has banned inefficient household lighting. Consequently, classic incandescent lamps have to be replaced by more efficient alternatives such as halogen and compact fluorescent lamps (CFL). Alternatives differ in their spectral power distributions, implying colour-rendering differences. Participants performed a colour discrimination task - the Farnsworth-Munsell 100 Hue Test--and a proofreading task under CFL or halogen lighting of comparable correlated colour temperatures at low (70 lx) or high (800 lx) illuminance. Illuminance positively affected colour discrimination and proofreading performance, whereas the light source was only relevant for colour discrimination. Discrimination was impaired with CFL lighting. There were no differences between light sources in terms of self-reported physical discomfort and mood state, but the majority of the participants correctly judged halogen lighting to be more appropriate for discriminating colours. The findings hint at the colour-rendering deficiencies associated with energy-efficient CFLs. In order to compare performance under energy-efficient alternatives of classic incandescent lighting, colour discrimination and proofreading performance was compared under CFL and halogen lighting. Colour discrimination was impaired under CFLs, which hints at the practical drawbacks associated with the reduced colour-rendering properties of energy-efficient CFLs.

A Critical Analysis of Anti-Discrimination Law and Microaggressions in Academia

ERIC Educational Resources Information Center

Lukes, Robin; Bangs, Joann

2014-01-01

This article provides a critical analysis of microaggressions and anti-discrimination law in academia. There are many challenges for faculty claiming discrimination under current civil rights laws. Examples of microaggressions that fall outside of anti-discrimination law will be provided. Traditional legal analysis of discrimination will not end…

Detection and identification of multiple adulterants in plant food supplements using attenuated total reflectance-Infrared spectroscopy.

PubMed

Deconinck, E; Aouadi, C; Bothy, J L; Courselle, P

2018-04-15

Due to the rising popularity of dietary supplements, especially plant food supplements, and alternative herbal medicines, a whole market developed and these products became freely available through internet. Though several searches revealed that at least a part of these products, especially the ones obtained from websites disclosing their physical identity, are aldulterated with pharmaceutical compounds. This causes a threat for public health, since these compounds are not declared and therefore adverse effects will not immediately be related to the product. The more the adulterants can interfere with other medicinal treatments. Since the present active pharmaceutical ingredients are not declared on the package and the products are sold as 100% natural or herbal in nature, it is very difficult for custom personnel to discriminate between products to be confiscated or not. Therefore easy to apply analytical approaches to discriminate between adulterated and non-adulterated products are necessary. This paper presents an approach based on infrared spectroscopy combined with attenuated total reflectance (ATR) and partial least squares- discriminant analysis (PLS-DA) to easily differentiate between adulterated and non- adulterated plant food supplements and to get a first idea of the nature of the adulterant present. The performance of PLS-DA models based on Mid-IR and NIR data were compared as well as models based on the combined data. Further three preprocessing strategies were compared. The best performance was obtained for a PLS-DA model using Mid-IR data with the second derivative as preprocessing method. This model showed a correct classification rate of 98.3% for an external test set. Also eight real samples were screened using the model and for seven of these samples a correct classification was obtained. Generally it could be concluded that the obtained model and the presented approach could be used at customs to discriminate between adulterated and non-adulterated herbal food supplements and even get a first idea of the nature of the adulterant present. The more the presented approach hardly needs sample preparation. Copyright © 2018 Elsevier B.V. All rights reserved.

Automatic analysis and classification of surface electromyography.

PubMed

Abou-Chadi, F E; Nashar, A; Saad, M

2001-01-01

In this paper, parametric modeling of surface electromyography (EMG) algorithms that facilitates automatic SEMG feature extraction and artificial neural networks (ANN) are combined for providing an integrated system for the automatic analysis and diagnosis of myopathic disorders. Three paradigms of ANN were investigated: the multilayer backpropagation algorithm, the self-organizing feature map algorithm and a probabilistic neural network model. The performance of the three classifiers was compared with that of the old Fisher linear discriminant (FLD) classifiers. The results have shown that the three ANN models give higher performance. The percentage of correct classification reaches 90%. Poorer diagnostic performance was obtained from the FLD classifier. The system presented here indicates that surface EMG, when properly processed, can be used to provide the physician with a diagnostic assist device.

Sex assessment from the acetabular rim by means of image analysis.

PubMed

Benazzi, S; Maestri, C; Parisini, S; Vecchi, F; Gruppioni, G

2008-08-25

Determining sex from skeletal remains is one of the most important steps in archaeological and forensic anthropology. The present study considers the diagnostic value of the acetabulum based on its planar image and related metric data. For this purpose, 83 adult os coxae of known age were examined. Digital photos of the acetabular area were taken, with each bone in a standardized orientation. Technical drawing software was used to trace the acetabular rim and to measure the related dimensions (area, perimeter, longitudinal and transverse maximum width). The measurements were subjected to SPSS discriminant and classification function analysis. There were significant differences (p

Assessing a traceability technique in fresh oranges (Citrus sinensis L. Osbeck) with an HS-SPME-GC-MS method. Towards a volatile characterisation of organic oranges.

PubMed

Cuevas, Francisco Julián; Moreno-Rojas, José Manuel; Ruiz-Moreno, María José

2017-04-15

A targeted approach using HS-SPME-GC-MS was performed to compare flavour compounds of 'Navelina' and 'Salustiana' orange cultivars from organic and conventional management systems. Both varieties of conventional oranges showed higher content of ester compounds. On the other hand, higher content of some compounds related with the geranyl-diphosphate pathway (neryl and geranyl acetates) and some terpenoids were found in the organic samples. Furthermore, the partial least square discriminant analysis (PLS-DA) achieved an effective classification for oranges based on the farming system using their volatile profiles (90 and 100% correct classification). To our knowledge, it is the first time that a comparative study dealing with farming systems and orange aroma profile has been performed. These new insights, taking into account local databases, cultivars and advanced analytical tools, highlight the potential of volatile composition for organic orange discrimination. Copyright © 2016 Elsevier Ltd. All rights reserved.

The ratio between corner frequencies of source spectra of P- and S-waves—a new discriminant between earthquakes and quarry blasts

NASA Astrophysics Data System (ADS)

Ataeva, G.; Gitterman, Y.; Shapira, A.

2017-01-01

This study analyzes and compares the P- and S-wave displacement spectra from local earthquakes and explosions of similar magnitudes. We propose a new approach to discrimination between low-magnitude shallow earthquakes and explosions by using ratios of P- to S-wave corner frequencies as a criterion. We have explored 2430 digital records of the Israeli Seismic Network (ISN) from 456 local events (226 earthquakes, 230 quarry blasts, and a few underwater explosions) of magnitudes Md = 1.4-3.4, which occurred at distances up to 250 km during 2001-2013 years. P-wave and S-wave displacement spectra were computed for all events following Brune's source model of earthquakes (1970, 1971) and applying the distance correction coefficients (Shapira and Hofstetter, Teconophysics 217:217-226, 1993; Ataeva G, Shapira A, Hofstetter A, J Seismol 19:389-401, 2015), The corner frequencies and moment magnitudes were determined using multiple stations for each event, and then the comparative analysis was performed.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Rapid classification of enzymes in cleaning products by hydrolysis, mass spectrometry and linear discriminant analysis.

PubMed

Beneito-Cambra, Miriam; Herrero-Martínez, José Manuel; Simó-Alfonso, Ernesto F; Ramis-Ramos, Guillermo

2008-11-01

A method for the rapid classification of proteases, lipases, amylases and cellulases used as enhancers in cleaning products, based on precipitation with acetone, hydrolysis with HCl, dilution of the hydrolysates with ethanol, and direct infusion into the electrospray ion source of an ion-trap mass spectrometer, has been developed. The abundances of the ([M+H]+ ions of the amino acids, from the hydrolysates of both the enzyme industrial concentrates and the detergent bases spiked with them, were used to construct linear discriminant analysis models, capable of distinguishing between the enzyme classes. For this purpose, the variables were normalized as follows: (A) the ion abundance of each amino acid was divided by the sum of the ion abundances of all the amino acids in the corresponding mass spectrum; (B) the ratios of pairs of ion abundances were obtained by dividing the ion abundance of each amino acid by each one of the ion abundances of the other 17 amino acids in the corresponding mass spectrum. Using normalization procedure B, excellent class-resolution between proteases, lipases, amylases and cellulases was achieved. In all cases, enzymes in industrial concentrates and manufactured cleaning products were correctly classified with >98% assignment probability.

Generic anthropometric and performance characteristics among elite adolescent boys in nine different sports.

PubMed

Pion, Johan; Segers, Veerle; Fransen, Job; Debuyck, Gijs; Deprez, Dieter; Haerens, Leen; Vaeyens, Roel; Philippaerts, Renaat; Lenoir, Matthieu

2015-01-01

The aim of the present study was to evaluate the Flemish Sports Compass (FSC), a non-sport-specific generic testing battery. It was hypothesised that a set of 22 tests would have sufficient discriminant power to allocate athletes to their own sport based on a unique combination of test scores. First, discriminant analyses were applied to the 22 tests of anthropometry, physical fitness and motor coordination in 141 boys under age 18 (16.1 ± 0.8 years) and post age at peak height velocity (maturity offset = 2.674 ± 0.926) from Flemish Top Sport Academies for badminton, basketball, gymnastics, handball, judo, soccer, table tennis, triathlon and volleyball. Second, nine sequential discriminant analyses were used to assess the ability of a set of relevant performance characteristics classifying participants and non-participants for the respective sports. Discriminant analyses resulted in a 96.4% correct classification of all participants for the nine different sports. When focusing on relevant performance characteristics, 80.1% to 97.2% of the total test sample was classified correctly within their respective disciplines. The discriminating characteristics were briefly the following: flexibility in gymnastics, explosive lower-limb strength in badminton and volleyball, speed and agility in badminton, judo, soccer and volleyball, upper-body strength in badminton, basketball and gymnastics, cardiorespiratory endurance in triathletes, dribbling skills in handball, basketball and soccer and overhead-throwing skills in badminton and volleyball. The generic talent characteristics of the FSC enable the distinction of adolescent boys according to their particular sport. Implications for talent programmes are discussed.

Determination of the Characteristics and Classification of Near-Infrared Spectra of Patchouli Oil (Pogostemon Cablin Benth.) from Different Origin

NASA Astrophysics Data System (ADS)

Diego, M. C. R.; Purwanto, Y. A.; Sutrisno; Budiastra, I. W.

2018-05-01

Research related to the non-destructive method of near-infrared (NIR) spectroscopy in aromatic oil is still in development in Indonesia. The objectives of the study were to determine the characteristics of the near-infrared spectra of patchouli oil and classify it based on its origin. The samples were selected from seven different places in Indonesia (Bogor and Garut from West Java, Aceh, and Jambi from Sumatra and Konawe, Masamba and Kolaka from Sulawesi Island). The spectral data of patchouli oil was obtained by FT-NIR spectrometer at the wavelength of 1000-2500 nm, and after that, the samples were subjected to composition analysis using Gas Chromatography-Mass Spectrometry. The transmittance and absorbance spectra were analyzed and then principal component analysis (PCA) was carried out. Discriminant analysis (DA) of the principal component was developed to classify patchouli oil based on its origin. The result shows that the data of both spectra (transmittance and absorbance spectra) by the PC analysis give a similar result for discriminating the seven types of patchouli oil due to their distribution and behavior. The DA of the three principal component in both data processed spectra could classify patchouli oil accurately. This result exposed that NIR spectroscopy can be successfully used as a correct method to classify patchouli oil based on its origin.

24 CFR 81.46 - Remedial actions.

Code of Federal Regulations, 2014 CFR

2014-04-01

... discrimination; (iv) The impact or seriousness of the harm; (v) The number of people affected by the discriminatory act(s); (vi) Whether the lender operates an effective program of self assessment and correction...

24 CFR 81.46 - Remedial actions.

Code of Federal Regulations, 2012 CFR

2012-04-01

... discrimination; (iv) The impact or seriousness of the harm; (v) The number of people affected by the discriminatory act(s); (vi) Whether the lender operates an effective program of self assessment and correction...

24 CFR 81.46 - Remedial actions.

Code of Federal Regulations, 2013 CFR

2013-04-01

... discrimination; (iv) The impact or seriousness of the harm; (v) The number of people affected by the discriminatory act(s); (vi) Whether the lender operates an effective program of self assessment and correction...

Model based on GRID-derived descriptors for estimating CYP3A4 enzyme stability of potential drug candidates

NASA Astrophysics Data System (ADS)

Crivori, Patrizia; Zamora, Ismael; Speed, Bill; Orrenius, Christian; Poggesi, Italo

2004-03-01

A number of computational approaches are being proposed for an early optimization of ADME (absorption, distribution, metabolism and excretion) properties to increase the success rate in drug discovery. The present study describes the development of an in silico model able to estimate, from the three-dimensional structure of a molecule, the stability of a compound with respect to the human cytochrome P450 (CYP) 3A4 enzyme activity. Stability data were obtained by measuring the amount of unchanged compound remaining after a standardized incubation with human cDNA-expressed CYP3A4. The computational method transforms the three-dimensional molecular interaction fields (MIFs) generated from the molecular structure into descriptors (VolSurf and Almond procedures). The descriptors were correlated to the experimental metabolic stability classes by a partial least squares discriminant procedure. The model was trained using a set of 1800 compounds from the Pharmacia collection and was validated using two test sets: the first one including 825 compounds from the Pharmacia collection and the second one consisting of 20 known drugs. This model correctly predicted 75% of the first and 85% of the second test set and showed a precision above 86% to correctly select metabolically stable compounds. The model appears a valuable tool in the design of virtual libraries to bias the selection toward more stable compounds. Abbreviations: ADME - absorption, distribution, metabolism and excretion; CYP - cytochrome P450; MIFs - molecular interaction fields; HTS - high throughput screening; DDI - drug-drug interactions; 3D - three-dimensional; PCA - principal components analysis; CPCA - consensus principal components analysis; PLS - partial least squares; PLSD - partial least squares discriminant; GRIND - grid independent descriptors; GRID - software originally created and developed by Professor Peter Goodford.

Multivariate analysis and visualization of soil quality data for no-till systems.

PubMed

Villamil, M B; Miguez, F E; Bollero, G A

2008-01-01

To evidence the multidimensionality of the soil quality concept, we propose the use of data visualization as a tool for exploratory data analyses, model building, and diagnostics. Our objective was to establish the best edaphic indicators for assessing soil quality in four no-till systems with regard to functioning as a medium for crop production and nutrient cycling across two Illinois locations. The compared situations were no-till corn-soybean rotations including either winter fallowing (C/S) or cover crops of rye (Secale cereale; C-R/S-R), hairy vetch (Vicia villosa; C-R/S-V), or their mixture (C-R/S-VR). The dataset included the variables bulk density (BD), penetration resistance (PR), water aggregate stability (WAS), soil reaction (pH), and the contents of soil organic matter (SOM), total nitrogen (TN), soil nitrates (NO(3)-N), and available phosphorus (P). Interactive data visualization along with canonical discriminant analysis (CDA) allowed us to show that WAS, BD, and the contents of P, TN, and SOM have the greatest potential as soil quality indicators in no-till systems in Illinois. It was more difficult to discriminate among WCC rotations than to separate these from C/S, considerably inflating the error rate associated with CDA. We predict that observations of no-till C/S will be classified correctly 51% of the time, while observations of no-till WCC rotations will be classified correctly 74% of the time. High error rates in CDA underscore the complexity of no-till systems and the need in this area for more long-term studies with larger datasets to increase accuracy to acceptable levels.

Evaluation of Psychometric Properties of Voice Activity and Participation Profile (VAPP): A Spanish Version.

PubMed

Bermúdez-de-Alvear, Rosa M; Gálvez-Ruiz, Pablo; Martínez-Arquero, A Ginés; Rando-Márquez, Sara; Fernández-Contreras, Elena

2018-06-11

This study aimed to analyze the psychometric properties of the Spanish version of the Voice Activity and Participation Profile (SVAPP) questionnaire. A randomized, cross-sectional sampling strategy with controls was used. Two samples with a total of 169 participants were analyzed, specifically 61 men (mean age 37.02) and 108 women (mean age 37.78). Of these participants, 112 were patients and 57 were controls. The instrument was submitted to reliability (internal consistency and corrected item-total correlations) and reproducibility analyses. Validation assessment was based on the construct validity, convergent validity, discriminant validity, and concurrent validity. The global internal consistency was excellent (Cronbach's α = 0.976), corrected item-total correlations were satisfactory and ranged 0.63-0.89, and factor loadings were above 0.50. The different subscales showed good internal consistency (alpha coefficients ranged 0.830-0.956) and test-retest values were consistently associated. The exploratory factor analysis evidenced a strongly defined five factors internal structure, with factors loadings ranging 0.51-0.86. Convergent validity demonstrated that all subscales and scores were very strongly correlated (Pearson r above 0.735) and significantly associated. The discriminant validity analysis showed that SVAPP had good specificity to distinguish dysphonic from healthy voice subjects. Concurrent validity with Voice Handicap Index Spanish version (SVHI) showed very strong correlations between total scores, and between SVHI total score and SVAPP Daily and Social Communication subscales; correlations between both tests subscales were strong; only between SVAPP Work and SVHI Physical sections correlations were moderate. The findings of the present study demonstrated evidence for the SVAPP questionnaire reliability and validity, and provided insightful implications of voice disorders on Spanish patients' quality of life. However, further investigations are required. Copyright © 2018 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Observation versus classification in supervised category learning.

PubMed

Levering, Kimery R; Kurtz, Kenneth J

2015-02-01

The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

Catatonia in inpatients with psychiatric disorders: A comparison of schizophrenia and mood disorders.

PubMed

Grover, Sandeep; Chakrabarti, Subho; Ghormode, Deepak; Agarwal, Munish; Sharma, Akhilesh; Avasthi, Ajit

2015-10-30

This study aimed to evaluate the symptom threshold for making the diagnosis of catatonia. Further the objectives were to (1) to study the factor solution of Bush Francis Catatonia Rating Scale (BFCRS); (2) To compare the prevalence and symptom profile of catatonia in patients with psychotic and mood disorders among patients admitted to the psychiatry inpatient of a general hospital psychiatric unit. 201 patients were screened for presence of catatonia by using BFCRS. By using cluster analysis, discriminant analysis, ROC curve, sensitivity and specificity analysis, data suggested that a threshold of 3 symptoms was able to correctly categorize 89.4% of patients with catatonia and 100% of patients without catatonia. Prevalence of catatonia was 9.45%. There was no difference in the prevalence rate and symptom profile of catatonia between those with schizophrenia and mood disorders (i.e., unipolar depression and bipolar affective disorder). Factor analysis of the data yielded 2 factor solutions, i.e., retarded and excited catatonia. To conclude this study suggests that presence of 3 symptoms for making the diagnosis of catatonia can correctly distinguish patients with and without catatonia. This is compatible with the recommendations of DSM-5. Prevalence of catatonia is almost equal in patients with schizophrenia and mood disorders. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Molecular reclassification of Crohn's disease: a cautionary note on population stratification.

PubMed

Maus, Bärbel; Jung, Camille; Mahachie John, Jestinah M; Hugot, Jean-Pierre; Génin, Emmanuelle; Van Steen, Kristel

2013-01-01

Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn's disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn's disease is widely acknowledged and has been demonstrated by identification of over 100 CD associated genetic loci. However, relating CD subphenotypes to disease susceptible loci has proven to be a difficult task. In this paper we discuss the use of cluster analysis on genetic markers to identify genetic-based subgroups while taking into account possible confounding by population stratification. We show that it is highly relevant to consider the confounding nature of population stratification in order to avoid that detected clusters are strongly related to population groups instead of disease-specific groups. Therefore, we explain the use of principal components to correct for population stratification while clustering affected individuals into genetic-based subgroups. The principal components are obtained using 30 ancestry informative markers (AIM), and the first two PCs are determined to discriminate between continental origins of the affected individuals. Genotypes on 51 CD associated single nucleotide polymorphisms (SNPs) are used to perform latent class analysis, hierarchical and Partitioning Around Medoids (PAM) cluster analysis within a sample of affected individuals with and without the use of principal components to adjust for population stratification. It is seen that without correction for population stratification clusters seem to be influenced by population stratification while with correction clusters are unrelated to continental origin of individuals.

Molecular Reclassification of Crohn’s Disease: A Cautionary Note on Population Stratification

PubMed Central

Maus, Bärbel; Jung, Camille; Mahachie John, Jestinah M.; Hugot, Jean-Pierre; Génin, Emmanuelle; Van Steen, Kristel

2013-01-01

Complex human diseases commonly differ in their phenotypic characteristics, e.g., Crohn’s disease (CD) patients are heterogeneous with regard to disease location and disease extent. The genetic susceptibility to Crohn’s disease is widely acknowledged and has been demonstrated by identification of over 100 CD associated genetic loci. However, relating CD subphenotypes to disease susceptible loci has proven to be a difficult task. In this paper we discuss the use of cluster analysis on genetic markers to identify genetic-based subgroups while taking into account possible confounding by population stratification. We show that it is highly relevant to consider the confounding nature of population stratification in order to avoid that detected clusters are strongly related to population groups instead of disease-specific groups. Therefore, we explain the use of principal components to correct for population stratification while clustering affected individuals into genetic-based subgroups. The principal components are obtained using 30 ancestry informative markers (AIM), and the first two PCs are determined to discriminate between continental origins of the affected individuals. Genotypes on 51 CD associated single nucleotide polymorphisms (SNPs) are used to perform latent class analysis, hierarchical and Partitioning Around Medoids (PAM) cluster analysis within a sample of affected individuals with and without the use of principal components to adjust for population stratification. It is seen that without correction for population stratification clusters seem to be influenced by population stratification while with correction clusters are unrelated to continental origin of individuals. PMID:24147066

Extinction of an instrumental response: a cognitive behavioral assay in Fmr1 knockout mice.

PubMed

Sidorov, M S; Krueger, D D; Taylor, M; Gisin, E; Osterweil, E K; Bear, M F

2014-06-01

Fragile X (FX) is the most common genetic cause of intellectual disability and autism. Previous studies have shown that partial inhibition of metabotropic glutamate receptor signaling is sufficient to correct behavioral phenotypes in a mouse model of FX, including audiogenic seizures, open-field hyperactivity and social behavior. These phenotypes model well the epilepsy (15%), hyperactivity (20%) and autism (30%) that are comorbid with FX in human patients. Identifying reliable and robust mouse phenotypes to model cognitive impairments is critical considering the 90% comorbidity of FX and intellectual disability. Recent work characterized a five-choice visuospatial discrimination assay testing cognitive flexibility, in which FX model mice show impairments associated with decreases in synaptic proteins in prefrontal cortex (PFC). In this study, we sought to determine whether instrumental extinction, another process requiring PFC, is altered in FX model mice, and whether downregulation of metabotropic glutamate receptor signaling pathways is sufficient to correct both visuospatial discrimination and extinction phenotypes. We report that instrumental extinction is consistently exaggerated in FX model mice. However, neither the extinction phenotype nor the visuospatial discrimination phenotype is corrected by approaches targeting metabotropic glutamate receptor signaling. This work describes a novel behavioral extinction assay to model impaired cognition in mouse models of neurodevelopmental disorders, provides evidence that extinction is exaggerated in the FX mouse model and suggests possible limitations of metabotropic glutamate receptor-based pharmacotherapy. © 2014 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.

Evaluation of hierarchical agglomerative cluster analysis methods for discrimination of primary biological aerosol

NASA Astrophysics Data System (ADS)

Crawford, I.; Ruske, S.; Topping, D. O.; Gallagher, M. W.

2015-11-01

In this paper we present improved methods for discriminating and quantifying primary biological aerosol particles (PBAPs) by applying hierarchical agglomerative cluster analysis to multi-parameter ultraviolet-light-induced fluorescence (UV-LIF) spectrometer data. The methods employed in this study can be applied to data sets in excess of 1 × 106 points on a desktop computer, allowing for each fluorescent particle in a data set to be explicitly clustered. This reduces the potential for misattribution found in subsampling and comparative attribution methods used in previous approaches, improving our capacity to discriminate and quantify PBAP meta-classes. We evaluate the performance of several hierarchical agglomerative cluster analysis linkages and data normalisation methods using laboratory samples of known particle types and an ambient data set. Fluorescent and non-fluorescent polystyrene latex spheres were sampled with a Wideband Integrated Bioaerosol Spectrometer (WIBS-4) where the optical size, asymmetry factor and fluorescent measurements were used as inputs to the analysis package. It was found that the Ward linkage with z-score or range normalisation performed best, correctly attributing 98 and 98.1 % of the data points respectively. The best-performing methods were applied to the BEACHON-RoMBAS (Bio-hydro-atmosphere interactions of Energy, Aerosols, Carbon, H2O, Organics and Nitrogen-Rocky Mountain Biogenic Aerosol Study) ambient data set, where it was found that the z-score and range normalisation methods yield similar results, with each method producing clusters representative of fungal spores and bacterial aerosol, consistent with previous results. The z-score result was compared to clusters generated with previous approaches (WIBS AnalysiS Program, WASP) where we observe that the subsampling and comparative attribution method employed by WASP results in the overestimation of the fungal spore concentration by a factor of 1.5 and the underestimation of bacterial aerosol concentration by a factor of 5. We suggest that this likely due to errors arising from misattribution due to poor centroid definition and failure to assign particles to a cluster as a result of the subsampling and comparative attribution method employed by WASP. The methods used here allow for the entire fluorescent population of particles to be analysed, yielding an explicit cluster attribution for each particle and improving cluster centroid definition and our capacity to discriminate and quantify PBAP meta-classes compared to previous approaches.

A new strategy for faster urinary biomarkers identification by Nano-LC-MALDI-TOF/TOF mass spectrometry

PubMed Central

Benkali, K; Marquet, P; Rérolle, JP; Le Meur, Y; Gastinel, LN

2008-01-01

Background LC-MALDI-TOF/TOF analysis is a potent tool in biomarkers discovery characterized by its high sensitivity and high throughput capacity. However, methods based on MALDI-TOF/TOF for biomarkers discovery still need optimization, in particular to reduce analysis time and to evaluate their reproducibility for peak intensities measurement. The aims of this methodological study were: (i) to optimize and critically evaluate each step of urine biomarker discovery method based on Nano-LC coupled off-line to MALDI-TOF/TOF, taking full advantage of the dual decoupling between Nano-LC, MS and MS/MS to reduce the overall analysis time; (ii) to evaluate the quantitative performance and reproducibility of nano-LC-MALDI analysis in biomarker discovery; and (iii) to evaluate the robustness of biomarkers selection. Results A pool of urine sample spiked at increasing concentrations with a mixture of standard peptides was used as a specimen for biological samples with or without biomarkers. Extraction and nano-LC-MS variabilities were estimated by analyzing in triplicates and hexaplicates, respectively. The stability of chromatographic fractions immobilised with MALDI matrix on MALDI plates was evaluated by successive MS acquisitions after different storage times at different temperatures. Low coefficient of variation (CV%: 10–22%) and high correlation (R2 > 0.96) values were obtained for the quantification of the spiked peptides, allowing quantification of these peptides in the low fentomole range, correct group discrimination and selection of "specific" markers using principal component analysis. Excellent peptide integrity and stable signal intensity were found when MALDI plates were stored for periods of up to 2 months at +4°C. This allowed storage of MALDI plates between LC separation and MS acquisition (first decoupling), and between MS and MSMS acquisitions while the selection of inter-group discriminative ions is done (second decoupling). Finally the recording of MSMS spectra to obtain structural information was focused only on discriminative ions in order to minimize analysis time. Conclusion Contrary to other classical approaches with direct online coupling of chromatographic separation and on the flight MS and/or MSMS data acquisition for all detected analytes, our dual decoupling strategy allowed us to focus on the most discriminative analytes, giving us more time to acquire more replicates of the same urine samples thus increasing detection sensitivity and mass precision. PMID:19014585

Simulation tools for scattering corrections in spectrally resolved x-ray computed tomography using McXtrace

NASA Astrophysics Data System (ADS)

Busi, Matteo; Olsen, Ulrik L.; Knudsen, Erik B.; Frisvad, Jeppe R.; Kehres, Jan; Dreier, Erik S.; Khalil, Mohamad; Haldrup, Kristoffer

2018-03-01

Spectral computed tomography is an emerging imaging method that involves using recently developed energy discriminating photon-counting detectors (PCDs). This technique enables measurements at isolated high-energy ranges, in which the dominating undergoing interaction between the x-ray and the sample is the incoherent scattering. The scattered radiation causes a loss of contrast in the results, and its correction has proven to be a complex problem, due to its dependence on energy, material composition, and geometry. Monte Carlo simulations can utilize a physical model to estimate the scattering contribution to the signal, at the cost of high computational time. We present a fast Monte Carlo simulation tool, based on McXtrace, to predict the energy resolved radiation being scattered and absorbed by objects of complex shapes. We validate the tool through measurements using a CdTe single PCD (Multix ME-100) and use it for scattering correction in a simulation of a spectral CT. We found the correction to account for up to 7% relative amplification in the reconstructed linear attenuation. It is a useful tool for x-ray CT to obtain a more accurate material discrimination, especially in the high-energy range, where the incoherent scattering interactions become prevailing (>50 keV).

On the analysis of EEG power, frequency and asymmetry in Parkinson’s disease during emotion processing

PubMed Central

2014-01-01

Objective While Parkinson’s disease (PD) has traditionally been described as a movement disorder, there is growing evidence of disruption in emotion information processing associated with the disease. The aim of this study was to investigate whether there are specific electroencephalographic (EEG) characteristics that discriminate PD patients and normal controls during emotion information processing. Method EEG recordings from 14 scalp sites were collected from 20 PD patients and 30 age-matched normal controls. Multimodal (audio-visual) stimuli were presented to evoke specific targeted emotional states such as happiness, sadness, fear, anger, surprise and disgust. Absolute and relative power, frequency and asymmetry measures derived from spectrally analyzed EEGs were subjected to repeated ANOVA measures for group comparisons as well as to discriminate function analysis to examine their utility as classification indices. In addition, subjective ratings were obtained for the used emotional stimuli. Results Behaviorally, PD patients showed no impairments in emotion recognition as measured by subjective ratings. Compared with normal controls, PD patients evidenced smaller overall relative delta, theta, alpha and beta power, and at bilateral anterior regions smaller absolute theta, alpha, and beta power and higher mean total spectrum frequency across different emotional states. Inter-hemispheric theta, alpha, and beta power asymmetry index differences were noted, with controls exhibiting greater right than left hemisphere activation. Whereas intra-hemispheric alpha power asymmetry reduction was exhibited in patients bilaterally at all regions. Discriminant analysis correctly classified 95.0% of the patients and controls during emotional stimuli. Conclusion These distributed spectral powers in different frequency bands might provide meaningful information about emotional processing in PD patients. PMID:24716619

Authentication of meat products: determination of animal feeding by parallel GC-MS analysis of three adipose tissues.

PubMed

Sivadier, Guilhem; Ratel, Jérémy; Bouvier, Frédéric; Engel, Erwan

2008-11-12

Authentication of farm animal rearing conditions, especially the type of feeding, is a key issue in certification of meat quality and meat products. The purpose of this article was to analyze in parallel the volatile fraction of three adipose tissues excised from 16 lambs in order to authenticate two animal diets: pasture (n = 8) and concentrate (n = 8). On the basis of growth rate and anatomical location, three different lamb adipose tissues were analyzed: perirenal fat (PRF), caudal subcutaneous fat (CSCF), and heart fat (HF). An initial experiment was used to optimize the extraction of volatile compounds from the adipose tissues. Using a lipid liquid phase extraction, heating the ground tissue to 70 degrees C, was shown to be the best sample preparation mode before dynamic headspace-gas chromatography-mass spectrometry (DH-GC-MS) analysis to achieve a good representation of the starting material, while getting a good extraction and reproducibility. Next, the application of an instrumental drifts correction procedure to DH-GC-MS data enabled the identification of 130 volatile compounds that discriminate the two diets in one or several of the three tissues: 104 were found in PRF, 75 in CSCF, and 70 in HF. Forty-eight of these diet tracers, including 2,3-octanedione, toluene, terpenes, alkanes, alkenes, and ketones, had previously been identified as ruminant pasture-diet tracers and can be considered generic of this type of animal feeding. Moreover, 49 of the 130 compounds could identify diets in only one tissue, suggesting that complementary analysis of several tissues is superior for diet identification. Finally, multivariate discriminant analyses confirmed that the discrimination was improved when PRF, CSCF, and HF were considered simultaneously, even if HF contributed minimal information.

Early identification of MCI converting to AD: a FDG PET study.

PubMed

Pagani, Marco; Nobili, Flavio; Morbelli, Silvia; Arnaldi, Dario; Giuliani, Alessandro; Öberg, Johanna; Girtler, Nicola; Brugnolo, Andrea; Picco, Agnese; Bauckneht, Matteo; Piva, Roberta; Chincarini, Andrea; Sambuceti, Gianmario; Jonsson, Cathrine; De Carli, Fabrizio

2017-11-01

Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not. FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy. The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients. In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Synthesis-identification integration: One-pot hydrothermal preparation of fluorescent nitrogen-doped carbon nanodots for differentiating nucleobases with the aid of multivariate chemometrics analysis.

PubMed

Zhuang, Qianfen; Cao, Wei; Ni, Yongnian; Wang, Yong

2018-08-01

Most of the conventional multidimensional differential sensors currently need at least two-step fabrication, namely synthesis of probe(s) and identification of multiple analytes by mixing of analytes with probe(s), and were conducted using multiple sensing elements or several devices. In the study, we chose five different nucleobases (adenine, cytosine, guanine, thymine, and uracil) as model analytes, and found that under hydrothermal conditions, sodium citrate could react directly with various nucleobases to yield different nitrogen-doped carbon nanodots (CDs). The CDs synthesized from different nucleobases exhibited different fluorescent properties, leading to their respective characteristic fluorescence spectra. Hence, we combined the fluorescence spectra of the CDs with advanced chemometrics like principle component analysis (PCA), hierarchical cluster analysis (HCA), K-nearest neighbor (KNN) and soft independent modeling of class analogy (SIMCA), to present a conceptually novel "synthesis-identification integration" strategy to construct a multidimensional differential sensor for nucleobase discrimination. Single-wavelength excitation fluorescence spectral data, single-wavelength emission fluorescence spectral data, and fluorescence Excitation-Emission Matrices (EEMs) of the CDs were respectively used as input data of the differential sensor. The results showed that the discrimination ability of the multidimensional differential sensor with EEM data set as input data was superior to those with single-wavelength excitation/emission fluorescence data set, suggesting that increasing the number of the data input could improve the discrimination power. Two supervised pattern recognition methods, namely KNN and SIMCA, correctly identified the five nucleobases with a classification accuracy of 100%. The proposed "synthesis-identification integration" strategy together with a multidimensional array of experimental data holds great promise in the construction of differential sensors. Copyright © 2018 Elsevier B.V. All rights reserved.

Development and validation of a Partial Least Squares-Discriminant Analysis (PLS-DA) model based on the determination of ethyl glucuronide (EtG) and fatty acid ethyl esters (FAEEs) in hair for the diagnosis of chronic alcohol abuse.

PubMed

Alladio, E; Giacomelli, L; Biosa, G; Corcia, D Di; Gerace, E; Salomone, A; Vincenti, M

2018-01-01

The chronic intake of an excessive amount of alcohol is currently ascertained by determining the concentration of direct alcohol metabolites in the hair samples of the alleged abusers, including ethyl glucuronide (EtG) and, less frequently, fatty acid ethyl esters (FAEEs). Indirect blood biomarkers of alcohol abuse are still determined to support hair EtG results and diagnose a consequent liver impairment. In the present study, the supporting role of hair FAEEs is compared with indirect blood biomarkers with respect to the contexts in which hair EtG interpretation is uncertain. Receiver Operating Characteristics (ROC) curves and multivariate Principal Component Analysis (PCA) demonstrated much stronger correlation of EtG results with FAEEs than with any single indirect biomarker or their combinations. Partial Least Squares Discriminant Analysis (PLS-DA) models based on hair EtG and FAEEs were developed to maximize the biomarkers information content on a multivariate background. The final PLS-DA model yielded 100% correct classification on a training/evaluation dataset of 155 subjects, including both chronic alcohol abusers and social drinkers. Then, the PLS-DA model was validated on an external dataset of 81 individual providing optimal discrimination ability between chronic alcohol abusers and social drinkers, in terms of specificity and sensitivity. The PLS-DA scores obtained for each subject, with respect to the PLS-DA model threshold that separates the probabilistic distributions for the two classes, furnished a likelihood ratio value, which in turn conveys the strength of the experimental data support to the classification decision, within a Bayesian logic. Typical boundary real cases from daily work are discussed, too. Copyright © 2017 Elsevier B.V. All rights reserved.

Direct Analysis in Real Time-Mass Spectrometry & Kohonen Artificial Neural Networks for the Rapid Species Identification of Larvae, Pupae and Adult Life Stages of Carrion Insects.

PubMed

Beyramysoltan, Samira; Giffen, Justine E; Rosati, Jennifer Y; Musah, Rabi Ann

2018-06-20

Species determination of the various life stages of flies (order: Diptera) is challenging, particularly for the immature forms, because analogous life stages of different species are difficult to differentiate morphologically. It is demonstrated here that DART high-resolution mass spectrometry (DART-HRMS) combined with supervised Kohonen Self-Organizing Maps (SOM) enables accomplishment of species-level identification of larvae, pupae and adult life stages of carrion flies. DART-HRMS data for each life stage were acquired from analysis of ethanol suspensions representing Calliphoridae, Phoridae and Sarcophagidae families, without additional sample preparation. After preprocessing, the data were subjected to a combination of minimum Redundancy Maximal Relevance (mRMR) and Sparse Discriminant Analysis (SDA) methods to select the most significant variables for creating accurate SOM models. The resulting data were divided into training and validation sets, and then analyzed by the SOM method to define the proper discrimination models. The 5-fold venetian blind cross-validation misclassification error was below 7% for all life stages, and the validation samples were correctly identified in all cases. The multiclass SOM model also revealed which chemical components were the most significant markers for each species, with several of these being amino acids. The results show that processing of DART-HRMS data using artificial neural networks (ANNs) based on the Kohonen SOM approach enables rapid discrimination and identification of fly species even for the immature life stages. The ANNs can be continuously expanded to include a larger number of species, and can be used to screen DART-HRMS data from unknowns to rapidly determine species identity.

Harvest locations of goose barnacles can be successfully discriminated using trace elemental signatures

PubMed Central

Albuquerque, Rui; Queiroga, Henrique; Swearer, Stephen E.; Calado, Ricardo; Leandro, Sérgio M.

2016-01-01

European Union regulations state that consumers must be rightfully informed about the provenance of fishery products to prevent fraudulent practices. However, mislabeling of the geographical origin is a common practice. It is therefore paramount to develop forensic methods that allow all players involved in the supply chain to accurately trace the origin of seafood. In this study, trace elemental signatures (TES) of the goose barnacle Pollicipes pollicipes, collected from ten sites along the Portuguese coast, were employed to discriminate individual’s origin. Barium (Ba), boron (B), cadmium (Cd), chromium (Cr), lithium (Li), magnesium (Mg), manganese (Mn), phosphorous (P), lead (Pb), strontium (Sr) and zinc (Zn) - were quantified using Inductively Coupled Plasma−Mass Spectrometry (ICP-MS). Significant differences were recorded among locations for all elements. A regularized discriminant analysis (RDA) revealed that 83% of all individuals were correctly assigned. This study shows TES can be a reliable tool to confirm the geographic origin of goose barnacles at fine spatial resolution. Although additional studies are required to ascertain the reliability of TES on cooked specimens and the temporal stability of the signature, the approach holds great promise for the management of goose barnacles fisheries, enforcement of conservation policies and assurance in accurate labeling. PMID:27292413

Temporal characteristics of the influence of punishment on perceptual decision making in the human brain.

PubMed

Blank, Helen; Biele, Guido; Heekeren, Hauke R; Philiastides, Marios G

2013-02-27

Perceptual decision making is the process by which information from sensory systems is combined and used to influence our behavior. In addition to the sensory input, this process can be affected by other factors, such as reward and punishment for correct and incorrect responses. To investigate the temporal dynamics of how monetary punishment influences perceptual decision making in humans, we collected electroencephalography (EEG) data during a perceptual categorization task whereby the punishment level for incorrect responses was parametrically manipulated across blocks of trials. Behaviorally, we observed improved accuracy for high relative to low punishment levels. Using multivariate linear discriminant analysis of the EEG, we identified multiple punishment-induced discriminating components with spatially distinct scalp topographies. Compared with components related to sensory evidence, components discriminating punishment levels appeared later in the trial, suggesting that punishment affects primarily late postsensory, decision-related processing. Crucially, the amplitude of these punishment components across participants was predictive of the size of the behavioral improvements induced by punishment. Finally, trial-by-trial changes in prestimulus oscillatory activity in the alpha and gamma bands were good predictors of the amplitude of these components. We discuss these findings in the context of increased motivation/attention, resulting from increases in punishment, which in turn yields improved decision-related processing.

Diagnosis of meningioma by time-resolved fluorescence spectroscopy.

PubMed

Butte, Pramod V; Pikul, Brian K; Hever, Aviv; Yong, William H; Black, Keith L; Marcu, Laura

2005-01-01

We investigate the use of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) as an adjunctive tool for the intraoperative rapid evaluation of tumor specimens and delineation of tumor from surrounding normal tissue. Tissue autofluorescence is induced with a pulsed nitrogen laser (337 nm, 1.2 ns) and the intensity decay profiles are recorded in the 370 to 500 nm spectral range with a fast digitizer (0.2 ns resolution). Experiments are conducted on excised specimens (meningioma, dura mater, cerebral cortex) from 26 patients (97 sites). Spectral intensities and time-dependent parameters derived from the time-resolved spectra of each site are used for tissue characterization. A linear discriminant analysis algorithm is used for tissue classification. Our results reveal that meningioma is characterized by unique fluorescence characteristics that enable discrimination of tumor from normal tissue with high sensitivity (>89%) and specificity (100%). The accuracy of classification is found to increase (92.8% cases in the training set and 91.8% in the cross-validated set correctly classified) when parameters from both the spectral and the time domain are used for discrimination. Our findings establish the feasibility of using TR-LIFS as a tool for the identification of meningiomas and enables further development of real-time diagnostic tools for analyzing surgical tissue specimens of meningioma or other brain tumors.

Diagnosis of meningioma by time-resolved fluorescence spectroscopy

PubMed Central

Butte, Pramod V.; Pikul, Brian K.; Hever, Aviv; Yong, William H.; Black, Keith L.; Marcu, Laura

2010-01-01

We investigate the use of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) as an adjunctive tool for the intraoperative rapid evaluation of tumor specimens and delineation of tumor from surrounding normal tissue. Tissue autofluorescence is induced with a pulsed nitrogen laser (337 nm, 1.2 ns) and the intensity decay profiles are recorded in the 370 to 500 nm spectral range with a fast digitizer (0.2 ns resolution). Experiments are conducted on excised specimens (meningioma, dura mater, cerebral cortex) from 26 patients (97 sites). Spectral intensities and time-dependent parameters derived from the time-resolved spectra of each site are used for tissue characterization. A linear discriminant analysis algorithm is used for tissue classification. Our results reveal that meningioma is characterized by unique fluorescence characteristics that enable discrimination of tumor from normal tissue with high sensitivity (>89%) and specificity (100%). The accuracy of classification is found to increase (92.8% cases in the training set and 91.8% in the cross-validated set correctly classified) when parameters from both the spectral and the time domain are used for discrimination. Our findings establish the feasibility of using TR-LIFS as a tool for the identification of meningiomas and enables further development of real-time diagnostic tools for analyzing surgical tissue specimens of meningioma or other brain tumors. PMID:16409091

Neurological soft signs precede the onset of schizophrenia: a study of individuals with schizotypy, ultra-high-risk individuals, and first-onset schizophrenia.

PubMed

Chan, Raymond C K; Cui, Hui-Ru; Chu, Min-Yi; Zhang, Tian-Hong; Wang, Ya; Wang, Yi; Li, Zhi; Lui, Simon S Y; Wang, Ji-Jun; Cheung, Eric F C

2018-02-01

Neurological soft signs (NSS) are one of the biomarkers for schizophrenia spectrum disorders. However, a few studies have examined the prevalence of NSS across the schizophrenia spectrum. The present study adopted a quasi-longitudinal study design and examined the prevalence of NSS and their associations with clinical and behavioural manifestations in participants in different stages of the illness. The abridged version of the Cambridge Neurological Inventory was administered to 39 patients with the first-episode schizophrenia, 39 individuals with ultra-high risk (UHR) for psychosis, 39 individuals with schizotypy, and 39 healthy controls. Patients with the first-episode schizophrenia had a higher prevalence of NSS in motor coordination than healthy controls as well as individuals with UHR and schizotypy. Individuals with UHR exhibited a higher prevalence of sensory integration items than individuals with schizotypy and healthy controls. Discriminant analysis classified the membership of the individuals correctly across the spectrum with an accuracy of up to 60.9%. In particular, NSS could discriminate individuals with UHR from healthy controls at up to 85.9% accuracy. These findings suggest that NSS are robust biomarkers to detect and discriminate individuals in different stages of the schizophrenia spectrum from healthy controls.

Does tip-of-the-tongue for proper names discriminate amnestic mild cognitive impairment?

PubMed

Juncos-Rabadán, Onésimo; Facal, David; Lojo-Seoane, Cristina; Pereiro, Arturo X

2013-04-01

Difficulty in retrieving people's names is very common in the early stages of Alzheimer's disease and mild cognitive impairment. Such difficulty is often observed as the tip-of-the-tongue (TOT) phenomenon. The main aim of this study was to explore whether a famous people's naming task that elicited the TOT state can be used to discriminate between amnestic mild cognitive impairment (aMCI) patients and normal controls. Eighty-four patients with aMCI and 106 normal controls aged over 50 years performed a task involving naming 50 famous people shown in pictures. Univariate and multivariate regression analyses were used to study the relationships between aMCI and semantic and phonological measures in the TOT paradigm. Univariate regression analyses revealed that all TOT measures significantly predicted aMCI. Multivariate analysis of all these measures correctly classified 70% of controls (specificity) and 71.6% of aMCI patients (sensitivity), with an AUC (area under curve ROC) value of 0.74, but only the phonological measure remained significant. This classification value was similar to that obtained with the Semantic verbal fluency test. TOTs for proper names may effectively discriminate aMCI patients from normal controls through measures that represent one of the naming processes affected, that is, phonological access.

Discrimination of Venezuelan spirituous beverages by a trace element-radial basis neural network approach.

PubMed

Hernández-Caraballo, Edwin A; Avila de Hernández, Rita M; Rivas-Echeverría, Francklin; Capote-Luna, Tarcisio

2008-01-15

Radial basis neural networks (RBNNs) were developed and evaluated for discrimination of specimens of 'aguardiente de Cocuy', a spirituous beverage produced in the northwestern region of Venezuela. The beverage is distilled from the must of Agave cocui Trelease in an artisanship fashion with little quality control. Forty specimens, with known concentrations of copper, iron, and zinc, were used in this study. The specimens were previously collected in various locations around Sucre Municipality (Falcón State) and Urdaneta Municipality (Lara State). The normalized concentrations of these elements served as indirect descriptors of origin (input data). They were presented to the neural networks through 1-3 input nodes in seven different combinations. In addition, two categories (two collection sites) and four categories (two collection sites+two manufacturing conditions) were designated as output data, in order to assess the impact of such selection on the discrimination performance. The overall performance of the four-category RBNNs was as follows (the input data is indicated in parentheses): (Cu-Fe)>(Cu-Zn)>(Cu)>(Zn)>(Fe-Zn)>(Cu-Fe-Zn)>(Fe). In this case, the highest percentage of correct hits was 82.5%. For the two-category RBNNs, the performance decreased as indicated below: (Cu)>(Cu-Fe)>(Cu-Zn)>(Fe-Zn)>(Zn) approximately (Cu-Fe-Zn)>(Fe). The reduction in the number of categories led to an increase in the discrimination performance of all the RBNNs, the best of which was 90.0%. The possibility of discriminating specimens of 'aguardiente de Cocuy' with such an accuracy, based on a single-element determination, is particularly attractive as it would result in a reduction of analysis' costs and laboratory's response time.

Tire traces - discrimination and classification of pyrolysis-GC/MS profiles.

PubMed

Gueissaz, Line; Massonnet, Geneviève

2013-07-10

Tire traces can be observed on several crime scenes as vehicles are often used by criminals. The tread abrasion on the road, while braking or skidding, leads to the production of small rubber particles which can be collected for comparison purposes. This research focused on the statistical comparison of Py-GC/MS profiles of tire traces and tire treads. The optimisation of the analytical method was carried out using experimental designs. The aim was to determine the best pyrolysis parameters regarding the repeatability of the results. Thus, the pyrolysis factor effect could also be calculated. The pyrolysis temperature was found to be five time more important than time. Finally, a pyrolysis at 650°C during 15s was selected. Ten tires of different manufacturers and models were used for this study. Several samples were collected on each tire, and several replicates were carried out to study the variability within each tire (intravariability). More than eighty compounds were integrated for each analysis and the variability study showed that more than 75% presented a relative standard deviation (RSD) below 5% for the ten tires, thus supporting a low intravariability. The variability between the ten tires (intervariability) presented higher values and the ten most variant compounds had a RSD value above 13%, supporting their high potential of discrimination between the tires tested. Principal Component Analysis (PCA) was able to fully discriminate the ten tires with the help of the first three principal components. The ten tires were finally used to perform braking tests on a racetrack with a vehicle equipped with an anti-lock braking system. The resulting tire traces were adequately collected using sheets of white gelatine. As for tires, the intravariability for the traces was found to be lower than the intervariability. Clustering methods were carried out and the Ward's method based on the squared Euclidean distance was able to correctly group all of the tire traces replicates in the same cluster than the replicates of their corresponding tire. Blind tests on traces were performed and were correctly assigned to their tire source. These results support the hypothesis that the tested tires, of different manufacturers and models, can be discriminated by a statistical comparison of their chemical profiles. The traces were found to be not differentiable from their source but differentiable from all the other tires present in the subset. The results are promising and will be extended on a larger sample set. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

[Psychometric properties of the Eating Disorder Inventory (EDI-2) in adolescents].

PubMed

Salbach-Andrae, Harriet; Schneider, Nora; Bürger, Arne; Pfeiffer, Ernst; Lehmkuhl, Ulrike; Holzhausen, Martin

2010-05-01

The present study examines the psychometric properties of the German version of the Eating Disorder Inventory EDI-2 (1997) in 371 adolescents aged 13 to 18 years. Internal consistency, convergent and divergent validity were examined and a confirmatory factor analysis was conducted. Internal consistency was high for the group of patients and satisfactory for both control groups. Associations with other clinical instruments point in the expected direction and support the external validity of the EDI-2. The EDI-2 differentiated very well between the group of eating disorder patients (n=71) and the female (n=150) and male control groups (n=150). A discriminant analysis demonstrated that 86.0% of the cases were correctly classified, and a confirmatory factor analysis largely supported the six-factor structure generated by the German version of the EDI-2 (Thiel et al., 1997).

On the Identification of Rayon/Viscose as a Major Fraction of Microplastics in the Marine Environment: Discrimination between Natural and Manmade Cellulosic Fibers Using Fourier Transform Infrared Spectroscopy

PubMed Central

Comnea-Stancu, Ionela Raluca; Wieland, Karin; Ramer, Georg; Schwaighofer, Andreas

2016-01-01

This work was sparked by the reported identification of man-made cellulosic fibers (rayon/viscose) in the marine environment as a major fraction of plastic litter by Fourier transform infrared (FT-IR) transmission spectroscopy and library search. To assess the plausibility of such findings, both natural and man-made fibers were examined using FT-IR spectroscopy. Spectra acquired by transmission microscopy, attenuated total reflection (ATR) microscopy, and ATR spectroscopy were compared. Library search was employed and results show significant differences in the identification rate depending on the acquisition method of the spectra. Careful selection of search parameters and the choice of spectra acquisition method were found to be essential for optimization of the library search results. When using transmission spectra of fibers and ATR libraries it was not possible to differentiate between man-made and natural fibers. Successful differentiation of natural and man-made cellulosic fibers has been achieved for FT-IR spectra acquired by ATR microscopy and ATR spectroscopy, and application of ATR libraries. As an alternative, chemometric methods such as unsupervised hierarchical cluster analysis, principal component analysis, and partial least squares-discriminant analysis were employed to facilitate identification based on intrinsic relationships of sample spectra and successful discrimination of the fiber type could be achieved. Differences in the ATR spectra depending on the internal reflection element (Ge versus diamond) were observed as expected; however, these did not impair correct classification by chemometric analysis. Moreover, the effects of different levels of humidity on the IR spectra of natural and man-made fibers were investigated, too. It has been found that drying and re-humidification leads to intensity changes of absorption bands of the carbohydrate backbone, but does not impair the identification of the fiber type by library search or cluster analysis. PMID:27650982

Stratiform/convective rain delineation for TRMM microwave imager

NASA Astrophysics Data System (ADS)

Islam, Tanvir; Srivastava, Prashant K.; Dai, Qiang; Gupta, Manika; Wan Jaafar, Wan Zurina

2015-10-01

This article investigates the potential for using machine learning algorithms to delineate stratiform/convective (S/C) rain regimes for passive microwave imager taking calibrated brightness temperatures as only spectral parameters. The algorithms have been implemented for the Tropical Rainfall Measuring Mission (TRMM) microwave imager (TMI), and calibrated as well as validated taking the Precipitation Radar (PR) S/C information as the target class variables. Two different algorithms are particularly explored for the delineation. The first one is metaheuristic adaptive boosting algorithm that includes the real, gentle, and modest versions of the AdaBoost. The second one is the classical linear discriminant analysis that includes the Fisher's and penalized versions of the linear discriminant analysis. Furthermore, prior to the development of the delineation algorithms, a feature selection analysis has been conducted for a total of 85 features, which contains the combinations of brightness temperatures from 10 GHz to 85 GHz and some derived indexes, such as scattering index, polarization corrected temperature, and polarization difference with the help of mutual information aided minimal redundancy maximal relevance criterion (mRMR). It has been found that the polarization corrected temperature at 85 GHz and the features derived from the "addition" operator associated with the 85 GHz channels have good statistical dependency to the S/C target class variables. Further, it has been shown how the mRMR feature selection technique helps to reduce the number of features without deteriorating the results when applying through the machine learning algorithms. The proposed scheme is able to delineate the S/C rain regimes with reasonable accuracy. Based on the statistical validation experience from the validation period, the Matthews correlation coefficients are in the range of 0.60-0.70. Since, the proposed method does not rely on any a priori information, this makes it very suitable for other microwave sensors having similar channels to the TMI. The method could possibly benefit the constellation sensors in the Global Precipitation Measurement (GPM) mission era.

Sensitivity and specificity of eustachian tube function tests in adults.

PubMed

Doyle, William J; Swarts, J Douglas; Banks, Julianne; Casselbrant, Margaretha L; Mandel, Ellen M; Alper, Cuneyt M

2013-07-01

The study demonstrates the utility of eustachian tube (ET) function (ETF) test results for accurately assigning ears to disease state. To determine if ETF tests can identify ears with physician-diagnosed ET dysfunction (ETD) in a mixed population at high sensitivity and specificity and to define the interrelatedness of ETF test parameters. Through use of the forced-response, inflation-deflation, Valsalva, and sniffing tests, ETF was evaluated in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). Data were analyzed using logistic regression including each parameter independently and then a step-down discriminant analysis including all ETF test parameters to predict group assignment. Factor analysis operating over all parameters was used to explore relatedness. ETF testing. ETF parameters for the forced response, inflation-deflation, Valsalva, and sniffing tests measured in 15 control ears of adult subjects after unilateral myringotomy (group 1) and in 23 ears of 19 adult subjects with ventilation tubes inserted for ETD (group 2). The discriminant analysis identified 4 ETF test parameters (Valsalva, ET opening pressure, dilatory efficiency, and percentage of positive pressure equilibrated) that together correctly assigned ears to group 2 at a sensitivity of 95% and a specificity of 83%. Individual parameters representing the efficiency of ET opening during swallowing showed moderately accurate assignments of ears to their respective groups. Three factors captured approximately 98% of the variance among parameters: the first had negative loadings of the ETF structural parameters; the second had positive loadings of the muscle-assisted ET opening parameters; and the third had negative loadings of the muscle-assisted ET opening parameters and positive loadings of the structural parameters. These results show that ETF tests can correctly assign individual ears to physician-diagnosed ETD with high sensitivity and specificity and that ETF test parameters can be grouped into structural-functional categories.

Classification and Lateralization of Temporal Lobe Epilepsies with and without Hippocampal Atrophy Based on Whole-Brain Automatic MRI Segmentation

PubMed Central

Keihaninejad, Shiva; Heckemann, Rolf A.; Gousias, Ioannis S.; Hajnal, Joseph V.; Duncan, John S.; Aljabar, Paul; Rueckert, Daniel; Hammers, Alexander

2012-01-01

Brain images contain information suitable for automatically sorting subjects into categories such as healthy controls and patients. We sought to identify morphometric criteria for distinguishing controls (n = 28) from patients with unilateral temporal lobe epilepsy (TLE), 60 with and 20 without hippocampal atrophy (TLE-HA and TLE-N, respectively), and for determining the presumed side of seizure onset. The framework employs multi-atlas segmentation to estimate the volumes of 83 brain structures. A kernel-based separability criterion was then used to identify structures whose volumes discriminate between the groups. Next, we applied support vector machines (SVM) to the selected set for classification on the basis of volumes. We also computed pairwise similarities between all subjects and used spectral analysis to convert these into per-subject features. SVM was again applied to these feature data. After training on a subgroup, all TLE-HA patients were correctly distinguished from controls, achieving an accuracy of 96 ± 2% in both classification schemes. For TLE-N patients, the accuracy was 86 ± 2% based on structural volumes and 91 ± 3% using spectral analysis. Structures discriminating between patients and controls were mainly localized ipsilaterally to the presumed seizure focus. For the TLE-HA group, they were mainly in the temporal lobe; for the TLE-N group they included orbitofrontal regions, as well as the ipsilateral substantia nigra. Correct lateralization of the presumed seizure onset zone was achieved using hippocampi and parahippocampal gyri in all TLE-HA patients using either classification scheme; in the TLE-N patients, lateralization was accurate based on structural volumes in 86 ± 4%, and in 94 ± 4% with the spectral analysis approach. Unilateral TLE has imaging features that can be identified automatically, even when they are invisible to human experts. Such morphometric image features may serve as classification and lateralization criteria. The technique also detects unsuspected distinguishing features like the substantia nigra, warranting further study. PMID:22523539

Perception of olive oils sensory defects using a potentiometric taste device.

PubMed

Veloso, Ana C A; Silva, Lucas M; Rodrigues, Nuno; Rebello, Ligia P G; Dias, Luís G; Pereira, José A; Peres, António M

2018-01-01

The capability of perceiving olive oils sensory defects and intensities plays a key role on olive oils quality grade classification since olive oils can only be classified as extra-virgin if no defect can be perceived by a human trained sensory panel. Otherwise, olive oils may be classified as virgin or lampante depending on the median intensity of the defect predominantly perceived and on the physicochemical levels. However, sensory analysis is time-consuming and requires an official sensory panel, which can only evaluate a low number of samples per day. In this work, the potential use of an electronic tongue as a taste sensor device to identify the defect predominantly perceived in olive oils was evaluated. The potentiometric profiles recorded showed that intra- and inter-day signal drifts could be neglected (i.e., relative standard deviations lower than 25%), being not statistically significant the effect of the analysis day on the overall recorded E-tongue sensor fingerprints (P-value = 0.5715, for multivariate analysis of variance using Pillai's trace test), which significantly differ according to the olive oils' sensory defect (P-value = 0.0084, for multivariate analysis of variance using Pillai's trace test). Thus, a linear discriminant model based on 19 potentiometric signal sensors, selected by the simulated annealing algorithm, could be established to correctly predict the olive oil main sensory defect (fusty, rancid, wet-wood or winey-vinegary) with average sensitivity of 75 ± 3% and specificity of 73 ± 4% (repeated K-fold cross-validation variant: 4 folds×10 repeats). Similarly, a linear discriminant model, based on 24 selected sensors, correctly classified 92 ± 3% of the olive oils as virgin or lampante, being an average specificity of 93 ± 3% achieved. The overall satisfactory predictive performances strengthen the feasibility of the developed taste sensor device as a complementary methodology for olive oils' defects analysis and subsequent quality grade classification. Furthermore, the capability of identifying the type of sensory defect of an olive oil may allow establishing helpful insights regarding bad practices of olives or olive oils production, harvesting, transport and storage. Copyright © 2017 Elsevier B.V. All rights reserved.

Natural Resources Inventory and Land Evaluation in Switzerland

NASA Technical Reports Server (NTRS)

Haefner, H. (Principal Investigator)

1975-01-01

The author has identified the following significant results. A system was developed to operationally map and measure the areal extent of various land use categories for updating existing and producing new and actual thematic maps showing the latest state of rural and urban landscapes and its changes. The processing system includes: (1) preprocessing steps for radiometric and geometric corrections; (2) classification of the data by a multivariate procedure, using a stepwise linear discriminant analysis based on carefully selected training cells; and (3) output in form of color maps by printing black and white theme overlays of a selected scale with photomation system and its coloring and combination into a color composite.

AVIRIS data characteristics and their effects on spectral discrimination of rocks exposed in the Drum Mountains, Utah: Results of a preliminary study

NASA Technical Reports Server (NTRS)

Bailey, G. B.; Dwyer, J. L.; Meyer, D. J.

1988-01-01

Airborne Visible and Infrared Imaging Spectrometer (AVIRIS) data collected over a geologically diverse field site and over a nearby calibration site were analyzed and interpreted in efforts to document radiometric and geometric characteristics of AVIRIS, quantify and correct for detrimental sensor phenomena, and evaluate the utility of AVIRIS data for discriminating rock types and identifying their constituent mineralogy. AVIRIS data acquired for these studies exhibit a variety of detrimental artifacts and have lower signal-to-noise ratios than expected in the longer wavelength bands. Artifacts are both inherent in the image data and introduced during ground processing, but most may be corrected by appropriate processing techniques. Poor signal-to-noise characteristics of this AVIRIS data set limited the usefulness of the data for lithologic discrimination and mineral identification. Various data calibration techniques, based on field-acquired spectral measurements, were applied to the AVIRIS data. Major absorption features of hydroxyl-bearing minerals were resolved in the spectra of the calibrated AVIRIS data, and the presence of hydroxyl-bearing minerals at the corresponding ground locations was confirmed by field data.

An effective biometric discretization approach to extract highly discriminative, informative, and privacy-protective binary representation

NASA Astrophysics Data System (ADS)

Lim, Meng-Hui; Teoh, Andrew Beng Jin

2011-12-01

Biometric discretization derives a binary string for each user based on an ordered set of biometric features. This representative string ought to be discriminative, informative, and privacy protective when it is employed as a cryptographic key in various security applications upon error correction. However, it is commonly believed that satisfying the first and the second criteria simultaneously is not feasible, and a tradeoff between them is always definite. In this article, we propose an effective fixed bit allocation-based discretization approach which involves discriminative feature extraction, discriminative feature selection, unsupervised quantization (quantization that does not utilize class information), and linearly separable subcode (LSSC)-based encoding to fulfill all the ideal properties of a binary representation extracted for cryptographic applications. In addition, we examine a number of discriminative feature-selection measures for discretization and identify the proper way of setting an important feature-selection parameter. Encouraging experimental results vindicate the feasibility of our approach.

Does perceived race affect discrimination and recognition of ambiguous-race faces? A test of the sociocognitive hypothesis.

PubMed

Rhodes, Gillian; Lie, Hanne C; Ewing, Louise; Evangelista, Emma; Tanaka, James W

2010-01-01

Discrimination and recognition are often poorer for other-race than own-race faces. These other-race effects (OREs) have traditionally been attributed to reduced perceptual expertise, resulting from more limited experience, with other-race faces. However, recent findings suggest that sociocognitive factors, such as reduced motivation to individuate other-race faces, may also contribute. If the sociocognitive hypothesis is correct, then it should be possible to alter discrimination and memory performance for identical faces by altering their perceived race. We made identical ambiguous-race morphed faces look either Asian or Caucasian by presenting them in Caucasian or Asian face contexts, respectively. However, this perceived-race manipulation had no effect on either discrimination (Experiment 1) or memory (Experiment 2) for the ambiguous-race faces, despite the presence of the usual OREs in discrimination and recognition of unambiguous Asian and Caucasian faces in our participant population. These results provide no support for the sociocognitive hypothesis. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Sound localization and word discrimination in reverberant environment in children with developmental dyslexia.

PubMed

Castro-Camacho, Wendy; Peñaloza-López, Yolanda; Pérez-Ruiz, Santiago J; García-Pedroza, Felipe; Padilla-Ortiz, Ana L; Poblano, Adrián; Villarruel-Rivas, Concepción; Romero-Díaz, Alfredo; Careaga-Olvera, Aidé

2015-04-01

Compare if localization of sounds and words discrimination in reverberant environment is different between children with dyslexia and controls. We studied 30 children with dyslexia and 30 controls. Sound and word localization and discrimination was studied in five angles from left to right auditory fields (-90o, -45o, 0o, +45o, +90o), under reverberant and no-reverberant conditions; correct answers were compared. Spatial location of words in no-reverberant test was deficient in children with dyslexia at 0º and +90o. Spatial location for reverberant test was altered in children with dyslexia at all angles, except –-90o. Word discrimination in no-reverberant test in children with dyslexia had a poor performance at left angles. In reverberant test, children with dyslexia exhibited deficiencies at -45o, -90o, and +45o angles. Children with dyslexia could had problems when have to locate sound, and discriminate words in extreme locations of the horizontal plane in classrooms with reverberation.

Shape discrimination and concept formation in the jungle crow (Corvus macrorhynchos).

PubMed

Bogale, Bezawork Afework; Sugita, Shoei

2014-01-01

We investigated whether jungle crows can learn concepts by using printouts of shapes in a simultaneous two-alternative task. Jungle crows were first trained with a red triangle and red square until they reached the discrimination criterion (80% of correct choices in two blocks of 10 trials each). Then, we tested crows with successive transfer tests to investigate both the discrimination cues being used and concept formation ability, by using novel triangular and non-triangular stimuli. All of the jungle crows learnt to discriminate between the triangle and square during training. The discrimination performance was generally not affected either by changes in the colour of the stimuli or when both shape and colour cues conflicted, with the previously non-rewarded shape but matching colour (red square) versus rewarded shape but non-matching colour (green triangle). The use of only outlines of the familiar stimuli also did not affect discrimination behaviour of crows. In addition, crows significantly discriminated novel triangular shapes during the limited trials given, suggesting their ability to form the concept of triangularity. However, failure to discriminate when the novel stimuli size deviated from the original suggests that there is a limit to shape concept formation in a familiar-novel context in the jungle crow.

Automated error correction in IBM quantum computer and explicit generalization

NASA Astrophysics Data System (ADS)

Ghosh, Debjit; Agarwal, Pratik; Pandey, Pratyush; Behera, Bikash K.; Panigrahi, Prasanta K.

2018-06-01

Construction of a fault-tolerant quantum computer remains a challenging problem due to unavoidable noise and fragile quantum states. However, this goal can be achieved by introducing quantum error-correcting codes. Here, we experimentally realize an automated error correction code and demonstrate the nondestructive discrimination of GHZ states in IBM 5-qubit quantum computer. After performing quantum state tomography, we obtain the experimental results with a high fidelity. Finally, we generalize the investigated code for maximally entangled n-qudit case, which could both detect and automatically correct any arbitrary phase-change error, or any phase-flip error, or any bit-flip error, or combined error of all types of error.

Hyperspectral surface materials map of quadrangle 3464, Shahrak (411) and Kasi (412) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3264, Naw Zad-Musa Qala (423) and Dihrawud (424) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3164, Lashkar Gah (605) and Kandahar (606) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3162, Chakhansur (603) and Kotalak (604) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3568, Pul-e Khumri (503) and Charikar (504) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3166, Jaldak (701) and Maruf-Nawa (702) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Giles, Stuart A.; Johnson, Michaela R.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3366, Gizab (513) and Nawer (514) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3362, Shindand (415) and Tulak (416) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Giles, Stuart A.; Johnson, Michaela R.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3262, Farah (421) and Hokumat-e-pur-Chaman (422) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3564, Jowand (405) and Gurziwan (406) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3364, Pasaband (417) and Markaz-e Kajiran (418) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.

Hyperspectral surface materials map of quadrangle 3368, Ghazni (515) and Gardez (516) quadrangles, Afghanistan, showing iron-bearing minerals and other materials

USGS Publications Warehouse

King, Trude V.V.; Hoefen, Todd M.; Kokaly, Raymond F.; Livo, Keith E.; Johnson, Michaela R.; Giles, Stuart A.

2013-01-01

This map shows the spatial distribution of selected iron-bearing minerals and other materials derived from analysis of airborne HyMap™ imaging spectrometer (hyperspectral) data of Afghanistan collected in late 2007. This map is one in a series of U.S. Geological Survey/Afghanistan Geological Survey quadrangle maps covering Afghanistan. Flown at an altitude of 50,000 feet (15,240 meters (m)), the HyMap™ imaging spectrometer measured reflected sunlight in 128 channels, covering wavelengths between 0.4 and 2.5 μm. The data were georeferenced, atmospherically corrected and converted to apparent surface reflectance, empirically adjusted using ground-based reflectance measurements, and combined into a mosaic with 23-m pixel spacing. Variations in water vapor and dust content of the atmosphere, in solar angle, and in surface elevation complicated correction; therefore, some classification differences may be present between adjacent flight lines. The reflectance spectrum of each pixel of HyMap™ imaging spectrometer data was compared to the reference materials in a spectral library of minerals, vegetation, water, and other materials. Minerals occurring abundantly at the surface and those having unique spectral features were easily detected and discriminated, while minerals having slightly different compositions but similar spectral features were less easily discriminated; thus, some map classes consist of several minerals having similar spectra, such as “Goethite and jarosite.” A designation of “Not classified” was assigned to the pixel when there was no match with reference spectra.