Psychometric properties of the mobility inventory for agoraphobia: convergent, discriminant, and criterion-related validity.

PubMed

Chambless, Dianne L; Sharpless, Brian A; Rodriguez, Dianeth; McCarthy, Kevin S; Milrod, Barbara L; Khalsa, Shabad-Ratan; Barber, Jacques P

2011-12-01

Aims of this study were (a) to summarize the psychometric literature on the Mobility Inventory for Agoraphobia (MIA), (b) to examine the convergent and discriminant validity of the MIA's Avoidance Alone and Avoidance Accompanied rating scales relative to clinical severity ratings of anxiety disorders from the Anxiety Disorders Interview Schedule (ADIS), and (c) to establish a cutoff score indicative of interviewers' diagnosis of agoraphobia for the Avoidance Alone scale. A meta-analytic synthesis of 10 published studies yielded positive evidence for internal consistency and convergent and discriminant validity of the scales. Participants in the present study were 129 people with a diagnosis of panic disorder. Internal consistency was excellent for this sample, α=.95 for AAC and .96 for AAL. When the MIA scales were correlated with interviewer ratings, evidence for convergent and discriminant validity for AAL was strong (convergent r with agoraphobia severity ratings=.63 vs. discriminant rs of .10-.29 for other anxiety disorders) and more modest but still positive for AAC (.54 vs. .01-.37). Receiver operating curve analysis indicated that the optimal operating point for AAL as an indicator of ADIS agoraphobia diagnosis was 1.61, which yielded sensitivity of .87 and specificity of .73. Copyright © 2011. Published by Elsevier Ltd.

Psychometric Properties of the Mobility Inventory for Agoraphobia: Convergent, Discriminant, and Criterion-Related Validity

PubMed Central

Chambless, Dianne L.; Sharpless, Brian A.; Rodriguez, Dianeth; McCarthy, Kevin S.; Milrod, Barbara L.; Khalsa, Shabad-Ratan; Barber, Jacques P.

2012-01-01

Aims of this study were (a) to summarize the psychometric literature on the Mobility Inventory for Agoraphobia (MIA), (b) to examine the convergent and discriminant validity of the MIA’s Avoidance Alone and Avoidance Accompanied rating scales relative to clinical severity ratings of anxiety disorders from the Anxiety Disorders Interview Schedule (ADIS), and (c) to establish a cutoff score indicative of interviewers’ diagnosis of agoraphobia for the Avoidance Alone scale. A meta-analytic synthesis of 10 published studies yielded positive evidence for internal consistency and convergent and discriminant validity of the scales. Participants in the present study were 129 people with a diagnosis of panic disorder. Internal consistency was excellent for this sample, α = .95 for AAC and .96 for AAL. When the MIA scales were correlated with interviewer ratings, evidence for convergent and discriminant validity for AAL was strong (convergent r with agoraphobia severity ratings = .63 vs. discriminant rs of .10-.29 for other anxiety disorders) and more modest but still positive for AAC (.54 vs. .01-.37). Receiver operating curve analysis indicated that the optimal operating point for AAL as an indicator of ADIS agoraphobia diagnosis was 1.61, which yielded sensitivity of .87 and specificity of .73. PMID:22035997

Sex differences in discriminative power of volleyball game-related statistics.

PubMed

João, Paulo Vicente; Leite, Nuno; Mesquita, Isabel; Sampaio, Jaime

2010-12-01

To identify sex differences in volleyball game-related statistics, the game-related statistics of several World Championships in 2007 (N=132) were analyzed using the software VIS from the International Volleyball Federation. Discriminant analysis was used to identify the game-related statistics which better discriminated performances by sex. Analysis yielded an emphasis on fault serves (SC = -.40), shot spikes (SC = .40), and reception digs (SC = .31). Specific robust numbers represent that considerable variability was evident in the game-related statistics profile, as men's volleyball games were better associated with terminal actions (errors of service), and women's volleyball games were characterized by continuous actions (in defense and attack). These differences may be related to the anthropometric and physiological differences between women and men and their influence on performance profiles.

Comparison of discriminant analysis methods: Application to occupational exposure to particulate matter

NASA Astrophysics Data System (ADS)

Ramos, M. Rosário; Carolino, E.; Viegas, Carla; Viegas, Sandra

2016-06-01

Health effects associated with occupational exposure to particulate matter have been studied by several authors. In this study were selected six industries of five different areas: Cork company 1, Cork company 2, poultry, slaughterhouse for cattle, riding arena and production of animal feed. The measurements tool was a portable device for direct reading. This tool provides information on the particle number concentration for six different diameters, namely 0.3 µm, 0.5 µm, 1 µm, 2.5 µm, 5 µm and 10 µm. The focus on these features is because they might be more closely related with adverse health effects. The aim is to identify the particles that better discriminate the industries, with the ultimate goal of classifying industries regarding potential negative effects on workers' health. Several methods of discriminant analysis were applied to data of occupational exposure to particulate matter and compared with respect to classification accuracy. The selected methods were linear discriminant analyses (LDA); linear quadratic discriminant analysis (QDA), robust linear discriminant analysis with selected estimators (MLE (Maximum Likelihood Estimators), MVE (Minimum Volume Elipsoid), "t", MCD (Minimum Covariance Determinant), MCD-A, MCD-B), multinomial logistic regression and artificial neural networks (ANN). The predictive accuracy of the methods was accessed through a simulation study. ANN yielded the highest rate of classification accuracy in the data set under study. Results indicate that the particle number concentration of diameter size 0.5 µm is the parameter that better discriminates industries.

Everyday discrimination and mood and substance use disorders: a latent profile analysis with African Americans and Caribbean Blacks.

PubMed

Clark, Trenette T; Salas-Wright, Christopher P; Vaughn, Michael G; Whitfield, Keith E

2015-01-01

Perceived discrimination is a major source of health-related stress. The purpose of this study was to model the heterogeneity of everyday-discrimination experiences among African American and Caribbean Blacks and to identify differences in the prevalence of mood and substance use outcomes, including generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder among the identified subgroups. The study uses data from the National Survey of American Life obtained from a sample of African American and Caribbean Black respondents (N=4,462) between 18 and 65 years. We used latent profile analysis and multinomial regression analyses to identify and validate latent subgroups and test hypotheses, yielding 4 classes of perceived everyday discrimination: Low Discrimination, Disrespect and Condescension, General Discrimination, and Chronic Discrimination. Findings show significant differences exist between the Low Discrimination and General Discrimination classes for major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Moreover, we find significant differences exist between the Low Discrimination and Chronic Discrimination classes for the four disorders examined. Compared with the Chronic Discrimination class, members of the other classes were significantly less likely to meet criteria for generalized anxiety disorder, major depressive disorder, alcohol-use disorder, and illicit drug-use disorder. Findings suggest elevated levels of discrimination increase risk for mood and substance-use disorders. Importantly, results suggest the prevalence of mood and substance-use disorders is a function of the type and frequency of discrimination that individuals experience. Copyright © 2014 Elsevier Ltd. All rights reserved.

Field hyperspectral data analysis for discriminating spectral behavior of tea plantations under various management practices

NASA Astrophysics Data System (ADS)

Kumar, Amit; Manjunath, K. R.; Meenakshi; Bala, Renu; Sud, R. K.; Singh, R. D.; Panigrahy, Sushma

2013-08-01

The quality and yield of tea depends upon management of tea plantations, which takes into account the factors like type, age of plantation, growth stage, pruning status, light conditions, and disease incidence. Recognizing the importance of hyperspectral data in detecting minute spectral variations in vegetation, the present study was conducted to explore applicability of such data in evaluating these factors. Also stepwise discriminant analysis and principal component analysis were conducted to identify the appropriate bands for accessing the above mentioned factors. The Green region followed by NIR region was found as most appropriate best band for discriminating different types of tea plants, and the tea in sunlit and shade condition. For discriminating age of plantation, growth stage of tea, and diseased and healthy bush, Blue region was most appropriate. The Red and NIR regions were best bands to discriminate pruned and unpruned tea. The study concluded that field hyperspectral data can be efficiently used to know the plantation that need special care and may be an indicator of tea productivity. The spectral signature of these characteristics of tea plantations may also be used to classify the hyperspectral satellite data to derive these parameters at regional scale.

Limitations to photosynthesis under light and heat stress in three high-yielding wheat genotypes.

PubMed

Monneveux, Philippe; Pastenes, Claudio; Reynolds, Matthew P

2003-06-01

Three high-yielding wheat genotypes (T. aestivum L., c.v. Siete Cerros, Seri and Bacanora, released in 1966, 1982 and 1988, respectively) were grown under irrigation in two high radiation, low relative humidity environments (Tlaltizapan and Ciudad Obregon CIMMYT experimental stations, Mexico). Gas exchange and fluorescence parameters were assessed on the flag leaf during the day. Carbon isotope discrimination (delta) was analysed in flag leaf at anthesis and in grain at maturity. In both environments, gas exchange and fluorescence parameters varied markedly with irradiance and temperature. Analysis of their respective variation indicated the occurrence of photo-respiration and photo-inhibition, particularly in Tlaltizapan, the warmest environment, and in Siete Cerros. In Ciudad Obregon (high-yielding environment) lower Ci (internal CO2 concentration) and delta La (carbon isotope discrimination of the leaf) suggested a higher intrinsic photosynthetic capacity in the variety Bacanora. Higher yield of this genotype was also associated with higher Fv'/Fo' (ratio of photochemical and non photochemical rate constants in the light) and Fm'/Fm (ratio of the non photochemical rate constants in the dark and light adapted state).

¹H NMR spectroscopy reveals the effect of genotype and growth conditions on composition of sea buckthorn (Hippophaë rhamnoides L.) berries.

PubMed

Kortesniemi, Maaria; Sinkkonen, Jari; Yang, Baoru; Kallio, Heikki

2014-03-15

¹H NMR spectroscopy and multivariate data analysis were applied to the metabolic profiling and discrimination of wild sea buckthorn (Hippophaë rhamnoides L.) berries from different locations in Finland (subspecies (ssp.) rhamnoides) and China (ssp. sinensis). Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) showed discrimination of the two subspecies and different growth sites. The discrimination of ssp. rhamnoides was mainly associated with typically higher temperature, radiation and humidity and lower precipitation in the south, yielding higher levels of O-ethyl β-d-glucopyranoside and d-glucose, and lower levels of malic, quinic and ascorbic acids. Significant metabolic differences (p<0.05) in genetically identical berries were observed between latitudes 60° and 67° north in Finland. High altitudes (> 2,000 m) correlated with greater levels of malic and ascorbic acids in ssp. sinensis. The NMR metabolomics approach applied here is effective for identification of metabolites, geographical origin and subspecies of sea buckthorn berries. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discriminative Nonlinear Analysis Operator Learning: When Cosparse Model Meets Image Classification.

PubMed

Wen, Zaidao; Hou, Biao; Jiao, Licheng

2017-05-03

Linear synthesis model based dictionary learning framework has achieved remarkable performances in image classification in the last decade. Behaved as a generative feature model, it however suffers from some intrinsic deficiencies. In this paper, we propose a novel parametric nonlinear analysis cosparse model (NACM) with which a unique feature vector will be much more efficiently extracted. Additionally, we derive a deep insight to demonstrate that NACM is capable of simultaneously learning the task adapted feature transformation and regularization to encode our preferences, domain prior knowledge and task oriented supervised information into the features. The proposed NACM is devoted to the classification task as a discriminative feature model and yield a novel discriminative nonlinear analysis operator learning framework (DNAOL). The theoretical analysis and experimental performances clearly demonstrate that DNAOL will not only achieve the better or at least competitive classification accuracies than the state-of-the-art algorithms but it can also dramatically reduce the time complexities in both training and testing phases.

Trial application of oxygen and carbon isotope analysis in tooth enamel for identification of past-war victims for discriminating between Japanese and US soldiers.

PubMed

Someda, Hidetoshi; Gakuhari, Takashi; Akai, Junko; Araki, Yoshiyuki; Kodera, Tsutomu; Tsumatori, Gentaro; Kobayashi, Yasushi; Matsunaga, Satoru; Abe, Shinichi; Hashimoto, Masatsugu; Saito, Megumi; Yoneda, Minoru; Ishida, Hajime

2016-04-01

Stable isotope analysis has undergone rapid development in recent years and yielded significant results in the field of forensic sciences. In particular, carbon and oxygen isotopic ratios in tooth enamel obtained from human remains can provide useful information for the crosschecking of morphological and DNA analyses and facilitate rapid on-site prescreening for the identification of remains. This study analyzes carbon and oxygen isotopic ratios in the tooth enamel of Japanese people born between 1878 and 1930, in order to obtain data for methodological differentiation of Japanese and American remains from the Second World War. The carbon and oxygen isotopic ratios in the tooth enamel of the examined Japanese individuals are compared to previously reported data for American individuals (born post WWII), and statistical analysis is conducted using a discrimination method based on a logistic regression analysis. The discrimination between the Japanese and US populations, including Alaska and Hawaii, is found to be highly accurate. Thus, the present method has potential as a discrimination technique for both populations for use in the examination of mixed remains comprising Japanese and American fallen soldiers. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Polarimetric Decomposition Analysis of the Deepwater Horizon Oil Slick Using L-Band UAVSAR Data

NASA Technical Reports Server (NTRS)

Jones, Cathleen; Minchew, Brent; Holt, Benjamin

2011-01-01

We report here an analysis of the polarization dependence of L-band radar backscatter from the main slick of the Deepwater Horizon oil spill, with specific attention to the utility of polarimetric decomposition analysis for discrimination of oil from clean water and identification of variations in the oil characteristics. For this study we used data collected with the UAVSAR instrument from opposing look directions directly over the main oil slick. We find that both the Cloude-Pottier and Shannon entropy polarimetric decomposition methods offer promise for oil discrimination, with the Shannon entropy method yielding the same information as contained in the Cloude-Pottier entropy and averaged in tensity parameters, but with significantly less computational complexity

Discriminating semiarid vegetation using airborne imaging spectrometer data - A preliminary assessment

NASA Technical Reports Server (NTRS)

Thomas, Randall W.; Ustin, Susan L.

1987-01-01

A preliminary assessment was made of Airborne Imaging Spectrometer (AIS) data for discriminating and characterizing vegetation in a semiarid environment. May and October AIS data sets were acquired over a large alluvial fan in eastern California, on which were found Great Basin desert shrub communities. Maximum likelihood classification of a principal components representation of the May AIS data enabled discrimination of subtle spatial detail in images relating to vegetation and soil characteristics. The spatial patterns in the May AIS classification were, however, too detailed for complete interpretation with existing ground data. A similar analysis of the October AIS data yielded poor results. Comparison of AIS results with a similar analysis of May Landsat Thematic Mapper data showed that the May AIS data contained approximately three to four times as much spectrally coherent information. When only two shortwave infrared TM bands were used, results were similar to those from AIS data acquired in October.

Improving Efficiency in Multi-Strange Baryon Reconstruction in d-Au at STAR

NASA Astrophysics Data System (ADS)

Leight, William

2003-10-01

We report preliminary multi-strange baryon measurements for d-Au collisions recorded at RHIC by the STAR experiment. After using classical topological analysis, in which cuts for each discriminating variable are adjusted by hand, we investigate improvements in signal-to-noise optimization using Linear Discriminant Analysis (LDA). LDA is an algorithm for finding, in the n-dimensional space of the n discriminating variables, the axis on which the signal and noise distributions are most separated. LDA is the first step in moving towards more sophisticated techniques for signal-to-noise optimization, such as Artificial Neural Nets. Due to the relatively low background and sufficiently high yields of d-Au collisions, they form an ideal system to study these possibilities for improving reconstruction methods. Such improvements will be extremely important for forthcoming Au-Au runs in which the size of the combinatoric background is a major problem in reconstruction efforts.

Origin Discrimination of Osmanthus fragrans var. thunbergii Flowers using GC-MS and UPLC-PDA Combined with Multivariable Analysis Methods.

PubMed

Zhou, Fei; Zhao, Yajing; Peng, Jiyu; Jiang, Yirong; Li, Maiquan; Jiang, Yuan; Lu, Baiyi

2017-07-01

Osmanthus fragrans flowers are used as folk medicine and additives for teas, beverages and foods. The metabolites of O. fragrans flowers from different geographical origins were inconsistent in some extent. Chromatography and mass spectrometry combined with multivariable analysis methods provides an approach for discriminating the origin of O. fragrans flowers. To discriminate the Osmanthus fragrans var. thunbergii flowers from different origins with the identified metabolites. GC-MS and UPLC-PDA were conducted to analyse the metabolites in O. fragrans var. thunbergii flowers (in total 150 samples). Principal component analysis (PCA), soft independent modelling of class analogy analysis (SIMCA) and random forest (RF) analysis were applied to group the GC-MS and UPLC-PDA data. GC-MS identified 32 compounds common to all samples while UPLC-PDA/QTOF-MS identified 16 common compounds. PCA of the UPLC-PDA data generated a better clustering than PCA of the GC-MS data. Ten metabolites (six from GC-MS and four from UPLC-PDA) were selected as effective compounds for discrimination by PCA loadings. SIMCA and RF analysis were used to build classification models, and the RF model, based on the four effective compounds (caffeic acid derivative, acteoside, ligustroside and compound 15), yielded better results with the classification rate of 100% in the calibration set and 97.8% in the prediction set. GC-MS and UPLC-PDA combined with multivariable analysis methods can discriminate the origin of Osmanthus fragrans var. thunbergii flowers. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Integration of statistical and physiological analyses of adaptation of near-isogenic barley lines.

PubMed

Romagosa, I; Fox, P N; García Del Moral, L F; Ramos, J M; García Del Moral, B; Roca de Togores, F; Molina-Cano, J L

1993-08-01

Seven near-isogenic barley lines, differing for three independent mutant genes, were grown in 15 environments in Spain. Genotype x environment interaction (G x E) for grain yield was examined with the Additive Main Effects and Multiplicative interaction (AMMI) model. The results of this statistical analysis of multilocation yield-data were compared with a morpho-physiological characterization of the lines at two sites (Molina-Cano et al. 1990). The first two principal component axes from the AMMI analysis were strongly associated with the morpho-physiological characters. The independent but parallel discrimination among genotypes reflects genetic differences and highlights the power of the AMMI analysis as a tool to investigate G x E. Characters which appear to be positively associated with yield in the germplasm under study could be identified for some environments.

Spectral analysis of winter wheat leaves for detection and differentiation of diseases and insects

USDA-ARS?s Scientific Manuscript database

Yellow rust (Puccinia striiformis f. sp. Tritici), powdery mildew (Blumeria graminis) and wheat aphid (Sitobion avenae F.) infestation are three serious conditions that have a severe impact on yield and grain quality of winter wheat worldwide. Discrimination among these three stressors is of practic...

Maximizing Enrollment Yield through Financial Aid Packaging Policies

ERIC Educational Resources Information Center

Spaulding, Randy; Olswang, Steven

2005-01-01

Using institutional data, this paper presents a model to enable researchers and enrollment managers to assess the effectiveness of financial aid packaging policies in light of student characteristics and institutional market position. The model uses discriminant analysis and a series of hypothetical financial aid award scenarios to predict the…

Impairments of colour vision induced by organic solvents: a meta-analysis study.

PubMed

Paramei, Galina V; Meyer-Baron, Monika; Seeber, Andreas

2004-09-01

The impairment of colour discrimination induced by occupational exposure to toluene, styrene and mixtures of organic solvents is reviewed and analysed using a meta-analytical approach. Thirty-nine studies were surveyed covering a wide range of exposure conditions. Those studies using the Lanthony Panel D-15 desaturated test (D-15d) were further considered. From these for 15 samples data on colour discrimination ability (Colour Confusion Index, CCI) and exposure levels were provided, required for the meta-analysis. In accordance with previously reported higher CCI values for the exposed groups, the computations yielded positive effect sizes for 13 of the 15 samples, indicating that in the great majority of the studies the exposed groups showed inferior colour discrimination. However, the meta-analysis showed great variation in effect sizes across the studies. Possible reasons for inconsistency among the reported findings are discussed. These pertain to exposure-related parameters, as well as to confounders such as conditions of test administration and characteristics of subject samples. Those factors vary considerably among the studies and might have greatly contributed to divergence in measured colour vision capacity, thereby obscuring consistent effects of organic solvents on colour discrimination.

On the Discriminant Analysis in the 2-Populations Case

NASA Astrophysics Data System (ADS)

Rublík, František

2008-01-01

The empirical Bayes Gaussian rule, which in the normal case yields good values of the probability of total error, may yield high values of the maximum probability error. From this point of view the presented modified version of the classification rule of Broffitt, Randles and Hogg appears to be superior. The modification included in this paper is termed as a WR method, and the choice of its weights is discussed. The mentioned methods are also compared with the K nearest neighbours classification rule.

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

Robust linear discriminant analysis with distance based estimators

NASA Astrophysics Data System (ADS)

Lim, Yai-Fung; Yahaya, Sharipah Soaad Syed; Ali, Hazlina

2017-11-01

Linear discriminant analysis (LDA) is one of the supervised classification techniques concerning relationship between a categorical variable and a set of continuous variables. The main objective of LDA is to create a function to distinguish between populations and allocating future observations to previously defined populations. Under the assumptions of normality and homoscedasticity, the LDA yields optimal linear discriminant rule (LDR) between two or more groups. However, the optimality of LDA highly relies on the sample mean and pooled sample covariance matrix which are known to be sensitive to outliers. To alleviate these conflicts, a new robust LDA using distance based estimators known as minimum variance vector (MVV) has been proposed in this study. The MVV estimators were used to substitute the classical sample mean and classical sample covariance to form a robust linear discriminant rule (RLDR). Simulation and real data study were conducted to examine on the performance of the proposed RLDR measured in terms of misclassification error rates. The computational result showed that the proposed RLDR is better than the classical LDR and was comparable with the existing robust LDR.

Predictor of increase in caregiver burden for disabled elderly at home.

PubMed

Okamoto, Kazushi; Harasawa, Yuko

2009-01-01

In order to classify the caregivers at high risk of increase in their burden early, linear discriminant analysis was performed to obtain an effective discriminant model for differentiation of the presence or absence of increase in caregiver burden. The data obtained by self-administered questionnaire from 193 caregivers of frail elderly from January to February of 2005 were used. The discriminant analysis yielded a statistically significant function explaining 35.0% (Rc=0.59; d.f.=6; p=0.0001). The configuration indicated that the psychological predictors of change in caregiver burden with much perceived stress (1.47), high caregiver burden at baseline (1.28), emotional control (0.75), effort to achieve (-0.28), symptomatic depression (0.20) and "ikigai" (purpose in life) (0.18) made statistically significant contributions to the differentiation between no increase and increase in caregiver burden. The discriminant function showed a sensitivity of 86% and specificity of 81%, and successfully classified 83% of the caregivers. The function at baseline is a simple and useful method for screening of an increase in caregiver burden among caregivers for the frail elderly at home.

Recent applications of multivariate data analysis methods in the authentication of rice and the most analyzed parameters: A review.

PubMed

Maione, Camila; Barbosa, Rommel Melgaço

2018-01-24

Rice is one of the most important staple foods around the world. Authentication of rice is one of the most addressed concerns in the present literature, which includes recognition of its geographical origin and variety, certification of organic rice and many other issues. Good results have been achieved by multivariate data analysis and data mining techniques when combined with specific parameters for ascertaining authenticity and many other useful characteristics of rice, such as quality, yield and others. This paper brings a review of the recent research projects on discrimination and authentication of rice using multivariate data analysis and data mining techniques. We found that data obtained from image processing, molecular and atomic spectroscopy, elemental fingerprinting, genetic markers, molecular content and others are promising sources of information regarding geographical origin, variety and other aspects of rice, being widely used combined with multivariate data analysis techniques. Principal component analysis and linear discriminant analysis are the preferred methods, but several other data classification techniques such as support vector machines, artificial neural networks and others are also frequently present in some studies and show high performance for discrimination of rice.

The prediction of swimming performance in competition from behavioral information.

PubMed

Rushall, B S; Leet, D

1979-06-01

The swimming performances of the Canadian Team at the 1976 Olympic Games were categorized as being improved or worse than previous best times in the events contested. The two groups had been previously assessed on the Psychological Inventories for Competitive Swimmers. A stepwise multiple-discriminant analysis of the inventory responses revealed that 13 test questions produced a perfect discrimination of group membership. The resultant discriminant functions for predicting performance classification were applied to the test responses of 157 swimmers at the 1977 Canadian Winter National Swimming Championships. Using the same performance classification criteria the accuracy of prediction was not better than chance in three of four sex by performance classifications. This yielded a failure to locate a set of behavioral factors which determine swimming performance improvements in elite competitive circumstances. The possibility of sets of factors which do not discriminate between performances in similar environments or between similar groups of swimmers was raised.

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.

Selecting predictors for discriminant analysis of species performance: an example from an amphibious softwater plant.

PubMed

Vanderhaeghe, F; Smolders, A J P; Roelofs, J G M; Hoffmann, M

2012-03-01

Selecting an appropriate variable subset in linear multivariate methods is an important methodological issue for ecologists. Interest often exists in obtaining general predictive capacity or in finding causal inferences from predictor variables. Because of a lack of solid knowledge on a studied phenomenon, scientists explore predictor variables in order to find the most meaningful (i.e. discriminating) ones. As an example, we modelled the response of the amphibious softwater plant Eleocharis multicaulis using canonical discriminant function analysis. We asked how variables can be selected through comparison of several methods: univariate Pearson chi-square screening, principal components analysis (PCA) and step-wise analysis, as well as combinations of some methods. We expected PCA to perform best. The selected methods were evaluated through fit and stability of the resulting discriminant functions and through correlations between these functions and the predictor variables. The chi-square subset, at P < 0.05, followed by a step-wise sub-selection, gave the best results. In contrast to expectations, PCA performed poorly, as so did step-wise analysis. The different chi-square subset methods all yielded ecologically meaningful variables, while probable noise variables were also selected by PCA and step-wise analysis. We advise against the simple use of PCA or step-wise discriminant analysis to obtain an ecologically meaningful variable subset; the former because it does not take into account the response variable, the latter because noise variables are likely to be selected. We suggest that univariate screening techniques are a worthwhile alternative for variable selection in ecology. © 2011 German Botanical Society and The Royal Botanical Society of the Netherlands.

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.

Development and Validation of a Racial Discrimination Measure for Cambodian American Adolescents

PubMed Central

Sangalang, Cindy C.; Chen, Angela C. C.; Kulis, Stephen S.; Yabiku, Scott T.

2015-01-01

To date, the majority of studies examining experiences of racial discrimination among youth use measures initially developed for African American and Latino adults or college students. Few studies have attended to the ways in which discrimination experiences may be unique for Asian American youth, particularly subgroups such as Southeast Asians. The purpose of this study was twofold: (a) to describe the development of a racial discrimination measure using community-based participatory research with Cambodian American adolescents and (b) to psychometrically test the measure with respect to validity and reliability. This research used mixed-methods and comprised 3 phases. Phase 1 consisted of qualitative focus group research to assess community-identified needs. Phase 2 included quantitative survey development with community members and resulted in an 18-item measure assessing the frequency of ethnicity-based discrimination. Phase 3 involved psychometric testing of the measure’s validity and reliability (n = 423). Exploratory factor analysis procedures yielded a 3-factor structure describing peer, school, and police discrimination from all items, capturing 96% of the combined variance. Using confirmatory factor analysis, the data demonstrated good fit with the 3-factor structure (CFI = .98; RMSEA = .054), with factor loadings ranging from .59 to .96 and all estimates statistically significant at the p < .05 level. Correlational analyses of racial discrimination subfactors and depression supported concurrent validity. In sum, this measure can be used to examine the degree and sources of racial discrimination reported by Cambodian American adolescents and potentially other adolescents of Southeast Asian descent living in diverse urban communities. PMID:26388972

Partial Least Squares for Discrimination in fMRI Data

PubMed Central

Andersen, Anders H.; Rayens, William S.; Liu, Yushu; Smith, Charles D.

2011-01-01

Multivariate methods for discrimination were used in the comparison of brain activation patterns between groups of cognitively normal women who are at either high or low Alzheimer's disease risk based on family history and apolipoprotein-E4 status. Linear discriminant analysis (LDA) was preceded by dimension reduction using either principal component analysis (PCA), partial least squares (PLS), or a new oriented partial least squares (OrPLS) method. The aim was to identify a spatial pattern of functionally connected brain regions that was differentially expressed by the risk groups and yielded optimal classification accuracy. Multivariate dimension reduction is required prior to LDA when the data contains more feature variables than there are observations on individual subjects. Whereas PCA has been commonly used to identify covariance patterns in neuroimaging data, this approach only identifies gross variability and is not capable of distinguishing among-groups from within-groups variability. PLS and OrPLS provide a more focused dimension reduction by incorporating information on class structure and therefore lead to more parsimonious models for discrimination. Performance was evaluated in terms of the cross-validated misclassification rates. The results support the potential of using fMRI as an imaging biomarker or diagnostic tool to discriminate individuals with disease or high risk. PMID:22227352

Automatic telangiectasia analysis in dermoscopy images using adaptive critic design.

PubMed

Cheng, B; Stanley, R J; Stoecker, W V; Hinton, K

2012-11-01

Telangiectasia, tiny skin vessels, are important dermoscopy structures used to discriminate basal cell carcinoma (BCC) from benign skin lesions. This research builds off of previously developed image analysis techniques to identify vessels automatically to discriminate benign lesions from BCCs. A biologically inspired reinforcement learning approach is investigated in an adaptive critic design framework to apply action-dependent heuristic dynamic programming (ADHDP) for discrimination based on computed features using different skin lesion contrast variations to promote the discrimination process. Lesion discrimination results for ADHDP are compared with multilayer perception backpropagation artificial neural networks. This study uses a data set of 498 dermoscopy skin lesion images of 263 BCCs and 226 competitive benign images as the input sets. This data set is extended from previous research [Cheng et al., Skin Research and Technology, 2011, 17: 278]. Experimental results yielded a diagnostic accuracy as high as 84.6% using the ADHDP approach, providing an 8.03% improvement over a standard multilayer perception method. We have chosen BCC detection rather than vessel detection as the endpoint. Although vessel detection is inherently easier, BCC detection has potential direct clinical applications. Small BCCs are detectable early by dermoscopy and potentially detectable by the automated methods described in this research. © 2011 John Wiley & Sons A/S.

Non-Destructive Quality Evaluation of Pepper (Capsicum annuum L.) Seeds Using LED-Induced Hyperspectral Reflectance Imaging

PubMed Central

Mo, Changyeun; Kim, Giyoung; Lee, Kangjin; Kim, Moon S.; Cho, Byoung-Kwan; Lim, Jongguk; Kang, Sukwon

2014-01-01

In this study, we developed a viability evaluation method for pepper (Capsicum annuum L.) seeds based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400–700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares–discriminant analysis (PLS-DA) model is developed to classify viable and non-viable seeds. Four spectral ranges generated with four types of LEDs (blue, green, red, and RGB), which were pretreated using various methods, are investigated to develop the classification models. The optimal PLS-DA model based on the standard normal variate for RGB LED illumination (400–700 nm) yields discrimination accuracies of 96.7% and 99.4% for viable seeds and nonviable seeds, respectively. The use of images based on the PLS-DA model with the first-order derivative of a 31.5-nm gap for red LED illumination (600–700 nm) yields 100% discrimination accuracy for both viable and nonviable seeds. The results indicate that a hyperspectral imaging technique based on LED light can be potentially applied to high-quality pepper seed sorting. PMID:24763251

Non-destructive quality evaluation of pepper (Capsicum annuum L.) seeds using LED-induced hyperspectral reflectance imaging.

PubMed

Mo, Changyeun; Kim, Giyoung; Lee, Kangjin; Kim, Moon S; Cho, Byoung-Kwan; Lim, Jongguk; Kang, Sukwon

2014-04-24

In this study, we developed a viability evaluation method for pepper (Capsicum annuum L.) seeds based on hyperspectral reflectance imaging. The reflectance spectra of pepper seeds in the 400-700 nm range are collected from hyperspectral reflectance images obtained using blue, green, and red LED illumination. A partial least squares-discriminant analysis (PLS-DA) model is developed to classify viable and non-viable seeds. Four spectral ranges generated with four types of LEDs (blue, green, red, and RGB), which were pretreated using various methods, are investigated to develop the classification models. The optimal PLS-DA model based on the standard normal variate for RGB LED illumination (400-700 nm) yields discrimination accuracies of 96.7% and 99.4% for viable seeds and nonviable seeds, respectively. The use of images based on the PLS-DA model with the first-order derivative of a 31.5-nm gap for red LED illumination (600-700 nm) yields 100% discrimination accuracy for both viable and nonviable seeds. The results indicate that a hyperspectral imaging technique based on LED light can be potentially applied to high-quality pepper seed sorting.

Photoacoustic spectroscopy based investigatory approach to discriminate breast cancer from normal: a pilot study

NASA Astrophysics Data System (ADS)

Priya, Mallika; Rao, Bola Sadashiva Satish; Chandra, Subhash; Ray, Satadru; Mathew, Stanley; Datta, Anirbit; Nayak, Subramanya G.; Mahato, Krishna Kishore

2016-02-01

In spite of many efforts for early detection of breast cancer, there is still lack of technology for immediate implementation. In the present study, the potential photoacoustic spectroscopy was evaluated in discriminating breast cancer from normal, involving blood serum samples seeking early detection. Three photoacoustic spectra in time domain were recorded from each of 20 normal and 20 malignant samples at 281nm pulsed laser excitations and a total of 120 spectra were generated. The time domain spectra were then Fast Fourier Transformed into frequency domain and 116.5625 - 206.875 kHz region was selected for further analysis using a combinational approach of wavelet, PCA and logistic regression. Initially, wavelet analysis was performed on the FFT data and seven features (mean, median, area under the curve, variance, standard deviation, skewness and kurtosis) from each were extracted. PCA was then performed on the feature matrix (7x120) for discriminating malignant samples from the normal by plotting a decision boundary using logistic regression analysis. The unsupervised mode of classification used in the present study yielded specificity and sensitivity values of 100% in each respectively with a ROC - AUC value of 1. The results obtained have clearly demonstrated the capability of photoacoustic spectroscopy in discriminating cancer from the normal, suggesting its possible clinical implications.

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

NASA Astrophysics Data System (ADS)

Phinyomark, A.; Hu, H.; Phukpattaranont, P.; Limsakul, C.

2012-01-01

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier.

Geodesic topological analysis of trabecular bone microarchitecture from high-spatial resolution magnetic resonance images.

PubMed

Carballido-Gamio, Julio; Krug, Roland; Huber, Markus B; Hyun, Ben; Eckstein, Felix; Majumdar, Sharmila; Link, Thomas M

2009-02-01

In vivo assessment of trabecular bone microarchitecture could improve the prediction of fracture risk and the efficacy of osteoporosis treatment and prevention. Geodesic topological analysis (GTA) is introduced as a novel technique to quantify the trabecular bone microarchitecture from high-spatial resolution magnetic resonance (MR) images. Trabecular bone parameters that quantify the scale, topology, and anisotropy of the trabecular bone network in terms of its junctions are the result of GTA. The reproducibility of GTA was tested with in vivo images of human distal tibiae and radii (n = 6) at 1.5 Tesla; and its ability to discriminate between subjects with and without vertebral fracture was assessed with ex vivo images of human calcanei at 1.5 and 3.0 Tesla (n = 30). GTA parameters yielded an average reproducibility of 4.8%, and their individual areas under the curve (AUC) of the receiver operating characteristic curve analysis for fracture discrimination performed better at 3.0 than at 1.5 Tesla reaching values of up to 0.78 (p < 0.001). Logistic regression analysis demonstrated that fracture discrimination was improved by combining GTA parameters, and that GTA combined with bone mineral density (BMD) allow for better discrimination than BMD alone (AUC = 0.95; p < 0.001). Results indicate that GTA can substantially contribute in studies of osteoporosis involving imaging of the trabecular bone microarchitecture. Copyright 2009 Wiley-Liss, Inc.

Forensic Discrimination of Latent Fingerprints Using Laser-Induced Breakdown Spectroscopy (LIBS) and Chemometric Approaches.

PubMed

Yang, Jun-Ho; Yoh, Jack J

2018-01-01

A novel technique is reported for separating overlapping latent fingerprints using chemometric approaches that combine laser-induced breakdown spectroscopy (LIBS) and multivariate analysis. The LIBS technique provides the capability of real time analysis and high frequency scanning as well as the data regarding the chemical composition of overlapping latent fingerprints. These spectra offer valuable information for the classification and reconstruction of overlapping latent fingerprints by implementing appropriate statistical multivariate analysis. The current study employs principal component analysis and partial least square methods for the classification of latent fingerprints from the LIBS spectra. This technique was successfully demonstrated through a classification study of four distinct latent fingerprints using classification methods such as soft independent modeling of class analogy (SIMCA) and partial least squares discriminant analysis (PLS-DA). The novel method yielded an accuracy of more than 85% and was proven to be sufficiently robust. Furthermore, through laser scanning analysis at a spatial interval of 125 µm, the overlapping fingerprints were reconstructed as separate two-dimensional forms.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning.

PubMed

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-06-07

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer.

Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep Learning

PubMed Central

Wang, Jinhua; Yang, Xi; Cai, Hongmin; Tan, Wanchang; Jin, Cangzheng; Li, Li

2016-01-01

Microcalcification is an effective indicator of early breast cancer. To improve the diagnostic accuracy of microcalcifications, this study evaluates the performance of deep learning-based models on large datasets for its discrimination. A semi-automated segmentation method was used to characterize all microcalcifications. A discrimination classifier model was constructed to assess the accuracies of microcalcifications and breast masses, either in isolation or combination, for classifying breast lesions. Performances were compared to benchmark models. Our deep learning model achieved a discriminative accuracy of 87.3% if microcalcifications were characterized alone, compared to 85.8% with a support vector machine. The accuracies were 61.3% for both methods with masses alone and improved to 89.7% and 85.8% after the combined analysis with microcalcifications. Image segmentation with our deep learning model yielded 15, 26 and 41 features for the three scenarios, respectively. Overall, deep learning based on large datasets was superior to standard methods for the discrimination of microcalcifications. Accuracy was increased by adopting a combinatorial approach to detect microcalcifications and masses simultaneously. This may have clinical value for early detection and treatment of breast cancer. PMID:27273294

Surface-enhanced Raman spectroscopy for differentiation between benign and malignant thyroid tissues

NASA Astrophysics Data System (ADS)

Li, Zuanfang; Li, Chao; Lin, Duo; Huang, Zufang; Pan, Jianji; Chen, Guannan; Lin, Juqiang; Liu, Nenrong; Yu, Yun; Feng, Shangyuan; Chen, Rong

2014-04-01

The aim of this study was to evaluate the potential of applying silver nano-particle based surface-enhanced Raman scattering (SERS) to discriminate different types of human thyroid tissues. SERS measurements were performed on three groups of tissue samples including thyroid cancers (n = 32), nodular goiters (n = 20) and normal thyroid tissues (n = 25). Tentative assignments of the measured tissue SERS spectra suggest interesting cancer specific biomolecular differences. The principal component analysis (PCA) and linear discriminate analysis (LDA) together with the leave-one-out, cross-validated technique yielded diagnostic sensitivities of 92%, 75% and 87.5%; and specificities of 82.6%, 89.4% and 84.4%, respectively, for differentiation among normal, nodular and malignant thyroid tissue samples. This work demonstrates that tissue SERS spectroscopy associated with multivariate analysis diagnostic algorithms has great potential for detection of thyroid cancer at the molecular level.

Raman spectroscopic study of reaction dynamics

NASA Astrophysics Data System (ADS)

MacPhail, R. A.

1990-12-01

The Raman spectra of reacting molecules in liquids can yield information about various aspects of the reaction dynamics. The author discusses the analysis of Raman spectra for three prototypical unimolecular reactions, the rotational isomerization of n-butane and 1,2-difluoroethane, and the barrierless exchange of axial and equatorial hydrogens in cyclopentane via pseudorotation. In the first two cases the spectra are sensitive to torsional oscillations of the gauche conformer, and yield estimates of the torsional solvent friction. In the case of cyclopentane, the spectra can be used to discriminate between different stochastic models of the pseudorotation dynamics, and to determine the relevant friction coefficients.

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

Mabe, Andrew N.; Glenn, Andrew M.; Carman, M. Leslie

Transparent plastic scintillators with pulse shape discrimination containing 6Li salicylate have been synthesized by bulk polymerization with a maximum 6Li loading of 0.40 wt%. Photoluminescence and scintillation responses to gamma-rays and neutrons are reported in this paper. Plastics containing 6Li salicylate exhibit higher light yields and permit a higher loading of 6Li as compared to previously reported plastics based on lithium 3-phenylsalicylate. However, pulse shape discrimination performance is reduced in lithium salicylate plastics due to the requirement of adding more nonaromatic monomers to the polymer matrix as compared to those based on lithium 3-phenylsalicylate. Finally, reduction in light yield andmore » pulse shape discrimination performance in lithium-loaded plastics as compared to pulse shape discrimination plastics without lithium is interpreted in terms of energy transfer interference by the aromatic lithium salts.« less

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

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.

ANALYSIS OF CLINICAL AND DERMOSCOPIC FEATURES FOR BASAL CELL CARCINOMA NEURAL NETWORK CLASSIFICATION

PubMed Central

Cheng, Beibei; Stanley, R. Joe; Stoecker, William V; Stricklin, Sherea M.; Hinton, Kristen A.; Nguyen, Thanh K.; Rader, Ryan K.; Rabinovitz, Harold S.; Oliviero, Margaret; Moss, Randy H.

2012-01-01

Background Basal cell carcinoma (BCC) is the most commonly diagnosed cancer in the United States. In this research, we examine four different feature categories used for diagnostic decisions, including patient personal profile (patient age, gender, etc.), general exam (lesion size and location), common dermoscopic (blue-gray ovoids, leaf-structure dirt trails, etc.), and specific dermoscopic lesion (white/pink areas, semitranslucency, etc.). Specific dermoscopic features are more restricted versions of the common dermoscopic features. Methods Combinations of the four feature categories are analyzed over a data set of 700 lesions, with 350 BCCs and 350 benign lesions, for lesion discrimination using neural network-based techniques, including Evolving Artificial Neural Networks and Evolving Artificial Neural Network Ensembles. Results Experiment results based on ten-fold cross validation for training and testing the different neural network-based techniques yielded an area under the receiver operating characteristic curve as high as 0.981 when all features were combined. The common dermoscopic lesion features generally yielded higher discrimination results than other individual feature categories. Conclusions Experimental results show that combining clinical and image information provides enhanced lesion discrimination capability over either information source separately. This research highlights the potential of data fusion as a model for the diagnostic process. PMID:22724561

A test of the validity of the motivational interviewing treatment integrity code.

PubMed

Forsberg, Lars; Berman, Anne H; Kallmén, Håkan; Hermansson, Ulric; Helgason, Asgeir R

2008-01-01

To evaluate the Swedish version of the Motivational Interviewing Treatment Code (MITI), MITI coding was applied to tape-recorded counseling sessions. Construct validity was assessed using factor analysis on 120 MITI-coded sessions. Discriminant validity was assessed by comparing MITI coding of motivational interviewing (MI) sessions with information- and advice-giving sessions as well as by comparing MI-trained practitioners with untrained practitioners. A principal-axis factoring analysis yielded some evidence for MITI construct validity. MITI differentiated between practitioners with different levels of MI training as well as between MI practitioners and advice-giving counselors, thus supporting discriminant validity. MITI may be used as a training tool together with supervision to confirm and enhance MI practice in clinical settings. MITI can also serve as a tool for evaluating MI integrity in clinical research.

Satellite Characterization of Biomass Burning: Fourier Transform Infrared Spectroscopy (FTIR) and Scanning Electron Microscope Study of Combustion Experiments

NASA Astrophysics Data System (ADS)

Padilla, D.; Steiner, J. C.

2005-12-01

Fourier Transform Infrared (FTIR) examination of the combustion products of selected forest materials using a meeker burner flame at temperatures up to 500 degrees Celsius produces a cluster of broad distinct peaks throughout the 400 to 4000 cm-1 wavenumber interval. Distinct bands bracketed by wavenumbers 400-700, 1500-1700, 2200-2400 and 3300-3600 cm-1 show variable intensity with an average difference between the least absorbing and most strongly absorbing species of approximately fifty percent. Given that spectral band differences of ten percent are within the range of modern satellite spectrometers, these band differences are of potential value for discriminating between fires that are impacting a range of vegetation types. Corresponding scanning electron microscope and energy dispersive micro-chemical (SEM/ED) analysis establishes that the evolved soot particles exhibit a characteristic rounded morphology, are carbon rich and host a wide range of adsorbed elements, including calcium, aluminum, potassium, silicon, sulfur and trace nitrogen. Combustion experiments involving leaves and branches as a subset of the biomass experiments at 200-500 degrees Celsius yield a similar broad background, but with peak shifts for maxima residing at less than 1700 cm-1. Additional peaks appear in the ranges 1438-1444, 875 and 713 cm-1. These peak are of potential use for discriminating between hot and smoldering fires, and between soot and smoke yields from green woods and whole-wood or lumber. The spectral shifts noted for low temperature smoldering conditions are in the vicinity of those cited for green vegetation and may not be resolved by present satellite platforms. Nevertheless, the experimental peak data set is of potential use for discriminating between a conflagration or accentuated fire and one characterized by smoldering at low temperature. SEM/ED analysis of the combusted leaf, branch, bark and various crown assemblages yields comparable morphological and geochemical signatures although potassium and light elements are slightly concentrated in effluent from the leafy matrix.

Source spectral variation and yield estimation for small, near-source explosions

NASA Astrophysics Data System (ADS)

Yoo, S.; Mayeda, K. M.

2012-12-01

Significant S-wave generation is always observed from explosion sources which can lead to difficulty in discriminating explosions from natural earthquakes. While there are numerous S-wave generation mechanisms that are currently the topic of significant research, the mechanisms all remain controversial and appear to be dependent upon the near-source emplacement conditions of that particular explosion. To better understand the generation and partitioning of the P and S waves from explosion sources and to enhance the identification and discrimination capability of explosions, we investigate near-source explosion data sets from the 2008 New England Damage Experiment (NEDE), the Humble-Redwood (HR) series of explosions, and a Massachusetts quarry explosion experiment. We estimate source spectra and characteristic source parameters using moment tensor inversions, direct P and S waves multi-taper analysis, and improved coda spectral analysis using high quality waveform records from explosions from a variety of emplacement conditions (e.g., slow/fast burning explosive, fully tamped, partially tamped, single/ripple-fired, and below/above ground explosions). The results from direct and coda waves are compared to theoretical explosion source model predictions. These well-instrumented experiments provide us with excellent data from which to document the characteristic spectral shape, relative partitioning between P and S-waves, and amplitude/yield dependence as a function of HOB/DOB. The final goal of this study is to populate a comprehensive seismic source reference database for small yield explosions based on the results and to improve nuclear explosion monitoring capability.

Accumulation of Carotenoids and Metabolic Profiling in Different Cultivars of Tagetes Flowers.

PubMed

Park, Yun Ji; Park, Soo-Yun; Valan Arasu, Mariadhas; Al-Dhabi, Naif Abdullah; Ahn, Hyung-Geun; Kim, Jae Kwang; Park, Sang Un

2017-02-18

Species of Tagetes , which belong to the family Asteraceae show different characteristics including, bloom size, shape, and color; plant size; and leaf shape. In this study, we determined the differences in primary metabolites and carotenoid yields among six cultivars from two Tagetes species, T. erecta and T. patula . In total, we detected seven carotenoids in the examined cultivars: violaxanthin, lutein, zeaxanthin, α-carotene, β-carotene, 9- cis -β-carotene, and 13- cis -β-carotene. In all the cultivars, lutein was the most abundant carotenoid. Furthermore, the contents of each carotenoid in flowers varied depending on the cultivar. Principal component analysis (PCA) facilitated metabolic discrimination between Tagetes cultivars, with the exception of Inca Yellow and Discovery Orange. Moreover, PCA and orthogonal projection to latent structure-discriminant analysis (OPLS-DA) results provided a clear discrimination between T. erecta and T. patula . Primary metabolites, including xylose, citric acid, valine, glycine, and galactose were the main components facilitating separation of the species. Positive relationships were apparent between carbon-rich metabolites, including those of the TCA cycle and sugar metabolism, and carotenoids.

Seasonal discrimination of C3 and C4 grasses functional types: An evaluation of the prospects of varying spectral configurations of new generation sensors

NASA Astrophysics Data System (ADS)

Shoko, Cletah; Mutanga, Onisimo

2017-10-01

The present study assessed the potential of varying spectral configuration of Landsat 8 Operational Land Imager (OLI), Sentinel 2 MultiSpectal Instrument (MSI) and Worldview 2 sensors in the seasonal discrimination of Festuca costata (C3) and Themeda Triandra (C4) grass species in the Drakensberg, South Africa. This was achieved by resampling hyperspectral measurements to the spectral windows corresponding to the three sensors at two distinct seasonal periods (summer peak and end of winter), using the Discriminant Analysis (DA) classification ensemble. In summer, standard bands of the Worldview 2 produced the highest overall classification accuracy (98.61%), followed by Sentinel 2 (97.52%), whereas the Landsat 8 spectral configuration was the least performer, using vegetation indices (95.83%). In winter, Sentinel 2 spectral bands produced the highest accuracy (96.18%) for the two species, followed by Worldview 2 (94.44%) and Landsat 8 yielded the least (91.67%) accuracy. Results also showed that maximum separability between C3 and C4 grasses was in summer, while at the end of winter considerable overlaps were noted, especially when using the spectral settings of the Landsat 8 OLI and Sentinel 2 shortwave infrared bands. Test of significance in species reflectance further confirmed that in summer, there were significant differences (P < 0.05), whereas in winter, most of the spectral windows of all sensors yielded insignificant differences (P > 0.05) between the two species. In this regard, the peak summer period presents a promising opportunity for the spectral discrimination of C3 and C4 grass species functional types, than the end of winter, when using multispectral sensors. Results from this study highlight the influence of seasonality on discrimination and therefore provide the basis for the successful discrimination and mapping of C3 and C4 grass species.

Plasma amino acid profile associated with fatty liver disease and co-occurrence of metabolic risk factors.

PubMed

Yamakado, Minoru; Tanaka, Takayuki; Nagao, Kenji; Imaizumi, Akira; Komatsu, Michiharu; Daimon, Takashi; Miyano, Hiroshi; Tani, Mizuki; Toda, Akiko; Yamamoto, Hiroshi; Horimoto, Katsuhisa; Ishizaka, Yuko

2017-11-03

Fatty liver disease (FLD) increases the risk of diabetes, cardiovascular disease, and steatohepatitis, which leads to fibrosis, cirrhosis, and hepatocellular carcinoma. Thus, the early detection of FLD is necessary. We aimed to find a quantitative and feasible model for discriminating the FLD, based on plasma free amino acid (PFAA) profiles. We constructed models of the relationship between PFAA levels in 2,000 generally healthy Japanese subjects and the diagnosis of FLD by abdominal ultrasound scan by multiple logistic regression analysis with variable selection. The performance of these models for FLD discrimination was validated using an independent data set of 2,160 subjects. The generated PFAA-based model was able to identify FLD patients. The area under the receiver operating characteristic curve for the model was 0.83, which was higher than those of other existing liver function-associated markers ranging from 0.53 to 0.80. The value of the linear discriminant in the model yielded the adjusted odds ratio (with 95% confidence intervals) for a 1 standard deviation increase of 2.63 (2.14-3.25) in the multiple logistic regression analysis with known liver function-associated covariates. Interestingly, the linear discriminant values were significantly associated with the progression of FLD, and patients with nonalcoholic steatohepatitis also exhibited higher values.

Pitch ranking, electrode discrimination, and physiological spread-of-excitation using Cochlear's dual-electrode mode.

PubMed

Goehring, Jenny L; Neff, Donna L; Baudhuin, Jacquelyn L; Hughes, Michelle L

2014-08-01

This study compared pitch ranking, electrode discrimination, and electrically evoked compound action potential (ECAP) spatial excitation patterns for adjacent physical electrodes (PEs) and the corresponding dual electrodes (DEs) for newer-generation Cochlear devices (Cochlear Ltd., Macquarie, New South Wales, Australia). The first goal was to determine whether pitch ranking and electrode discrimination yield similar outcomes for PEs and DEs. The second goal was to determine if the amount of spatial separation among ECAP excitation patterns (separation index, Σ) between adjacent PEs and the PE-DE pairs can predict performance on the psychophysical tasks. Using non-adaptive procedures, 13 subjects completed pitch ranking and electrode discrimination for adjacent PEs and the corresponding PE-DE pairs (DE versus each flanking PE) from the basal, middle, and apical electrode regions. Analysis of d' scores indicated that pitch-ranking and electrode-discrimination scores were not significantly different, but rather produced similar levels of performance. As expected, accuracy was significantly better for the PE-PE comparison than either PE-DE comparison. Correlations of the psychophysical versus ECAP Σ measures were positive; however, not all test/region correlations were significant across the array. Thus, the ECAP separation index is not sensitive enough to predict performance on behavioral tasks of pitch ranking or electrode discrimination for adjacent PEs or corresponding DEs.

Pitch ranking, electrode discrimination, and physiological spread-of-excitation using Cochlear's dual-electrode mode

PubMed Central

Goehring, Jenny L.; Neff, Donna L.; Baudhuin, Jacquelyn L.; Hughes, Michelle L.

2014-01-01

This study compared pitch ranking, electrode discrimination, and electrically evoked compound action potential (ECAP) spatial excitation patterns for adjacent physical electrodes (PEs) and the corresponding dual electrodes (DEs) for newer-generation Cochlear devices (Cochlear Ltd., Macquarie, New South Wales, Australia). The first goal was to determine whether pitch ranking and electrode discrimination yield similar outcomes for PEs and DEs. The second goal was to determine if the amount of spatial separation among ECAP excitation patterns (separation index, Σ) between adjacent PEs and the PE-DE pairs can predict performance on the psychophysical tasks. Using non-adaptive procedures, 13 subjects completed pitch ranking and electrode discrimination for adjacent PEs and the corresponding PE-DE pairs (DE versus each flanking PE) from the basal, middle, and apical electrode regions. Analysis of d′ scores indicated that pitch-ranking and electrode-discrimination scores were not significantly different, but rather produced similar levels of performance. As expected, accuracy was significantly better for the PE-PE comparison than either PE-DE comparison. Correlations of the psychophysical versus ECAP Σ measures were positive; however, not all test/region correlations were significant across the array. Thus, the ECAP separation index is not sensitive enough to predict performance on behavioral tasks of pitch ranking or electrode discrimination for adjacent PEs or corresponding DEs. PMID:25096106

Differentiation of Organically and Conventionally Grown Tomatoes by Chemometric Analysis of Combined Data from Proton Nuclear Magnetic Resonance and Mid-infrared Spectroscopy and Stable Isotope Analysis.

PubMed

Hohmann, Monika; Monakhova, Yulia; Erich, Sarah; Christoph, Norbert; Wachter, Helmut; Holzgrabe, Ulrike

2015-11-04

Because the basic suitability of proton nuclear magnetic resonance spectroscopy ((1)H NMR) to differentiate organic versus conventional tomatoes was recently proven, the approach to optimize (1)H NMR classification models (comprising overall 205 authentic tomato samples) by including additional data of isotope ratio mass spectrometry (IRMS, δ(13)C, δ(15)N, and δ(18)O) and mid-infrared (MIR) spectroscopy was assessed. Both individual and combined analytical methods ((1)H NMR + MIR, (1)H NMR + IRMS, MIR + IRMS, and (1)H NMR + MIR + IRMS) were examined using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), linear discriminant analysis (LDA), and common components and specific weight analysis (ComDim). With regard to classification abilities, fused data of (1)H NMR + MIR + IRMS yielded better validation results (ranging between 95.0 and 100.0%) than individual methods ((1)H NMR, 91.3-100%; MIR, 75.6-91.7%), suggesting that the combined examination of analytical profiles enhances authentication of organically produced tomatoes.

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.

Accurate Diabetes Risk Stratification Using Machine Learning: Role of Missing Value and Outliers.

PubMed

Maniruzzaman, Md; Rahman, Md Jahanur; Al-MehediHasan, Md; Suri, Harman S; Abedin, Md Menhazul; El-Baz, Ayman; Suri, Jasjit S

2018-04-10

Diabetes mellitus is a group of metabolic diseases in which blood sugar levels are too high. About 8.8% of the world was diabetic in 2017. It is projected that this will reach nearly 10% by 2045. The major challenge is that when machine learning-based classifiers are applied to such data sets for risk stratification, leads to lower performance. Thus, our objective is to develop an optimized and robust machine learning (ML) system under the assumption that missing values or outliers if replaced by a median configuration will yield higher risk stratification accuracy. This ML-based risk stratification is designed, optimized and evaluated, where: (i) the features are extracted and optimized from the six feature selection techniques (random forest, logistic regression, mutual information, principal component analysis, analysis of variance, and Fisher discriminant ratio) and combined with ten different types of classifiers (linear discriminant analysis, quadratic discriminant analysis, naïve Bayes, Gaussian process classification, support vector machine, artificial neural network, Adaboost, logistic regression, decision tree, and random forest) under the hypothesis that both missing values and outliers when replaced by computed medians will improve the risk stratification accuracy. Pima Indian diabetic dataset (768 patients: 268 diabetic and 500 controls) was used. Our results demonstrate that on replacing the missing values and outliers by group median and median values, respectively and further using the combination of random forest feature selection and random forest classification technique yields an accuracy, sensitivity, specificity, positive predictive value, negative predictive value and area under the curve as: 92.26%, 95.96%, 79.72%, 91.14%, 91.20%, and 0.93, respectively. This is an improvement of 10% over previously developed techniques published in literature. The system was validated for its stability and reliability. RF-based model showed the best performance when outliers are replaced by median values.

Transparent plastic scintillators for neutron detection based on lithium salicylate

DOE PAGES

Mabe, Andrew N.; Glenn, Andrew M.; Carman, M. Leslie; ...

2015-10-14

Transparent plastic scintillators with pulse shape discrimination containing 6Li salicylate have been synthesized by bulk polymerization with a maximum 6Li loading of 0.40 wt%. Photoluminescence and scintillation responses to gamma-rays and neutrons are reported in this paper. Plastics containing 6Li salicylate exhibit higher light yields and permit a higher loading of 6Li as compared to previously reported plastics based on lithium 3-phenylsalicylate. However, pulse shape discrimination performance is reduced in lithium salicylate plastics due to the requirement of adding more nonaromatic monomers to the polymer matrix as compared to those based on lithium 3-phenylsalicylate. Finally, reduction in light yield andmore » pulse shape discrimination performance in lithium-loaded plastics as compared to pulse shape discrimination plastics without lithium is interpreted in terms of energy transfer interference by the aromatic lithium salts.« less

Detection of feigned mental disorders on the personality assessment inventory: a discriminant analysis.

PubMed

Rogers, R; Sewell, K W; Morey, L C; Ustad, K L

1996-12-01

Psychological assessment with multiscale inventories is largely dependent on the honesty and forthrightness of those persons evaluated. We investigated the effectiveness of the Personality Assessment Inventory (PAI) in detecting participants feigning three specific disorders: schizophrenia, major depression, and generalized anxiety disorder. With a simulation design, we tested the PAI validity scales on 166 naive (undergraduates with minimal preparation) and 80 sophisticated (doctoral psychology students with 1 week preparation) participants. We compared their results to persons with the designated disorders: schizophrenia (n = 45), major depression (n = 136), and generalized anxiety disorder (n = 40). Although moderately effective with naive simulators, the validity scales evidenced only modest positive predictive power with their sophisticated counterparts. Therefore, we performed a two-stage discriminant analysis that yielded a moderately high hit rate (> 80%) that was maintained in the cross-validation sample, irrespective of the feigned disorder or the sophistication of the simulators.

Development of Attitudes Toward Homosexuality Scale for Indians (AHSI).

PubMed

Ahuja, Kanika K

2017-01-01

Attitudes toward homosexuality vary across cultures, with the legal and societal position being rather complicated in India. This study describes the process of developing and validating a Likert-type scale to assess attitudes toward homosexuality among heterosexuals. Phase 1 describes the development of the scale. Items were written based on thematic analysis of narratives generated from 50 college students and reviewing existing scales. After administering the 70-item scale to 68 participants, item analysis yielded 20 statements with item-total correlations over .70. Cronbach's alpha was .97. In Phase 2, the 20-item Attitudes Toward Homosexuality Scale for Indians (AHSI) was administered to 142 participants. Analysis yielded a corrected split-half correlation of .91. Further, AHSI discriminated between women and men; between liberal arts and STEM/business students; and those who reported interpersonal contact with gay men and lesbian women and those who did not. The scale has satisfactory reliability and shows promising construct validity.

High wavenumber Raman spectroscopic characterization of normal and oral cancer using blood plasma

NASA Astrophysics Data System (ADS)

Pachaiappan, Rekha; Prakasarao, Aruna; Suresh Kumar, Murugesan; Singaravelu, Ganesan

2017-02-01

Blood plasma possesses the biomolecules released from cells/tissues after metabolism and reflects the pathological conditions of the subjects. The analysis of biofluids for disease diagnosis becomes very attractive in the diagnosis of cancers due to the ease in the collection of samples, easy to transport, multiple sampling for regular screening of the disease and being less invasive to the patients. Hence, the intention of this study was to apply near-infrared (NIR) Raman spectroscopy in the high wavenumber (HW) region (2500-3400 cm-1) for the diagnosis of oral malignancy using blood plasma. From the Raman spectra it is observed that the biomolecules protein and lipid played a major role in the discrimination between groups. The diagnostic algorithms based on principal components analysis coupled with linear discriminant analysis (PCA-LDA) with the leave-one-patient-out cross-validation method on HW Raman spectra yielded a promising results in the identification of oral malignancy. The details of results will be discussed.

Gaussian Discriminant Analysis for Optimal Delineation of Mild Cognitive Impairment in Alzheimer's Disease.

PubMed

Fang, Chen; Li, Chunfei; Cabrerizo, Mercedes; Barreto, Armando; Andrian, Jean; Rishe, Naphtali; Loewenstein, David; Duara, Ranjan; Adjouadi, Malek

2018-04-12

Over the past few years, several approaches have been proposed to assist in the early diagnosis of Alzheimer's disease (AD) and its prodromal stage of mild cognitive impairment (MCI). Using multimodal biomarkers for this high-dimensional classification problem, the widely used algorithms include Support Vector Machines (SVM), Sparse Representation-based classification (SRC), Deep Belief Networks (DBN) and Random Forest (RF). These widely used algorithms continue to yield unsatisfactory performance for delineating the MCI participants from the cognitively normal control (CN) group. A novel Gaussian discriminant analysis-based algorithm is thus introduced to achieve a more effective and accurate classification performance than the aforementioned state-of-the-art algorithms. This study makes use of magnetic resonance imaging (MRI) data uniquely as input to two separate high-dimensional decision spaces that reflect the structural measures of the two brain hemispheres. The data used include 190 CN, 305 MCI and 133 AD subjects as part of the AD Big Data DREAM Challenge #1. Using 80% data for a 10-fold cross-validation, the proposed algorithm achieved an average F1 score of 95.89% and an accuracy of 96.54% for discriminating AD from CN; and more importantly, an average F1 score of 92.08% and an accuracy of 90.26% for discriminating MCI from CN. Then, a true test was implemented on the remaining 20% held-out test data. For discriminating MCI from CN, an accuracy of 80.61%, a sensitivity of 81.97% and a specificity of 78.38% were obtained. These results show significant improvement over existing algorithms for discriminating the subtle differences between MCI participants and the CN group.

Landsat analysis of tropical forest succession employing a terrain model

NASA Technical Reports Server (NTRS)

Barringer, T. H.; Robinson, V. B.; Coiner, J. C.; Bruce, R. C.

1980-01-01

Landsat multispectral scanner (MSS) data have yielded a dual classification of rain forest and shadow in an analysis of a semi-deciduous forest on Mindonoro Island, Philippines. Both a spatial terrain model, using a fifth side polynomial trend surface analysis for quantitatively estimating the general spatial variation in the data set, and a spectral terrain model, based on the MSS data, have been set up. A discriminant analysis, using both sets of data, has suggested that shadowing effects may be due primarily to local variations in the spectral regions and can therefore be compensated for through the decomposition of the spatial variation in both elevation and MSS data.

MR PROSTATE SEGMENTATION VIA DISTRIBUTED DISCRIMINATIVE DICTIONARY (DDD) LEARNING.

PubMed

Guo, Yanrong; Zhan, Yiqiang; Gao, Yaozong; Jiang, Jianguo; Shen, Dinggang

2013-01-01

Segmenting prostate from MR images is important yet challenging. Due to non-Gaussian distribution of prostate appearances in MR images, the popular active appearance model (AAM) has its limited performance. Although the newly developed sparse dictionary learning method[1, 2] can model the image appearance in a non-parametric fashion, the learned dictionaries still lack the discriminative power between prostate and non-prostate tissues, which is critical for accurate prostate segmentation. In this paper, we propose to integrate deformable model with a novel learning scheme, namely the Distributed Discriminative Dictionary ( DDD ) learning, which can capture image appearance in a non-parametric and discriminative fashion. In particular, three strategies are designed to boost the tissue discriminative power of DDD. First , minimum Redundancy Maximum Relevance (mRMR) feature selection is performed to constrain the dictionary learning in a discriminative feature space. Second , linear discriminant analysis (LDA) is employed to assemble residuals from different dictionaries for optimal separation between prostate and non-prostate tissues. Third , instead of learning the global dictionaries, we learn a set of local dictionaries for the local regions (each with small appearance variations) along prostate boundary, thus achieving better tissue differentiation locally. In the application stage, DDDs will provide the appearance cues to robustly drive the deformable model onto the prostate boundary. Experiments on 50 MR prostate images show that our method can yield a Dice Ratio of 88% compared to the manual segmentations, and have 7% improvement over the conventional AAM.

Temperature discrimination by captive free-swimming tuna, Euthynnus affinis

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

Steffel, S.; Dizon, A.E.; Magnuson, J.J.

1976-09-01

Captive kawakawa, Euthynnus affinis, were instrumentally conditioned to respond to an increase in temperature to determine discrimination abilities. Two fish yielded a discrimination threshold of 0.10 to 0.15/sup 0/C. Thermal sensitivity of this high-seas pelagic fish is thus no more acute than that of inshore fishes and appears inadequate for direct sensing of weak horizontal temperature gradients at sea.

US line-ups outperform UK line-ups

PubMed Central

Seale-Carlisle, Travis M.

2016-01-01

In the USA and the UK, many thousands of police suspects are identified by eyewitnesses every year. Unfortunately, many of those suspects are innocent, which becomes evident when they are exonerated by DNA testing, often after having been imprisoned for years. It is, therefore, imperative to use identification procedures that best enable eyewitnesses to discriminate innocent from guilty suspects. Although police investigators in both countries often administer line-up procedures, the details of how line-ups are presented are quite different and an important direct comparison has yet to be conducted. We investigated whether these two line-up procedures differ in terms of (i) discriminability (using receiver operating characteristic analysis) and (ii) reliability (using confidence–accuracy characteristic analysis). A total of 2249 participants watched a video of a crime and were later tested using either a six-person simultaneous photo line-up procedure (USA) or a nine-person sequential video line-up procedure (UK). US line-up procedure yielded significantly higher discriminability and significantly higher reliability. The results do not pinpoint the reason for the observed difference between the two procedures, but they do suggest that there is much room for improvement with the UK line-up. PMID:27703695

Seismic Attenuation, Event Discrimination, Magnitude and Yield Estimation, and Capability Analysis

DTIC Science & Technology

2011-09-01

waves are subject to path-dependent variations in amplitudes. We see geographic similarities between the crustal shear-wave attenuation and the...either Sn or Lg depending on tectonic region, distance, and frequency. Over the past year, we have made great progress on the calibration of surface...between the crustal shear-wave attenuation and the results from the coda attenuation. Calibration of coda in the Middle East and other areas is

Full-Waveform Envelope Templates for Low Magnitude Discrimination and Yield Estimation at Local and Regional Distances with Application to the North Korean Nuclear Tests

NASA Astrophysics Data System (ADS)

Yoo, S. H.

2017-12-01

Monitoring seismologists have successfully used seismic coda for event discrimination and yield estimation for over a decade. In practice seismologists typically analyze long-duration, S-coda signals with high signal-to-noise ratios (SNR) at regional and teleseismic distances, since the single back-scattering model reasonably predicts decay of the late coda. However, seismic monitoring requirements are shifting towards smaller, locally recorded events that exhibit low SNR and short signal lengths. To be successful at characterizing events recorded at local distances, we must utilize the direct-phase arrivals, as well as the earlier part of the coda, which is dominated by multiple forward scattering. To remedy this problem, we have developed a new hybrid method known as full-waveform envelope template matching to improve predicted envelope fits over the entire waveform and account for direct-wave and early coda complexity. We accomplish this by including a multiple forward-scattering approximation in the envelope modeling of the early coda. The new hybrid envelope templates are designed to fit local and regional full waveforms and produce low-variance amplitude estimates, which will improve yield estimation and discrimination between earthquakes and explosions. To demonstrate the new technique, we applied our full-waveform envelope template-matching method to the six known North Korean (DPRK) underground nuclear tests and four aftershock events following the September 2017 test. We successfully discriminated the event types and estimated the yield for all six nuclear tests. We also applied the same technique to the 2015 Tianjin explosions in China, and another suspected low-yield explosion at the DPRK test site on May 12, 2010. Our results show that the new full-waveform envelope template-matching method significantly improves upon longstanding single-scattering coda prediction techniques. More importantly, the new method allows monitoring seismologists to extend coda-based techniques to lower magnitude thresholds and low-yield local explosions.

Arbitrary conditional discriminative functions of meaningful stimuli and enhanced equivalence class formation.

PubMed

Nedelcu, Roxana I; Fields, Lanny; Arntzen, Erik

2015-03-01

Equivalence class formation by college students was influenced through the prior acquisition of conditional discriminative functions by one of the abstract stimuli (C) in the to-be-formed classes. Participants in the GR-0, GR-1, and GR-5 groups attempted to form classes under the simultaneous protocol, after mastering 0, 1, or 5 conditional relations between C and other abstract stimuli (V, W, X, Y, Z) that were not included in the to-be-formed classes (ABCDE). Participants in the GR-many group attempted to form classes that contained four abstract stimuli and one meaningful picture as the C stimulus. In the GR-0, GR-1, GR-5, and GR-many groups, classes were formed by 17, 25, 58, and 67% of participants, respectively. Thus, likelihood of class formation was enhanced by the prior formation of five C-based conditional relations (the GR-5 vs. GR-0 condition), or the inclusion of a meaningful stimulus as a class member (the GR-many vs. GR-0 condition). The GR-5 and GR-many conditions produced very similar yields, indicating that class formation was enhanced to a similar degree by including a meaningful stimulus or an abstract stimulus that had become a member of five conditional relations prior to equivalence class formation. Finally, the low and high yields produced by the GR-1 and GR-5 conditions showed that the class enhancement effect of the GR-5 condition was due to the number of conditional relations established during preliminary training and not to the sheer amount of reinforcement provided while learning these conditional relations. Class enhancement produced by meaningful stimuli, then, can be attributed to their acquired conditional discriminative functions as well as their discriminative, connotative, and denotative properties. © Society for the Experimental Analysis of Behavior.

Cultivar evaluation and essential test locations identification for sugarcane breeding in China.

PubMed

Luo, Jun; Pan, Yong-Bao; Xu, Liping; Zhang, Hua; Yuan, Zhaonian; Deng, Zuhu; Chen, Rukai; Que, Youxiong

2014-01-01

The discrepancies across test sites and years, along with the interaction between cultivar and environment, make it difficult to accurately evaluate the differences of the sugarcane cultivars. Using a genotype main effect plus genotype-environment interaction (GGE) Biplot software, the yield performance data of seven sugarcane cultivars in the 8th Chinese National Sugarcane Regional Tests were analyzed to identify cultivars recommended for commercial release. Fn38 produced a high and stable sugar yield. Gn02-70 had the lowest cane yield with high stability. Yz06-407 was a high cane yield cultivar with poor stability in sugar yield. Yz05-51 and Lc03-1137 had an unstable cane yield but relatively high sugar yield. Fn39 produced stable high sugar yield with low and unstable cane production. Significantly different sugar and cane yields were observed across seasons due to strong cultivar-environment interactions. Three areas, Guangxi Chongzuo, Guangxi Baise, and Guangxi Hechi, showed better representativeness of cane yield and sugar content than the other four areas. On the other hand, the areas Guangxi Chongzuo, Yunnan Lincang, and Yunnan Baoshan showed strong discrimination ability, while the areas Guangxi Hechi and Guangxi Liuzhou showed poor discrimination ability. This study provides a reference for cultivar evaluation and essential test locations identification for sugarcane breeding in China.

Cultivar Evaluation and Essential Test Locations Identification for Sugarcane Breeding in China

PubMed Central

Luo, Jun; Xu, Liping; Zhang, Hua; Yuan, Zhaonian; Deng, Zuhu; Chen, Rukai

2014-01-01

The discrepancies across test sites and years, along with the interaction between cultivar and environment, make it difficult to accurately evaluate the differences of the sugarcane cultivars. Using a genotype main effect plus genotype-environment interaction (GGE) Biplot software, the yield performance data of seven sugarcane cultivars in the 8th Chinese National Sugarcane Regional Tests were analyzed to identify cultivars recommended for commercial release. Fn38 produced a high and stable sugar yield. Gn02-70 had the lowest cane yield with high stability. Yz06-407 was a high cane yield cultivar with poor stability in sugar yield. Yz05-51 and Lc03-1137 had an unstable cane yield but relatively high sugar yield. Fn39 produced stable high sugar yield with low and unstable cane production. Significantly different sugar and cane yields were observed across seasons due to strong cultivar-environment interactions. Three areas, Guangxi Chongzuo, Guangxi Baise, and Guangxi Hechi, showed better representativeness of cane yield and sugar content than the other four areas. On the other hand, the areas Guangxi Chongzuo, Yunnan Lincang, and Yunnan Baoshan showed strong discrimination ability, while the areas Guangxi Hechi and Guangxi Liuzhou showed poor discrimination ability. This study provides a reference for cultivar evaluation and essential test locations identification for sugarcane breeding in China. PMID:24982939

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.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction.

PubMed

Abulnaga, S Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M; Onyike, Chiadi U; Ying, Sarah H; Prince, Jerry L

2016-02-27

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

A toolbox to visually explore cerebellar shape changes in cerebellar disease and dysfunction

NASA Astrophysics Data System (ADS)

Abulnaga, S. Mazdak; Yang, Zhen; Carass, Aaron; Kansal, Kalyani; Jedynak, Bruno M.; Onyike, Chiadi U.; Ying, Sarah H.; Prince, Jerry L.

2016-03-01

The cerebellum plays an important role in motor control and is also involved in cognitive processes. Cerebellar function is specialized by location, although the exact topographic functional relationship is not fully understood. The spinocerebellar ataxias are a group of neurodegenerative diseases that cause regional atrophy in the cerebellum, yielding distinct motor and cognitive problems. The ability to study the region-specific atrophy patterns can provide insight into the problem of relating cerebellar function to location. In an effort to study these structural change patterns, we developed a toolbox in MATLAB to provide researchers a unique way to visually explore the correlation between cerebellar lobule shape changes and function loss, with a rich set of visualization and analysis modules. In this paper, we outline the functions and highlight the utility of the toolbox. The toolbox takes as input landmark shape representations of subjects' cerebellar substructures. A principal component analysis is used for dimension reduction. Following this, a linear discriminant analysis and a regression analysis can be performed to find the discriminant direction associated with a specific disease type, or the regression line of a specific functional measure can be generated. The characteristic structural change pattern of a disease type or of a functional score is visualized by sampling points on the discriminant or regression line. The sampled points are used to reconstruct synthetic cerebellar lobule shapes. We showed a few case studies highlighting the utility of the toolbox and we compare the analysis results with the literature.

Small rural hospitals: an example of market segmentation analysis.

PubMed

Mainous, A G; Shelby, R L

1991-01-01

In recent years, market segmentation analysis has shown increased popularity among health care marketers, although marketers tend to focus upon hospitals as sellers. The present analysis suggests that there is merit to viewing hospitals as a market of consumers. Employing a random sample of 741 small rural hospitals, the present investigation sought to determine, through the use of segmentation analysis, the variables associated with hospital success (occupancy). The results of a discriminant analysis yielded a model which classifies hospitals with a high degree of predictive accuracy. Successful hospitals have more beds and employees, and are generally larger and have more resources. However, there was no significant relationship between organizational success and number of services offered by the institution.

Calibration of Attenuation Structure in Eurasia to Improve Discrimination and Yield

DTIC Science & Technology

2010-09-01

and travel-times over large and tectonically complicated regions. As a result regional discrimination methods (e.g., high-frequency P/S, Ms:mb) and...a poor job of predicting both regional amplitudes and travel-times over large and tectonically complicated regions. As a result regional...regions. Earthquake-explosion discrimination using high-frequency regional P/S amplitude ratios over large and tectonically complicated regions can only

Enhanced equivalence class formation by the delay and relational functions of meaningful stimuli.

PubMed

Arntzen, Erik; Nartey, Richard K; Fields, Lanny

2015-05-01

Undergraduates in six groups of 10 attempted to form three 3-node 5-member equivalence classes (A → B → C → D → E) under the simultaneous protocol. In five of six groups, all stimuli were abstract shapes; in the PIC group, C stimuli were pictures with the remainder being abstract shapes. Before class formation, participants in the Identity-S and Identity-D groups were given preliminary training to form identity conditional discriminations with the C stimuli using simultaneous and 6 s delayed matching-to-sample procedures, respectively. In the Arbitrary-S and Arbitrary-D groups, before class formation, arbitrary conditional discriminations were formed between C and X stimuli using simultaneous and 6 s delayed matching-to-sample procedures, respectively. With no preliminary training, classes in the PIC and ABS groups were formed by 80% and 0% of participants, respectively. After preliminary training, class formation (yield) increased with delay, regardless of relational type. For each of the two delays, yield was slightly greater after forming arbitrary- instead of identity-relations. Yield was greatest, however, when a class contained a meaningful stimulus (PIC). During failed class formation, probes produced experimenter-defined relations, participant-defined relations, and unsystematic responding; delay, but not the relation type in preliminary training influenced relational and indeterminate responding. These results suggest how meaningful stimuli enhance equivalence class formation. © Society for the Experimental Analysis of Behavior.

Discrimination and Measurements of Three Flavonols with Similar Structure Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Yan, Ling; Liu, Changhong; Qu, Hao; Liu, Wei; Zhang, Yan; Yang, Jianbo; Zheng, Lei

2018-03-01

Terahertz (THz) technique, a recently developed spectral method, has been researched and used for the rapid discrimination and measurements of food compositions due to its low-energy and non-ionizing characteristics. In this study, THz spectroscopy combined with chemometrics has been utilized for qualitative and quantitative analysis of myricetin, quercetin, and kaempferol with concentrations of 0.025, 0.05, and 0.1 mg/mL. The qualitative discrimination was achieved by KNN, ELM, and RF models with the spectra pre-treatments. An excellent discrimination (100% CCR in the prediction set) could be achieved using the RF model. Furthermore, the quantitative analyses were performed by partial least square regression (PLSR) and least squares support vector machine (LS-SVM). Comparing to the PLSR models, the LS-SVM yielded better results with low RMSEP (0.0044, 0.0039, and 0.0048), higher Rp (0.9601, 0.9688, and 0.9359), and higher RPD (8.6272, 9.6333, and 7.9083) for myricetin, quercetin, and kaempferol, respectively. Our results demonstrate that THz spectroscopy technique is a powerful tool for identification of three flavonols with similar chemical structures and quantitative determination of their concentrations.

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.

Investment in Social Marketing Campaign to Reduce Stigma and Discrimination Associated with Mental Illness Yields Positive Economic Benefits to California.

PubMed

Ashwood, J Scott; Briscombe, Brian; Collins, Rebecca L; Wong, Eunice C; Eberhart, Nicole K; Cerully, Jennifer; May, Libby; Roth, Beth; Burnam, M Audrey

2017-01-01

This article examines the potential impact of the California Mental Health Services Authority's stigma and discrimination reduction social marketing campaign on the use of adult behavioral health services, and it estimates the benefit-cost ratios.

Co-production of GroELS discriminates between intrinsic and thermally-induced recombinant protein aggregation during substrate quality control

PubMed Central

2011-01-01

Background The effects and effectiveness of the chaperone pair GroELS on the yield and quality of recombinant polypeptides produced in Escherichia coli are matter of controversy, as the reported activities of this complex are not always consistent and eventually indicate undesired side effects. The divergence in the reported data could be due, at least partially, to different experimental conditions in independent research approaches. Results We have then selected two structurally different model proteins (namely GFP and E. coli β-galactosidase) and two derived aggregation-prone fusions to explore, in a systematic way, the eventual effects of GroELS co-production on yield, solubility and conformational quality. Host cells were cultured at two alternative temperatures below the threshold at which thermal stress is expected to be triggered, to minimize the involvement of independent stress factors. Conclusions From the analysis of protein yield, solubility and biological activity of the four model proteins produced alone or along the chaperones, we conclude that GroELS impacts on yield and quality of aggregation-prone proteins with intrinsic determinants but not on thermally induced protein aggregation. No effective modifications of protein solubility have been observed, but significant stabilization of small (encapsulable) substrates and moderate chaperone-induced degradation of larger (excluded) polypeptides. These findings indicate that the activities of this chaperone pair in the context of actively producing recombinant bacteria discriminate between intrinsic and thermally-induced protein aggregation, and that the side effects of GroELS overproduction might be determined by substrate size. PMID:21992454

3D surface rendered MR images of the brain and its vasculature.

PubMed

Cline, H E; Lorensen, W E; Souza, S P; Jolesz, F A; Kikinis, R; Gerig, G; Kennedy, T E

1991-01-01

Both time-of-flight and phase contrast magnetic resonance angiography images are combined with stationary tissue images to provide data depicting two contrast relationships yielding intrinsic discrimination of brain matter and flowing blood. A computer analysis is based on nearest neighbor segmentation and the connection between anatomical structures to partition the images into different tissue categories: from which, high resolution brain parenchymal and vascular surfaces are constructed and rendered in juxtaposition, aiding in surgical planning.

A first comparison of the responses of a 4He-based fast-neutron detector and a NE-213 liquid-scintillator reference detector

NASA Astrophysics Data System (ADS)

Jebali, R.; Scherzinger, J.; Annand, J. R. M.; Chandra, R.; Davatz, G.; Fissum, K. G.; Friederich, H.; Gendotti, U.; Hall-Wilton, R.; Håkansson, E.; Kanaki, K.; Lundin, M.; Murer, D.; Nilsson, B.; Rosborg, A.; Svensson, H.

2015-09-01

A first comparison has been made between the pulse-shape discrimination characteristics of a novel 4He-based pressurized scintillation detector and a NE-213 liquid-scintillator reference detector using an Am/Be mixed-field neutron and gamma-ray source and a high-resolution scintillation-pulse digitizer. In particular, the capabilities of the two fast neutron detectors to discriminate between neutrons and gamma-rays were investigated. The NE-213 liquid-scintillator reference cell produced a wide range of scintillation-light yields in response to the gamma-ray field of the source. In stark contrast, due to the size and pressure of the 4He gas volume, the 4He-based detector registered a maximum scintillation-light yield of 750keVee to the same gamma-ray field. Pulse-shape discrimination for particles with scintillation-light yields of more than 750keVee was excellent in the case of the 4He-based detector. Above 750keVee its signal was unambiguously neutron, enabling particle identification based entirely upon the amount of scintillation light produced.

Linking multimetric and multivariate approaches to assess the ecological condition of streams.

PubMed

Collier, Kevin J

2009-10-01

Few attempts have been made to combine multimetric and multivariate analyses for bioassessment despite recognition that an integrated method could yield powerful tools for bioassessment. An approach is described that integrates eight macroinvertebrate community metrics into a Principal Components Analysis to develop a Multivariate Condition Score (MCS) from a calibration dataset of 511 samples. The MCS is compared to an Index of Biotic Integrity (IBI) derived using the same metrics based on the ratio to the reference site mean. Both approaches were highly correlated although the MCS appeared to offer greater potential for discriminating a wider range of impaired conditions. Both the MCS and IBI displayed low temporal variability within reference sites, and were able to distinguish between reference conditions and low levels of catchment modification and local habitat degradation, although neither discriminated among three levels of low impact. Pseudosamples developed to test the response of the metric aggregation approaches to organic enrichment, urban, mining, pastoral and logging stressor scenarios ranked pressures in the same order, but the MCS provided a lower score for the urban scenario and a higher score for the pastoral scenario. The MCS was calculated for an independent test dataset of urban and reference sites, and yielded similar results to the IBI. Although both methods performed comparably, the MCS approach may have some advantages because it removes the subjectivity of assigning thresholds for scoring biological condition, and it appears to discriminate a wider range of degraded conditions.

Discrimination, Racial Bias, and Telomere Length in African-American Men

PubMed Central

Chae, David H.; Nuru-Jeter, Amani M.; Adler, Nancy E.; Brody, Gene H.; Lin, Jue; Blackburn, Elizabeth H.; Epel, Elissa S.

2013-01-01

Background Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. Purpose To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Methods Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. Results After controlling for chronologic age, socioeconomic, and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b= −0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Conclusions Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. PMID:24439343

Investment in Social Marketing Campaign to Reduce Stigma and Discrimination Associated with Mental Illness Yields Positive Economic Benefits to California

PubMed Central

Ashwood, J. Scott; Briscombe, Brian; Collins, Rebecca L.; Wong, Eunice C.; Eberhart, Nicole K.; Cerully, Jennifer; May, Libby; Roth, Beth; Burnam, M. Audrey

2017-01-01

Abstract This article examines the potential impact of the California Mental Health Services Authority's stigma and discrimination reduction social marketing campaign on the use of adult behavioral health services, and it estimates the benefit-cost ratios. PMID:28845343

Utility of histogram analysis of apparent diffusion coefficient maps obtained using 3.0T MRI for distinguishing uterine carcinosarcoma from endometrial carcinoma.

PubMed

Takahashi, Masahiro; Kozawa, Eito; Tanisaka, Megumi; Hasegawa, Kousei; Yasuda, Masanori; Sakai, Fumikazu

2016-06-01

We explored the role of histogram analysis of apparent diffusion coefficient (ADC) maps for discriminating uterine carcinosarcoma and endometrial carcinoma. We retrospectively evaluated findings in 13 patients with uterine carcinosarcoma and 50 patients with endometrial carcinoma who underwent diffusion-weighted imaging (b = 0, 500, 1000 s/mm(2) ) at 3T with acquisition of corresponding ADC maps. We derived histogram data from regions of interest drawn on all slices of the ADC maps in which tumor was visualized, excluding areas of necrosis and hemorrhage in the tumor. We used the Mann-Whitney test to evaluate the capacity of histogram parameters (mean ADC value, 5th to 95th percentiles, skewness, kurtosis) to discriminate uterine carcinosarcoma and endometrial carcinoma and analyzed the receiver operating characteristic (ROC) curve to determine the optimum threshold value for each parameter and its corresponding sensitivity and specificity. Carcinosarcomas demonstrated significantly higher mean vales of ADC, 95th, 90th, 75th, 50th, 25th percentiles and kurtosis than endometrial carcinomas (P < 0.05). ROC curve analysis of the 75th percentile yielded the best area under the ROC curve (AUC; 0.904), sensitivity of 100%, and specificity of 78.0%, with a cutoff value of 1.034 × 10(-3) mm(2) /s. Histogram analysis of ADC maps might be helpful for discriminating uterine carcinosarcomas and endometrial carcinomas. J. Magn. Reson. Imaging 2016;43:1301-1307. © 2015 Wiley Periodicals, Inc.

Biomolecular filters for improved separation of output signals in enzyme logic systems applied to biomedical analysis.

PubMed

Halámek, Jan; Zhou, Jian; Halámková, Lenka; Bocharova, Vera; Privman, Vladimir; Wang, Joseph; Katz, Evgeny

2011-11-15

Biomolecular logic systems processing biochemical input signals and producing "digital" outputs in the form of YES/NO were developed for analysis of physiological conditions characteristic of liver injury, soft tissue injury, and abdominal trauma. Injury biomarkers were used as input signals for activating the logic systems. Their normal physiological concentrations were defined as logic-0 level, while their pathologically elevated concentrations were defined as logic-1 values. Since the input concentrations applied as logic 0 and 1 values were not sufficiently different, the output signals being at low and high values (0, 1 outputs) were separated with a short gap making their discrimination difficult. Coupled enzymatic reactions functioning as a biomolecular signal processing system with a built-in filter property were developed. The filter process involves a partial back-conversion of the optical-output-signal-yielding product, but only at its low concentrations, thus allowing the proper discrimination between 0 and 1 output values.

A Finnish validation study of the SCL-90.

PubMed

Holi, M M; Sammallahti, P R; Aalberg, V A

1998-01-01

The Symptom Check-List-90 (SCL-90) is a widely used psychiatric questionnaire which has not yet been validated in Finland. We investigated the utility of the translated version of the SCL-90 in the Finnish population, and set community norms for it. The internal consistency of the original subscales was checked and found to be good. Discriminant function analysis, based on the nine original subscales, showed that the power of the SCL-90 to discriminate between patients and the community is good. Factor analysis of the items of the questionnaire yielded a very strong unrotated first factor, suggesting that a general factor may be present. This together with the fact that high intercorrelations were found between the nine original subscales suggests that the instrument is not multidimensional. The SCL-90 may be useful in a research setting as an instrument for measuring the change in symptomatic distress, or as a screening instrument. The American community norms should be used with caution, as the Finnish community sample scored consistently higher on all subscales.

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.

Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria.

PubMed

Ojima-Kato, Teruyo; Yamamoto, Naomi; Takahashi, Hajime; Tamura, Hiroto

2016-01-01

The genetic lineages of Listeria monocytogenes and other species of the genus Listeria are correlated with pathogenesis in humans. Although matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has become a prevailing tool for rapid and reliable microbial identification, the precise discrimination of Listeria species and lineages remains a crucial issue in clinical settings and for food safety. In this study, we constructed an accurate and reliable MS database to discriminate the lineages of L. monocytogenes and the species of Listeria (L. monocytogenes, L. innocua, L. welshimeri, L. seeligeri, L. ivanovii, L. grayi, and L. rocourtiae) based on the S10-spc-alpha operon gene encoded ribosomal protein mass spectrum (S10-GERMS) proteotyping method, which relies on both genetic information (genomics) and observed MS peaks in MALDI-TOF MS (proteomics). The specific set of eight biomarkers (ribosomal proteins L24, L6, L18, L15, S11, S9, L31 type B, and S16) yielded characteristic MS patterns for the lineages of L. monocytogenes and the different species of Listeria, and led to the construction of a MS database that was successful in discriminating between these organisms in MALDI-TOF MS fingerprinting analysis followed by advanced proteotyping software Strain Solution analysis. We also confirmed the constructed database on the proteotyping software Strain Solution by using 23 Listeria strains collected from natural sources.

Matrix-assisted Laser Desorption Ionization-Time of Flight Mass Spectrometry (MALDI-TOF MS) Can Precisely Discriminate the Lineages of Listeria monocytogenes and Species of Listeria

PubMed Central

Yamamoto, Naomi; Takahashi, Hajime; Tamura, Hiroto

2016-01-01

The genetic lineages of Listeria monocytogenes and other species of the genus Listeria are correlated with pathogenesis in humans. Although matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has become a prevailing tool for rapid and reliable microbial identification, the precise discrimination of Listeria species and lineages remains a crucial issue in clinical settings and for food safety. In this study, we constructed an accurate and reliable MS database to discriminate the lineages of L. monocytogenes and the species of Listeria (L. monocytogenes, L. innocua, L. welshimeri, L. seeligeri, L. ivanovii, L. grayi, and L. rocourtiae) based on the S10-spc-alpha operon gene encoded ribosomal protein mass spectrum (S10-GERMS) proteotyping method, which relies on both genetic information (genomics) and observed MS peaks in MALDI-TOF MS (proteomics). The specific set of eight biomarkers (ribosomal proteins L24, L6, L18, L15, S11, S9, L31 type B, and S16) yielded characteristic MS patterns for the lineages of L. monocytogenes and the different species of Listeria, and led to the construction of a MS database that was successful in discriminating between these organisms in MALDI-TOF MS fingerprinting analysis followed by advanced proteotyping software Strain Solution analysis. We also confirmed the constructed database on the proteotyping software Strain Solution by using 23 Listeria strains collected from natural sources. PMID:27442502

A computerized method for automated identification of erect posteroanterior and supine anteroposterior chest radiographs

NASA Astrophysics Data System (ADS)

Kao, E.-Fong; Lin, Wei-Chen; Hsu, Jui-Sheng; Chou, Ming-Chung; Jaw, Twei-Shiun; Liu, Gin-Chung

2011-12-01

A computerized scheme was developed for automated identification of erect posteroanterior (PA) and supine anteroposterior (AP) chest radiographs. The method was based on three features, the tilt angle of the scapula superior border, the tilt angle of the clavicle and the extent of radiolucence in lung fields, to identify the view of a chest radiograph. The three indices Ascapula, Aclavicle and Clung were determined from a chest image for the three features. Linear discriminant analysis was used to classify PA and AP chest images based on the three indices. The performance of the method was evaluated by receiver operating characteristic analysis. The proposed method was evaluated using a database of 600 PA and 600 AP chest radiographs. The discriminant performances Az of Ascapula, Aclavicle and Clung were 0.878 ± 0.010, 0.683 ± 0.015 and 0.962 ± 0.006, respectively. The combination of the three indices obtained an Az value of 0.979 ± 0.004. The results indicate that the combination of the three indices could yield high discriminant performance. The proposed method could provide radiologists with information about the view of chest radiographs for interpretation or could be used as a preprocessing step for analyzing chest images.

Surface-enhanced Raman spectroscopy of saliva proteins for the noninvasive differentiation of benign and malignant breast tumors

PubMed Central

Feng, Shangyuan; Huang, Shaohua; Lin, Duo; Chen, Guannan; Xu, Yuanji; Li, Yongzeng; Huang, Zufang; Pan, Jianji; Chen, Rong; Zeng, Haishan

2015-01-01

The capability of saliva protein analysis, based on membrane protein purification and surface-enhanced Raman spectroscopy (SERS), for detecting benign and malignant breast tumors is presented in this paper. A total of 97 SERS spectra from purified saliva proteins were acquired from samples obtained from three groups: 33 healthy subjects; 33 patients with benign breast tumors; and 31 patients with malignant breast tumors. Subtle but discernible changes in the mean SERS spectra of the three groups were observed. Tentative assignments of the saliva protein SERS spectra demonstrated that benign and malignant breast tumors led to several specific biomolecular changes of the saliva proteins. Multiclass partial least squares–discriminant analysis was utilized to analyze and classify the saliva protein SERS spectra from healthy subjects, benign breast tumor patients, and malignant breast tumor patients, yielding diagnostic sensitivities of 75.75%, 72.73%, and 74.19%, as well as specificities of 93.75%, 81.25%, and 86.36%, respectively. The results from this exploratory work demonstrate that saliva protein SERS analysis combined with partial least squares–discriminant analysis diagnostic algorithms has great potential for the noninvasive and label-free detection of breast cancer. PMID:25609959

Food cravings discriminate between anorexia and bulimia nervosa. Implications for "success" versus "failure" in dietary restriction.

PubMed

Moreno, Silvia; Warren, Cortney S; Rodríguez, Sonia; Fernández, M Carmen; Cepeda-Benito, Antonio

2009-06-01

Food cravings are subjective, motivational states thought to induce binge eating among eating disorder patients. This study compared food cravings across eating disorders. Women (N=135) diagnosed with anorexia nervosa, restrictive (ANR) or binge-purging (ANBP) types, or bulimia nervosa, non-purging (BNNP) or purging (BNP) types completed measures of food cravings. Discriminant analysis yielded two statistically significant functions. The first function differentiated between all the four group pairs except ANBP and BNNP, with levels of various food-craving dimensions successively increasing for ANR, ANBP, BNNP, and BNP participants. The second function differentiated between ANBP and BNNP participants. Overall, the functions improved classification accuracy above chance level (44% fewer errors). The findings suggest that cravings are more strongly associated with loss of control over eating than with dietary restraint tendencies.

Investigating a computerised test of the Stroop effect extended by inclusion of a third, more difficult task.

PubMed

Federmann, Rolf; Goldsmith, Robert; Bäckström, Martin

2007-04-01

A validation study of a computerised test recently developed involving the Stroop effect, extended here by inclusion of a third, more difficult test series, is presented. Three groups of men belonging to the Swedish armed forces and adjudged to differ in their qualifications (20, 32, and 19 men of levels 1, 2, and 3, respectively) and a fourth group of 18 men convicted of serious crimes of violence were given this test, termed the Stress Strategy Test. Discriminant analysis of the test's 12 variables (four for each of the three test series) yielded a discriminant power of 65% for the total group, highest for the level 1 group (80%) and for the nonmilitary group (72%), results substantially better than obtained for the original version of the test with use of similar subject groups.

Comparison of base composition analysis and Sanger sequencing of mitochondrial DNA for four U.S. population groups.

PubMed

Kiesler, Kevin M; Coble, Michael D; Hall, Thomas A; Vallone, Peter M

2014-01-01

A set of 711 samples from four U.S. population groups was analyzed using a novel mass spectrometry based method for mitochondrial DNA (mtDNA) base composition profiling. Comparison of the mass spectrometry results with Sanger sequencing derived data yielded a concordance rate of 99.97%. Length heteroplasmy was identified in 46% of samples and point heteroplasmy was observed in 6.6% of samples in the combined mass spectral and Sanger data set. Using discrimination capacity as a metric, Sanger sequencing of the full control region had the highest discriminatory power, followed by the mass spectrometry base composition method, which was more discriminating than Sanger sequencing of just the hypervariable regions. This trend is in agreement with the number of nucleotides covered by each of the three assays. Published by Elsevier Ireland Ltd.

Psychometric properties of the defense style questionnaire (DSQ-40) in adolescents.

PubMed

Ruuttu, Titta; Pelkonen, Mirjami; Holi, Matti; Karlsson, Linnea; Kiviruusu, Olli; Heilä, Hannele; Tuisku, Virpi; Tuulio-Henriksson, Annamari; Marttunen, Mauri

2006-02-01

This study examined the psychometric properties of the Defense Style Questionnaire (DSQ-40) in adolescents. Internal consistency, factor structure, and discriminant and concurrent validity of the DSQ-40 were studied in 211 adolescent psychiatric outpatients aged 13 to 19 years and 199 age-matched and sex-matched controls. Principal components analysis yielded four internally consistent components: mature, neurotic, image-distorting, and immature defense styles. The outpatients reported more immature, image-distorting, and neurotic styles and less mature style than did the controls, suggesting adequate discriminant validity. As a demonstration of convergent and concurrent validity, the severity of psychiatric symptoms assessed by the General Health Questionnaire and psychosocial adjustment assessed by the Global Assessment of Functioning Scale correlated theoretically meaningfully with the different defense styles. The DSQ-40 appears to be a reliable and valid instrument for adolescents.

Cs2LiLa(Br,Cl)6 Crystals for Nuclear Security Applications

NASA Astrophysics Data System (ADS)

Hawrami, R.; Pandian, L. Soundara; Ariesanti, E.; Glodo, J.; Finkelstein, J.; Tower, J.; Shah, K.

2016-04-01

Properties of dual-mode scintillation detectors based on CLLBC crystals are reported. Energy resolution and light yield are measured at 2.9% (FWHM) at 662 keV and 45000 photons/MeV, respectively, for a 1-in-diameter and 1-in-long crystal. With less than 2% variation in light yield as a function of energy, CLLBC has better proportionality than LaBr3 and NaI:Tl. Neutron peak resulting from reactions with neutrons emitted by 252Cf (moderated) is measured at a gamma energy equivalent of 3.1 MeVee (electron energy equivalent), making pulse height discrimination between gamma-rays and neutrons easy. The material is also of effective pulse shape discrimination. The figure-of-merit for discrimination of gamma rays and thermal neutrons in CLLBC can be as high as 3.2, which is comparable to that of CLYC.

Identifying Discrimination at Work: The Use of Field Experiments.

PubMed

Pager, Devah; Western, Bruce

2012-06-01

Antidiscrimination law offers protection to workers who have been treated unfairly on the basis of their race, gender, religion, or national origin. In order for these protections to be invoked, however, potential plaintiffs must be aware of and able to document discriminatory treatment. Given the subtlety of contemporary forms of discrimination, it is often difficult to identify discrimination when it has taken place. The methodology of field experiments offers one approach to measuring and detecting hiring discrimination, providing direct observation of discrimination in real-world settings. In this article, we discuss the findings of two recent field experiments measuring racial discrimination in low wage labor markets. This research provides several relevant findings for researchers and those interested in civil rights enforcement: (1) it produces estimates of the rate of discrimination at the point of hire; (2) it yields evidence about the interactions associated with discrimination (many of which reveal the subtlety with which contemporary discrimination is practiced); and (3) it provides a vehicle for both research on and enforcement of antidiscrimination law.

Proceedings of the 11th Annual DARPA/AFGL Seismic Research symposium

NASA Astrophysics Data System (ADS)

Lewkowicz, James F.; McPhetres, Jeanne M.

1990-11-01

The following subjects are covered: near source observations of quarry explosions; small explosion discrimination and yield estimation; Rg as a depth discriminant for earthquakes and explosions: a case study in New England; a comparative study of high frequency seismic noise at selected sites in the USSR and USA; chemical explosions and the discrimination problem; application of simulated annealing to joint hypocenter determination; frequency dependence of Q(sub Lg) and Q in the continental crust; statistical approaches to testing for compliance with a threshold test ban treaty; broad-band studies of seismic sources at regional and teleseismic distances using advanced time series analysis methods; effects of depth of burial and tectonic release on regional and teleseismic explosion waveforms; finite difference simulations of seismic wave excitation at Soviet test sites with deterministic structures; stochastic geologic effects on near-field ground motions; the damage mechanics of porous rock; nonlinear attenuation mechanism in salt at moderate strain; compressional- and shear-wave polarizations at the Anza seismic array; and a generalized beamforming approach to real time network detection and phase association.

Discrimination, racial bias, and telomere length in African-American men.

PubMed

Chae, David H; Nuru-Jeter, Amani M; Adler, Nancy E; Brody, Gene H; Lin, Jue; Blackburn, Elizabeth H; Epel, Elissa S

2014-02-01

Leukocyte telomere length (LTL) is an indicator of general systemic aging, with shorter LTL being associated with several chronic diseases of aging and earlier mortality. Identifying factors related to LTL among African Americans may yield insights into mechanisms underlying racial disparities in health. To test whether the combination of more frequent reports of racial discrimination and holding a greater implicit anti-black racial bias is associated with shorter LTL among African-American men. Cross-sectional study of a community sample of 92 African-American men aged between 30 and 50 years. Participants were recruited from February to May 2010. Ordinary least squares regressions were used to examine LTL in kilobase pairs in relation to racial discrimination and implicit racial bias. Data analysis was completed in July 2013. After controlling for chronologic age and socioeconomic and health-related characteristics, the interaction between racial discrimination and implicit racial bias was significantly associated with LTL (b=-0.10, SE=0.04, p=0.02). Those demonstrating a stronger implicit anti-black bias and reporting higher levels of racial discrimination had the shortest LTL. Household income-to-poverty threshold ratio was also associated with LTL (b=0.05, SE=0.02, p<0.01). Results suggest that multiple levels of racism, including interpersonal experiences of racial discrimination and the internalization of negative racial bias, operate jointly to accelerate biological aging among African-American men. Societal efforts to address racial discrimination in concert with efforts to promote positive in-group racial attitudes may protect against premature biological aging in this population. © 2013 American Journal of Preventive Medicine Published by American Journal of Preventive Medicine All rights reserved.

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.

An experimental case study to estimate Pre-harvest Wheat Acreage/Production in Hilly and Plain region of Uttarakhand state: Challenges and solutions of problems by using satellite data

NASA Astrophysics Data System (ADS)

Uniyal, D.; Kimothi, M. M.; Bhagya, N.; Ram, R. D.; Patel, N. K.; Dhaundiya, V. K.

2014-11-01

Wheat is an economically important Rabi crop for the state, which is grown on around 26 % of total available agriculture area in the state. There is a variation in productivity of wheat crop in hilly and tarai region. The agricultural productivity is less in hilly region in comparison of tarai region due to terrace cultivation, traditional system of agriculture, small land holdings, variation in physiography, top soil erosion, lack of proper irrigation system etc. Pre-harvest acreage/yield/production estimation of major crops is being done with the help of conventional crop cutting method, which is biased, inaccurate and time consuming. Remote Sensing data with multi-temporal and multi-spectral capabilities has shown new dimension in crop discrimination analysis and acreage/yield/production estimation in recent years. In view of this, Uttarakhand Space Applications Centre (USAC), Dehradun with the collaboration of Space Applications Centre (SAC), ISRO, Ahmedabad and Uttarakhand State Agriculture Department, have developed different techniques for the discrimination of crops and estimation of pre-harvest wheat acreage/yield/production. In the 1st phase, five districts (Dehradun, Almora, Udham Singh Nagar, Pauri Garhwal and Haridwar) with distinct physiography i.e. hilly and plain regions, have been selected for testing and verification of techniques using IRS (Indian Remote Sensing Satellites), LISS-III, LISS-IV satellite data of Rabi season for the year 2008-09 and whole 13 districts of the Uttarakhand state from 2009-14 along with ground data were used for detailed analysis. Five methods have been developed i.e. NDVI (Normalized Differential Vegetation Index), Supervised classification, Spatial modeling, Masking out method and Programming on visual basics methods using multitemporal satellite data of Rabi season along with the collateral and ground data. These methods were used for wheat discriminations and preharvest acreage estimations and subsequently results were compared with Bureau of Estimation Statistics (BES). Out of these five different methods, wheat area that was estimated by spatial modeling and programming on visual basics has been found quite near to Bureau of Estimation Statistics (BES). But for hilly region, maximum fields were going in shadow region, so it was difficult to estimate accurate result, so frequency distribution curve method has been used and frequency range has been decided to discriminate wheat pixels from other pixels in hilly region, digitized those regions and result shows good result. For yield estimation, an algorithm has been developed by using soil characteristics i.e. texture, depth, drainage, temperature, rainfall and historical yield data. To get the production estimation, estimated yield multiplied by acreage of crop per hectare. Result shows deviation for acreage estimation from BES is around 3.28 %, 2.46 %, 3.45 %, 1.56 %, 1.2 % and 1.6 % (estimation not declared till now by state Agriculture dept. For the year 2013-14) estimation and deviation for production estimation is around 4.98 %, 3.66 % 3.21 % , 3.1 % NA and 2.9 % for the consecutive above mentioned years i.e. 2008-09, 2009-10, 2010-11, 2011-12, 2012-13 and 2013-14. The estimated data has been provided to State Agriculture department for their use. To forecast production before harvest facilitate the formulation of workable marketing strategies leading to better export/import of crop in the state, which will help to lead better economic condition of the state. Yield estimation would help agriculture department in assessment of productivity of land for specific crop. Pre-harvest wheat acreage/production estimation, is useful to facilitate the reliable and timely estimates and enable the administrators and planners to take strategic decisions on import-export policy matters and trade negotiations.

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.

Information loss in approximately bayesian data assimilation: a comparison of generative and discriminative approaches to estimating agricultural yield

USDA-ARS?s Scientific Manuscript database

Data assimilation and regression are two commonly used methods for predicting agricultural yield from remote sensing observations. Data assimilation is a generative approach because it requires explicit approximations of the Bayesian prior and likelihood to compute the probability density function...

Signal yields of keV electronic recoils and their discrimination from nuclear recoils in liquid xenon

NASA Astrophysics Data System (ADS)

Aprile, E.; Aalbers, J.; Agostini, F.; Alfonsi, M.; Amaro, F. D.; Anthony, M.; Arneodo, F.; Barrow, P.; Baudis, L.; Bauermeister, B.; Benabderrahmane, M. L.; Berger, T.; Breur, P. A.; Brown, A.; Brown, E.; Bruenner, S.; Bruno, G.; Budnik, R.; Bütikofer, L.; Calvén, J.; Cardoso, J. M. R.; Cervantes, M.; Cichon, D.; Coderre, D.; Colijn, A. P.; Conrad, J.; Cussonneau, J. P.; Decowski, M. P.; de Perio, P.; di Gangi, P.; di Giovanni, A.; Diglio, S.; Eurin, G.; Fei, J.; Ferella, A. D.; Fieguth, A.; Fulgione, W.; Gallo Rosso, A.; Galloway, M.; Gao, F.; Garbini, M.; Geis, C.; Goetzke, L. W.; Grandi, L.; Greene, Z.; Grignon, C.; Hasterok, C.; Hogenbirk, E.; Howlett, J.; Itay, R.; Kaminsky, B.; Kazama, S.; Kessler, G.; Kish, A.; Landsman, H.; Lang, R. F.; Lellouch, D.; Levinson, L.; Lin, Q.; Lindemann, S.; Lindner, M.; Lombardi, F.; Lopes, J. A. M.; Mahlstedt, J.; Manfredini, A.; Maris, I.; Marrodán Undagoitia, T.; Masbou, J.; Massoli, F. V.; Masson, D.; Mayani, D.; Messina, M.; Micheneau, K.; Molinario, A.; Morâ, K.; Murra, M.; Naganoma, J.; Ni, K.; Oberlack, U.; Pakarha, P.; Pelssers, B.; Persiani, R.; Piastra, F.; Pienaar, J.; Pizzella, V.; Piro, M.-C.; Plante, G.; Priel, N.; Ramírez García, D.; Rauch, L.; Reichard, S.; Reuter, C.; Rizzo, A.; Rupp, N.; Saldanha, R.; Dos Santos, J. M. F.; Sartorelli, G.; Scheibelhut, M.; Schindler, S.; Schreiner, J.; Schumann, M.; Scotto Lavina, L.; Selvi, M.; Shagin, P.; Shockley, E.; Silva, M.; Simgen, H.; Sivers, M. V.; Stein, A.; Thers, D.; Tiseni, A.; Trinchero, G.; Tunnell, C.; Vargas, M.; Wang, H.; Wang, Z.; Wei, Y.; Weinheimer, C.; Wittweg, C.; Wulf, J.; Ye, J.; Zhang, Y.; Zhu, T.; Xenon Collaboration

2018-05-01

We report on the response of liquid xenon to low energy electronic recoils below 15 keV from beta decays of tritium at drift fields of 92 V /cm , 154 V /cm and 366 V /cm using the XENON100 detector. A data-to-simulation fitting method based on Markov Chain Monte Carlo is used to extract the photon yields and recombination fluctuations from the experimental data. The photon yields measured at the two lower fields are in agreement with those from literature; additional measurements at a higher field of 366 V /cm are presented. The electronic and nuclear recoil discrimination as well as its dependence on the drift field and photon detection efficiency are investigated at these low energies. The results provide new measurements in the energy region of interest for dark matter searches using liquid xenon.

Advanced plastic scintillators for fast neutron discrimination

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

Feng, Patrick L; Anstey, Mitchell; Doty, F. Patrick

2014-09-01

The present work addresses the need for solid-state, fast neutron discriminating scintillators that possess higher light yields and faster decay kinetics than existing organic scintillators. These respective attributes are of critical importance for improving the gamma-rejection capabilities and increasing the neutron discrimination performance under high-rate conditions. Two key applications that will benefit from these improvements include large-volume passive detection scenarios as well as active interrogation search for special nuclear materials. Molecular design principles were employed throughout this work, resulting in synthetically tailored materials that possess the targeted scintillation properties.

When fiends become friends: the need to belong and perceptions of personal and group discrimination.

PubMed

Carvallo, Mauricio; Pelham, Brett W

2006-01-01

The present article examines the role that the need to belong (NTB) plays in people's judgments of personal and group discrimination and in the attributions people make for potentially discriminatory evaluations. The authors hypothesized that the NTB motivates people to conclude that (a) whereas they rarely experience personal discrimination, (b) their fellow in-group members do experience discrimination. In Study 1, people high in the NTB reported experiencing lower than average levels of personal and higher than average levels of group discrimination. In Study 2, an experimental manipulation of the NTB yielded similar results. In Study 3, women who were motivated to be accepted by a bogus male participant were less likely to attribute his negative evaluations of their work to prejudice. ((c) 2006 APA, all rights reserved).

Does cognitive performance map to categorical diagnoses of schizophrenia, schizoaffective disorder and bipolar disorder? A discriminant functions analysis.

PubMed

Van Rheenen, Tamsyn E; Bryce, Shayden; Tan, Eric J; Neill, Erica; Gurvich, Caroline; Louise, Stephanie; Rossell, Susan L

2016-03-01

Despite known overlaps in the pattern of cognitive impairments in individuals with bipolar disorder (BD), schizophrenia (SZ) and schizoaffective disorder (SZA), few studies have examined the extent to which cognitive performance validates traditional diagnostic boundaries in these groups. Individuals with SZ (n=49), schizoaffective disorder (n=33) and BD (n=35) completed a battery of cognitive tests measuring the domains of processing speed, immediate memory, semantic memory, learning, working memory, executive function and sustained attention. A discriminant functions analysis revealed a significant function comprising semantic memory, immediate memory and processing speed that maximally separated patients with SZ from those with BD. Initial classification scores on the basis of this function showed modest diagnostic accuracy, owing in part to the misclassification of SZA patients as having SZ. When SZA patients were removed from the model, a second cross-validated classifier yielded slightly improved diagnostic accuracy and a single function solution, of which semantic memory loaded most heavily. A cluster of non-executive cognitive processes appears to have some validity in mapping onto traditional nosological boundaries. However, since semantic memory performance was the primary driver of the discrimination between BD and SZ, it is possible that performance differences between the disorders in this cognitive domain in particular, index separate underlying aetiologies. Copyright © 2015 Elsevier B.V. All rights reserved.

Whole-lesion histogram analysis metrics of the apparent diffusion coefficient as a marker of breast lesions characterization at 1.5 T.

PubMed

Bougias, H; Ghiatas, A; Priovolos, D; Veliou, K; Christou, A

2017-05-01

To retrospectively assess the role of whole-lesion apparent diffusion coefficient (ADC) in the characterization of breast tumors by comparing different histogram metrics. 49 patients with 53 breast lesions underwent magnetic resonance imaging (MRI). ADC histogram parameters, including the mean, mode, 10th/50th/90th percentile, skewness, kurtosis, and entropy ADCs, were derived for the whole-lesion volume in each patient. Mann-Whitney U-test, area under the receiver-operating characteristic curve (AUC) were used for statistical analysis. The mean, mode and 10th/50th/90th percentile ADC values were significantly lower in malignant lesions compared with benign ones (all P < 0.0001), while skewness was significantly higher in malignant lesions P = 0.02. However, no significant difference was found between entropy and kurtosis values in malignant lesions compared with benign ones (P = 0.06 and P = 1.00, respectively). Univariate logistic regression showed that 10th and 50th percentile ADC yielded the highest AUC (0.985; 95% confidence interval [CI]: 0.902, 1.000 and 0.982; 95% confidence interval [CI]: 0.896, 1.000 respectively), whereas kurtosis value yielded the lowest AUC (0.500; 95% CI: 0.355, 0.645), indicating that 10th and 50th percentile ADC values may be more accurate for lesion discrimination. Whole-lesion ADC histogram analysis could be a helpful index in the characterization and differentiation between benign and malignant breast lesions with the 10th and 50th percentile ADC be the most accurate discriminators. Copyright © 2017 The College of Radiographers. Published by Elsevier Ltd. All rights reserved.

Identification of Dyslipidemic Patients Attending Primary Care Clinics Using Electronic Medical Record (EMR) Data from the Canadian Primary Care Sentinel Surveillance Network (CPCSSN) Database.

PubMed

Aref-Eshghi, Erfan; Oake, Justin; Godwin, Marshall; Aubrey-Bassler, Kris; Duke, Pauline; Mahdavian, Masoud; Asghari, Shabnam

2017-03-01

The objective of this study was to define the optimal algorithm to identify patients with dyslipidemia using electronic medical records (EMRs). EMRs of patients attending primary care clinics in St. John's, Newfoundland and Labrador (NL), Canada during 2009-2010, were studied to determine the best algorithm for identification of dyslipidemia. Six algorithms containing three components, dyslipidemia ICD coding, lipid lowering medication use, and abnormal laboratory lipid levels, were tested against a gold standard, defined as the existence of any of the three criteria. Linear discriminate analysis, and bootstrapping were performed following sensitivity/specificity testing and receiver's operating curve analysis. Two validating datasets, NL records of 2011-2014, and Canada-wide records of 2010-2012, were used to replicate the results. Relative to the gold standard, combining laboratory data together with lipid lowering medication consumption yielded the highest sensitivity (99.6%), NPV (98.1%), Kappa agreement (0.98), and area under the curve (AUC, 0.998). The linear discriminant analysis for this combination resulted in an error rate of 0.15 and an Eigenvalue of 1.99, and the bootstrapping led to AUC: 0.998, 95% confidence interval: 0.997-0.999, Kappa: 0.99. This algorithm in the first validating dataset yielded a sensitivity of 97%, Negative Predictive Value (NPV) = 83%, Kappa = 0.88, and AUC = 0.98. These figures for the second validating data set were 98%, 93%, 0.95, and 0.99, respectively. Combining laboratory data with lipid lowering medication consumption within the EMR is the best algorithm for detecting dyslipidemia. These results can generate standardized information systems for dyslipidemia and other chronic disease investigations using EMRs.

Using complex networks for text classification: Discriminating informative and imaginative documents

NASA Astrophysics Data System (ADS)

de Arruda, Henrique F.; Costa, Luciano da F.; Amancio, Diego R.

2016-01-01

Statistical methods have been widely employed in recent years to grasp many language properties. The application of such techniques have allowed an improvement of several linguistic applications, such as machine translation and document classification. In the latter, many approaches have emphasised the semantical content of texts, as is the case of bag-of-word language models. These approaches have certainly yielded reasonable performance. However, some potential features such as the structural organization of texts have been used only in a few studies. In this context, we probe how features derived from textual structure analysis can be effectively employed in a classification task. More specifically, we performed a supervised classification aiming at discriminating informative from imaginative documents. Using a networked model that describes the local topological/dynamical properties of function words, we achieved an accuracy rate of up to 95%, which is much higher than similar networked approaches. A systematic analysis of feature relevance revealed that symmetry and accessibility measurements are among the most prominent network measurements. Our results suggest that these measurements could be used in related language applications, as they play a complementary role in characterising texts.

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.

Accumulator and random-walk models of psychophysical discrimination: a counter-evaluation.

PubMed

Vickers, D; Smith, P

1985-01-01

In a recent assessment of models of psychophysical discrimination, Heath criticises the accumulator model for its reliance on computer simulation and qualitative evidence, and contrasts it unfavourably with a modified random-walk model, which yields exact predictions, is susceptible to critical test, and is provided with simple parameter-estimation techniques. A counter-evaluation is presented, in which the approximations employed in the modified random-walk analysis are demonstrated to be seriously inaccurate, the resulting parameter estimates to be artefactually determined, and the proposed test not critical. It is pointed out that Heath's specific application of the model is not legitimate, his data treatment inappropriate, and his hypothesis concerning confidence inconsistent with experimental results. Evidence from adaptive performance changes is presented which shows that the necessary assumptions for quantitative analysis in terms of the modified random-walk model are not satisfied, and that the model can be reconciled with data at the qualitative level only by making it virtually indistinguishable from an accumulator process. A procedure for deriving exact predictions for an accumulator process is outlined.

Discrimination of ginseng cultivation regions using light stable isotope analysis.

PubMed

Kim, Kiwook; Song, Joo-Hyun; Heo, Sang-Cheol; Lee, Jin-Hee; Jung, In-Woo; Min, Ji-Sook

2015-10-01

Korean ginseng is considered to be a precious health food in Asia. Today, thieves frequently compromise ginseng farms by pervasive theft. Thus, studies regarding the characteristics of ginseng according to growth region are required in order to deter ginseng thieves and prevent theft. In this study, 6 regions were selected on the basis of Korea regional criteria (si, gun, gu), and two ginseng-farms were randomly selected from each of the 6 regions. Then 4-6 samples of ginseng were acquired from each ginseng farm. The stable isotopic compositions of H, O, C, and N of the collected ginseng samples were analyzed. As a result, differences in the hydrogen isotope ratios could be used to distinguish regional differences, and differences in the nitrogen isotope ratios yielded characteristic information regarding the farms from which the samples were obtained. Thus, stable isotope values could be used to differentiate samples according to regional differences. Therefore, stable isotope analysis serves as a powerful tool to discriminate the regional origin of Korean ginseng samples from across Korea. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Apparent Yield Strength of Hot-Pressed SiCs

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

Daloz, William L; Wereszczak, Andrew A; Jadaan, Osama M.

2008-01-01

Apparent yield strengths (YApp) of four hot-pressed silicon carbides (SiC-B, SiC-N,SiC-HPN, and SiC-SC-1RN) were estimated using diamond spherical or Hertzian indentation. The von Mises and Tresca criteria were considered. The developed test method was robust, simple and quick to execute, and thusly enabled the acquisition of confident sampling statistics. The choice of indenter size, test method, and method of analysis are described. The compressive force necessary to initiate apparent yielding was identified postmortem using differential interference contrast (or Nomarski) imaging with an optical microscope. It was found that the YApp of SiC-HPN (14.0 GPa) was approximately 10% higher than themore » equivalently valued YApp of SiC-B, SiC-N, and SiC-SC-1RN. This discrimination in YApp shows that the use of this test method could be insightful because there were no differences among the average Knoop hardnesses of the four SiC grades.« less

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

The timing resolution of scintillation-detector systems: Monte Carlo analysis

NASA Astrophysics Data System (ADS)

Choong, Woon-Seng

2009-11-01

Recent advancements in fast scintillating materials and fast photomultiplier tubes (PMTs) have stimulated renewed interest in time-of-flight (TOF) positron emission tomography (PET). It is well known that the improvement in the timing resolution in PET can significantly reduce the noise variance in the reconstructed image resulting in improved image quality. In order to evaluate the timing performance of scintillation detectors used in TOF PET, we use Monte Carlo analysis to model the physical processes (crystal geometry, crystal surface finish, scintillator rise time, scintillator decay time, photoelectron yield, PMT transit time spread, PMT single-electron response, amplifier response and time pick-off method) that can contribute to the timing resolution of scintillation-detector systems. In the Monte Carlo analysis, the photoelectron emissions are modeled by a rate function, which is used to generate the photoelectron time points. The rate function, which is simulated using Geant4, represents the combined intrinsic light emissions of the scintillator and the subsequent light transport through the crystal. The PMT output signal is determined by the superposition of the PMT single-electron response resulting from the photoelectron emissions. The transit time spread and the single-electron gain variation of the PMT are modeled in the analysis. Three practical time pick-off methods are considered in the analysis. Statistically, the best timing resolution is achieved with the first photoelectron timing. The calculated timing resolution suggests that a leading edge discriminator gives better timing performance than a constant fraction discriminator and produces comparable results when a two-threshold or three-threshold discriminator is used. For a typical PMT, the effect of detector noise on the timing resolution is negligible. The calculated timing resolution is found to improve with increasing mean photoelectron yield, decreasing scintillator decay time and decreasing transit time spread. However, only substantial improvement in the timing resolution is obtained with improved transit time spread if the first photoelectron timing is less than the transit time spread. While the calculated timing performance does not seem to be affected by the pixel size of the crystal, it improves for an etched crystal compared to a polished crystal. In addition, the calculated timing resolution degrades with increasing crystal length. These observations can be explained by studying the initial photoelectron rate. Experimental measurements provide reasonably good agreement with the calculated timing resolution. The Monte Carlo analysis developed in this work will allow us to optimize the scintillation detectors for timing and to understand the physical factors limiting their performance.

The timing resolution of scintillation-detector systems: Monte Carlo analysis.

PubMed

Choong, Woon-Seng

2009-11-07

Recent advancements in fast scintillating materials and fast photomultiplier tubes (PMTs) have stimulated renewed interest in time-of-flight (TOF) positron emission tomography (PET). It is well known that the improvement in the timing resolution in PET can significantly reduce the noise variance in the reconstructed image resulting in improved image quality. In order to evaluate the timing performance of scintillation detectors used in TOF PET, we use Monte Carlo analysis to model the physical processes (crystal geometry, crystal surface finish, scintillator rise time, scintillator decay time, photoelectron yield, PMT transit time spread, PMT single-electron response, amplifier response and time pick-off method) that can contribute to the timing resolution of scintillation-detector systems. In the Monte Carlo analysis, the photoelectron emissions are modeled by a rate function, which is used to generate the photoelectron time points. The rate function, which is simulated using Geant4, represents the combined intrinsic light emissions of the scintillator and the subsequent light transport through the crystal. The PMT output signal is determined by the superposition of the PMT single-electron response resulting from the photoelectron emissions. The transit time spread and the single-electron gain variation of the PMT are modeled in the analysis. Three practical time pick-off methods are considered in the analysis. Statistically, the best timing resolution is achieved with the first photoelectron timing. The calculated timing resolution suggests that a leading edge discriminator gives better timing performance than a constant fraction discriminator and produces comparable results when a two-threshold or three-threshold discriminator is used. For a typical PMT, the effect of detector noise on the timing resolution is negligible. The calculated timing resolution is found to improve with increasing mean photoelectron yield, decreasing scintillator decay time and decreasing transit time spread. However, only substantial improvement in the timing resolution is obtained with improved transit time spread if the first photoelectron timing is less than the transit time spread. While the calculated timing performance does not seem to be affected by the pixel size of the crystal, it improves for an etched crystal compared to a polished crystal. In addition, the calculated timing resolution degrades with increasing crystal length. These observations can be explained by studying the initial photoelectron rate. Experimental measurements provide reasonably good agreement with the calculated timing resolution. The Monte Carlo analysis developed in this work will allow us to optimize the scintillation detectors for timing and to understand the physical factors limiting their performance.

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…

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.

Moment tensor analysis of very shallow sources

DOE PAGES

Chiang, Andrea; Dreger, Douglas S.; Ford, Sean R.; ...

2016-10-11

An issue for moment tensor (MT) inversion of shallow seismic sources is that some components of the Green’s functions have vanishing amplitudes at the free surface, which can result in bias in the MT solution. The effects of the free surface on the stability of the MT method become important as we continue to investigate and improve the capabilities of regional full MT inversion for source–type identification and discrimination. It is important to understand free–surface effects on discriminating shallow explosive sources for nuclear monitoring purposes. It may also be important in natural systems that have very shallow seismicity, such asmore » volcanic and geothermal systems. We examine the effects of the free surface on the MT via synthetic testing and apply the MT–based discrimination method to three quarry blasts from the HUMMING ALBATROSS experiment. These shallow chemical explosions at ~10 m depth and recorded up to several kilometers distance represent rather severe source–station geometry in terms of free–surface effects. 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. Furthermore, recovering the design yield using seismic moment estimates from MT inversion remains challenging, but we can begin to put error bounds on our moment estimates using the network sensitivity solution technique.« less

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.

Brownian motion curve-based textural classification and its application in cancer diagnosis.

PubMed

Mookiah, Muthu Rama Krishnan; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

2011-06-01

To develop an automated diagnostic methodology based on textural features of the oral mucosal epithelium to discriminate normal and oral submucous fibrosis (OSF). A total of 83 normal and 29 OSF images from histopathologic sections of the oral mucosa are considered. The proposed diagnostic mechanism consists of two parts: feature extraction using Brownian motion curve (BMC) and design ofa suitable classifier. The discrimination ability of the features has been substantiated by statistical tests. An error back-propagation neural network (BPNN) is used to classify OSF vs. normal. In development of an automated oral cancer diagnostic module, BMC has played an important role in characterizing textural features of the oral images. Fisher's linear discriminant analysis yields 100% sensitivity and 85% specificity, whereas BPNN leads to 92.31% sensitivity and 100% specificity, respectively. In addition to intensity and morphology-based features, textural features are also very important, especially in histopathologic diagnosis of oral cancer. In view of this, a set of textural features are extracted using the BMC for the diagnosis of OSF. Finally, a textural classifier is designed using BPNN, which leads to a diagnostic performance with 96.43% accuracy. (Anal Quant

Sensitive and Structure-Informative N-Glycosylation Analysis by MALDI-MS; Ionization, Fragmentation, and Derivatization

PubMed Central

Nishikaze, Takashi

2017-01-01

Mass spectrometry (MS) has become an indispensable tool for analyzing post translational modifications of proteins, including N-glycosylated molecules. Because most glycosylation sites carry a multitude of glycans, referred to as “glycoforms,” the purpose of an N-glycosylation analysis is glycoform profiling and glycosylation site mapping. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) has unique characteristics that are suited for the sensitive analysis of N-glycosylated products. However, the analysis is often hampered by the inherent physico-chemical properties of N-glycans. Glycans are highly hydrophilic in nature, and therefore tend to show low ion yields in both positive- and negative-ion modes. The labile nature and complicated branched structures involving various linkage isomers make structural characterization difficult. This review focuses on MALDI-MS-based approaches for enhancing analytical performance in N-glycosylation research. In particular, the following three topics are emphasized: (1) Labeling for enhancing the ion yields of glycans and glycopeptides, (2) Negative-ion fragmentation for less ambiguous elucidation of the branched structure of N-glycans, (3) Derivatization for the stabilization and linkage isomer discrimination of sialic acid residues. PMID:28794918

Leaf gas exchange, carbon isotope discrimination, and grain yield in contrasting rice genotypes subjected to water deficits during the reproductive stage.

PubMed

Centritto, Mauro; Lauteri, Marco; Monteverdi, Maria Cristina; Serraj, Rachid

2009-01-01

Genotypic variations in leaf gas exchange and yield were analysed in five upland-adapted and three lowland rice cultivars subjected to a differential soil moisture gradient, varying from well-watered to severely water-stressed conditions. A reduction in the amount of water applied resulted in a significant decrease in leaf gas exchange and, subsequently, in above-ground dry mass and grain yield, that varied among genotypes and distance from the line source. The comparison between the variable J and the Delta values in recently synthesized sugars methods, yielded congruent estimations of mesophyll conductance (g(m)), confirming the reliability of these two techniques. Our data demonstrate that g(m) is a major determinant of photosynthesis (A), because rice genotypes with inherently higher g(m) were capable of keeping higher A in stressed conditions. Furthermore, A, g(s), and g(m) of water-stressed genotypes rapidly recovered to the well-watered values upon the relief of water stress, indicating that drought did not cause any lasting metabolic limitation to photosynthesis. The comparisons between the A/C(i) and corresponding A/C(c) curves, measured in the genotypes that showed intrinsically higher and lower instantaneous A, confirmed this finding. Moreover, the effect of drought stress on grain yield was correlated with the effects on both A and total diffusional limitations to photosynthesis. Overall, these data indicate that genotypes which showed higher photosynthesis and conductances were also generally more productive across the entire soil moisture gradient. The analysis of Delta revealed a substantial variation of water use efficiency among the genotypes, both on the long-term (leaf pellet analysis) and short-term scale (leaf soluble sugars analysis).

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.

Effects of Cerebral Blood Flow and Vessel Conditions on Speech Recognition in Patients With Postlingual Adult Cochlear Implant: Predictable Factors for the Efficacy of Cochlear Implant.

PubMed

Ishino, Takashi; Ragaee, Mahmoud Ali; Maruhashi, Tatsuya; Kajikawa, Masato; Higashi, Yukihito; Sonoyama, Toru; Takeno, Sachio; Hirakawa, Katsuhiro

Cochlear implantation (CI) has been the most successful procedure for restoring hearing in a patient with severe and profound hearing loss. However, possibly owing to the variable brain functions of each patient, its performance and the associated patient satisfaction are widely variable. The authors hypothesize that peripheral and cerebral circulation can be assessed by noninvasive and globally available methods, yielding superior presurgical predictive factors of the performance of CI in adult patients with postlingual hearing loss who are scheduled to undergo CI. Twenty-two adult patients with cochlear implants for postlingual hearing loss were evaluated using Doppler sonography measurement of the cervical arteries (reflecting cerebral blood flow), flow-mediated dilation (FMD; reflecting the condition of cerebral arteries), and their pre-/post-CI best score on a monosyllabic discrimination test (pre-/post-CI best monosyllabic discrimination [BMD] score). Correlations between post-CI BMD score and the other factors were examined using univariate analysis and stepwise multiple linear regression analysis. The prediction factors were calculated by examining the receiver-operating characteristic curve between post-CI BMD score and the significantly positively correlated factors. Age and duration of deafness had a moderately negative correlation. The mean velocity of the internal carotid arteries and FMD had a moderate-to-strong positive correlation with the post-CI BMD score in univariate analysis. Stepwise multiple linear regression analysis revealed that only FMD was significantly positively correlated with post-CI BMD score. Analysis of the receiver-operating characteristic curve showed that a FMD cutoff score of 1.8 significantly predicted post-CI BMD score. These data suggest that FMD is a convenient, noninvasive, and widely available tool for predicting the efficacy of cochlear implants. An FMD cutoff score of 1.8 could be a good index for determining whether patients will hear well with cochlear implants. It could also be used to predict whether cochlear implants will provide good speech recognition benefits to candidates, even if their speech discrimination is poor. This FMD index could become a useful predictive tool for candidates with poor speech discrimination to determine the efficacy of CI before surgery.

Bacterial discrimination by means of a universal array approach mediated by LDR (ligase detection reaction)

PubMed Central

Busti, Elena; Bordoni, Roberta; Castiglioni, Bianca; Monciardini, Paolo; Sosio, Margherita; Donadio, Stefano; Consolandi, Clarissa; Rossi Bernardi, Luigi; Battaglia, Cristina; De Bellis, Gianluca

2002-01-01

Background PCR amplification of bacterial 16S rRNA genes provides the most comprehensive and flexible means of sampling bacterial communities. Sequence analysis of these cloned fragments can provide a qualitative and quantitative insight of the microbial population under scrutiny although this approach is not suited to large-scale screenings. Other methods, such as denaturing gradient gel electrophoresis, heteroduplex or terminal restriction fragment analysis are rapid and therefore amenable to field-scale experiments. A very recent addition to these analytical tools is represented by microarray technology. Results Here we present our results using a Universal DNA Microarray approach as an analytical tool for bacterial discrimination. The proposed procedure is based on the properties of the DNA ligation reaction and requires the design of two probes specific for each target sequence. One oligo carries a fluorescent label and the other a unique sequence (cZipCode or complementary ZipCode) which identifies a ligation product. Ligated fragments, obtained in presence of a proper template (a PCR amplified fragment of the 16s rRNA gene) contain either the fluorescent label or the unique sequence and therefore are addressed to the location on the microarray where the ZipCode sequence has been spotted. Such an array is therefore "Universal" being unrelated to a specific molecular analysis. Here we present the design of probes specific for some groups of bacteria and their application to bacterial diagnostics. Conclusions The combined use of selective probes, ligation reaction and the Universal Array approach yielded an analytical procedure with a good power of discrimination among bacteria. PMID:12243651

Performance of the Swedish version of the Revised Piper Fatigue Scale.

PubMed

Jakobsson, Sofie; Taft, Charles; Östlund, Ulrika; Ahlberg, Karin

2013-12-01

The Revised Piper Fatigue scale is one of the most widely used instruments internationally to assess cancer-related fatigue. The aim of the present study was to evaluate selected psychometric properties of a Swedish version of the RPFS (SPFS). An earlier translation of the SPFS was further evaluated and developed. The new version was mailed to 300 patients undergoing curative radiotherapy. The internal validity was assessed using Principal Axis Factor Analysis with oblimin rotation and multitrait analysis. External validity was examined in relation to the Multidimensional Fatigue Inventory-20 (MFI-20) and in known-groups analyses. Totally 196 patients (response rate = 65%) returned evaluable questionnaires. Principal axis factoring analysis yielded three factors (74% of the variance) rather than four as in the original RPFS. Multitrait analyses confirmed the adequacy of scaling assumptions. Known-groups analyses failed to support the discriminative validity. Concurrent validity was satisfactory. The new Swedish version of the RPFS showed good acceptability, reliability and convergent and- discriminant item-scale validity. Our results converge with other international versions of the RPFS in failing to support the four-dimension conceptual model of the instrument. Hence, RPFS suitability for use in international comparisons may be limited which also may have implications for cross-cultural validity of the newly released 12-item version of the RPFS. Further research on the Swedish version should address reasons for high missing rates for certain items in the subscale of affective meaning, further evaluation of the discriminative validity and assessment of its sensitivity in detecting changes over time. Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

Temporal dynamics of sensorimotor integration in speech perception and production: independent component analysis of EEG data

PubMed Central

Jenson, David; Bowers, Andrew L.; Harkrider, Ashley W.; Thornton, David; Cuellar, Megan; Saltuklaroglu, Tim

2014-01-01

Activity in anterior sensorimotor regions is found in speech production and some perception tasks. Yet, how sensorimotor integration supports these functions is unclear due to a lack of data examining the timing of activity from these regions. Beta (~20 Hz) and alpha (~10 Hz) spectral power within the EEG μ rhythm are considered indices of motor and somatosensory activity, respectively. In the current study, perception conditions required discrimination (same/different) of syllables pairs (/ba/ and /da/) in quiet and noisy conditions. Production conditions required covert and overt syllable productions and overt word production. Independent component analysis was performed on EEG data obtained during these conditions to (1) identify clusters of μ components common to all conditions and (2) examine real-time event-related spectral perturbations (ERSP) within alpha and beta bands. 17 and 15 out of 20 participants produced left and right μ-components, respectively, localized to precentral gyri. Discrimination conditions were characterized by significant (pFDR < 0.05) early alpha event-related synchronization (ERS) prior to and during stimulus presentation and later alpha event-related desynchronization (ERD) following stimulus offset. Beta ERD began early and gained strength across time. Differences were found between quiet and noisy discrimination conditions. Both overt syllable and word productions yielded similar alpha/beta ERD that began prior to production and was strongest during muscle activity. Findings during covert production were weaker than during overt production. One explanation for these findings is that μ-beta ERD indexes early predictive coding (e.g., internal modeling) and/or overt and covert attentional/motor processes. μ-alpha ERS may index inhibitory input to the premotor cortex from sensory regions prior to and during discrimination, while μ-alpha ERD may index sensory feedback during speech rehearsal and production. PMID:25071633

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…

Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

PubMed

Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

2007-02-01

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

Discrimination, work outcomes, and mental health among women of color: The protective role of womanist attitudes.

PubMed

Velez, Brandon L; Cox, Robert; Polihronakis, Charles J; Moradi, Bonnie

2018-03-01

With a sample of employed women of color (N = 276), we tested the associations of sexist and racist discrimination with poor work outcomes (job-related burnout and turnover intentions) and mental health outcomes (i.e., psychological distress). Drawing from the Theory of Work Adjustment, Organizational Support Theory, and scholarship on discrimination, we tested perceived person-organization (P-O) fit, perceived organizational support, and self-esteem as mediators of the associations of workplace discrimination with the outcomes. Based on intersectionality scholarship, womanist attitudes were tested as a moderator. Participants provided cross-sectional data via an online survey. Latent variable structural equation modeling results indicated that a second-order latent workplace discrimination variable yielded better fit to the data than modeling sexist and racist discrimination separately. Workplace discrimination was directly and indirectly (via the mediating role of self-esteem) associated with higher psychological distress. Furthermore, workplace discrimination was indirectly associated with poor work outcomes through the mediating roles of perceived P-O fit, perceived organizational support, and self-esteem. Last, moderation analyses indicated that higher womanist attitudes weakened the direct association of workplace discrimination with psychological distress. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Supervised non-negative tensor factorization for automatic hyperspectral feature extraction and target discrimination

NASA Astrophysics Data System (ADS)

Anderson, Dylan; Bapst, Aleksander; Coon, Joshua; Pung, Aaron; Kudenov, Michael

2017-05-01

Hyperspectral imaging provides a highly discriminative and powerful signature for target detection and discrimination. Recent literature has shown that considering additional target characteristics, such as spatial or temporal profiles, simultaneously with spectral content can greatly increase classifier performance. Considering these additional characteristics in a traditional discriminative algorithm requires a feature extraction step be performed first. An example of such a pipeline is computing a filter bank response to extract spatial features followed by a support vector machine (SVM) to discriminate between targets. This decoupling between feature extraction and target discrimination yields features that are suboptimal for discrimination, reducing performance. This performance reduction is especially pronounced when the number of features or available data is limited. In this paper, we propose the use of Supervised Nonnegative Tensor Factorization (SNTF) to jointly perform feature extraction and target discrimination over hyperspectral data products. SNTF learns a tensor factorization and a classification boundary from labeled training data simultaneously. This ensures that the features learned via tensor factorization are optimal for both summarizing the input data and separating the targets of interest. Practical considerations for applying SNTF to hyperspectral data are presented, and results from this framework are compared to decoupled feature extraction/target discrimination pipelines.

Starting Block Performance in Sprinters: A Statistical Method for Identifying Discriminative Parameters of the Performance and an Analysis of the Effect of Providing Feedback over a 6-Week Period

PubMed Central

Fortier, Sylvie; Basset, Fabien A.; Mbourou, Ginette A.; Favérial, Jérôme; Teasdale, Normand

2005-01-01

The purpose of this study was twofold: (a) to examine if kinetic and kinematic parameters of the sprint start could differentiate elite from sub-elite sprinters and, (b) to investigate whether providing feedback (FB) about selected parameters could improve starting block performance of intermediate sprinters over a 6-week training period. Twelve male sprinters, assigned to an elite or a sub-elite group, participated in Experiment 1. Eight intermediate sprinters participated in Experiment 2. All athletes were required to perform three sprint starts at maximum intensity followed by a 10-m run. To detect differences between elite and sub-elite groups, comparisons were made using t-tests for independent samples. Parameters reaching a significant group difference were retained for the linear discriminant analysis (LDA). The LDA yielded four discriminative kinetic parameters. Feedback about these selected parameters was given to sprinters in Experiment 2. For this experiment, data acquisition was divided into three periods. The first six sessions were without specific FB, whereas the following six sessions were enriched by kinetic FB. Finally, athletes underwent a retention session (without FB) 4 weeks after the twelfth session. Even though differences were found in the time to front peak force, the time to rear peak force, and the front peak force in the retention session, the results of the present study showed that providing FB about selected kinetic parameters differentiating elite from sub-elite sprinters did not improve the starting block performance of intermediate sprinters. Key Points The linear discriminative analysis allows the identification of starting block parameters differentiating elite from sub-elite athletes. 6-week of feedback does not alter starting block performance in training context. The present results failed to confirm previous studies since feedback did not improve targeted kinetic parameters of the complex motor task in real-world context. PMID:24431969

Starting Block Performance in Sprinters: A Statistical Method for Identifying Discriminative Parameters of the Performance and an Analysis of the Effect of Providing Feedback over a 6-Week Period.

PubMed

Fortier, Sylvie; Basset, Fabien A; Mbourou, Ginette A; Favérial, Jérôme; Teasdale, Normand

2005-06-01

(a) to examine if kinetic and kinematic parameters of the sprint start could differentiate elite from sub-elite sprinters and, (b) to investigate whether providing feedback (FB) about selected parameters could improve starting block performance of intermediate sprinters over a 6-week training period. Twelve male sprinters, assigned to an elite or a sub-elite group, participated in Experiment 1. Eight intermediate sprinters participated in Experiment 2. All athletes were required to perform three sprint starts at maximum intensity followed by a 10-m run. To detect differences between elite and sub-elite groups, comparisons were made using t-tests for independent samples. Parameters reaching a significant group difference were retained for the linear discriminant analysis (LDA). The LDA yielded four discriminative kinetic parameters. Feedback about these selected parameters was given to sprinters in Experiment 2. For this experiment, data acquisition was divided into three periods. The first six sessions were without specific FB, whereas the following six sessions were enriched by kinetic FB. Finally, athletes underwent a retention session (without FB) 4 weeks after the twelfth session. Even though differences were found in the time to front peak force, the time to rear peak force, and the front peak force in the retention session, the results of the present study showed that providing FB about selected kinetic parameters differentiating elite from sub-elite sprinters did not improve the starting block performance of intermediate sprinters. Key PointsThe linear discriminative analysis allows the identification of starting block parameters differentiating elite from sub-elite athletes.6-week of feedback does not alter starting block performance in training context.The present results failed to confirm previous studies since feedback did not improve targeted kinetic parameters of the complex motor task in real-world context.

Perceived Discrimination, Coping Strategies, and Mexican Origin Adolescents' Internalizing and Externalizing Behaviors: Examining the Moderating Role of Gender and Cultural Orientation.

PubMed

Brittian, Aerika S; Toomey, Russell B; Gonzales, Nancy A; Dumka, Larry E

2013-01-01

The literature identifying effective coping strategies related to perceived discrimination has yielded mixed findings, suggesting that recommendations for effective coping may vary by individual and group differences. The current study examined the influence of perceived discrimination and coping strategies on Mexican origin adolescents' later internalizing symptoms and externalizing behaviors, and assessed the moderating roles of gender and cultural orientation. Participants included 189 adolescents (46% male, 54% female) interviewed at 7 th and 8 th grade. Results suggested that the associations between perceived discrimination and internalizing symptoms were buffered by distraction coping among youth that were low on Anglo orientation but not among youth high on Anglo orientation. In addition, the associations between perceived discrimination and externalizing behaviors were buffered by social support seeking, but only among youth that were low on Mexican orientation. Directions for future research and application of the current research are discussed.

Matterwave interferometric velocimetry of cold Rb atoms

NASA Astrophysics Data System (ADS)

Carey, Max; Belal, Mohammad; Himsworth, Matthew; Bateman, James; Freegarde, Tim

2018-03-01

We consider the matterwave interferometric measurement of atomic velocities, which forms a building block for all matterwave inertial measurements. A theoretical analysis, addressing both the laboratory and atomic frames and accounting for residual Doppler sensitivity in the beamsplitter and recombiner pulses, is followed by an experimental demonstration, with measurements of the velocity distribution within a 20 ?K cloud of rubidium atoms. Our experiments use Raman transitions between the long-lived ground hyperfine states, and allow quadrature measurements that yield the full complex interferometer signal and hence discriminate between positive and negative velocities. The technique is most suitable for measurement of colder samples.

Matterwave interferometric velocimetry of cold Rb atoms

NASA Astrophysics Data System (ADS)

Carey, Max; Belal, Mohammad; Himsworth, Matthew; Bateman, James; Freegarde, Tim

2018-02-01

We consider the matterwave interferometric measurement of atomic velocities, which forms a building block for all matterwave inertial measurements. A theoretical analysis, addressing both the laboratory and atomic frames and accounting for residual Doppler sensitivity in the beamsplitter and recombiner pulses, is followed by an experimental demonstration, with measurements of the velocity distribution within a 20 $\\mu$K cloud of rubidium atoms. Our experiments use Raman transitions between the long-lived ground hyperfine states, and allow quadrature measurements that yield the full complex interferometer signal and hence discriminate between positive and negative velocities. The technique is most suitable for measurement of colder samples.

Structure, recognition and adaptive binding in RNA aptamer complexes.

PubMed

Patel, D J; Suri, A K; Jiang, F; Jiang, L; Fan, P; Kumar, R A; Nonin, S

1997-10-10

Novel features of RNA structure, recognition and discrimination have been recently elucidated through the solution structural characterization of RNA aptamers that bind cofactors, aminoglycoside antibiotics, amino acids and peptides with high affinity and specificity. This review presents the solution structures of RNA aptamer complexes with adenosine monophosphate, flavin mononucleotide, arginine/citrulline and tobramycin together with an example of hydrogen exchange measurements of the base-pair kinetics for the AMP-RNA aptamer complex. A comparative analysis of the structures of these RNA aptamer complexes yields the principles, patterns and diversity associated with RNA architecture, molecular recognition and adaptive binding associated with complex formation.

Discrimination of premalignant conditions of oral cancer using Raman spectroscopy of urinary metabolites

NASA Astrophysics Data System (ADS)

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

2015-03-01

Oral cancers are considered to be one of the most commonly occurring malignancy worldwide. Over 70% of the cases report to the doctor only in advanced stages of the disease, resulting in poor survival rates. Hence it is necessary to detect the disease at the earliest which may increase the five year survival rate up to 90%. Among various optical spectroscopic techniques, Raman spectroscopy has been emerged as a tool in identifying several diseased conditions, including oral cancers. Around 30 - 80% of the malignancies of the oral cavity arise from premalignant lesions. Hence, understanding the molecular/spectral differences at the premalignant stage may help in identifying the cancer at the earliest and increase patient's survival rate. Among various bio-fluids such as blood, urine and saliva, urine is considered as one of the diagnostically potential bio-fluids, as it has many metabolites. The distribution and the physiochemical properties of the urinary metabolites may vary due to the changes associated with the pathologic conditions. The present study is aimed to characterize the urine of 70 healthy subjects and 51 pre-malignant patients using Raman spectroscopy under 785nm excitation, to know the molecular/spectral differences between healthy subjects and premalignant conditions of oral malignancy. Principal component analysis based Linear discriminant analysis were also made to find the statistical significance and the present technique yields the sensitivity and specificity of 86.3% and 92.9% with an overall accuracy of 90.9% in the discrimination of premalignant conditions from healthy subjects urine.

Two models for evaluating landslide hazards

USGS Publications Warehouse

Davis, J.C.; Chung, C.-J.; Ohlmacher, G.C.

2006-01-01

Two alternative procedures for estimating landslide hazards were evaluated using data on topographic digital elevation models (DEMs) and bedrock lithologies in an area adjacent to the Missouri River in Atchison County, Kansas, USA. The two procedures are based on the likelihood ratio model but utilize different assumptions. The empirical likelihood ratio model is based on non-parametric empirical univariate frequency distribution functions under an assumption of conditional independence while the multivariate logistic discriminant model assumes that likelihood ratios can be expressed in terms of logistic functions. The relative hazards of occurrence of landslides were estimated by an empirical likelihood ratio model and by multivariate logistic discriminant analysis. Predictor variables consisted of grids containing topographic elevations, slope angles, and slope aspects calculated from a 30-m DEM. An integer grid of coded bedrock lithologies taken from digitized geologic maps was also used as a predictor variable. Both statistical models yield relative estimates in the form of the proportion of total map area predicted to already contain or to be the site of future landslides. The stabilities of estimates were checked by cross-validation of results from random subsamples, using each of the two procedures. Cell-by-cell comparisons of hazard maps made by the two models show that the two sets of estimates are virtually identical. This suggests that the empirical likelihood ratio and the logistic discriminant analysis models are robust with respect to the conditional independent assumption and the logistic function assumption, respectively, and that either model can be used successfully to evaluate landslide hazards. ?? 2006.

Raman spectroscopy of normal oral buccal mucosa tissues: study on intact and incised biopsies

NASA Astrophysics Data System (ADS)

Deshmukh, Atul; Singh, S. P.; Chaturvedi, Pankaj; Krishna, C. Murali

2011-12-01

Oral squamous cell carcinoma is one of among the top 10 malignancies. Optical spectroscopy, including Raman, is being actively pursued as alternative/adjunct for cancer diagnosis. Earlier studies have demonstrated the feasibility of classifying normal, premalignant, and malignant oral ex vivo tissues. Spectral features showed predominance of lipids and proteins in normal and cancer conditions, respectively, which were attributed to membrane lipids and surface proteins. In view of recent developments in deep tissue Raman spectroscopy, we have recorded Raman spectra from superior and inferior surfaces of 10 normal oral tissues on intact, as well as incised, biopsies after separation of epithelium from connective tissue. Spectral variations and similarities among different groups were explored by unsupervised (principal component analysis) and supervised (linear discriminant analysis, factorial discriminant analysis) methodologies. Clusters of spectra from superior and inferior surfaces of intact tissues show a high overlap; whereas spectra from separated epithelium and connective tissue sections yielded clear clusters, though they also overlap on clusters of intact tissues. Spectra of all four groups of normal tissues gave exclusive clusters when tested against malignant spectra. Thus, this study demonstrates that spectra recorded from the superior surface of an intact tissue may have contributions from deeper layers but has no bearing from the classification of a malignant tissues point of view.

Lagged segmented Poincaré plot analysis for risk stratification in patients with dilated cardiomyopathy.

PubMed

Voss, Andreas; Fischer, Claudia; Schroeder, Rico; Figulla, Hans R; Goernig, Matthias

2012-07-01

The objectives of this study were to introduce a new type of heart-rate variability analysis improving risk stratification in patients with idiopathic dilated cardiomyopathy (DCM) and to provide additional information about impaired heart beat generation in these patients. Beat-to-beat intervals (BBI) of 30-min ECGs recorded from 91 DCM patients and 21 healthy subjects were analyzed applying the lagged segmented Poincaré plot analysis (LSPPA) method. LSPPA includes the Poincaré plot reconstruction with lags of 1-100, rotating the cloud of points, its normalized segmentation adapted to their standard deviations, and finally, a frequency-dependent clustering. The lags were combined into eight different clusters representing specific frequency bands within 0.012-1.153 Hz. Statistical differences between low- and high-risk DCM could be found within the clusters II-VIII (e.g., cluster IV: 0.033-0.038 Hz; p = 0.0002; sensitivity = 85.7 %; specificity = 71.4 %). The multivariate statistics led to a sensitivity of 92.9 %, specificity of 85.7 % and an area under the curve of 92.1 % discriminating these patient groups. We introduced the LSPPA method to investigate time correlations in BBI time series. We found that LSPPA contributes considerably to risk stratification in DCM and yields the highest discriminant power in the low and very low-frequency bands.

Analysis and classification of optical tomographic images of rheumatoid fingers with ANOVA and discriminate analysis

NASA Astrophysics Data System (ADS)

Montejo, Ludguier D.; Kim, Hyun K.; Häme, Yrjö; Jia, Jingfei; Montejo, Julio D.; Netz, Uwe J.; Blaschke, Sabine; Zwaka, Paul; Müeller, Gerhard A.; Beuthan, Jürgen; Hielscher, Andreas H.

2011-03-01

We present a study on the effectiveness of computer-aided diagnosis (CAD) of rheumatoid arthritis (RA) from frequency-domain diffuse optical tomographic (FDOT) images. FDOT is used to obtain the distribution of tissue optical properties. Subsequently, the non-parametric Kruskal-Wallis ANOVA test is employed to verify statistically significant differences between the optical parameters of patients affected by RA and healthy volunteers. Furthermore, quadratic discriminate analysis (QDA) of the absorption (μa) and scattering (μa or μ's) distributions is used to classify subjects as affected or not affected by RA. We evaluate the classification efficiency by determining the sensitivity (Se), specificity (Sp), and the Youden index (Y). We find that combining features extracted from μa and μa or μ's images allows for more accurate classification than when μa or μa or μ's features are considered individually on their own. Combining μa and μa or μ's features yields values of up to Y = 0.75 (Se = 0.84 and Sp = 0.91). The best results when μa or μ's features are considered individually are Y = 0.65 (Se = 0.85 and Sp = 0.80) and Y = 0.70 (Se = 0.80 and Sp = 0.90), respectively.

The Bolivian "Altiplano" and "Valle" sheep are two different peripatric breeds.

PubMed

Parés-Casanova, Pere M; Pérezgrovas Garza, Raúl

2014-06-01

Forty-nine sheep belonged to the Andean Altiplano region ("Altiplano") and 30 in the lowland regions of Bolivia ("Valle"), aged 1 to 4 years, were wool sampled to determine the extent of difference between these local breeds. Fibre length and the percentage of each type of fibre (long-thick, short-thin and kemp), yield and fibre diameter were measured. There was a highly significant difference between the two sheep populations that were not clearly separated in the first two principal component of a principal components analysis (PC); the first PC explained 67.1 % and the second PC explained 26.6 % of the total variation. The variables that contributed most to the separation of the sheep populations were the percentage of long-thick and short-thin fibres in the first PC and yield in the second PC. A discriminant analysis, which was used to classify individuals with respect to their breeding, achieved an accurate classification rate of 84.2 %. Thus, the Altiplano and Valle sheep must be viewed as two closely peripatric breeds rather than different "ecotypes", as more than 80 % could be correctly assigned to one of the breeds; however, the differences are based on composition of long-thick and short-thin fibres and yield after alcohol scouring.

A Window of Opportunity for Cognitive Training in Adolescence

PubMed Central

Knoll, Lisa J.; Fuhrmann, Delia; Sakhardande, Ashok L.; Stamp, Fabian; Speekenbrink, Maarten; Blakemore, Sarah-Jayne

2016-01-01

In the current study, we investigated windows for enhanced learning of cognitive skills during adolescence. Six hundred thirty-three participants (11–33 years old) were divided into four age groups, and each participant was randomly allocated to one of three training groups. Each training group completed up to 20 days of online training in numerosity discrimination (i.e., discriminating small from large numbers of objects), relational reasoning (i.e., detecting abstract relationships between groups of items), or face perception (i.e., identifying differences in faces). Training yielded some improvement in performance on the numerosity-discrimination task, but only in older adolescents or adults. In contrast, training in relational reasoning improved performance on that task in all age groups, but training benefits were greater for people in late adolescence and adulthood than for people earlier in adolescence. Training did not increase performance on the face-perception task for any age group. Our findings suggest that for certain cognitive skills, training during late adolescence and adulthood yields greater improvement than training earlier in adolescence, which highlights the relevance of this late developmental stage for education. PMID:27815519

Hand-movement-based in-vehicle driver/front-seat passenger discrimination for centre console controls

NASA Astrophysics Data System (ADS)

Herrmann, Enrico; Makrushin, Andrey; Dittmann, Jana; Vielhauer, Claus; Langnickel, Mirko; Kraetzer, Christian

2010-01-01

Successful user discrimination in a vehicle environment may yield a reduction of the number of switches, thus significantly reducing costs while increasing user convenience. The personalization of individual controls permits conditional passenger enable/driver disable and vice versa options which may yield safety improvement. The authors propose a prototypic optical sensing system based on hand movement segmentation in near-infrared image sequences implemented in an Audi A6 Avant. Analyzing the number of movements in special regions, the system recognizes the direction of the forearm and hand motion and decides whether driver or front-seat passenger touch a control. The experimental evaluation is performed independently for uniformly and non-uniformly illuminated video data as well as for the complete video data set which includes both subsets. The general test results in error rates of up to 14.41% FPR / 16.82% FNR and 17.61% FPR / 14.77% FNR for driver and passenger respectively. Finally, the authors discuss the causes of the most frequently occurring errors as well as the prospects and limitations of optical sensing for user discrimination in passenger compartments.

A Workplace Divided: How Americans View Discrimination and Race on the Job. Work Trends: Americans' Attitudes about Work, Employers and Government.

ERIC Educational Resources Information Center

Dixon, K. A.; Storen, Duke; Van Horn, Carl E.

U.S. workers' views on discrimination and race on the job were examined in a telephone survey of 1,470 adults across the 48 contiguous United States that yielded 1,005 complete interviews. White workers were far more likely than workers of other races to believe that everyone is treated fairly at work. Race was a more powerful indicator of opinion…

A photonic chip based frequency discriminator for a high performance microwave photonic link.

PubMed

Marpaung, David; Roeloffzen, Chris; Leinse, Arne; Hoekman, Marcel

2010-12-20

We report a high performance phase modulation direct detection microwave photonic link employing a photonic chip as a frequency discriminator. The photonic chip consists of five optical ring resonators (ORRs) which are fully programmable using thermo-optical tuning. In this discriminator a drop-port response of an ORR is cascaded with a through response of another ORR to yield a linear phase modulation (PM) to intensity modulation (IM) conversion. The balanced photonic link employing the PM to IM conversion exhibits high second-order and third-order input intercept points of + 46 dBm and + 36 dBm, respectively, which are simultaneously achieved at one bias point.

Impact of intensive horticulture practices on groundwater content of nitrates, sodium, potassium, and pesticides.

PubMed

Melo, Armindo; Pinto, Edgar; Aguiar, Ana; Mansilha, Catarina; Pinho, Olívia; Ferreira, Isabel M P L V O

2012-07-01

A monitoring program of nitrate, nitrite, potassium, sodium, and pesticides was carried out in water samples from an intensive horticulture area in a vulnerable zone from north of Portugal. Eight collecting points were selected and water-analyzed in five sampling campaigns, during 1 year. Chemometric techniques, such as cluster analysis, principal component analysis (PCA), and discriminant analysis, were used in order to understand the impact of intensive horticulture practices on dug and drilled wells groundwater and to study variations in the hydrochemistry of groundwater. PCA performed on pesticide data matrix yielded seven significant PCs explaining 77.67% of the data variance. Although PCA rendered considerable data reduction, it could not clearly group and distinguish the sample types. However, a visible differentiation between the water samples was obtained. Cluster and discriminant analysis grouped the eight collecting points into three clusters of similar characteristics pertaining to water contamination, indicating that it is necessary to improve the use of water, fertilizers, and pesticides. Inorganic fertilizers such as potassium nitrate were suspected to be the most important factors for nitrate contamination since highly significant Pearson correlation (r = 0.691, P < 0.01) was obtained between groundwater nitrate and potassium contents. Water from dug wells is especially prone to contamination from the grower and their closer neighbor's practices. Water from drilled wells is also contaminated from distant practices.

Development and validation of the pro-environmental behaviour scale for women's health.

PubMed

Kim, HyunKyoung

2017-05-01

This study was aimed to develop and test the Pro-environmental Behavior Scale for Women's Health. Women adopt sustainable behaviours and alter their life styles to protect the environment and their health from environmental pollution. The conceptual framework of pro-environmental behaviours was based on Rogers' protection motivation theory and Weinstein's precaution adoption process model. The cross-sectional design was used for instrument development. The instrument development process consisted of a literature review, personal depth interviews and focus group interviews. The sample comprised 356 adult women recruited in April-May 2012 in South Korea using quota sampling. For construct validity, exploratory factor analysis was conducted to examine the factor structure, after which convergent and discriminant validity and known-group comparisons were tested. Principal component analysis yielded 17 items with four factors, including 'women's health protection,' 'chemical exposure prevention,' 'alternative consumption,' and 'community-oriented behaviour'. The Cronbach's α was 0·81. Convergent and discriminant validity were supported by performing correlations with other environmental-health and health-behaviour measures. Nursing professionals can reliably use the instrument to assess women's behaviours, which protect their health and the environment. © 2016 John Wiley & Sons Ltd.

Label-free haemogram using wavelength modulated Raman spectroscopy for identifying immune-cell subset

NASA Astrophysics Data System (ADS)

Ashok, Praveen C.; Praveen, Bavishna B.; Campbell, Elaine C.; Dholakia, Kishan; Powis, Simon J.

2014-03-01

Leucocytes in the blood of mammals form a powerful protective system against a wide range of dangerous pathogens. There are several types of immune cells that has specific role in the whole immune system. The number and type of immune cells alter in the disease state and identifying the type of immune cell provides information about a person's state of health. There are several immune cell subsets that are essentially morphologically identical and require external labeling to enable discrimination. Here we demonstrate the feasibility of using Wavelength Modulated Raman Spectroscopy (WMRS) with suitable machine learning algorithms as a label-free method to distinguish between different closely lying immune cell subset. Principal Component Analysis (PCA) was performed on WMRS data from single cells, obtained using confocal Raman microscopy for feature reduction, followed by Support Vector Machine (SVM) for binary discrimination of various cell subset, which yielded an accuracy >85%. The method was successful in discriminating between untouched and unfixed purified populations of CD4+CD3+ and CD8+CD3+ T lymphocyte subsets, and CD56+CD3- natural killer cells with a high degree of specificity. It was also proved sensitive enough to identify unique Raman signatures that allow clear discrimination between dendritic cell subsets, comprising CD303+CD45+ plasmacytoid and CD1c+CD141+ myeloid dendritic cells. The results of this study clearly show that WMRS is highly sensitive and can distinguish between cell types that are morphologically identical.

Carr-Purcell-Meiboom-Gill imaging of prostate cancer: quantitative T2 values for cancer discrimination.

PubMed

Roebuck, Joseph R; Haker, Steven J; Mitsouras, Dimitris; Rybicki, Frank J; Tempany, Clare M; Mulkern, Robert V

2009-05-01

Quantitative, apparent T(2) values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T(2) values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy-proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 x 1.1 x 4 mm(3) was obtained in 10.7 min, resulting in data sets suitable for generating high-quality images with variable T(2)-weighting and for evaluating quantitative T(2) values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T(1)- and T(2)-weighted signal intensities and available histopathology reports, yielded significantly (P<.0001) longer apparent T(2) values in suspected healthy tissue (193+/-49 ms) vs. suspected cancer (100+/-26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T(2)-weighted fast spin echo (FSE) imaging alone, including quantitative T(2) values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time FSE sequences.

Carr-Purcell-Meiboom-Gill (CPMG) Imaging of Prostate Cancer: Quantitative T2 Values for Cancer Discrimination

PubMed Central

Roebuck, Joseph R.; Haker, Steven J.; Mitsouras, Dimitris; Rybicki, Frank J.; Tempany, Clare M.; Mulkern, Robert V.

2009-01-01

Quantitative, apparent T2 values of suspected prostate cancer and healthy peripheral zone tissue in men with prostate cancer were measured using a Carr-Purcell-Meiboom-Gill (CPMG) imaging sequence in order to assess the cancer discrimination potential of tissue T2 values. The CPMG imaging sequence was used to image the prostates of 18 men with biopsy proven prostate cancer. Whole gland coverage with nominal voxel volumes of 0.54 × 1.1 × 4 mm3 was obtained in 10.7 minutes, resulting in data sets suitable for generating high quality images with variable T2-weighting and for evaluating quantitative T2 values on a pixel-by-pixel basis. Region-of-interest analysis of suspected healthy peripheral zone tissue and suspected cancer, identified on the basis of both T1- and T2-weighted signal intensities and available histopathology reports, yielded significantly (p < 0.0001) longer apparent T2 values in suspected healthy tissue (193 ± 49 ms) vs. suspected cancer (100 ± 26 ms), suggesting potential utility of this method as a tissue specific discrimination index for prostate cancer. We conclude that CPMG imaging of the prostate can be performed in reasonable scan times and can provide advantages over T2-weighted fast spin echo imaging alone, including quantitative T2 values for cancer discrimination as well as proton density maps without the point spread function degradation associated with short effective echo time fast spin echo (FSE) sequences. PMID:18823731

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.

Classification of Uxo by Principal Dipole Polarizability

NASA Astrophysics Data System (ADS)

Kappler, K. N.

2010-12-01

Data acquired by multiple-Transmitter, multiple-receiver time-domain electromagnetic devices show great potential for determining the geometric and compositional information relating to near surface conductive targets. Here is presented an analysis of data from one such system; the Berkeley Unexploded-ordnance Discriminator (BUD) system. BUD data are succinctly reduced by processing the multi-static data matrices to obtain magnetic dipole polarizability matrices for data from each time gate. When viewed over all time gates, the projections of the data onto the principal polar axes yield so-called polarizability curves. These curves are especially well suited to discriminating between subsurface conductivity anomalies which correspond to objects of rotational symmetry and irregularly shaped objects. The curves have previously been successfully employed as library elements in a pattern recognition scheme aimed at discriminating harmless scrap metal from dangerous intact unexploded ordnance. However, previous polarizability-curve matching methods have only been applied at field sites which are known a priori to be contaminated by a single type of ordnance, and furthermore, the particular ordnance present in the subsurface was known to be large. Thus signal amplitude was a key element in the discrimination process. The work presented here applies feature-based pattern classification techniques to BUD field data where more than 20 categories of object are present. Data soundings from a calibration grid at the Yuma, AZ proving ground are used in a cross validation study to calibrate the pattern recognition method. The resultant method is then applied to a Blind Test Grid. Results indicate that when lone UXO are present and SNR is reasonably high, Polarizability Curve Matching successfully discriminates UXO from scrap metal when a broad range of objects are present.

Pulse shape discrimination based on fast signals from silicon photomultipliers

NASA Astrophysics Data System (ADS)

Yu, Junhao; Wei, Zhiyong; Fang, Meihua; Zhang, Zixia; Cheng, Can; Wang, Yi; Su, Huiwen; Ran, Youquan; Zhu, Qingwei; Zhang, He; Duan, Kai; Chen, Ming; Liu, Meng

2018-06-01

Recent developments in organic plastic scintillators capable of pulse shape discrimination (PSD) enable a breakthrough in discrimination between neutrons and gammas. Plastic scintillator detectors coupled with silicon photomultipliers (SiPMs) offer many advantages, such as lower power consumption, smaller volume, and especially insensitivity to magnetic fields, compared with conventional photomultiplier tubes (PMTs). A SensL SiPM has two outputs: a standard output and a fast output. It is known that the charge injected into the fast output electrode is typically approximately 2% of the total charge generated during the avalanche, whereas the charge injected into the standard output electrode is nearly 98% of the total. Fast signals from SiPMs exhibit better performance in terms of timing and time-correlated measurements compared with standard signals. The pulse duration of a standard signal is on the order of hundreds of nanoseconds, whereas the pulse duration of the main monopole waveform of a fast signal is a few tens of nanoseconds. Fast signals are traditionally thought to be suitable for photon counting at very high speeds but unsuitable for PSD due to the partial charge collection. Meanwhile, the standard outputs of SiPMs coupled with discriminating scintillators have yielded nice PSD performances, but there have been no reports on PSD using fast signals. Our analysis shows that fast signals can also provide discrimination if the rate of charge injection into the fast output electrode is fixed for each event, even though only a portion of the charge is collected. In this work, we achieved successful PSD using fast signals; meanwhile, using a coincidence timing window of less 3 nanoseconds between the readouts from both ends of the detector reduced the influence of the high SiPM dark current. We experimentally achieved good timing performance and PSD capability simultaneously.

Shared biomarkers between female diastolic heart failure and pre‐eclampsia: a systematic review and meta‐analysis

PubMed Central

Bokslag, Anouk; Maas, Angela H.E.M.; Franx, Arie; Paulus, Walter J.; de Groot, Christianne J.M.

2017-01-01

Abstract Evidence accumulates for associations between hypertensive pregnancy disorders and increased cardiovascular risk later. The main goal of this study was to explore shared biomarkers representing common pathogenic pathways between heart failure with preserved ejection fraction (HFpEF) and pre‐eclampsia where these biomarkers might be potentially eligible for cardiovascular risk stratification in women after hypertensive pregnancy disorders. We sought for blood markers in women with diastolic dysfunction in a first literature search, and through a second search, we investigated whether these same biochemical markers were present in pre‐eclampsia.This systematic review and meta‐analysis presents two subsequent systematic searches in PubMed and EMBASE. Search I yielded 3014 studies on biomarkers discriminating women with HFpEF from female controls, of which 13 studies on 11 biochemical markers were included. Cases had HFpEF, and controls had no heart failure. The second search was for studies discriminating women with pre‐eclampsia from women with non‐hypertensive pregnancies with at least one of the biomarkers found in Search I. Search II yielded 1869 studies, of which 51 studies on seven biomarkers were included in meta‐analyses and 79 studies on 12 biomarkers in systematic review.Eleven biological markers differentiated women with diastolic dysfunction from controls, of which the following 10 markers differentiated women with pre‐eclampsia from controls as well: C‐reactive protein, HDL, insulin, fatty acid‐binding protein 4, brain natriuretic peptide, N terminal pro brain natriuretic peptide, adrenomedullin, mid‐region pro adrenomedullin, cardiac troponin I, and cancer antigen 125.Our study supports the hypothesis that HFpEF in women shares a common pathogenic background with pre‐eclampsia. The biomarkers representing inflammatory state, disturbances in myocardial function/structure, and unfavourable lipid metabolism may possibly be eligible for future prognostic tools. PMID:28451444

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.

Metabolomic profile of systemic sclerosis patients.

PubMed

Murgia, Federica; Svegliati, Silvia; Poddighe, Simone; Lussu, Milena; Manzin, Aldo; Spadoni, Tatiana; Fischetti, Colomba; Gabrielli, Armando; Atzori, Luigi

2018-05-16

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726-0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7-0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

Statistical analysis of fragmentation patterns of electron ionization mass spectra of enolized-trimethylsilylated anabolic androgenic steroids

NASA Astrophysics Data System (ADS)

Fragkaki, A. G.; Angelis, Y. S.; Tsantili-Kakoulidou, A.; Koupparis, M.; Georgakopoulos, C.

2009-08-01

Anabolic androgenic steroids (AAS) are included in the List of prohibited substances of the World Anti-Doping Agency (WADA) as substances abused to enhance athletic performance. Gas chromatography coupled to mass spectrometry (GC-MS) plays an important role in doping control analyses identifying AAS as their enolized-trimethylsilyl (TMS)-derivatives using the electron ionization (EI) mode. This paper explores the suitability of complementary GC-MS mass spectra and statistical analysis (principal component analysis, PCA and partial least squares-discriminant analysis, PLS-DA) to differentiate AAS as a function of their structural and conformational features expressed by their fragment ions. The results obtained showed that the application of PCA yielded a classification among the AAS molecules which became more apparent after applying PLS-DA to the dataset. The application of PLS-DA yielded a clear separation among the AAS molecules which were, thus, classified as: 1-ene-3-keto, 3-hydroxyl with saturated A-ring, 1-ene-3-hydroxyl, 4-ene-3-keto, 1,4-diene-3-keto and 3-keto with saturated A-ring anabolic steroids. The study of this paper also presents structurally diagnostic fragment ions and dissociation routes providing evidence for the presence of unknown AAS or chemically modified molecules known as designer steroids.

Legitimating Racial Discrimination: Emotions, Not Beliefs, Best Predict Discrimination in a Meta-Analysis

PubMed Central

Talaska, Cara A.; Chaiken, Shelly

2013-01-01

Investigations of racial bias have emphasized stereotypes and other beliefs as central explanatory mechanisms and as legitimating discrimination. In recent theory and research, emotional prejudices have emerged as another, more direct predictor of discrimination. A new comprehensive meta-analysis of 57 racial attitude-discrimination studies finds a moderate relationship between overall attitudes and discrimination. Emotional prejudices are twices as closely related to racial discrimination as stereotypes and beliefs are. Moreover, emotional prejudices are closely related to both observed and self-reported discrimination, whereas stereotypes and beliefs are related only to self-reported discrimination. Implications for justifying discrimination are discussed. PMID:24052687

Multivariate statistical analysis of the polyphenolic constituents in kiwifruit juices to trace fruit varieties and geographical origins.

PubMed

Guo, Jing; Yuan, Yahong; Dou, Pei; Yue, Tianli

2017-10-01

Fifty-one kiwifruit juice samples of seven kiwifruit varieties from five regions in China were analyzed to determine their polyphenols contents and to trace fruit varieties and geographical origins by multivariate statistical analysis. Twenty-one polyphenols belonging to four compound classes were determined by ultra-high-performance liquid chromatography coupled with ultra-high-resolution TOF mass spectrometry. (-)-Epicatechin, (+)-catechin, procyanidin B1 and caffeic acid derivatives were the predominant phenolic compounds in the juices. Principal component analysis (PCA) allowed a clear separation of the juices according to kiwifruit varieties. Stepwise linear discriminant analysis (SLDA) yielded satisfactory categorization of samples, provided 100% success rate according to kiwifruit varieties and 92.2% success rate according to geographical origins. The result showed that polyphenolic profiles of kiwifruit juices contain enough information to trace fruit varieties and geographical origins. Copyright © 2017 Elsevier Ltd. All rights reserved.

Selecting risk factors: a comparison of discriminant analysis, logistic regression and Cox's regression model using data from the Tromsø Heart Study.

PubMed

Brenn, T; Arnesen, E

1985-01-01

For comparative evaluation, discriminant analysis, logistic regression and Cox's model were used to select risk factors for total and coronary deaths among 6595 men aged 20-49 followed for 9 years. Groups with mortality between 5 and 93 per 1000 were considered. Discriminant analysis selected variable sets only marginally different from the logistic and Cox methods which always selected the same sets. A time-saving option, offered for both the logistic and Cox selection, showed no advantage compared with discriminant analysis. Analysing more than 3800 subjects, the logistic and Cox methods consumed, respectively, 80 and 10 times more computer time than discriminant analysis. When including the same set of variables in non-stepwise analyses, all methods estimated coefficients that in most cases were almost identical. In conclusion, discriminant analysis is advocated for preliminary or stepwise analysis, otherwise Cox's method should be used.

Perceived Discrimination and Mental Health Symptoms among Black Men with HIV

PubMed Central

Bogart, Laura M.; Wagner, Glenn J.; Galvan, Frank H.; Landrine, Hope; Klein, David J.; Sticklor, Laurel A.

2011-01-01

Objective People living with HIV (PLWH) exhibit more severe mental health symptoms than do members of the general public (including depression and post-traumatic stress disorder/PTSD symptoms). We examined whether perceived discrimination, which has been associated with poor mental health in prior research, contributes to greater depression and PTSD symptoms among HIV-positive Black men who have sex with men (MSM), who are at high risk for discrimination from multiple stigmatized characteristics (HIV-serostatus, race/ethnicity, sexual orientation). Method A total of 181 Black MSM living with HIV completed audio computer-assisted self-interviews (ACASI) that included measures of mental health symptoms (depression, PTSD) and scales assessing perceived discrimination due to HIV-serostatus, race/ethnicity, and sexual orientation. Results In bivariate tests, all three perceived discrimination scales were significantly associated with greater symptoms of depression and PTSD (i.e., re-experiencing, avoidance, and arousal subscales) (all p-values < .05). The multivariate model for depression yielded a three-way interaction among all three discrimination types (p < .01), indicating that perceived racial discrimination was negatively associated with depression symptoms when considered in isolation from other forms of discrimination, but positively associated when all three types of discrimination were present. In multivariate tests, only perceived HIV-related discrimination was associated with PTSD symptoms (p < .05). Conclusion Findings suggest that some types of perceived discrimination contribute to poor mental health among PLWH. Researchers need to take into account intersecting stigmas when developing interventions to improve mental health among PLWH. PMID:21787061

Perceived discrimination and mental health symptoms among Black men with HIV.

PubMed

Bogart, Laura M; Wagner, Glenn J; Galvan, Frank H; Landrine, Hope; Klein, David J; Sticklor, Laurel A

2011-07-01

People living with HIV (PLWH) exhibit more severe mental health symptoms, including depression and posttraumatic stress disorder (PTSD) symptoms, than do members of the general public. We examined whether perceived discrimination, which has been associated with poor mental health in prior research, contributes to greater depression and PTSD symptoms among HIV-positive Black men who have sex with men (MSM), who are at high risk for discrimination from multiple stigmatized characteristics (HIV-serostatus, race/ethnicity, sexual orientation). A total of 181 Black MSM living with HIV completed audio computer-assisted self-interviews (ACASI) that included measures of mental health symptoms (depression, PTSD) and scales assessing perceived discrimination due to HIV-serostatus, race/ethnicity, and sexual orientation. In bivariate tests, all three perceived discrimination scales were significantly associated with greater symptoms of depression and PTSD (i.e., reexperiencing, avoidance, and arousal subscales; all p values < .05). The multivariate model for depression yielded a three-way interaction among all three discrimination types (p < .01), indicating that perceived racial discrimination was negatively associated with depression symptoms when considered in isolation from other forms of discrimination, but positively associated when all three types of discrimination were present. In multivariate tests, only perceived HIV-related discrimination was associated with PTSD symptoms (p < .05). Findings suggest that some types of perceived discrimination contribute to poor mental health among PLWH. Researchers need to take into account intersecting stigmata when developing interventions to improve mental health among PLWH.

Reliability and validity of the McDonald Play Inventory.

PubMed

McDonald, Ann E; Vigen, Cheryl

2012-01-01

This study examined the ability of a two-part self-report instrument, the McDonald Play Inventory, to reliably and validly measure the play activities and play styles of 7- to 11-yr-old children and to discriminate between the play of neurotypical children and children with known learning and developmental disabilities. A total of 124 children ages 7-11 recruited from a sample of convenience and a subsample of 17 parents participated in this study. Reliability estimates yielded moderate correlations for internal consistency, total test intercorrelations, and test-retest reliability. Validity estimates were established for content and construct validity. The results suggest that a self-report instrument yields reliable and valid measures of a child's perceived play performance and discriminates between the play of children with and without disabilities. Copyright © 2012 by the American Occupational Therapy Association, Inc.

Stable carbon and nitrogen isotope analysis of avian uric acid.

PubMed

Bird, Michael I; Tait, Elaine; Wurster, Christopher M; Furness, Robert W

2008-11-01

We report results obtained using a new technique developed to measure the stable-isotope composition of uric acid isolated from bird excreta (guano). Results from a diet-switch feeding trial using zebra finches suggest that the delta(13)C of uric acid in the guano equilibrates with the diet of the bird within 3 days of a change in diet, while the equilibration time for delta(15)N may be longer. The average carbon isotope discrimination between uric acid and food before the diet switch was +0.34 +/- 1 per thousand (1sigma) while after the diet switch this increased slightly to +0.83 +/- 0.7 per thousand (1sigma). Nitrogen isotope discrimination was +1.3 +/- 0.3 per thousand (1sigma) and +0.3 +/- 0.3 per thousand (1sigma) before and after the diet switch; however, it is possible that the nitrogen isotope values did not fully equilibrate with diet switch over the course of the experiment. Analyses of other chemical fractions of the guano (organic residue after uric acid extraction and non-uric acid organics solubilised during extraction) suggest a total range of up to 3 per thousand for both delta(13)C and delta(15)N values in individual components of a single bulk guano sample. The analysis of natural samples from a range of terrestrial and marine species demonstrates that the technique yields isotopic compositions consistent with the known diets of the birds. The results from natural samples further demonstrate that multiple samples from the same species collected from the same location yield similar results, while different species from the same location exhibit a range of isotopic compositions indicative of different dietary preferences. Given that many samples of guano can be rapidly collected without any requirement to capture specimens for invasive sampling, the stable-isotope analysis of uric acid offers a new, simple and potentially powerful tool for studying avian ecology and metabolism.

[Discrimination of Rice Syrup Adulterant of Acacia Honey Based Using Near-Infrared Spectroscopy].

PubMed

Zhang, Yan-nan; Chen, Lan-zhen; Xue, Xiao-feng; Wu, Li-ming; Li, Yi; Yang, Juan

2015-09-01

At present, the rice syrup as a low price of the sweeteners was often adulterated into acacia honey and the adulterated honeys were sold in honey markets, while there is no suitable and fast method to identify honey adulterated with rice syrup. In this study, Near infrared spectroscopy (NIR) combined with chemometric methods were used to discriminate authenticity of honey. 20 unprocessed acacia honey samples from the different honey producing areas, mixed? with different proportion of rice syrup, were prepared of seven different concentration gradient? including 121 samples. The near infrared spectrum (NIR) instrument and spectrum processing software have been applied in the? spectrum? scanning and data conversion on adulterant samples, respectively. Then it was analyzed by Principal component analysis (PCA) and canonical discriminant analysis methods in order to discriminating adulterated honey. The results showed that after principal components analysis, the first two principal components accounted for 97.23% of total variation, but the regionalism of the score plot of the first two PCs was not obvious, so the canonical discriminant analysis was used to make the further discrimination, all samples had been discriminated correctly, the first two discriminant functions accounted for 91.6% among the six canonical discriminant functions, Then the different concentration of adulterant samples can be discriminated correctly, it illustrate that canonical discriminant analysis method combined with NIR spectroscopy is not only feasible but also practical for rapid and effective discriminate of the rice syrup adulterant of acacia honey.

Perceived Discrimination, Coping Strategies, and Mexican Origin Adolescents’ Internalizing and Externalizing Behaviors: Examining the Moderating Role of Gender and Cultural Orientation

PubMed Central

Brittian, Aerika S.; Toomey, Russell B.; Gonzales, Nancy A.; Dumka, Larry E.

2013-01-01

The literature identifying effective coping strategies related to perceived discrimination has yielded mixed findings, suggesting that recommendations for effective coping may vary by individual and group differences. The current study examined the influence of perceived discrimination and coping strategies on Mexican origin adolescents’ later internalizing symptoms and externalizing behaviors, and assessed the moderating roles of gender and cultural orientation. Participants included 189 adolescents (46% male, 54% female) interviewed at 7th and 8th grade. Results suggested that the associations between perceived discrimination and internalizing symptoms were buffered by distraction coping among youth that were low on Anglo orientation but not among youth high on Anglo orientation. In addition, the associations between perceived discrimination and externalizing behaviors were buffered by social support seeking, but only among youth that were low on Mexican orientation. Directions for future research and application of the current research are discussed. PMID:23833550

THE BRIEF PSYCHIATRIC RATING SCALE IN POSITIVE AND NEGATIVE SUBTYPES OF SCHIZOPHRENIA

PubMed Central

Kulhara, P.; Mattoo, S.K.; Avasthi, A.; Malhotra, A.

1987-01-01

SUMMARY Usefulness of the Brief Psychiatric Rating Scale (BPRS) in distinguishing positive and negative subtypes of schizophrenia is presented. Ninety five schizophrenic patients were assessed on BPRS. Significant differences emerged between positive and negative subtypes of schizophrenia on items like emotional withdrawal, guilt feelings, tension, hallucinatory behaviour, motor retardation, blunted affect and excitement. Discriminant function equation generated by these items had a high rate of prediction of group membership either to positive or negative schizophrenia group. Principal components analysis of BPRS scores yielded factors which favour categorization of patients in positive, negative subtypes. The study provides support for classification of schizophrenia into these subtypes. PMID:21927241

Psychometric Properties of the Behavioral Inhibition Questionnaire in Preschool Children

PubMed Central

Kim, Jiyon; Klein, Daniel N.; Olino, Thomas M.; Dyson, Margaret W.; Dougherty, Lea R.; Durbin, C. Emily

2012-01-01

We examined the psychometric properties of the Behavioral Inhibition Questionnaire (BIQ), a rating scale for children’s behavioral inhibition (BI). Parent and teacher ratings, parent interviews, and laboratory observations were obtained for 495 preschoolers. Confirmatory factor analysis yielded six factors, each reflecting the BIQ’s subscales, and all loading onto a second-order general dimension. Model fit was acceptable for parent ratings, but only marginal for teacher ratings. The convergent and discriminant validity of the BIQ was examined by using a multitrait multimethod approach. Results indicate that the BIQ displays evidence of reliability and validity that can complement observational paradigms. PMID:21999378

Absolute wind velocities in the lower thermosphere of Venus using infrared heterodyne spectroscopy

NASA Technical Reports Server (NTRS)

Goldstein, Jeffrey J.; Mumma, Michael J.; Kostiuk, Theodor; Deming, Drake; Espenak, Fred; Zipoy, David

1991-01-01

NASA's IR Telescope Facility and the McMath Solar Telescope have yielded absolute wind velocities in the Venus thermosphere for December 1985 to March 1987 with sufficient spatial resolution for circulation model discrimination. A qualitative analysis of beam-integrated winds indicates subsolar-to-antisolar circulation in the lower thermosphere; horizontal wind velocity was derived from a two-parameter model wind field of subsolar-antisolar and zonal components. A unique model fit common to all observing periods possessed 120 m/sec subsolar-antisolar and 25 m/sec zonal retrograde components, consistent with the Bougher et al. (1986, 1988) hydrodynamical models for 110 km.

Ion microscopy with resonant ionization mass spectrometry : time-of-flight depth profiling with improved isotopic precision.

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

Pellin, M. J.; Veryovkin, I. V.; Levine, J.

2010-01-01

There are four generally mutually exclusive requirements that plague many mass spectrometric measurements of trace constituents: (1) the small size (limited by the depth probed) of many interesting materials requires high useful yields to simply detect some trace elements, (2) the low concentrations of interesting elements require efficient discrimination from isobaric interferences, (3) it is often necessary to measure the depth distribution of elements with high surface and low bulk contributions, and (4) many applications require precise isotopic analysis. Resonant ionization mass spectrometry has made dramatic progress in addressing these difficulties over the past five years.

A lung sound classification system based on the rational dilation wavelet transform.

PubMed

Ulukaya, Sezer; Serbes, Gorkem; Sen, Ipek; Kahya, Yasemin P

2016-08-01

In this work, a wavelet based classification system that aims to discriminate crackle, normal and wheeze lung sounds is presented. While the previous works related with this problem use constant low Q-factor wavelets, which have limited frequency resolution and can not cope with oscillatory signals, in the proposed system, the Rational Dilation Wavelet Transform, whose Q-factors can be tuned, is employed. Proposed system yields an accuracy of 95 % for crackle, 97 % for wheeze, 93.50 % for normal and 95.17 % for total sound signal types using energy feature subset and proposed approach is superior to conventional low Q-factor wavelet analysis.

Mapping permafrost in the boreal forest with Thematic Mapper satellite data

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Strong, L. L.; Card, D. H.

1986-01-01

A geographic data base incorporating Landsat TM data was used to develop and evaluate logistic discriminant functions for predicting the distribution of permafrost in a boreal forest watershed. The data base included both satellite-derived information and ancillary map data. Five permafrost classifications were developed from a stratified random sample of the data base and evaluated by comparison with a photo-interpreted permafrost map using contingency table analysis and soil temperatures recorded at sites within the watershed. A classification using a TM thermal band and a TM-derived vegetation map as independent variables yielded the highest mapping accuracy for all permafrost categories.

Structural equation modeling of the effects of racism, LGBTQ discrimination, and internalized oppression on illicit drug use in LGBTQ people of color.

PubMed

Drazdowski, Tess K; Perrin, Paul B; Trujillo, Michael; Sutter, Megan; Benotsch, Eric G; Snipes, Daniel J

2016-02-01

Experiences with lesbian, gay, bisexual, transgender, or queer (LGBTQ) discrimination and racism have both been associated with mental health problems and illicit drug use. However, the cumulative effects of both forms of discrimination--and resulting internalized oppression--on illicit drug use in LGBTQ people of color (POC) has not been examined in the research literature. Using online questionnaires, this study collected self-report data from 200 LGBTQ POC about their experiences with racism, LGBTQ discrimination, internalized racism, internalized LGBTQ discrimination, and illicit drug use. Two structural equation models yielded adequate fit indices in which experiences with racism and LGBTQ discrimination led to more internalized oppression, which then led to greater illicit drug use magnitude. LGBTQ discrimination was directly related to increased internalized oppression, which was positively associated with illicit drug use magnitude; the relationship between LGBTQ discrimination and illicit drug use magnitude was mediated by internalized oppression in both models. However, racism and the interaction between racism and LGBTQ discrimination did not show valid direct effects on internalized oppression or indirect effects on illicit drug use magnitude. LGBTQ POC can be the targets of both racism and LGBTQ discrimination, although the current study found that the most psychologically damaging effects may come from LGBTQ discrimination. Interventions meant to decrease or prevent illicit drug use in LGBTQ POC may benefit from helping participants examine the links among LGBTQ discrimination, internalized oppression, and illicit drug use as a coping strategy, focusing on substituting more adaptive coping. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Building a pantheoretical model of dehumanization with transgender men: Integrating objectification and minority stress theories.

PubMed

Velez, Brandon L; Breslow, Aaron S; Brewster, Melanie E; Cox, Robert; Foster, Aasha B

2016-10-01

With a national sample of 304 transgender men, the present study tested a pantheoretical model of dehumanization (Moradi, 2013) with hypotheses derived from objectification theory (Fredrickson & Roberts, 1997), minority stress theory (Meyer, 2003), and prior research regarding men's body image concerns. Specifically, we tested common objectification theory constructs (internalization of sociocultural standards of attractiveness [SSA], body surveillance, body satisfaction) as direct and indirect predictors of compulsive exercise. We also examined the roles of transgender-specific minority stress variables-antitransgender discrimination and transgender identity congruence-in the model. Results of a latent variable structural equation model yielded mixed support for the posited relations. The direct and indirect interrelations of internalization of SSA, body surveillance, and body satisfaction were consistent with prior objectification theory research, but only internalization of SSA yielded a significant direct relation with compulsive exercise. In addition, neither internalization of SSA nor body surveillance yielded significant indirect relations with compulsive exercise. However, antitransgender discrimination yielded predicted indirect relations with body surveillance, body satisfaction, and compulsive exercise, with transgender congruence playing a key mediating role in most of these relations. The implications of this pantheoretical model for research and practice with transgender men are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Partially supervised speaker clustering.

PubMed

Tang, Hao; Chu, Stephen Mingyu; Hasegawa-Johnson, Mark; Huang, Thomas S

2012-05-01

Content-based multimedia indexing, retrieval, and processing as well as multimedia databases demand the structuring of the media content (image, audio, video, text, etc.), one significant goal being to associate the identity of the content to the individual segments of the signals. In this paper, we specifically address the problem of speaker clustering, the task of assigning every speech utterance in an audio stream to its speaker. We offer a complete treatment to the idea of partially supervised speaker clustering, which refers to the use of our prior knowledge of speakers in general to assist the unsupervised speaker clustering process. By means of an independent training data set, we encode the prior knowledge at the various stages of the speaker clustering pipeline via 1) learning a speaker-discriminative acoustic feature transformation, 2) learning a universal speaker prior model, and 3) learning a discriminative speaker subspace, or equivalently, a speaker-discriminative distance metric. We study the directional scattering property of the Gaussian mixture model (GMM) mean supervector representation of utterances in the high-dimensional space, and advocate exploiting this property by using the cosine distance metric instead of the euclidean distance metric for speaker clustering in the GMM mean supervector space. We propose to perform discriminant analysis based on the cosine distance metric, which leads to a novel distance metric learning algorithm—linear spherical discriminant analysis (LSDA). We show that the proposed LSDA formulation can be systematically solved within the elegant graph embedding general dimensionality reduction framework. Our speaker clustering experiments on the GALE database clearly indicate that 1) our speaker clustering methods based on the GMM mean supervector representation and vector-based distance metrics outperform traditional speaker clustering methods based on the “bag of acoustic features” representation and statistical model-based distance metrics, 2) our advocated use of the cosine distance metric yields consistent increases in the speaker clustering performance as compared to the commonly used euclidean distance metric, 3) our partially supervised speaker clustering concept and strategies significantly improve the speaker clustering performance over the baselines, and 4) our proposed LSDA algorithm further leads to state-of-the-art speaker clustering performance.

Assessing the Everyday Discrimination Scale Among American Indians and Alaska Natives

PubMed Central

Gonzales, Kelly L.; Noonan, Carolyn; Goins, R. Turner; Henderson, William G.; Beals, Janette; Manson, Spero M.; Acton, Kelly J.; Roubideaux, Yvette

2015-01-01

The Everyday Discrimination Scale (EDS) has been used widely as a measure of subjective experiences of discrimination. The usefulness of this measure for assessments of perceived experiences of discrimination by American Indian and Alaska Native (AI/AN) peoples has not been explored. Data derived from the Special Diabetes Program for Indians – Healthy Heart Demonstration Project (SDPI-HH), a large-scale initiative to reduce cardiovascular risk among AI/ANs with Type 2 diabetes. Participants (N=3,039) completed a self-report survey that included the EDS and measures of convergent and divergent validity. Missing data were estimated by multiple imputation techniques. Reliability estimates for the EDS were calculated, yielding a single factor with high internal consistency (α=0.92). Younger, more educated respondents reported greater perceived discrimination; retired or widowed respondents reported less. Convergent validity was evidenced by levels of distress, anger, and hostility, which increased as the level of perceived discrimination increased (all p<0.001). Divergent validity was evidenced by the absence of an association between EDS and resilient coping. Resilient coping and insulin-specific diabetes knowledge were not significantly associated with perceived discrimination (p=0.61 and 0.16, respectively). However, general diabetes-related health knowledge was significantly associated with perceived discrimination (p=0.02). The EDS is a promising measure for assessing perceived experiences of discrimination among those AI/ANs who participated in the SDPI-HH. PMID:26146948

Clinical Use of an Optical Coherence Tomography Linear Discriminant Function for Differentiating Glaucoma From Normal Eyes.

PubMed

Choi, Yun Jeong; Jeoung, Jin Wook; Park, Ki Ho; Kim, Dong Myung

2016-03-01

To determine and validate the diagnostic ability of a linear discriminant function (LDF) based on retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thickness obtained using high-definition optical coherence tomography (Cirrus HD-OCT) for discriminating between healthy controls and early glaucoma subjects. We prospectively selected 214 healthy controls and 152 glaucoma subjects (teaching set) and another independent sample of 86 healthy controls and 71 glaucoma subjects (validating set). Two scans, including 1 macular and 1 peripapillary RNFL scan, were obtained. After calculating the LDF in the teaching set using the binary logistic regression analysis, receiver operating characteristic curves were plotted and compared between the OCT-provided parameters and LDF in the validating set. The proposed LDF was 16.529-(0.132×superior RNFL)-(0.064×inferior RNFL)+(0.039×12 o'clock RNFL)+(0.038×1 o'clock RNFL)+(0.084×superior GCIPL)-(0.144×minimum GCIPL). The highest area under the receiver operating characteristic (AUROC) curve was obtained for LDF in both sets (AUROC=0.95 and 0.96). In the validating set, the LDF showed significantly higher AUROC than the best RNFL (inferior RNFL=0.91) and GCIPL parameter (minimum GCIPL=0.88). The LDF yielded a sensitivity of 93.0% at a fixed specificity of 85.0%. The LDF showed better diagnostic ability for differentiating between healthy and early glaucoma subjects than individual OCT parameters. A classification algorithm based on the LDF can be used in the OCT analysis for glaucoma diagnosis.

A locus for an auditory processing deficit and language impairment in an extended pedigree maps to 12p13.31-q14.3

PubMed Central

Addis, L; Friederici, A D; Kotz, S A; Sabisch, B; Barry, J; Richter, N; Ludwig, A A; Rübsamen, R; Albert, F W; Pääbo, S; Newbury, D F; Monaco, A P

2010-01-01

Despite the apparent robustness of language learning in humans, a large number of children still fail to develop appropriate language skills despite adequate means and opportunity. Most cases of language impairment have a complex etiology, with genetic and environmental influences. In contrast, we describe a three-generation German family who present with an apparently simple segregation of language impairment. Investigations of the family indicate auditory processing difficulties as a core deficit. Affected members performed poorly on a nonword repetition task and present with communication impairments. The brain activation pattern for syllable duration as measured by event-related brain potentials showed clear differences between affected family members and controls, with only affected members displaying a late discrimination negativity. In conjunction with psychoacoustic data showing deficiencies in auditory duration discrimination, the present results indicate increased processing demands in discriminating syllables of different duration. This, we argue, forms the cognitive basis of the observed language impairment in this family. Genome-wide linkage analysis showed a haplotype in the central region of chromosome 12 which reaches the maximum possible logarithm of odds ratio (LOD) score and fully co-segregates with the language impairment, consistent with an autosomal dominant, fully penetrant mode of inheritance. Whole genome analysis yielded no novel inherited copy number variants strengthening the case for a simple inheritance pattern. Several genes in this region of chromosome 12 which are potentially implicated in language impairment did not contain polymorphisms likely to be the causative mutation, which is as yet unknown. PMID:20345892

Discrimination and quantification of autofluorescence spectra of human lung cells

NASA Astrophysics Data System (ADS)

Rahmani, Mahya; Khani, Mohammad Mehdi; Khazaei Koohpar, Zeinab; Molik, Paria

2016-10-01

To study laser-induced autofluorescence spectroscopy of the human lung cell line, we evaluated the native fluorescence properties of cancer QU-DB and normal MRC-5 human lung cells during continuous exposure to 405 nm laser light. Two emission bands centered at ~470 nm and ~560 nm were observed. These peaks are most likely attributable to mitochondrial fluorescent reduced nicotinamide adenine dinucleotide and riboflavin fluorophores, respectively. This article highlights lung cell autofluorescence characterization and signal discrimination by collective investigation of different spectral features. The absolute intensity, the spectral shape factor or redox ratio, the full width of half-maximum and the full width of quarter maximum was evaluated. Moreover, the intensity ratio, the area under the peak and the area ratio as a contrast factor for normal and cancerous cells were also calculated. Among all these features it seems that the contrast factor precisely and significantly discriminates the spectral differences of normal and cancerous lung cells. On the other hand, the relative quantum yield for both cell types were found by comparing the quantum yield of an unknown compound with known fluorescein sodium as a reference solution.

Correlates of Sexual Satisfaction Among Sexually Active Postmenopausal Women in the Women’s Health Initiative-Observational Study

PubMed Central

Jaramillo, Sarah A.; Legault, Claudine; Freund, Karen M.; Cochrane, Barbara B.; Manson, JoAnn E.; Wenger, Nanette K.; Eaton, Charles B.; Rodriguez, Beatriz L.; McNeeley, S. Gene; Bonds, Denise

2008-01-01

BACKGROUND Satisfaction with sexual activity is important for health-related quality of life, but little is known about the sexual health of postmenopausal women. OBJECTIVE Describe factors associated with sexual satisfaction among sexually active postmenopausal women. DESIGN Cross-sectional analysis. PARTICIPANTS All members of the Women’s Health Initiative-Observational Study (WHI-OS), ages 50–79, excluding women who did not respond to the sexual satisfaction question or reported no partnered sexual activity in the past year (N = 46,525). MEASUREMENTS Primary outcome: dichotomous response to the question, “How satisfied are you with your sexual activity (satisfied versus unsatisfied)?” Covariates included sociodemographic factors, measures of physical and mental health, and gynecological variables, medications, and health behaviors related to female sexual health. RESULTS Of the cohort, 52% reported sexual activity with a partner in the past year, and 96% of these answered the sexual satisfaction question. Nonmodifiable factors associated with sexual dissatisfaction included age, identification with certain racial or ethnic groups, marital status, parity, and smoking history. Potentially modifiable factors included lower mental health status and use of SSRIs. The final model yielded a c-statistic of 0.613, reflecting only a modest ability to discriminate between the sexually satisfied and dissatisfied. CONCLUSIONS Among postmenopausal women, the variables selected for examination yielded modest ability to discriminate between sexually satisfied and dissatisfied participants. Further study is necessary to better describe the cofactors associated with sexual satisfaction in postmenopausal women. PMID:18839256

Perceived Discrimination and Health: A Meta-Analytic Review

PubMed Central

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which perceiving discrimination may affect health, including through psychological and physiological stress responses and health behaviors. Analysis of 134 samples suggests that when weighting each study’s contribution by sample size, perceived discrimination has a significant negative effect on both mental and physical health. Perceived discrimination also produces significantly heightened stress responses and is related to participation in unhealthy and nonparticipation in healthy behaviors. These findings suggest potential pathways linking perceived discrimination to negative health outcomes. PMID:19586161

Differentiation of essential oils in Atractylodes lancea and Atractylodes koreana by gas chromatography with mass spectrometry.

PubMed

Liu, Qiutao; Zhang, Shanshan; Yang, Xihui; Wang, Ruilin; Guo, Weiying; Kong, Weijun; Yang, Meihua

2016-12-01

Atractylodes rhizome is a valuable traditional Chinese medicinal herb that comprises complex several species whose essential oils are the primary pharmacologically active component. Essential oils of Atractylodes lancea and Atractylodes koreana were extracted by hydrodistillation, and the yield was determined. The average yield of essential oil obtained from A. lancea (2.91%) was higher than that from A. koreana (2.42%). The volatile components of the essential oils were then identified by a gas chromatography with mass spectrometry method that demonstrated good precision. The method showed clear differences in the numbers and contents of volatile components between the two species. 41 and 45 volatile components were identified in A. lancea and A. koreana, respectively. Atractylon (48.68%) was the primary volatile component in A. lancea, while eudesma-4(14)-en-11-ol (11.81%) was major in A. koreana. However, the most significant difference between A. lancea and A. koreana was the major component of atractylon and atractydin. Principal component analysis was utilized to reveal the correlation between volatile components and species, and the analysis was used to successfully discriminate between A. lancea and A. koreana samples. These results suggest that different species of Atractylodes rhizome may yield essential oils that differ significantly in content and composition. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Investigating the sex-related geometric variation of the human cranium.

PubMed

Bertsatos, Andreas; Papageorgopoulou, Christina; Valakos, Efstratios; Chovalopoulou, Maria-Eleni

2018-01-29

Accurate sexing methods are of great importance in forensic anthropology since sex assessment is among the principal tasks when examining human skeletal remains. The present study explores a novel approach in assessing the most accurate metric traits of the human cranium for sex estimation based on 80 ectocranial landmarks from 176 modern individuals of known age and sex from the Athens Collection. The purpose of the study is to identify those distance and angle measurements that can be most effectively used in sex assessment. Three-dimensional landmark coordinates were digitized with a Microscribe 3DX and analyzed in GNU Octave. An iterative linear discriminant analysis of all possible combinations of landmarks was performed for each unique set of the 3160 distances and 246,480 angles. Cross-validated correct classification as well as multivariate DFA on top performing variables reported 13 craniometric distances with over 85% classification accuracy, 7 angles over 78%, as well as certain multivariate combinations yielding over 95%. Linear regression of these variables with the centroid size was used to assess their relation to the size of the cranium. In contrast to the use of generalized procrustes analysis (GPA) and principal component analysis (PCA), which constitute the common analytical work flow for such data, our method, although computational intensive, produced easily applicable discriminant functions of high accuracy, while at the same time explored the maximum of cranial variability.

Multiplexed analysis combining distinctly-sized CdTe-MPA quantum dots and chemometrics for multiple mutually interfering analyte determination.

PubMed

Bittar, Dayana B; Ribeiro, David S M; Páscoa, Ricardo N M J; Soares, José X; Rodrigues, S Sofia M; Castro, Rafael C; Pezza, Leonardo; Pezza, Helena R; Santos, João L M

2017-11-01

Semiconductor quantum dots (QDs) have demonstrated a great potential as fluorescent probes for heavy metals monitoring. However, their great reactivity, whose tunability could be difficult to attain, could impair selectivity yielding analytical results with poor accuracy. In this work, the combination in the same analysis of multiple QDs, each with a particular ability to interact with the analyte, assured a multi-point detection that was not only exploited for a more precise analyte discrimination but also for the simultaneous discrimination of multiple mutually interfering species, in the same sample. Three different MPA-CdTe QDs (2.5, 3.0 and 3.8nm) with a good size distribution, confirmed by the FWHM values of 48.6, 55.4 and 80.8nm, respectively, were used. Principal component analysis (PCA) and partial least squares regression (PLS) were used for fluorescence data analysis. Mixtures of two MPA-CdTe QDs, emitting at different wavelength namely 549/566, 549/634 and 566/634nm were assayed. The 549/634nm emitting QDs mixture provided the best results for the discrimination of distinct ions on binary and ternary mixtures. The obtained RMSECV and R 2 CV values for the binary mixture were good, namely, from 0.01 to 0.08mgL -1 and from 0.74 to 0.89, respectively. Regarding the ternary mixture the RMSECV and R 2 CV values were good for Hg(II) (0.06 and 0.73mgL -1 , respectively) and Pb(II) (0.08 and 0.87mg L -1 , respectively) and acceptable for Cu(II) (0.02 and 0.51mgL -1 , respectively). In conclusion, the obtained results showed that the developed approach is capable of resolve binary and ternary mixtures of Pb (II), Hg (II) and Cu (II), providing accurate information about lead (II) and mercury (II) concentration and signaling the occurrence of Cu (II). Copyright © 2017 Elsevier B.V. All rights reserved.

Label-Free Quantitative Proteomics Identifies Novel Plasma Biomarkers for Distinguishing Pulmonary Tuberculosis and Latent Infection.

PubMed

Sun, Huishan; Pan, Liping; Jia, Hongyan; Zhang, Zhiguo; Gao, Mengqiu; Huang, Mailing; Wang, Jinghui; Sun, Qi; Wei, Rongrong; Du, Boping; Xing, Aiying; Zhang, Zongde

2018-01-01

The lack of effective differential diagnostic methods for active tuberculosis (TB) and latent infection (LTBI) is still an obstacle for TB control. Furthermore, the molecular mechanism behind the progression from LTBI to active TB has been not elucidated. Therefore, we performed label-free quantitative proteomics to identify plasma biomarkers for discriminating pulmonary TB (PTB) from LTBI. A total of 31 overlapping proteins with significant difference in expression level were identified in PTB patients ( n = 15), compared with LTBI individuals ( n = 15) and healthy controls (HCs, n = 15). Eight differentially expressed proteins were verified using western blot analysis, which was 100% consistent with the proteomics results. Statistically significant differences of six proteins were further validated in the PTB group compared with the LTBI and HC groups in the training set ( n = 240), using ELISA. Classification and regression tree (CART) analysis was employed to determine the ideal protein combination for discriminating PTB from LTBI and HC. A diagnostic model consisting of alpha-1-antichymotrypsin (ACT), alpha-1-acid glycoprotein 1 (AGP1), and E-cadherin (CDH1) was established and presented a sensitivity of 81.2% (69/85) and a specificity of 95.2% (80/84) in discriminating PTB from LTBI, and a sensitivity of 81.2% (69/85) and a specificity of 90.1% (64/81) in discriminating PTB from HCs. Additional validation was performed by evaluating the diagnostic model in blind testing set ( n = 113), which yielded a sensitivity of 75.0% (21/28) and specificity of 96.1% (25/26) in PTB vs. LTBI, 75.0% (21/28) and 92.3% (24/26) in PTB vs. HCs, and 75.0% (21/28) and 81.8% (27/33) in PTB vs. lung cancer (LC), respectively. This study obtained the plasma proteomic profiles of different M.TB infection statuses, which contribute to a better understanding of the pathogenesis involved in the transition from latent infection to TB activation and provide new potential diagnostic biomarkers for distinguishing PTB and LTBI.

Mental disability and discriminatory practices: effects of social representations of the Mexican population.

PubMed

Mariana, Espinola-Nadurille; Guadalupe, Delgado

2009-05-01

The prevalence of mental disorders in Mexico is 26.1%. This shows that an important percentage of the population suffers from mental disability. Despite this the country's healthcare system does not provide the least acceptable standard of care for the mentally disabled. The aim of this study was to describe the general population's social representations of the disabled and analyze their relationship with the discriminatory practices from the state towards the mentally ill with respect to their right to health. This study was a secondary analysis of the First National Survey on Discrimination in Mexico. In the survey 1,437 effective interviews that comprised a representative sample, were obtained from people aged 18 to 60 living in rural and urban settings. The response rate was 76.5%. The assessment tool was a self-administered questionnaire that yielded perceptions, attitudes, values and social representations about discrimination towards groups of people that supposedly were targets of discrimination by the general population. In the survey the mentally ill were included under disability. As a secondary analysis of the survey for the purpose of this study, we selected a subset of questions that provided important information about social representations of the general Mexican population towards persons with disabilities. The general population's social representations of the disabled were analyzed. The disabled are the second group after the elderly perceived as the most discriminated and neglected and bearing more suffering. A whole set of negative representations concerning the disabled, such as lack of acceptance and respect, low self-confidence, mistreatment, incomprehension, isolation, intolerance, indifference and bad attitudes from others, were elicited. Social representations are social correspondents of the discriminatory practices that the state exerts toward the mentally ill with respect to their right to health. These representations serve to maintain, naturalize and legitimize these practices. All sectors of society should make an effort to change the negative social representations towards this vulnerable section of society.

Discriminative capacity of calcaneal quantitative ultrasound and of osteoporosis and fracture risk factors in postmenopausal women with osteoporotic fractures.

PubMed

Hernández, J L; Marin, F; González-Macías, J; Díez-Pérez, A; Vila, J; Giménez, S; Galán, B; Arenas, M S; Suárez, F; Gayola, L; Guillén, G; Sagredo, T; Belenguer, R; Moron, A; Arriaza, E

2004-04-01

Bone fragility fractures constitute the principal complication of osteoporosis. The identification of individuals at high risk of sustaining osteoporotic fractures is important for implementing preventive measures. The purpose of this study is to analyze the discriminative capacity of a series of osteoporosis and fracture risk factors, and of calcaneal quantitative ultrasound (QUS), in a population of postmenopausal women with a history of osteoporotic fracture. A cross-sectional analysis was made of a cohort of 5195 women aged 65 or older (mean +/- SD: 72.3 +/- 5.4 years) seen in 58 primary care centers in Spain. A total of 1042 women (20.1%) presented with a history of osteoporotic fracture. Most fractures (93%) were non-vertebral. Age-adjusted odds ratios corresponding to each decrease in one standard deviation of the different QUS parameters ranged from 1.47 to 1.55 (P < 0.001) for fractures. The age-adjusted multivariate analysis yielded the following risk factors independently associated with a history of osteoporotic fracture: number of fertile years, a family history of fracture, falls in the previous year, a history of chronic obstructive airway disease, the use of antiarrhythmic drugs, and a low value for any of the QUS parameters. The area under the receiver operating characteristic curve of the best model was 0.656. In summary, a series of easily assessable osteoporotic fracture risk factors has been identified. QUS was shown to discriminate between women with and without a history of fracture, and constitutes a useful tool for assessing fracture risk. Various of the vertebral and hip fracture risk factors frequently cited in North American and British populations showed no discriminative capacity in our series--thus suggesting that such factors may not be fully applicable to our population and/or to the predominant type of fractures included in the present study.

Study on bayes discriminant analysis of EEG data.

PubMed

Shi, Yuan; He, DanDan; Qin, Fang

2014-01-01

In this paper, we have done Bayes Discriminant analysis to EEG data of experiment objects which are recorded impersonally come up with a relatively accurate method used in feature extraction and classification decisions. In accordance with the strength of α wave, the head electrodes are divided into four species. In use of part of 21 electrodes EEG data of 63 people, we have done Bayes Discriminant analysis to EEG data of six objects. Results In use of part of EEG data of 63 people, we have done Bayes Discriminant analysis, the electrode classification accuracy rates is 64.4%. Bayes Discriminant has higher prediction accuracy, EEG features (mainly αwave) extract more accurate. Bayes Discriminant would be better applied to the feature extraction and classification decisions of EEG data.

Wavelet filtered shifted phase-encoded joint transform correlation for face recognition

NASA Astrophysics Data System (ADS)

Moniruzzaman, Md.; Alam, Mohammad S.

2017-05-01

A new wavelet-filtered-based Shifted- phase-encoded Joint Transform Correlation (WPJTC) technique has been proposed for efficient face recognition. The proposed technique uses discrete wavelet decomposition for preprocessing and can effectively accommodate various 3D facial distortions, effects of noise, and illumination variations. After analyzing different forms of wavelet basis functions, an optimal method has been proposed by considering the discrimination capability and processing speed as performance trade-offs. The proposed technique yields better correlation discrimination compared to alternate pattern recognition techniques such as phase-shifted phase-encoded fringe-adjusted joint transform correlator. The performance of the proposed WPJTC has been tested using the Yale facial database and extended Yale facial database under different environments such as illumination variation, noise, and 3D changes in facial expressions. Test results show that the proposed WPJTC yields better performance compared to alternate JTC based face recognition techniques.

Regional Magnitude Research Supporting Broad-Area Monitoring of Small Seismic Events

DTIC Science & Technology

2007-09-01

detonated at the Nevada Test Site (NTS) and the Semipalatinsk Test Site (STS). Observations for both test sites show that Pn amplitudes yield scale 10...identification procedures, and yield, via direct comparison to test site results for high frequencies (>1 Hz). Coda techniques are known to be effective...2006). Source spectral modeling of regional P/S discriminants at nuclear test sites in China and the former Soviet Union, Bull. Seismol. Soc. Am

Social status correlates of reporting gender discrimination and racial discrimination among racially diverse women.

PubMed

Ro, Annie E; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in North California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design.

Drop coating deposition Raman spectroscopy of blood plasma for the detection of colorectal cancer

NASA Astrophysics Data System (ADS)

Li, Pengpeng; Chen, Changshui; Deng, Xiaoyuan; Mao, Hua; Jin, Shaoqin

2015-03-01

We have recently applied the technique of drop coating deposition Raman (DCDR) spectroscopy for colorectal cancer (CRC) detection using blood plasma. The aim of this study was to develop a more convenient and stable method based on blood plasma for noninvasive CRC detection. Significant differences are observed in DCDR spectra between healthy (n=105) and cancer (n=75) plasma from 15 CRC patients and 21 volunteers, particularly in the spectra that are related to proteins, nucleic acids, and β-carotene. The multivariate analysis principal components analysis and the linear discriminate analysis, together with leave-one-out, cross validation were used on DCDR spectra and yielded a sensitivity of 100% (75/75) and specificity of 98.1% (103/105) for detection of CRC. This study demonstrates that DCDR spectroscopy of blood plasma associated with multivariate statistical algorithms has the potential for the noninvasive detection of CRC.

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES

PubMed Central

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D.

2009-01-01

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component’s discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies. PMID:20582334

EXTRACTING PRINCIPLE COMPONENTS FOR DISCRIMINANT ANALYSIS OF FMRI IMAGES.

PubMed

Liu, Jingyu; Xu, Lai; Caprihan, Arvind; Calhoun, Vince D

2008-05-12

This paper presents an approach for selecting optimal components for discriminant analysis. Such an approach is useful when further detailed analyses for discrimination or characterization requires dimensionality reduction. Our approach can accommodate a categorical variable such as diagnosis (e.g. schizophrenic patient or healthy control), or a continuous variable like severity of the disorder. This information is utilized as a reference for measuring a component's discriminant power after principle component decomposition. After sorting each component according to its discriminant power, we extract the best components for discriminant analysis. An application of our reference selection approach is shown using a functional magnetic resonance imaging data set in which the sample size is much less than the dimensionality. The results show that the reference selection approach provides an improved discriminant component set as compared to other approaches. Our approach is general and provides a solid foundation for further discrimination and classification studies.

A new unified framework for the early detection of the progression to diabetic retinopathy from fundus images.

PubMed

Leontidis, Georgios

2017-11-01

Human retina is a diverse and important tissue, vastly studied for various retinal and other diseases. Diabetic retinopathy (DR), a leading cause of blindness, is one of them. This work proposes a novel and complete framework for the accurate and robust extraction and analysis of a series of retinal vascular geometric features. It focuses on studying the registered bifurcations in successive years of progression from diabetes (no DR) to DR, in order to identify the vascular alterations. Retinal fundus images are utilised, and multiple experimental designs are employed. The framework includes various steps, such as image registration and segmentation, extraction of features, statistical analysis and classification models. Linear mixed models are utilised for making the statistical inferences, alongside the elastic-net logistic regression, boruta algorithm, and regularised random forests for the feature selection and classification phases, in order to evaluate the discriminative potential of the investigated features and also build classification models. A number of geometric features, such as the central retinal artery and vein equivalents, are found to differ significantly across the experiments and also have good discriminative potential. The classification systems yield promising results with the area under the curve values ranging from 0.821 to 0.968, across the four different investigated combinations. Copyright © 2017 Elsevier Ltd. All rights reserved.

Habits with killer instincts: in vivo analysis on the severity of oral mucosal alterations using autofluorescence spectroscopy

NASA Astrophysics Data System (ADS)

Nazeer Shaiju, S.; Ariya, Saraswathy; Asish, Rajasekharan; Salim Haris, Padippurakkakath; Anita, Balan; Arun Kumar, Gupta; Jayasree, Ramapurath S.

2011-08-01

Oral habits like chewing and smoking are main causes of oral cancer, which has a higher mortality rate than many other cancer forms. Currently, the long term survival rate of oral cancer is less than 50%, as a majority of cases are detected very late. The clinician's main challenge is to differentiate among a multitude of red, white, or ulcerated lesions. Hence, new noninvasive, reliable, and fast techniques for the discrimination of oral cavity disorders are to be developed. This study includes autofluorescence spectroscopic screening of normal volunteers with and without lifestyle oral habits and patients with oral submucous fibrosis (OSF). The spectra from different sites of habitués, non-habitués, and OSF patients were analyzed using the intensity ratio, redox ratio, and linear discriminant analysis (LDA). The spectral disparities among these groups are well demonstrated in the emission regions of collagen and Flavin adenine dinucleotide. We observed that LDA gives better efficiency of classification than the intensity ratio technique. Even the differentiation of habitués and non-habitués could be well established with LDA. The study concludes that the clinical application of autofluorescence spectroscopy along with LDA, yields spontaneous screening among individuals, facilitating better patient management for clinicians and better quality of life for patients.

Body Shape and Life Style of the Extinct Balearic Dormouse Hypnomys (Rodentia, Gliridae): New Evidence from the Study of Associated Skeletons

PubMed Central

Bover, Pere; Alcover, Josep A.; Michaux, Jacques J.; Hautier, Lionel; Hutterer, Rainer

2010-01-01

Hypnomys is a genus of Gliridae (Rodentia) that occurred in the Balearic Islands until Late Holocene. Recent finding of a complete skeleton of the chronospecies H. morpheus (Late Pleistocene-Early Holocene) and two articulated skeletons of H. cf. onicensis (Late Pliocene) allowed the inference of body size and the calculation of several postcranial indexes. We also performed a Factorial Discriminant Analysis (FDA) in order to evaluate locomotory behaviour and body shape of the taxa. Using allometric models based on skull and tooth measurements, we calculated a body weight between 173 and 284 g for H. morpheus, and direct measurements of articulated skeletons yielded a Head and Body Length (HBL) of 179 mm and a Total Body Length of 295 mm for this species. In addition to the generally higher robustness of postcranial bones already recorded by previous authors, H. morpheus, similar to Canariomys tamarani, another extinct island species, displayed elongated zygopodium bones of the limbs and a wider distal humerus and femur than in an extant related taxon, Eliomys quercinus. Indexes indicated that Hypnomys was more terrestrial and had greater fossorial abilities than E. quercinus. This was also corroborated by a Discriminant Analysis, although no clear additional inference of locomotory abilities could be calculated. PMID:21209820

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

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

Dalla Palma, M.; Quaranta, A.; INFN, Laboratori Nazionali di Legnaro,Viale dell'Universita, 2, 35020 Legnaro - Padova

In the last decade, attention toward neutron detection has been growing in the scientific community, driven by new requirements in different fields of application ranging from homeland security to medical and material analysis, from research physics, to nuclear energy production. So far neutron detection, with particular attention to fast neutrons, has been mainly based on organic liquid scintillators, owing to their good efficiency and pulse shape discrimination (PSD) capability. Most of these liquids have however some main drawbacks given by toxicity, flammability, volatility and sensitivity to dissolved oxygen that limits the duration and the quality of their performances with worsemore » handiness and increased costs. Phenyl-substituted polysiloxanes could address most of these issues, being characterized by low toxicity, low volatility and low flammability. Their optical properties can be tailored by changing the phenyl distribution and concentration thus allowing to increase the solubility of organic dyes, to modify the fluorescence spectra and to vary the refractive index of the medium. Furthermore, polysiloxanes have been recently exploited for the production of plastic scintillators with very good chemical and thermal stability and very good radiation hardness and the development of polysiloxane liquid scintillators could allow to combine these interesting properties with the supremacy of liquid scintillators as regarding PSD over plastics. For these reasons, the properties of several phenyl-substituted polysiloxane with different phenyl amounts and different viscosities have been investigated, with particular attention to the scintillation response and the pulse shape discrimination capability, and the results of the investigation are reported in this work. More in details, the scintillation light yield towards gamma rays ({sup 60}Co and {sup 137}Cs) of several polysiloxane liquids has been analyzed and compared with the light yield of a commercial non-toxic liquid scintillator (EJ309). The results have been related to the optical characterization of these materials, especially as regarding the fluorescence response, and the best performing material (1,1,5,5-Tetraphenyl 1,3,3,5-Tetramethyl Trisiloxane) showed a scintillation light-yield only slightly lower than EJ309, proving to be a promising candidate for the production of an efficient polysiloxane based liquid scintillator. The results as regarding the neutron-gamma pulse shape discrimination capability of the best performing materials are also reported in this work and the scintillation decay time of these materials are compared to the results of fluorescence lifetime analysis. PSD tests have been performed at CN accelerator in Legnaro National Laboratories with a 2.2 MeV pulsed neutron beam using TOF procedure and the pulses have been analyzed in order to evidence the PSD capability of every sample. The reported results pave the way to the development of a new promising class of non-toxic liquid scintillating materials for neutron detection, with good light output and interesting PSD characteristics. (authors)« less

Elevated Genetic Diversity in an F2:6 Population of Quinoa (Chenopodium quinoa) Developed through an Inter-ecotype Cross

PubMed Central

Benlhabib, Ouafae; Boujartani, Noura; Maughan, Peter J.; Jacobsen, Sven E.; Jellen, Eric N.

2016-01-01

Quinoa (Chenopodium quinoa) is a seed crop of the Andean highlands and Araucanian coastal regions of South America that has recently expanded in use and production beyond its native range. This is largely due to its superb nutritional value, consisting of protein that is rich in essential amino acids along with vitamins and minerals. Quinoa also presents a remarkable degree of tolerance to saline conditions, drought, and frost. The present study involved 72 F2:6 recombinant-inbred lines and parents developed through hybridization between highland (0654) and coastal (NL-6) germplasm groups. The purpose was to characterize the quinoa germplasm developed, to assess the discriminating potential of 21 agro-morpho-phenological traits, and to evaluate the extent of genetic variability recovered through selfing. A vast amount of genetic variation was detected among the 72 lines evaluated for quantitative and qualitative traits. Impressive transgressive segregation was measured for seed yield (22.42 g/plant), while plant height and maturity had higher heritabilities (73 and 89%, respectively). Other notable characters segregating in the population included panicle and stem color, panicle form, and resistance to downy mildew. In the Principal Component analysis, the first axis explained 74% of the total variation and was correlated to plant height, panicle size, stem diameter, biomass, mildew reaction, maturation, and seed yield; those traits are relevant discriminatory characters. Yield correlated positively with panicle length and biomass. Unweighted Pair Group Method with Arithmetic Mean-based cluster analysis identified three groups: one consisting of late, mildew-resistant, high-yielding lines; one having semi-late lines with intermediate yield and mildew susceptibility; and a third cluster consisting of early to semi-late accessions with low yield and mildew susceptibility. This study highlighted the extended diversity regenerated among the 72 accessions and helped to identify potentially adapted quinoa genotypes for production in the Moroccan coastal environment. PMID:27582753

Discrimination against Latina/os: A Meta-Analysis of Individual-Level Resources and Outcomes

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2012-01-01

This meta-analysis synthesizes the findings of 60 independent samples from 51 studies examining racial/ethnic discrimination against Latina/os in the United States. The purpose was to identify individual-level resources and outcomes that most strongly relate to discrimination. Discrimination against Latina/os significantly results in outcomes…

Illumination robust face recognition using spatial adaptive shadow compensation based on face intensity prior

NASA Astrophysics Data System (ADS)

Hsieh, Cheng-Ta; Huang, Kae-Horng; Lee, Chang-Hsing; Han, Chin-Chuan; Fan, Kuo-Chin

2017-12-01

Robust face recognition under illumination variations is an important and challenging task in a face recognition system, particularly for face recognition in the wild. In this paper, a face image preprocessing approach, called spatial adaptive shadow compensation (SASC), is proposed to eliminate shadows in the face image due to different lighting directions. First, spatial adaptive histogram equalization (SAHE), which uses face intensity prior model, is proposed to enhance the contrast of each local face region without generating visible noises in smooth face areas. Adaptive shadow compensation (ASC), which performs shadow compensation in each local image block, is then used to produce a wellcompensated face image appropriate for face feature extraction and recognition. Finally, null-space linear discriminant analysis (NLDA) is employed to extract discriminant features from SASC compensated images. Experiments performed on the Yale B, Yale B extended, and CMU PIE face databases have shown that the proposed SASC always yields the best face recognition accuracy. That is, SASC is more robust to face recognition under illumination variations than other shadow compensation approaches.

Status of LUMINEU program to search for neutrinoless double beta decay of 100Mo with cryogenic ZnMoO4 scintillating bolometers

NASA Astrophysics Data System (ADS)

Danevich, F. A.; Bergé, L.; Boiko, R. S.; Chapellier, M.; Chernyak, D. M.; Coron, N.; Devoyon, L.; Drillien, A.-A.; Dumoulin, L.; Enss, C.; Fleischmann, A.; Gastaldo, L.; Giuliani, A.; Gray, D.; Gros, M.; Hervé, S.; Humbert, V.; Ivanov, I. M.; Juillard, A.; Kobychev, V. V.; Koskas, F.; Loidl, M.; Magnier, P.; Makarov, E. P.; Mancuso, M.; de Marcillac, P.; Marnieros, S.; Marrache-Kikuchi, C.; Navick, X.-F.; Nones, C.; Olivieri, E.; Paul, B.; Penichot, Y.; Pessina, G.; Plantevin, O.; Poda, D. V.; Redon, T.; Rodrigues, M.; Shlegel, V. N.; Strazzer, O.; Tenconi, M.; Torres, L.; Tretyak, V. I.; Vasiliev, Ya. V.; Velazquez, M.; Viraphong, O.

2015-10-01

The LUMTNEU program aims at performing a pilot experiment on 0ν2β decay of 100Mo using radiopure ZnMoO4 crystals enriched in 100Mo operated as cryogenic scintillating bolometers. Large volume ZnMoO4 crystal scintillators (˜ 0.3 kg) were developed and tested showing high performance in terms of radiopurity, energy resolution and α/β particle discrimination capability. Zinc molybdate crystal scintillators enriched in 100Mo were grown for the first time by the low-thermal-gradient Czochralski technique with a high crystal yield and an acceptable level of enriched molybdenum irrecoverable losses. A background level of ˜ 0.5 counts/(yr keV ton) in the region of interest can be reached in a large detector array thanks to the excellent detectors radiopurity and particle discrimination capability, suppression of randomly coinciding events by pulse-shape analysis, and anticoincidence cut. These results pave the way to future sensitive searches based on the LUMTNEU technology, capable of approachingand exploring the inverted hierarchy region of the neutrino mass pattern.

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

Danevich, F. A., E-mail: danevich@kinr.kiev.ua; Boiko, R. S.; Chernyak, D. M.

The LUMTNEU program aims at performing a pilot experiment on 0ν2β decay of {sup 100}Mo using radiopure ZnMoO{sub 4} crystals enriched in {sup 100}Mo operated as cryogenic scintillating bolometers. Large volume ZnMoO{sub 4} crystal scintillators (∼ 0.3 kg) were developed and tested showing high performance in terms of radiopurity, energy resolution and α/β particle discrimination capability. Zinc molybdate crystal scintillators enriched in {sup 100}Mo were grown for the first time by the low-thermal-gradient Czochralski technique with a high crystal yield and an acceptable level of enriched molybdenum irrecoverable losses. A background level of ∼ 0.5 counts/(yr keV ton) in the regionmore » of interest can be reached in a large detector array thanks to the excellent detectors radiopurity and particle discrimination capability, suppression of randomly coinciding events by pulse-shape analysis, and anticoincidence cut. These results pave the way to future sensitive searches based on the LUMTNEU technology, capable of approachingand exploring the inverted hierarchy region of the neutrino mass pattern.« less

Motivational Values, Parental Influences and the Experience of Discrimination among Romanian and Moroccan Young Immigrants in Spain.

PubMed

Espinosa, Pablo; Clemente, Miguel; Uña, Octavio

2016-11-08

This study examines the role that motivational values play in the experience of discrimination in young immigrants in Spain and how this role is mediated by parental values. Participants in the study were 193 dyads of pre-adolescent to young adult first and second generation immigrants and one of their parents. All participants were either of Moroccan or Romanian ascent, the two largest immigrant groups in Spain. The proposed SEM model had an adequate fit, χ2(2, N = 193) = 2.272, p = .321, RMSEA = .027, CFI = .999, NFI = .994, and yielded a large R 2, both for the Moroccan group (R 2 = .79, p < .01), and the Romanian group (R 2 = .80, p < .01). It showed that the value dimension openness to change vs. conservation is positively related to their experience of discrimination (β = .35, p < .01, for Moroccans group; and β = .29, p < .001, for Romanians). This relationship was mediated by parental values and their parents' experience of discrimination. A possible explanation is that immigrants high in openness to change are likely to pursue contact with the host culture more intensely, and thus increase the probability of interactions involving discrimination. Additionally, parental values and their own experience of discrimination influences their children, making them more vulnerable to discrimination stress and more likely to perceive discrimination. While most research is focused on external or environmental variables, this study highlights the importance of value orientations and parental influences in immigrants' experience of discrimination.

Tower of London test: a comparison between conventional statistic approach and modelling based on artificial neural network in differentiating fronto-temporal dementia from Alzheimer's disease.

PubMed

Franceschi, Massimo; Caffarra, Paolo; Savarè, Rita; Cerutti, Renata; Grossi, Enzo

2011-01-01

The early differentiation of Alzheimer's disease (AD) from frontotemporal dementia (FTD) may be difficult. The Tower of London (ToL), thought to assess executive functions such as planning and visuo-spatial working memory, could help in this purpose. Twentytwo Dementia Centers consecutively recruited patients with early FTD or AD. ToL performances of these groups were analyzed using both the conventional statistical approaches and the Artificial Neural Networks (ANNs) modelling. Ninety-four non aphasic FTD and 160 AD patients were recruited. ToL Accuracy Score (AS) significantly (p < 0.05) differentiated FTD from AD patients. However, the discriminant validity of AS checked by ROC curve analysis, yielded no significant results in terms of sensitivity and specificity (AUC 0.63). The performances of the 12 Success Subscores (SS) together with age, gender and schooling years were entered into advanced ANNs developed by Semeion Institute. The best ANNs were selected and submitted to ROC curves. The non-linear model was able to discriminate FTD from AD with an average AUC for 7 independent trials of 0.82. The use of hidden information contained in the different items of ToL and the non linear processing of the data through ANNs allows a high discrimination between FTD and AD in individual patients.

Morphometric analysis of sex differences in contemporary Japanese pelves using multidetector computed tomography.

PubMed

Torimitsu, Suguru; Makino, Yohsuke; Saitoh, Hisako; Sakuma, Ayaka; Ishii, Namiko; Yajima, Daisuke; Inokuchi, Go; Motomura, Ayumi; Chiba, Fumiko; Yamaguchi, Rutsuko; Hashimoto, Mari; Hoshioka, Yumi; Iwase, Hirotaro

2015-12-01

Sex estimation of decomposed or skeletal remains is clearly important in forensic contexts. Recently, contemporary population-specific data has been obtained using multidetector computed tomography (MDCT) scanning. The main purpose of this study was to investigate skeletal pelvic dimorphism in a contemporary Japanese forensic sample and to quantify the accuracy of sex estimation using various pelvic measurements obtained from three-dimensional (3D) CT images. This study used a total of 208 cadavers (104 males, 104 females) of which postmortem CT scanning and subsequent forensic autopsy were conducted between December 2011 and August 2014. Eleven measurements of each pelvis were obtained from 3D CT reconstructed images that extracted only bone data. The measurements were analyzed using descriptive statistics and discriminant function analyses. All except one measurement were dimorphic in terms of sex differences. Univariate discriminant function analyses using these measurements provided sex classification accuracy rates of 62.0-98.1%. The subpubic angle was found to contribute most significantly to accurate sex estimation. Multivariate discriminant functions yielded sex prediction accuracy rates of 63.9-98.1%. In conclusion, the pelvic measurements obtained from 3D CT images of a contemporary Japanese population successfully demonstrated sexual dimorphism and may be useful for the estimation of skeletal sex in the field of forensic anthropology. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Broadband Evaluation of DPRK Explosions, Collapse Event, and Induced Aftershocks

NASA Astrophysics Data System (ADS)

Mayeda, K.; Roman-Nieves, J. I.; Wagner, G.; Jeon, Y. S.

2017-12-01

We report on the past 6 declared DPRK nuclear explosions, a collapse event, and recent associated induced shear dislocation sources using long-period waveform modeling, direct regional phases, and stable P-coda and S-coda spectral ratios. We find that the recent September 3rd, 2017 explosion is well modeled with an MM71 explosion source model at normal scale depth, but the previous 5 smaller yield explosions exhibit much larger relative high frequency radiation, strongly suggesting they are all over buried by varying amounts. The collapse event that occurred 8 minutes following the September 3rd DPRK explosion shares significant similarities with a number of NTS collapse events for explosions of comparable yield, both in absolute amplitude and spectral fall-off. A large number of smaller sources have been observed, which from stable coda spectral analysis and waveform modeling, are consistent with shallow shear dislocations likely caused by stress redistribution following the past nuclear explosions. We conclude with testing of a new discriminant that is specific to this region.

Measuring Community Resilience to Coastal Hazards along the Northern Gulf of Mexico

PubMed Central

Lam, Nina S. N.; Reams, Margaret; Li, Kenan; Li, Chi; Mata, Lillian P.

2016-01-01

The abundant research examining aspects of social-ecological resilience, vulnerability, and hazards and risk assessment has yielded insights into these concepts and suggested the importance of quantifying them. Quantifying resilience is complicated by several factors including the varying definitions of the term applied in the research, difficulties involved in selecting and aggregating indicators of resilience, and the lack of empirical validation for the indices derived. This paper applies a new model, called the resilience inference measurement (RIM) model, to quantify resilience to climate-related hazards for 52 U.S. counties along the northern Gulf of Mexico. The RIM model uses three elements (exposure, damage, and recovery indicators) to denote two relationships (vulnerability and adaptability), and employs both K-means clustering and discriminant analysis to derive the resilience rankings, thus enabling validation and inference. The results yielded a classification accuracy of 94.2% with 28 predictor variables. The approach is theoretically sound and can be applied to derive resilience indices for other study areas at different spatial and temporal scales. PMID:27499707

Crude ethanolic extract from spent coffee grounds: Volatile and functional properties.

PubMed

Page, Julio C; Arruda, Neusa P; Freitas, Suely P

2017-11-01

Espresso capsule consumption and spent coffee ground (SCG) generation have increased, and the present study was undertaken to evaluate the volatile profile (VP), the antioxidant activity (AA) and the sun protection factor (SPF) of the Crude ethanolic extract obtained from the SCG in capsules. The extract yield was superior to the ether yield because a higher unsaponifiable matter (U.M.) amount was recovered by ethanol. The obtained VP (70 compounds) was typical of roasted coffee oil. Furthermore, chemometric analysis using principal components (PCA) discriminated the extracts and grouped the replicates for each sample, which showed the repeatability of the extraction process. The AA ranged from 18.4 to 23.6 (mg extract mg DPPH -1 ) and the SPF from 2.27 to 2.76. The combination of the coffee VP, AA and SPF gave the espresso SCG's crude ethanolicextract, desirable properties that can be used in cosmetic and food industries. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measuring Community Resilience to Coastal Hazards along the Northern Gulf of Mexico.

PubMed

Lam, Nina S N; Reams, Margaret; Li, Kenan; Li, Chi; Mata, Lillian P

2016-02-01

The abundant research examining aspects of social-ecological resilience, vulnerability, and hazards and risk assessment has yielded insights into these concepts and suggested the importance of quantifying them. Quantifying resilience is complicated by several factors including the varying definitions of the term applied in the research, difficulties involved in selecting and aggregating indicators of resilience, and the lack of empirical validation for the indices derived. This paper applies a new model, called the resilience inference measurement (RIM) model, to quantify resilience to climate-related hazards for 52 U.S. counties along the northern Gulf of Mexico. The RIM model uses three elements (exposure, damage, and recovery indicators) to denote two relationships (vulnerability and adaptability), and employs both K-means clustering and discriminant analysis to derive the resilience rankings, thus enabling validation and inference. The results yielded a classification accuracy of 94.2% with 28 predictor variables. The approach is theoretically sound and can be applied to derive resilience indices for other study areas at different spatial and temporal scales.

Investigating the complexity of precipitation sets within California via the fractal-multifractal method

NASA Astrophysics Data System (ADS)

Puente, Carlos E.; Maskey, Mahesh L.; Sivakumar, Bellie

2017-04-01

A deterministic geometric approach, the fractal-multifractal (FM) method, is adapted in order to encode highly intermittent daily rainfall records observed over a year. Using such a notion, this research investigates the complexity of rainfall in various stations within the State of California. Specifically, records gathered at (from South to North) Cherry Valley, Merced, Sacramento and Shasta Dam, containing 59, 116, 115 and 72 years, all ending at water year 2015, were encoded and analyzed in detail. The analysis reveals that: (a) the FM approach yields faithful encodings of all records, by years, with mean square and maximum errors in accumulated rain that are less than a mere 2% and 10%, respectively; (b) the evolution of the corresponding "best" FM parameters, allowing visualization of the inter-annual rainfall dynamics from a reduced vantage point, exhibit implicit variability that precludes discriminating between sites and extrapolating to the future; (c) the evolution of the FM parameters, restricted to specific regions within space, allows finding sensible future simulations; and (d) the rain signals at all sites may be termed "equally complex," as usage of k-means clustering and conventional phase space analysis of FM parameters yields comparable results for all sites.

A pattern recognition approach to transistor array parameter variance

NASA Astrophysics Data System (ADS)

da F. Costa, Luciano; Silva, Filipi N.; Comin, Cesar H.

2018-06-01

The properties of semiconductor devices, including bipolar junction transistors (BJTs), are known to vary substantially in terms of their parameters. In this work, an experimental approach, including pattern recognition concepts and methods such as principal component analysis (PCA) and linear discriminant analysis (LDA), was used to experimentally investigate the variation among BJTs belonging to integrated circuits known as transistor arrays. It was shown that a good deal of the devices variance can be captured using only two PCA axes. It was also verified that, though substantially small variation of parameters is observed for BJT from the same array, larger variation arises between BJTs from distinct arrays, suggesting the consideration of device characteristics in more critical analog designs. As a consequence of its supervised nature, LDA was able to provide a substantial separation of the BJT into clusters, corresponding to each transistor array. In addition, the LDA mapping into two dimensions revealed a clear relationship between the considered measurements. Interestingly, a specific mapping suggested by the PCA, involving the total harmonic distortion variation expressed in terms of the average voltage gain, yielded an even better separation between the transistor array clusters. All in all, this work yielded interesting results from both semiconductor engineering and pattern recognition perspectives.

Generation of high-yield insulin producing cells from human bone marrow mesenchymal stem cells.

PubMed

Jafarian, Arefeh; Taghikhani, Mohammad; Abroun, Saeid; Pourpak, Zahra; Allahverdi, Amir; Soleimani, Masoud

2014-07-01

Allogenic islet transplantation is a most efficient approach for treatment of diabetes mellitus. However, the scarcity of islets and long term need for an immunosuppressant limits its application. Recently, cell replacement therapies that generate of unlimited sources of β cells have been developed to overcome these limitations. In this study we have described a stage specific differentiation protocol for the generation of insulin producing islet-like clusters from human bone marrow mesenchymal stem cells (hBM-MSCs). This specific stepwise protocol induced differentiation of hMSCs into definitive endoderm, pancreatic endoderm and pancreatic endocrine cells that expressed of sox17, foxa2, pdx1, ngn3, nkx2.2, insulin, glucagon, somatostatin, pancreatic polypeptide, and glut2 transcripts respectively. In addition, immunocytochemical analysis confirmed protein expression of the above mentioned genes. Western blot analysis discriminated insulin from proinsulin in the final differentiated cells. In derived insulin producing cells (IPCs), secreted insulin and C-peptide was in a glucose dependent manner. We have developed a protocol that generates effective high-yield human IPCs from hBM-MSCs in vitro. These finding suggest that functional IPCs generated by this procedure can be used as a cell-based approach for insulin dependent diabetes mellitus.

Classification of Fusarium-Infected Korean Hulled Barley Using Near-Infrared Reflectance Spectroscopy and Partial Least Squares Discriminant Analysis

PubMed Central

Lim, Jongguk; Kim, Giyoung; Mo, Changyeun; Oh, Kyoungmin; Yoo, Hyeonchae; Ham, Hyeonheui; Kim, Moon S.

2017-01-01

The purpose of this study is to use near-infrared reflectance (NIR) spectroscopy equipment to nondestructively and rapidly discriminate Fusarium-infected hulled barley. Both normal hulled barley and Fusarium-infected hulled barley were scanned by using a NIR spectrometer with a wavelength range of 1175 to 2170 nm. Multiple mathematical pretreatments were applied to the reflectance spectra obtained for Fusarium discrimination and the multivariate analysis method of partial least squares discriminant analysis (PLS-DA) was used for discriminant prediction. The PLS-DA prediction model developed by applying the second-order derivative pretreatment to the reflectance spectra obtained from the side of hulled barley without crease achieved 100% accuracy in discriminating the normal hulled barley and the Fusarium-infected hulled barley. These results demonstrated the feasibility of rapid discrimination of the Fusarium-infected hulled barley by combining multivariate analysis with the NIR spectroscopic technique, which is utilized as a nondestructive detection method. PMID:28974012

Discrimination of red and white rice bran from Indonesia using HPLC fingerprint analysis combined with chemometrics.

PubMed

Sabir, Aryani; Rafi, Mohamad; Darusman, Latifah K

2017-04-15

HPLC fingerprint analysis combined with chemometrics was developed to discriminate between the red and the white rice bran grown in Indonesia. The major component in rice bran is γ-oryzanol which consisted of 4 main compounds, namely cycloartenol ferulate, cyclobranol ferulate, campesterol ferulate and β-sitosterol ferulate. Separation of these four compounds along with other compounds was performed using C18 and methanol-acetonitrile with gradient elution system. By using these intensity variations, principal component and discriminant analysis were performed to discriminate the two samples. Discriminant analysis was successfully discriminated the red from the white rice bran with predictive ability of the model showed a satisfactory classification for the test samples. The results of this study indicated that the developed method was suitable as quality control method for rice bran in terms of identification and discrimination of the red and the white rice bran. Copyright © 2016 Elsevier Ltd. All rights reserved.

Explosive Yield Estimation using Fourier Amplitude Spectra of Velocity Histories

NASA Astrophysics Data System (ADS)

Steedman, D. W.; Bradley, C. R.

2016-12-01

The Source Physics Experiment (SPE) is a series of explosive shots of various size detonated at varying depths in a borehole in jointed granite. The testbed includes an extensive array of accelerometers for measuring the shock environment close-in to the explosive source. One goal of SPE is to develop greater understanding of the explosion phenomenology in all regimes: from near-source, non-linear response to the far-field linear elastic region, and connecting the analyses from the respective regimes. For example, near-field analysis typically involves review of kinematic response (i.e., acceleration, velocity and displacement) in the time domain and looks at various indicators (e.g., peaks, pulse duration) to facilitate comparison among events. Review of far-field data more often is based on study of response in the frequency domain to facilitate comparison of event magnitudes. To try to "bridge the gap" between approaches, we have developed a scaling law for Fourier amplitude spectra of near-field velocity histories that successfully collapses data from a wide range of yields (100 kg to 5000 kg) and range to sensors in jointed granite. Moreover, we show that we can apply this scaling law to data from a new event to accurately estimate the explosive yield of that event. This approach presents a new way of working with near-field data that will be more compatible with traditional methods of analysis of seismic data and should serve to facilitate end-to-end event analysis. The goal is that this new approach to data analysis will eventually result in improved methods for discrimination of event type (i.e., nuclear or chemical explosion, or earthquake) and magnitude.

Discrimination of Aurantii Fructus Immaturus and Fructus Poniciri Trifoliatae Immaturus by Flow Injection UV Spectroscopy (FIUV) and 1H NMR using Partial Least-squares Discriminant Analysis (PLS-DA)

USDA-ARS?s Scientific Manuscript database

Two simple fingerprinting methods, flow-injection UV spectroscopy (FIUV) and 1H nuclear magnetic resonance (NMR), for discrimination of Aurantii FructusImmaturus and Fructus Poniciri TrifoliataeImmaturususing were described. Both methods were combined with partial least-squares discriminant analysis...

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

Phillips, William Scott

This seminar presentation describes amplitude models and yield estimations that look at the data in order to inform legislation. The following points were brought forth in the summary: global models that will predict three-component amplitudes (R-T-Z) were produced; Q models match regional geology; corrected source spectra can be used for discrimination and yield estimation; three-component data increase coverage and reduce scatter in source spectral estimates; three-component efforts must include distance-dependent effects; a community effort on instrument calibration is needed.

Social Status Correlates of Reporting Racial Discrimination and Gender Discrimination among Racially Diverse Women

PubMed Central

Ro, Annie E.; Choi, Kyung-Hee

2009-01-01

The growing body of research on discrimination and health indicates a deleterious effect of discrimination on various health outcomes. However, less is known about the sociodemographic correlates of reporting racial discrimination and gender discrimination among racially diverse women. We examined the associations of social status characteristics with lifetime experiences of racial discrimination and gender discrimination using a racially-diverse sample of 754 women attending family planning clinics in Northern California (11.4% African American, 16.8% Latina, 10.1% Asian and 61.7% Caucasian). A multivariate analysis revealed that race, financial difficulty and marital status were significantly correlated with higher reports of racial discrimination, while race, education, financial difficulty and nativity were significantly correlated with gender discrimination scores. Our findings suggest that the social patterning of perceiving racial discrimination is somewhat different from that of gender discrimination. This has implications in the realm of discrimination research and applied interventions, as different forms of discrimination may have unique covariates that should be accounted for in research analysis or program design. PMID:19485231

Screening depressive symptoms in Jordanian women: evaluation of the Center for Epidemiologic Studies-Depression scale (CES-D).

PubMed

Al-Modallal, Hanan

2010-08-01

This study examined the psychometric qualities of the Center for Epidemiologic Studies-Depression scale (CES-D) in Jordanian women. Cronbach's alpha for the 20-item CES-D was .90. Factor analysis yielded three components. Four of the items had poor factor loadings and, therefore, were dropped. Cronbach's alpha for the remaining 16 items was .85. Validity testing using independent samples t-test provided evidence of discriminant validity for the 20-item and the 16-item CES-D. Attributes of the CES-D items indicated that depression status can be easily identified by clinicians. Co morbidity of depressive symptoms with physical and mental problems necessitates routine screening for depressed mood.

Classification of debtor credit status and determination amount of credit risk by using linier discriminant function

NASA Astrophysics Data System (ADS)

Aidi, Muhammad Nur; Sari, Resty Indah

2012-05-01

A decision of credit that given by bank or another creditur must have a risk and it called credit risk. Credit risk is an investor's risk of loss arising from a borrower who does not make payments as promised. The substantial of credit risk can lead to losses for the banks and the debtor. To minimize this problem need a further study to identify a potential new customer before the decision given. Identification of debtor can using various approaches analysis, one of them is by using discriminant analysis. Discriminant analysis in this study are used to classify whether belonging to the debtor's good credit or bad credit. The result of this study are two discriminant functions that can identify new debtor. Before step built the discriminant function, selection of explanatory variables should be done. Purpose of selection independent variable is to choose the variable that can discriminate the group maximally. Selection variables in this study using different test, for categoric variable selection of variable using proportion chi-square test, and stepwise discriminant for numeric variable. The result of this study are two discriminant functions that can identify new debtor. The selected variables that can discriminating two groups of debtor maximally are status of existing checking account, credit history, credit amount, installment rate in percentage of disposable income, sex, age in year, other installment plans, and number of people being liable to provide maintenance. This classification produce a classification accuracy rate is good enough, that is equal to 74,70%. Debtor classification using discriminant analysis has risk level that is small enough, and it ranged beetwen 14,992% and 17,608%. Based on that credit risk rate, using discriminant analysis on the classification of credit status can be used effectively.

Consumption value theory and the marketing of public health: an effective formative research tool.

PubMed

Nelson, Douglas G; Byus, Kent

2002-01-01

Contemporary public health requires the support and participation of its constituency. This study assesses the capacity of consumption value theory to identify the basis of this support. A telephone survey design used simple random sampling of adult residents of Cherokee County, Oklahoma. Factor analysis and stepwise discriminant analysis was used to identify and classify personal and societal level support variables. Most residents base societal level support on epistemic values. Direct services clientele base their support on positive emotional values derived from personal contact and attractive programs. Residents are curious about public health and want to know more about the health department. Where marketing the effectiveness of public health programs would yield relatively little support, marketing health promotion activities may attract public opposition. This formative research tool suggests a marketing strategy for public health practitioners.

Measuring Global Physical Health in Children with Cerebral Palsy: Illustration of a Multidimensional Bi-factor Model and Computerized Adaptive Testing

PubMed Central

Haley, Stephen M.; Ni, Pengsheng; Dumas, Helene M.; Fragala-Pinkham, Maria A.; Hambleton, Ronald K.; Montpetit, Kathleen; Bilodeau, Nathalie; Gorton, George E.; Watson, Kyle; Tucker, Carole A

2009-01-01

Purpose The purpose of this study was to apply a bi-factor model for the determination of test dimensionality and a multidimensional CAT using computer simulations of real data for the assessment of a new global physical health measure for children with cerebral palsy (CP). Methods Parent respondents of 306 children with cerebral palsy were recruited from four pediatric rehabilitation hospitals and outpatient clinics. We compared confirmatory factor analysis results across four models: (1) one-factor unidimensional; (2) two-factor multidimensional (MIRT); (3) bi-factor MIRT with fixed slopes; and (4) bi-factor MIRT with varied slopes. We tested whether the general and content (fatigue and pain) person score estimates could discriminate across severity and types of CP, and whether score estimates from a simulated CAT were similar to estimates based on the total item bank, and whether they correlated as expected with external measures. Results Confirmatory factor analysis suggested separate pain and fatigue sub-factors; all 37 items were retained in the analyses. From the bi-factor MIRT model with fixed slopes, the full item bank scores discriminated across levels of severity and types of CP, and compared favorably to external instruments. CAT scores based on 10- and 15-item versions accurately captured the global physical health scores. Conclusions The bi-factor MIRT CAT application, especially the 10- and 15-item version, yielded accurate global physical health scores that discriminated across known severity groups and types of CP, and correlated as expected with concurrent measures. The CATs have potential for collecting complex data on the physical health of children with CP in an efficient manner. PMID:19221892

A translatable predictor of human radiation exposure.

PubMed

Lucas, Joseph; Dressman, Holly K; Suchindran, Sunil; Nakamura, Mai; Chao, Nelson J; Himburg, Heather; Minor, Kerry; Phillips, Gary; Ross, Joel; Abedi, Majid; Terbrueggen, Robert; Chute, John P

2014-01-01

Terrorism using radiological dirty bombs or improvised nuclear devices is recognized as a major threat to both public health and national security. In the event of a radiological or nuclear disaster, rapid and accurate biodosimetry of thousands of potentially affected individuals will be essential for effective medical management to occur. Currently, health care providers lack an accurate, high-throughput biodosimetric assay which is suitable for the triage of large numbers of radiation injury victims. Here, we describe the development of a biodosimetric assay based on the analysis of irradiated mice, ex vivo-irradiated human peripheral blood (PB) and humans treated with total body irradiation (TBI). Interestingly, a gene expression profile developed via analysis of murine PB radiation response alone was inaccurate in predicting human radiation injury. In contrast, generation of a gene expression profile which incorporated data from ex vivo irradiated human PB and human TBI patients yielded an 18-gene radiation classifier which was highly accurate at predicting human radiation status and discriminating medically relevant radiation dose levels in human samples. Although the patient population was relatively small, the accuracy of this classifier in discriminating radiation dose levels in human TBI patients was not substantially confounded by gender, diagnosis or prior exposure to chemotherapy. We have further incorporated genes from this human radiation signature into a rapid and high-throughput chemical ligation-dependent probe amplification assay (CLPA) which was able to discriminate radiation dose levels in a pilot study of ex vivo irradiated human blood and samples from human TBI patients. Our results illustrate the potential for translation of a human genetic signature for the diagnosis of human radiation exposure and suggest the basis for further testing of CLPA as a candidate biodosimetric assay.

Multivariate classification of the infrared spectra of cell and tissue samples

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

Haaland, D.M.; Jones, H.D.; Thomas, E.V.

1997-03-01

Infrared microspectroscopy of biopsied canine lymph cells and tissue was performed to investigate the possibility of using IR spectra coupled with multivariate classification methods to classify the samples as normal, hyperplastic, or neoplastic (malignant). IR spectra were obtained in transmission mode through BaF{sub 2} windows and in reflection mode from samples prepared on gold-coated microscope slides. Cytology and histopathology samples were prepared by a variety of methods to identify the optimal methods of sample preparation. Cytospinning procedures that yielded a monolayer of cells on the BaF{sub 2} windows produced a limited set of IR transmission spectra. These transmission spectra weremore » converted to absorbance and formed the basis for a classification rule that yielded 100{percent} correct classification in a cross-validated context. Classifications of normal, hyperplastic, and neoplastic cell sample spectra were achieved by using both partial least-squares (PLS) and principal component regression (PCR) classification methods. Linear discriminant analysis applied to principal components obtained from the spectral data yielded a small number of misclassifications. PLS weight loading vectors yield valuable qualitative insight into the molecular changes that are responsible for the success of the infrared classification. These successful classification results show promise for assisting pathologists in the diagnosis of cell types and offer future potential for {ital in vivo} IR detection of some types of cancer. {copyright} {ital 1997} {ital Society for Applied Spectroscopy}« less

Neural networks using broadband spectral discriminators reduces illumination required for broccoli identification in weedy fields

NASA Astrophysics Data System (ADS)

Hahn, Federico

1996-03-01

Statistical discriminative analysis and neural networks were used to prove that crop/weed/soil discrimination by optical reflectance was feasible. The wavelengths selected as inputs on those neural networks were ten nanometers width, reducing the total collected radiation for the sensor. Spectral data collected from several farms having different weed populations were introduced to discriminant analysis. The best discriminant wavelengths were used to build a wavelength histogram which selected the three best spectral broadbands for broccoli/weed/soil discrimination. The broadbands were analyzed using a new single broadband discriminator index named the discriminative integration index, DII, and the DII values obtained were used to train a neural network. This paper introduces the index concept, its results and its use for minimizing artificial lightning requirements with broadband spectral measurements for broccoli/weed/soil discrimination.

High-efficiency organic glass scintillators

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

Feng, Patrick L.; Carlson, Joseph S.

A new family of neutron/gamma discriminating scintillators is disclosed that comprises stable organic glasses that may be melt-cast into transparent monoliths. These materials have been shown to provide light yields greater than solution-grown trans-stilbene crystals and efficient PSD capabilities when combined with 0.01 to 0.05% by weight of the total composition of a wavelength-shifting fluorophore. Photoluminescence measurements reveal fluorescence quantum yields that are 2 to 5 times greater than conventional plastic or liquid scintillator matrices, which accounts for the superior light yield of these glasses. The unique combination of high scintillation light-yields, efficient neutron/gamma PSD, and straightforward scale-up via melt-castingmore » distinguishes the developed organic glasses from existing scintillators.« less

Automated fine structure image analysis method for discrimination of diabetic retinopathy stage using conjunctival microvasculature images

PubMed Central

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

2016-01-01

The conjunctiva is a densely vascularized mucus membrane covering the sclera of the eye with a unique advantage of accessibility for direct visualization and non-invasive imaging. The purpose of this study is to apply an automated quantitative method for discrimination of different stages of diabetic retinopathy (DR) using conjunctival microvasculature images. Fine structural analysis of conjunctival microvasculature images was performed by ordinary least square regression and Fisher linear discriminant analysis. Conjunctival images between groups of non-diabetic and diabetic subjects at different stages of DR were discriminated. The automated method’s discriminate rates were higher than those determined by human observers. The method allowed sensitive and rapid discrimination by assessment of conjunctival microvasculature images and can be potentially useful for DR screening and monitoring. PMID:27446692

DNA barcoding the native flowering plants and conifers of Wales.

PubMed

de Vere, Natasha; Rich, Tim C G; Ford, Col R; Trinder, Sarah A; Long, Charlotte; Moore, Chris W; Satterthwaite, Danielle; Davies, Helena; Allainguillaume, Joel; Ronca, Sandra; Tatarinova, Tatiana; Garbett, Hannah; Walker, Kevin; Wilkinson, Mike J

2012-01-01

We present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the native Welsh flora. We have sampled multiple individuals for each species, resulting in 3304 rbcL and 2419 matK sequences. The majority of our samples (85%) are from DNA extracted from herbarium specimens. Recoverability of DNA barcodes is lower using herbarium specimens, compared to freshly collected material, mostly due to lower amplification success, but this is balanced by the increased efficiency of sampling species that have already been collected, identified, and verified by taxonomic experts. The effectiveness of the DNA barcodes for identification (level of discrimination) is assessed using four approaches: the presence of a barcode gap (using pairwise and multiple alignments), formation of monophyletic groups using Neighbour-Joining trees, and sequence similarity in BLASTn searches. These approaches yield similar results, providing relative discrimination levels of 69.4 to 74.9% of all species and 98.6 to 99.8% of genera using both markers. Species discrimination can be further improved using spatially explicit sampling. Mean species discrimination using barcode gap analysis (with a multiple alignment) is 81.6% within 10×10 km squares and 93.3% for 2×2 km squares. Our database of DNA barcodes for Welsh native flowering plants and conifers represents the most complete coverage of any national flora, and offers a valuable platform for a wide range of applications that require accurate species identification.

DNA Barcoding the Native Flowering Plants and Conifers of Wales

PubMed Central

de Vere, Natasha; Rich, Tim C. G.; Ford, Col R.; Trinder, Sarah A.; Long, Charlotte; Moore, Chris W.; Satterthwaite, Danielle; Davies, Helena; Allainguillaume, Joel; Ronca, Sandra; Tatarinova, Tatiana; Garbett, Hannah; Walker, Kevin; Wilkinson, Mike J.

2012-01-01

We present the first national DNA barcode resource that covers the native flowering plants and conifers for the nation of Wales (1143 species). Using the plant DNA barcode markers rbcL and matK, we have assembled 97.7% coverage for rbcL, 90.2% for matK, and a dual-locus barcode for 89.7% of the native Welsh flora. We have sampled multiple individuals for each species, resulting in 3304 rbcL and 2419 matK sequences. The majority of our samples (85%) are from DNA extracted from herbarium specimens. Recoverability of DNA barcodes is lower using herbarium specimens, compared to freshly collected material, mostly due to lower amplification success, but this is balanced by the increased efficiency of sampling species that have already been collected, identified, and verified by taxonomic experts. The effectiveness of the DNA barcodes for identification (level of discrimination) is assessed using four approaches: the presence of a barcode gap (using pairwise and multiple alignments), formation of monophyletic groups using Neighbour-Joining trees, and sequence similarity in BLASTn searches. These approaches yield similar results, providing relative discrimination levels of 69.4 to 74.9% of all species and 98.6 to 99.8% of genera using both markers. Species discrimination can be further improved using spatially explicit sampling. Mean species discrimination using barcode gap analysis (with a multiple alignment) is 81.6% within 10×10 km squares and 93.3% for 2×2 km squares. Our database of DNA barcodes for Welsh native flowering plants and conifers represents the most complete coverage of any national flora, and offers a valuable platform for a wide range of applications that require accurate species identification. PMID:22701588

Identifying Plant Part Composition of Forest Logging Residue Using Infrared Spectral Data and Linear Discriminant Analysis

PubMed Central

Acquah, Gifty E.; Via, Brian K.; Billor, Nedret; Fasina, Oladiran O.; Eckhardt, Lori G.

2016-01-01

As new markets, technologies and economies evolve in the low carbon bioeconomy, forest logging residue, a largely untapped renewable resource will play a vital role. The feedstock can however be variable depending on plant species and plant part component. This heterogeneity can influence the physical, chemical and thermochemical properties of the material, and thus the final yield and quality of products. Although it is challenging to control compositional variability of a batch of feedstock, it is feasible to monitor this heterogeneity and make the necessary changes in process parameters. Such a system will be a first step towards optimization, quality assurance and cost-effectiveness of processes in the emerging biofuel/chemical industry. The objective of this study was therefore to qualitatively classify forest logging residue made up of different plant parts using both near infrared spectroscopy (NIRS) and Fourier transform infrared spectroscopy (FTIRS) together with linear discriminant analysis (LDA). Forest logging residue harvested from several Pinus taeda (loblolly pine) plantations in Alabama, USA, were classified into three plant part components: clean wood, wood and bark and slash (i.e., limbs and foliage). Five-fold cross-validated linear discriminant functions had classification accuracies of over 96% for both NIRS and FTIRS based models. An extra factor/principal component (PC) was however needed to achieve this in FTIRS modeling. Analysis of factor loadings of both NIR and FTIR spectra showed that, the statistically different amount of cellulose in the three plant part components of logging residue contributed to their initial separation. This study demonstrated that NIR or FTIR spectroscopy coupled with PCA and LDA has the potential to be used as a high throughput tool in classifying the plant part makeup of a batch of forest logging residue feedstock. Thus, NIR/FTIR could be employed as a tool to rapidly probe/monitor the variability of forest biomass so that the appropriate online adjustments to parameters can be made in time to ensure process optimization and product quality. PMID:27618901

Cross-modal transfer of the conditioned eyeblink response during interstimulus interval discrimination training in young rats

PubMed Central

Brown, Kevin L.; Stanton, Mark E.

2008-01-01

Eyeblink classical conditioning (EBC) was observed across a broad developmental period with tasks utilizing two interstimulus intervals (ISIs). In ISI discrimination, two distinct conditioned stimuli (CSs; light and tone) are reinforced with a periocular shock unconditioned stimulus (US) at two different CS-US intervals. Temporal uncertainty is identical in design with the exception that the same CS is presented at both intervals. Developmental changes in conditioning have been reported in each task beyond ages when single-ISI learning is well developed. The present study sought to replicate and extend these previous findings by testing each task at four separate ages. Consistent with previous findings, younger rats (postnatal day – PD - 23 and 30) trained in ISI discrimination showed evidence of enhanced cross-modal influence of the short CS-US pairing upon long CS conditioning relative to older subjects. ISI discrimination training at PD43-47 yielded outcomes similar to those in adults (PD65-71). Cross-modal transfer effects in this task therefore appear to diminish between PD30 and PD43-47. Comparisons of ISI discrimination with temporal uncertainty indicated that cross-modal transfer in ISI discrimination at the youngest ages did not represent complete generalization across CSs. ISI discrimination undergoes a more protracted developmental emergence than single-cue EBC and may be a more sensitive indicator of developmental disorders involving cerebellar dysfunction. PMID:18726989

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses

PubMed Central

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-01-01

Background Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. Methods A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Results Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12–0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Conclusion Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ. PMID:27660543

Psychometric Properties of the Heart Disease Knowledge Scale: Evidence from Item and Confirmatory Factor Analyses.

PubMed

Lim, Bee Chiu; Kueh, Yee Cheng; Arifin, Wan Nor; Ng, Kok Huan

2016-07-01

Heart disease knowledge is an important concept for health education, yet there is lack of evidence on proper validated instruments used to measure levels of heart disease knowledge in the Malaysian context. A cross-sectional, survey design was conducted to examine the psychometric properties of the adapted English version of the Heart Disease Knowledge Questionnaire (HDKQ). Using proportionate cluster sampling, 788 undergraduate students at Universiti Sains Malaysia, Malaysia, were recruited and completed the HDKQ. Item analysis and confirmatory factor analysis (CFA) were used for the psychometric evaluation. Construct validity of the measurement model was included. Most of the students were Malay (48%), female (71%), and from the field of science (51%). An acceptable range was obtained with respect to both the difficulty and discrimination indices in the item analysis results. The difficulty index ranged from 0.12-0.91 and a discrimination index of ≥ 0.20 were reported for the final retained 23 items. The final CFA model showed an adequate fit to the data, yielding a 23-item, one-factor model [weighted least squares mean and variance adjusted scaled chi-square difference = 1.22, degrees of freedom = 2, P-value = 0.544, the root mean square error of approximation = 0.03 (90% confidence interval = 0.03, 0.04); close-fit P-value = > 0.950]. Adequate psychometric values were obtained for Malaysian undergraduate university students using the 23-item, one-factor model of the adapted HDKQ.

Dissection of genotype × environment interactions for mucilage and seed yield in Plantago species: Application of AMMI and GGE biplot analyses

PubMed Central

Shahriari, Zolfaghar; Dadkhodaie, Ali

2018-01-01

Genotype × environment interaction (GEI) is an important aspect of both plant breeding and the successful introduction of new cultivars. In the present study, additive main effects and multiplicative interactions (AMMI) and genotype (G) main effects and genotype (G) × environment (E) interaction (GGE) biplot analyses were used to identify stable genotypes and to dissect GEI in Plantago. In total, 10 managed field trials were considered as environments to analyze GEI in thirty genotypes belonging to eight Plantago species. Genotypes were evaluated in a drought stress treatment and in normal irrigation conditions at two locations in Shiraz (Bajgah) for three years (2013-2014- 2015) and Kooshkak (Marvdasht, Fars, Iran) for two years (2014–2015). Three traits, seed yield and mucilage yield and content, were measured at each experimental site and in natural Plantago habitats. AMMI2 biplot analyses identified genotypes from several species with higher stability for seed yield and other genotypes with stable mucilage content and yield. P. lanceolata (G26), P. officinalis (G10), P. ovata (G14), P. ampleexcaulis (G11) and P. major (G4) had higher stability for seed yield. For mucilage yield, G21, G18 and G20 (P. psyllium), G1, G2 and G4 (P. major), G9 and G10 (P. officinalis) and P. lanceolata were identified as stable. G13 (P. ovata), G5 and G6 (P. major) and G30 (P. lagopus) had higher stability for mucilage content. No one genotype was found to have high levels of stability for more than one trait but some species had more than one genotype exhibiting stable trait performance. Based on trait variation, GGE biplot analysis identified two representative environments, one for seed yield and one for mucilage yield and content, with good discriminating ability. The identification of stable genotypes and representative environments should assist the breeding of new Plantago cultivars. PMID:29715274

Dissection of genotype × environment interactions for mucilage and seed yield in Plantago species: Application of AMMI and GGE biplot analyses.

PubMed

Shahriari, Zolfaghar; Heidari, Bahram; Dadkhodaie, Ali

2018-01-01

Genotype × environment interaction (GEI) is an important aspect of both plant breeding and the successful introduction of new cultivars. In the present study, additive main effects and multiplicative interactions (AMMI) and genotype (G) main effects and genotype (G) × environment (E) interaction (GGE) biplot analyses were used to identify stable genotypes and to dissect GEI in Plantago. In total, 10 managed field trials were considered as environments to analyze GEI in thirty genotypes belonging to eight Plantago species. Genotypes were evaluated in a drought stress treatment and in normal irrigation conditions at two locations in Shiraz (Bajgah) for three years (2013-2014- 2015) and Kooshkak (Marvdasht, Fars, Iran) for two years (2014-2015). Three traits, seed yield and mucilage yield and content, were measured at each experimental site and in natural Plantago habitats. AMMI2 biplot analyses identified genotypes from several species with higher stability for seed yield and other genotypes with stable mucilage content and yield. P. lanceolata (G26), P. officinalis (G10), P. ovata (G14), P. ampleexcaulis (G11) and P. major (G4) had higher stability for seed yield. For mucilage yield, G21, G18 and G20 (P. psyllium), G1, G2 and G4 (P. major), G9 and G10 (P. officinalis) and P. lanceolata were identified as stable. G13 (P. ovata), G5 and G6 (P. major) and G30 (P. lagopus) had higher stability for mucilage content. No one genotype was found to have high levels of stability for more than one trait but some species had more than one genotype exhibiting stable trait performance. Based on trait variation, GGE biplot analysis identified two representative environments, one for seed yield and one for mucilage yield and content, with good discriminating ability. The identification of stable genotypes and representative environments should assist the breeding of new Plantago cultivars.

Label consistent K-SVD: learning a discriminative dictionary for recognition.

PubMed

Jiang, Zhuolin; Lin, Zhe; Davis, Larry S

2013-11-01

A label consistent K-SVD (LC-KSVD) algorithm to learn a discriminative dictionary for sparse coding is presented. In addition to using class labels of training data, we also associate label information with each dictionary item (columns of the dictionary matrix) to enforce discriminability in sparse codes during the dictionary learning process. More specifically, we introduce a new label consistency constraint called "discriminative sparse-code error" and combine it with the reconstruction error and the classification error to form a unified objective function. The optimal solution is efficiently obtained using the K-SVD algorithm. Our algorithm learns a single overcomplete dictionary and an optimal linear classifier jointly. The incremental dictionary learning algorithm is presented for the situation of limited memory resources. It yields dictionaries so that feature points with the same class labels have similar sparse codes. Experimental results demonstrate that our algorithm outperforms many recently proposed sparse-coding techniques for face, action, scene, and object category recognition under the same learning conditions.

Discrimination and Reliance on Conceptual Fluency Cues are Inversely Related in Patients with Mild Alzheimer’s Disease

PubMed Central

Wolk, David A.; Gold, Carl A.; Signoff, Eric D.; Budson, Andrew E.

2009-01-01

Prior work suggests that patients with mild Alzheimer’s disease (AD) often base their recognition memory decisions on familiarity. It has been argued that conceptual fluency may play an important role in the feeling of familiarity. In the present study we measured the effect of conceptual fluency manipulations on recognition judgments of patients with mild AD and older adult controls. “Easy” and “hard” test conditions were created by manipulating encoding depth and list length to yield high and low discrimination, respectively. When the two participant groups performed identical procedures, AD patients displayed lower discrimination and greater reliance on fluency cues than controls. However, when the discrimination of older adult controls was decreased to the level of AD patients by use of a shallow encoding task, we found that controls reliance on fluency did not statistically differ from AD patients. Furthermore, we found that increasing discrimination using shorter study lists resulted in AD patients decreasing their reliance on fluency cues to a similar extent as controls. These findings support the notion that patients with AD are able to attribute conceptual fluency to prior experience. In addition these findings suggest that discrimination and reliance on fluency cues may be inversely related in both AD patients and older adult controls. PMID:19428418

Computer-aided diagnosis of prostate cancer in the peripheral zone using multiparametric MRI

NASA Astrophysics Data System (ADS)

Niaf, Emilie; Rouvière, Olivier; Mège-Lechevallier, Florence; Bratan, Flavie; Lartizien, Carole

2012-06-01

This study evaluated a computer-assisted diagnosis (CADx) system for determining a likelihood measure of prostate cancer presence in the peripheral zone (PZ) based on multiparametric magnetic resonance (MR) imaging, including T2-weighted, diffusion-weighted and dynamic contrast-enhanced MRI at 1.5 T. Based on a feature set derived from grey-level images, including first-order statistics, Haralick features, gradient features, semi-quantitative and quantitative (pharmacokinetic modelling) dynamic parameters, four kinds of classifiers were trained and compared : nonlinear support vector machine (SVM), linear discriminant analysis, k-nearest neighbours and naïve Bayes classifiers. A set of feature selection methods based on t-test, mutual information and minimum-redundancy-maximum-relevancy criteria were also compared. The aim was to discriminate between the relevant features as well as to create an efficient classifier using these features. The diagnostic performances of these different CADx schemes were evaluated based on a receiver operating characteristic (ROC) curve analysis. The evaluation database consisted of 30 sets of multiparametric MR images acquired from radical prostatectomy patients. Using histologic sections as the gold standard, both cancer and nonmalignant (but suspicious) tissues were annotated in consensus on all MR images by two radiologists, a histopathologist and a researcher. Benign tissue regions of interest (ROIs) were also delineated in the remaining prostate PZ. This resulted in a series of 42 cancer ROIs, 49 benign but suspicious ROIs and 124 nonsuspicious benign ROIs. From the outputs of all evaluated feature selection methods on the test bench, a restrictive set of about 15 highly informative features coming from all MR sequences was discriminated, thus confirming the validity of the multiparametric approach. Quantitative evaluation of the diagnostic performance yielded a maximal area under the ROC curve (AUC) of 0.89 (0.81-0.94) for the discrimination of the malignant versus nonmalignant tissues and 0.82 (0.73-0.90) for the discrimination of the malignant versus suspicious tissues when combining the t-test feature selection approach with a SVM classifier. A preliminary comparison showed that the optimal CADx scheme mimicked, in terms of AUC, the human experts in differentiating malignant from suspicious tissues, thus demonstrating its potential for assisting cancer identification in the PZ.

Discrimination Enhancement with Transient Feature Analysis of a Graphene Chemical Sensor.

PubMed

Nallon, Eric C; Schnee, Vincent P; Bright, Collin J; Polcha, Michael P; Li, Qiliang

2016-01-19

A graphene chemical sensor is subjected to a set of structurally and chemically similar hydrocarbon compounds consisting of toluene, o-xylene, p-xylene, and mesitylene. The fractional change in resistance of the sensor upon exposure to these compounds exhibits a similar response magnitude among compounds, whereas large variation is observed within repetitions for each compound, causing a response overlap. Therefore, traditional features depending on maximum response change will cause confusion during further discrimination and classification analysis. More robust features that are less sensitive to concentration, sampling, and drift variability would provide higher quality information. In this work, we have explored the advantage of using transient-based exponential fitting coefficients to enhance the discrimination of similar compounds. The advantages of such feature analysis to discriminate each compound is evaluated using principle component analysis (PCA). In addition, machine learning-based classification algorithms were used to compare the prediction accuracies when using fitting coefficients as features. The additional features greatly enhanced the discrimination between compounds while performing PCA and also improved the prediction accuracy by 34% when using linear discrimination analysis.

Discrimination between smiling faces: Human observers vs. automated face analysis.

PubMed

Del Líbano, Mario; Calvo, Manuel G; Fernández-Martín, Andrés; Recio, Guillermo

2018-05-11

This study investigated (a) how prototypical happy faces (with happy eyes and a smile) can be discriminated from blended expressions with a smile but non-happy eyes, depending on type and intensity of the eye expression; and (b) how smile discrimination differs for human perceivers versus automated face analysis, depending on affective valence and morphological facial features. Human observers categorized faces as happy or non-happy, or rated their valence. Automated analysis (FACET software) computed seven expressions (including joy/happiness) and 20 facial action units (AUs). Physical properties (low-level image statistics and visual saliency) of the face stimuli were controlled. Results revealed, first, that some blended expressions (especially, with angry eyes) had lower discrimination thresholds (i.e., they were identified as "non-happy" at lower non-happy eye intensities) than others (especially, with neutral eyes). Second, discrimination sensitivity was better for human perceivers than for automated FACET analysis. As an additional finding, affective valence predicted human discrimination performance, whereas morphological AUs predicted FACET discrimination. FACET can be a valid tool for categorizing prototypical expressions, but is currently more limited than human observers for discrimination of blended expressions. Configural processing facilitates detection of in/congruence(s) across regions, and thus detection of non-genuine smiling faces (due to non-happy eyes). Copyright © 2018 Elsevier B.V. All rights reserved.

Temperature dependence of alpha-induced scintillation in the 1,1,4,4-tetraphenyl-1,3-butadiene wavelength shifter

NASA Astrophysics Data System (ADS)

Veloce, L. M.; Kuźniak, M.; Di Stefano, P. C. F.; Noble, A. J.; Boulay, M. G.; Nadeau, P.; Pollmann, T.; Clark, M.; Piquemal, M.; Schreiner, K.

2016-06-01

Liquid noble based particle detectors often use the organic wavelength shifter 1,1,4,4-tetraphenyl-1,3-butadiene (TPB) which shifts UV scintillation light to the visible regime, facilitating its detection, but which also can scintillate on its own. Dark matter searches based on this type of detector commonly rely on pulse-shape discrimination (PSD) for background mitigation. Alpha-induced scintillation therefore represents a possible background source in dark matter searches. The timing characteristics of this scintillation determine whether this background can be mitigated through PSD. We have therefore characterized the pulse shape and light yield of alpha induced TPB scintillation at temperatures ranging from 300 K down to 4 K, with special attention given to liquid noble gas temperatures. We find that the pulse shapes and light yield depend strongly on temperature. In addition, the significant contribution of long time constants above ~50 K provides an avenue for discrimination between alpha decay events in TPB and nuclear-recoil events in noble liquid detectors.

Electrochemical product detection of an asymmetric convective polymerase chain reaction.

PubMed

Duwensee, Heiko; Mix, Maren; Stubbe, Marco; Gimsa, Jan; Adler, Marcel; Flechsig, Gerd-Uwe

2009-10-15

For the first time, we describe the application of heated microwires for an asymmetric convective polymerase chain reaction (PCR) in a modified PCR tube in a small volume. The partly single-stranded product was labeled with the electrochemically active compound osmium tetroxide bipyridine using a partially complementary protective strand with five mismatches compared to the single-stranded product. The labeled product could be successfully detected at a gold electrode modified with a complementary single-stranded capture probe immobilized via a thiol-linker. Our simple thermo-convective PCR yielded electrochemically detectable products after only 5-10 min. A significant discrimination between complementary and non-complementary target was possible using different immobilized capture probes. The total product yield was approx. half the amount of the classical thermocycler PCR. Numerical simulations describing the thermally driven convective PCR explain the received data. Discrimination between complementary capture probes and non-complementary capture probes was performed using square-wave voltammetry. The coupling of asymmetric thermo-convective PCR with electrochemical detection is very promising for future compact DNA sensor devices.

DIFFERENTIATION OF AURANTII FRUCTUS IMMATURUS AND FRUCTUS PONICIRI TRIFOLIATAE IMMATURUS BY FLOW-INJECTION WITH ULTRAVIOLET SPECTROSCOPIC DETECTION AND PROTON NUCLEAR MAGNETIC RESONANCE USING PARTIAL LEAST-SQUARES DISCRIMINANT ANALYSIS.

PubMed

Zhang, Mengliang; Zhao, Yang; Harrington, Peter de B; Chen, Pei

2016-03-01

Two simple fingerprinting methods, flow-injection coupled to ultraviolet spectroscopy and proton nuclear magnetic resonance, were used for discriminating between Aurantii fructus immaturus and Fructus poniciri trifoliatae immaturus . Both methods were combined with partial least-squares discriminant analysis. In the flow-injection method, four data representations were evaluated: total ultraviolet absorbance chromatograms, averaged ultraviolet spectra, absorbance at 193, 205, 225, and 283 nm, and absorbance at 225 and 283 nm. Prediction rates of 100% were achieved for all data representations by partial least-squares discriminant analysis using leave-one-sample-out cross-validation. The prediction rate for the proton nuclear magnetic resonance data by partial least-squares discriminant analysis with leave-one-sample-out cross-validation was also 100%. A new validation set of data was collected by flow-injection with ultraviolet spectroscopic detection two weeks later and predicted by partial least-squares discriminant analysis models constructed by the initial data representations with no parameter changes. The classification rates were 95% with the total ultraviolet absorbance chromatograms datasets and 100% with the other three datasets. Flow-injection with ultraviolet detection and proton nuclear magnetic resonance are simple, high throughput, and low-cost methods for discrimination studies.

Advanced Signal Processing Analysis of Laser-Induced Breakdown Spectroscopy Data for the Discrimination of Obsidian Sources

DTIC Science & Technology

2012-02-09

different sources [12,13], but the analytical techniques needed for such analysis (XRD, INAA , & ICP-MS) are time consuming and require expensive...partial least-squares discriminant analysis (PLSDA) that used the SIMPLS solving method [33]. In the experi- ment design, a leave-one-sample-out (LOSO) para...REPORT Advanced signal processing analysis of laser-induced breakdown spectroscopy data for the discrimination of obsidian sources 14. ABSTRACT 16

Elemental analysis of glass by laser ablation inductively coupled plasma optical emission spectrometry (LA-ICP-OES).

PubMed

Schenk, Emily R; Almirall, José R

2012-04-10

The elemental analysis of glass evidence has been established as a powerful discrimination tool for forensic analysts. Laser ablation inductively coupled plasma optical emission spectrometry (LA-ICP-OES) has been compared to laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and energy dispersive micro X-ray fluorescence spectroscopy (μXRF/EDS) as competing instrumentation for the elemental analysis of glass. The development of a method for the forensic analysis of glass coupling laser ablation to ICP-OES is presented for the first time. LA-ICP-OES has demonstrated comparable analytical performance to LA-ICP-MS based on the use of the element menu, Al (Al I 396.15 nm), Ba (Ba II 455.40 nm), Ca (Ca II 315.88 nm), Fe (Fe II 238.20 nm), Li (Li I 670.78 nm), Mg (Mg I 285.21 nm), Sr (Sr II 407.77 nm), Ti (Ti II 368.51 nm), and Zr (Zr II 343.82 nm). The relevant figures of merit, such as precision, accuracy and sensitivity, are presented and compared to LA-ICP-MS. A set of 41 glass samples was used to assess the discrimination power of the LA-ICP-OES method in comparison to other elemental analysis techniques. This sample set consisted of several vehicle glass samples that originated from the same source (inside and outside windshield panes) and several glass samples that originated from different vehicles. Different match criteria were used and compared to determine the potential for Type I and Type II errors. It was determined that broader match criteria is more applicable to the forensic comparison of glass analysis because it can reduce the affect that micro-heterogeneity inherent in the glass fragments and a less than ideal sampling strategy can have on the interpretation of the results. Based on the test set reported here, a plus or minus four standard deviation (± 4s) match criterion yielded the lowest possibility of Type I and Type II errors. The developed LA-ICP-OES method has been shown to perform similarly to LA-ICP-MS in the discrimination among different sources of glass while offering the advantages of a lower cost of acquisition and operation of analytical instrumentation making ICP-OES a possible alternative elemental analysis method for the forensic laboratory. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

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.

Links between patterns of racial socialization and discrimination experiences and psychological adjustment: a cluster analysis.

PubMed

Ajayi, Alex A; Syed, Moin

2014-10-01

This study used a person-oriented analytic approach to identify meaningful patterns of barriers-focused racial socialization and perceived racial discrimination experiences in a sample of 295 late adolescents. Using cluster analysis, three distinct groups were identified: Low Barrier Socialization-Low Discrimination, High Barrier Socialization-Low Discrimination, and High Barrier Socialization-High Discrimination clusters. These groups were substantively unique in terms of the frequency of racial socialization messages about bias preparation and out-group mistrust its members received and their actual perceived discrimination experiences. Further, individuals in the High Barrier Socialization-High Discrimination cluster reported significantly higher depressive symptoms than those in the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. However, no differences in adjustment were observed between the Low Barrier Socialization-Low Discrimination and High Barrier Socialization-Low Discrimination clusters. Overall, the findings highlight important individual differences in how young people of color experience their race and how these differences have significant implications on psychological adjustment. Copyright © 2014 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

A proposed metabolic strategy for monitoring disease progression in Alzheimer's disease.

PubMed

Greenberg, Nicola; Grassano, Antonio; Thambisetty, Madhav; Lovestone, Simon; Legido-Quigley, Cristina

2009-04-01

A specific, sensitive and essentially non-invasive assay to diagnose and monitor Alzheimer's disease (AD) would be valuable to both clinicians and medical researchers. The aim of this study was to perform a metabonomic statistical analysis on plasma fingerprints. Objectives were to investigate novel biomarkers indicative of AD, to consider the role of bile acids as AD biomarkers and to consider whether mild cognitive impairment (MCI) is a separate disease from AD. Samples were analysed by ultraperformance liquid chromatography-MS and resulting data sets were interpreted using soft-independent modelling of class analogy statistical analysis methods. PCA models did not show any grouping of subjects by disease state. Partial least-squares discriminant analysis (PLS-DS) models yielded class separation for AD. However, as with earlier studies, model validation revealed a predictive power of Q(2)<0.5 and indicating their unsuitability for predicting disease state. Three bile acids were extracted from the data and quantified, up-regulation was observed for MCI and AD patients. PLS-DA did not support MCI being considered as a separate disease from AD with MCI patient metabolic profiles being significantly closer to AD patients than controls. This study suggested that further investigation into the lipid fraction of the metabolome may yield useful biomarkers for AD and metabolomic profiles could be used to predict disease state in a clinical setting.

Detection and characterization of glaucoma-like canine retinal tissues using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Wang, Qi; Grozdanic, Sinisa D.; Harper, Matthew M.; Hamouche, Karl; Hamouche, Nicholas; Kecova, Helga; Lazic, Tatjana; Hernandez-Merino, Elena; Yu, Chenxu

2013-06-01

Early detection of pathological changes and progression in glaucoma and other neuroretinal diseases remains a great challenge and is critical to reduce permanent structural and functional retina and optic nerve damage. Raman spectroscopy is a sensitive technique that provides rapid biochemical characterization of tissues in a nondestructive and noninvasive fashion. In this study, spectroscopic analysis was conducted on the retinal tissues of seven beagles with acute elevation of intraocular pressure (AEIOP), six beagles with compressive optic neuropathy (CON), and five healthy beagles. Spectroscopic markers were identified associated with the different neuropathic conditions. Furthermore, the Raman spectra were subjected to multivariate discriminate analysis to classify independent tissue samples into diseased/healthy categories. The multivariate discriminant model yielded an average optimal classification accuracy of 72.6% for AEIOP and 63.4% for CON with 20 principal components being used that accounted for 87% of the total variance in the data set. A strong correlation (R2>0.92) was observed between pattern electroretinography characteristics of AEIOP dogs and Raman separation distance that measures the separation of spectra of diseased tissues from normal tissues; however, the underlining mechanism of this correlation remains to be understood. Since AEIOP mimics the pathological symptoms of acute/early-stage glaucoma, it was demonstrated that Raman spectroscopic screening has the potential to become a powerful tool for the detection and characterization of early-stage disease.

Alcohol use and the Traveller community in the west of Ireland.

PubMed

Van Hout, Marie Claire

2010-01-01

The Traveller community as ethnic minority is vulnerable to problematic alcohol use, because of social exclusion, discrimination, lack of awareness and difficulties in engaging with addiction treatment protocols. This research yielded an exploratory account of Travellers and alcohol use according to the perspectives of the Travellers and key service providers in the west of Ireland, within the context of a large-scale study on Travellers and substance use. The research consisted of 12 peer-accompanied focus groups of Traveller men and women (n = 57) and 45 semistructured interviews with a self-selecting sample of key service agencies. The research themes related to Traveller culture and alcohol use, sex differences, reasons for consuming alcohol, attitude to alcohol use, problematic alcohol use, levels of alcohol harm-related knowledge, perceptions of alcohol-related risk and experiences of addiction services. A thematic analysis of the information garnered guided this comparative analysis. The Traveller community, and in particular Traveller men, are presenting with increasingly problematic alcohol use, because of dissipation of their culture and their experiences of marginalisation, discrimination, depression, illiteracy and poverty. Difficulties engaging with law enforcement, community health and addiction services compromise their efforts to deal with this problem and home detoxification attempts are common. Services must aim to take into consideration the cultural needs of Travellers and provide appropriate educational materials, peer education programs and flexible treatment approaches for those Travellers experiencing problematic alcohol use.

Development and validation of a SYBR Green I-based real-time polymerase chain reaction method for detection of haptoglobin gene deletion in clinical materials.

PubMed

Soejima, Mikiko; Tsuchiya, Yuji; Egashira, Kouichi; Kawano, Hiroyuki; Sagawa, Kimitaka; Koda, Yoshiro

2010-06-01

Anhaptoglobinemic patients run the risk of severe anaphylactic transfusion reaction because they produce serum haptoglobin (Hp) antibodies. Being homozygous for the Hp gene deletion (HP(del)) is the only known cause of congenital anhaptoglobinemia, and clinical diagnosis of HP(del) before transfusion is important to prevent anaphylactic shock. We recently developed a 5'-nuclease (TaqMan) real-time polymerase chain reaction (PCR) method. A SYBR Green I-based duplex real-time PCR assay using two forward primers and a common reverse primer followed by melting curve analysis was developed to determine HP(del) zygosity in a single tube. In addition, to obviate initial DNA extraction, we examined serially diluted blood samples as PCR templates. Allelic discrimination of HP(del) yielded optimal results at blood sample dilutions of 1:64 to 1:1024. The results from 2231 blood samples were fully concordant with those obtained by the TaqMan-based real-time PCR method. The detection rate of the HP(del) allele by the SYBR Green I-based method is comparable with that using the TaqMan-based method. This method is readily applicable due to its low initial cost and analyzability using economical real-time PCR machines and is suitable for high-throughput analysis as an alternative method for allelic discrimination of HP(del).

Magnetic resonance imaging and magnetic resonance spectroscopy for detection of early Alzheimer's disease.

PubMed

Westman, Eric; Wahlund, Lars-Olof; Foy, Catherine; Poppe, Michaela; Cooper, Allison; Murphy, Declan; Spenger, Christian; Lovestone, Simon; Simmons, Andrew

2011-01-01

Alzheimer's disease is the most common form of neurodegenerative disorder and early detection is of great importance if new therapies are to be effectively administered. We have investigated whether the discrimination between early Alzheimer's disease (AD) and elderly healthy control subjects can be improved by adding magnetic resonance spectroscopy (MRS) measures to magnetic resonance imaging (MRI) measures. In this study 30 AD patients and 36 control subjects were included. High resolution T1-weighted axial magnetic resonance images were obtained from each subject. Automated regional volume segmentation and cortical thickness measures were determined for the images. 1H MRS was acquired from the hippocampus and LCModel was used for metabolic quantification. Altogether, this yielded 58 different volumetric, cortical thickness and metabolite ratio variables which were used for multivariate analysis to distinguish between subjects with AD and Healthy controls. Combining MRI and MRS measures resulted in a sensitivity of 97% and a specificity of 94% compared to using MRI or MRS measures alone (sensitivity: 87%, 76%, specificity: 86%, 83% respectively). Adding the MRS measures to the MRI measures more than doubled the positive likelihood ratio from 6 to 17. Adding MRS measures to a multivariate analysis of MRI measures resulted in significantly better classification than using MRI measures alone. The method shows strong potential for discriminating between Alzheimer's disease and controls.

An ICA-EBM-Based sEMG Classifier for Recognizing Lower Limb Movements in Individuals With and Without Knee Pathology.

PubMed

Naik, Ganesh R; Selvan, S Easter; Arjunan, Sridhar P; Acharyya, Amit; Kumar, Dinesh K; Ramanujam, Arvind; Nguyen, Hung T

2018-03-01

Surface electromyography (sEMG) data acquired during lower limb movements has the potential for investigating knee pathology. Nevertheless, a major challenge encountered with sEMG signals generated by lower limb movements is the intersubject variability, because the signals recorded from the leg or thigh muscles are contingent on the characteristics of a subject such as gait activity and muscle structure. In order to cope with this difficulty, we have designed a three-step classification scheme. First, the multichannel sEMG is decomposed into activities of the underlying sources by means of independent component analysis via entropy bound minimization. Next, a set of time-domain features, which would best discriminate various movements, are extracted from the source estimates. Finally, the feature selection is performed with the help of the Fisher score and a scree-plot-based statistical technique, prior to feeding the dimension-reduced features to the linear discriminant analysis. The investigation involves 11 healthy subjects and 11 individuals with knee pathology performing three different lower limb movements, namely, walking, sitting, and standing, which yielded an average classification accuracy of 96.1% and 86.2%, respectively. While the outcome of this study per se is very encouraging, with suitable improvement, the clinical application of such an sEMG-based pattern recognition system that distinguishes healthy and knee pathological subjects would be an attractive consequence.

Precision of coherence analysis to detect cerebral autoregulation by near-infrared spectroscopy in preterm infants

NASA Astrophysics Data System (ADS)

Hahn, Gitte Holst; Christensen, Karl Bang; Leung, Terence S.; Greisen, Gorm

2010-05-01

Coherence between spontaneous fluctuations in arterial blood pressure (ABP) and the cerebral near-infrared spectroscopy signal can detect cerebral autoregulation. Because reliable measurement depends on signals with high signal-to-noise ratio, we hypothesized that coherence is more precisely determined when fluctuations in ABP are large rather than small. Therefore, we investigated whether adjusting for variability in ABP (variabilityABP) improves precision. We examined the impact of variabilityABP within the power spectrum in each measurement and between repeated measurements in preterm infants. We also examined total monitoring time required to discriminate among infants with a simulation study. We studied 22 preterm infants (GA<30) yielding 215 10-min measurements. Surprisingly, adjusting for variabilityABP within the power spectrum did not improve the precision. However, adjusting for the variabilityABP among repeated measurements (i.e., weighting measurements with high variabilityABP in favor of those with low) improved the precision. The evidence of drift in individual infants was weak. Minimum monitoring time needed to discriminate among infants was 1.3-3.7 h. Coherence analysis in low frequencies (0.04-0.1 Hz) had higher precision and statistically more power than in very low frequencies (0.003-0.04 Hz). In conclusion, a reliable detection of cerebral autoregulation takes hours and the precision is improved by adjusting for variabilityABP between repeated measurements.

Epileptic Seizure Prediction Using Diffusion Distance and Bayesian Linear Discriminate Analysis on Intracranial EEG.

PubMed

Yuan, Shasha; Zhou, Weidong; Chen, Liyan

2018-02-01

Epilepsy is a chronic neurological disorder characterized by sudden and apparently unpredictable seizures. A system capable of forecasting the occurrence of seizures is crucial and could open new therapeutic possibilities for human health. This paper addresses an algorithm for seizure prediction using a novel feature - diffusion distance (DD) in intracranial Electroencephalograph (iEEG) recordings. Wavelet decomposition is conducted on segmented electroencephalograph (EEG) epochs and subband signals at scales 3, 4 and 5 are utilized to extract the diffusion distance. The features of all channels composing a feature vector are then fed into a Bayesian Linear Discriminant Analysis (BLDA) classifier. Finally, postprocessing procedure is applied to reduce false prediction alarms. The prediction method is evaluated on the public intracranial EEG dataset, which consists of 577.67[Formula: see text]h of intracranial EEG recordings from 21 patients with 87 seizures. We achieved a sensitivity of 85.11% for a seizure occurrence period of 30[Formula: see text]min and a sensitivity of 93.62% for a seizure occurrence period of 50[Formula: see text]min, both with the seizure prediction horizon of 10[Formula: see text]s. Our false prediction rate was 0.08/h. The proposed method yields a high sensitivity as well as a low false prediction rate, which demonstrates its potential for real-time prediction of seizures.

Discriminative power of visual attributes in dermatology.

PubMed

Giotis, Ioannis; Visser, Margaretha; Jonkman, Marcel; Petkov, Nicolai

2013-02-01

Visual characteristics such as color and shape of skin lesions play an important role in the diagnostic process. In this contribution, we quantify the discriminative power of such attributes using an information theoretical approach. We estimate the probability of occurrence of each attribute as a function of the skin diseases. We use the distribution of this probability across the studied diseases and its entropy to define the discriminative power of the attribute. The discriminative power has a maximum value for attributes that occur (or do not occur) for only one disease and a minimum value for those which are equally likely to be observed among all diseases. Verrucous surface, red and brown colors, and the presence of more than 10 lesions are among the most informative attributes. A ranking of attributes is also carried out and used together with a naive Bayesian classifier, yielding results that confirm the soundness of the proposed method. proposed measure is proven to be a reliable way of assessing the discriminative power of dermatological attributes, and it also helps generate a condensed dermatological lexicon. Therefore, it can be of added value to the manual or computer-aided diagnostic process. © 2012 John Wiley & Sons A/S.

Statistical inference for classification of RRIM clone series using near IR reflectance properties

NASA Astrophysics Data System (ADS)

Ismail, Faridatul Aima; Madzhi, Nina Korlina; Hashim, Hadzli; Abdullah, Noor Ezan; Khairuzzaman, Noor Aishah; Azmi, Azrie Faris Mohd; Sampian, Ahmad Faiz Mohd; Harun, Muhammad Hafiz

2015-08-01

RRIM clone is a rubber breeding series produced by RRIM (Rubber Research Institute of Malaysia) through "rubber breeding program" to improve latex yield and producing clones attractive to farmers. The objective of this work is to analyse measurement of optical sensing device on latex of selected clone series. The device using transmitting NIR properties and its reflectance is converted in terms of voltage. The obtained reflectance index value via voltage was analyzed using statistical technique in order to find out the discrimination among the clones. From the statistical results using error plots and one-way ANOVA test, there is an overwhelming evidence showing discrimination of RRIM 2002, RRIM 2007 and RRIM 3001 clone series with p value = 0.000. RRIM 2008 cannot be discriminated with RRIM 2014; however both of these groups are distinct from the other clones.

Application of otolith shape analysis for stock discrimination and species identification of five goby species (Perciformes: Gobiidae) in the northern Chinese coastal waters

NASA Astrophysics Data System (ADS)

Yu, Xin; Cao, Liang; Liu, Jinhu; Zhao, Bo; Shan, Xiujuan; Dou, Shuozeng

2014-09-01

We tested the use of otolith shape analysis to discriminate between species and stocks of five goby species ( Ctenotrypauchen chinensis, Odontamblyopus lacepedii, Amblychaeturichthys hexanema, Chaeturichthys stigmatias, and Acanthogobius hasta) found in northern Chinese coastal waters. The five species were well differentiated with high overall classification success using shape indices (83.7%), elliptic Fourier coefficients (98.6%), or the combination of both methods (94.9%). However, shape analysis alone was only moderately successful at discriminating among the four stocks (Liaodong Bay, LD; Bohai Bay, BH; Huanghe (Yellow) River estuary HRE, and Jiaozhou Bay, JZ stocks) of A. hasta (50%-54%) and C. stigmatias (65.7%-75.8%). For these two species, shape analysis was moderately successful at discriminating the HRE or JZ stocks from other stocks, but failed to effectively identify the LD and BH stocks. A large number of otoliths were misclassified between the HRE and JZ stocks, which are geographically well separated. The classification success for stock discrimination was higher using elliptic Fourier coefficients alone (70.2%) or in combination with shape indices (75.8%) than using only shape indices (65.7%) in C. stigmatias whereas there was little difference among the three methods for A. hasta. Our results supported the common belief that otolith shape analysis is generally more effective for interspecific identification than intraspecific discrimination. Moreover, compared with shape indices analysis, Fourier analysis improves classification success during inter- and intra-species discrimination by otolith shape analysis, although this did not necessarily always occur in all fish species.

Probabilistic cross-link analysis and experiment planning for high-throughput elucidation of protein structure.

PubMed

Ye, Xiaoduan; O'Neil, Patrick K; Foster, Adrienne N; Gajda, Michal J; Kosinski, Jan; Kurowski, Michal A; Bujnicki, Janusz M; Friedman, Alan M; Bailey-Kellogg, Chris

2004-12-01

Emerging high-throughput techniques for the characterization of protein and protein-complex structures yield noisy data with sparse information content, placing a significant burden on computation to properly interpret the experimental data. One such technique uses cross-linking (chemical or by cysteine oxidation) to confirm or select among proposed structural models (e.g., from fold recognition, ab initio prediction, or docking) by testing the consistency between cross-linking data and model geometry. This paper develops a probabilistic framework for analyzing the information content in cross-linking experiments, accounting for anticipated experimental error. This framework supports a mechanism for planning experiments to optimize the information gained. We evaluate potential experiment plans using explicit trade-offs among key properties of practical importance: discriminability, coverage, balance, ambiguity, and cost. We devise a greedy algorithm that considers those properties and, from a large number of combinatorial possibilities, rapidly selects sets of experiments expected to discriminate pairs of models efficiently. In an application to residue-specific chemical cross-linking, we demonstrate the ability of our approach to plan experiments effectively involving combinations of cross-linkers and introduced mutations. We also describe an experiment plan for the bacteriophage lambda Tfa chaperone protein in which we plan dicysteine mutants for discriminating threading models by disulfide formation. Preliminary results from a subset of the planned experiments are consistent and demonstrate the practicality of planning. Our methods provide the experimenter with a valuable tool (available from the authors) for understanding and optimizing cross-linking experiments.

PREDICTING ABUSE POTENTIAL OF STIMULANTS AND OTHER DOPAMINERGIC DRUGS: OVERVIEW AND RECOMMENDATIONS

PubMed Central

Huskinson, Sally L.; Naylor, Jennifer E.; Rowlett, James K.; Freeman, Kevin B.

2014-01-01

Examination of a drug’s abuse potential at multiple levels of analysis (molecular/cellular action, whole-organism behavior, epidemiological data) is an essential component to regulating controlled substances under the Controlled Substances Act (CSA). We reviewed studies that examined several central nervous system (CNS) stimulants, focusing on those with primarily dopaminergic actions, in drug self-administration, drug discrimination, and physical dependence. For drug self-administration and drug discrimination, we distinguished between experiments conducted with rats and nonhuman primates (NHP) to highlight the common and unique attributes of each model in the assessment of abuse potential. Our review of drug self-administration studies suggests that this procedure is important in predicting abuse potential of dopaminergic compounds, but there were many false positives. We recommended that tests to determine how reinforcing a drug is relative to a known drug of abuse may be more predictive of abuse potential than tests that yield a binary, yes-or-no classification. Several false positives also occurred with drug discrimination. With this procedure, we recommended that future research follow a standard decision-tree approach that may require examining the drug being tested for abuse potential as the training stimulus. This approach would also allow several known drugs of abuse to be tested for substitution, and this may reduce false positives. Finally, we reviewed evidence of physical dependence with stimulants and discussed the feasibility of modeling these phenomena in nonhuman animals in a rational and practical fashion. PMID:24662599

[Discrimination of Red Tide algae by fluorescence spectra and principle component analysis].

PubMed

Su, Rong-guo; Hu, Xu-peng; Zhang, Chuan-song; Wang, Xiu-lin

2007-07-01

Fluorescence discrimination technology for 11 species of the Red Tide algae at genus level was constructed by principle component analysis and non-negative least squares. Rayleigh and Raman scattering peaks of 3D fluorescence spectra were eliminated by Delaunay triangulation method. According to the results of Fisher linear discrimination, the first principle component score and the second component score of 3D fluorescence spectra were chosen as discriminant feature and the feature base was established. The 11 algae species were tested, and more than 85% samples were accurately determinated, especially for Prorocentrum donghaiense, Skeletonema costatum, Gymnodinium sp., which have frequently brought Red tide in the East China Sea. More than 95% samples were right discriminated. The results showed that the genus discriminant feature of 3D fluorescence spectra of Red Tide algae given by principle component analysis could work well.

Fast discrimination of hydroxypropyl methyl cellulose using portable Raman spectrometer and multivariate methods

NASA Astrophysics Data System (ADS)

Song, Biao; Lu, Dan; Peng, Ming; Li, Xia; Zou, Ye; Huang, Meizhen; Lu, Feng

2017-02-01

Raman spectroscopy is developed as a fast and non-destructive method for the discrimination and classification of hydroxypropyl methyl cellulose (HPMC) samples. 44 E series and 41 K series of HPMC samples are measured by a self-developed portable Raman spectrometer (Hx-Raman) which is excited by a 785 nm diode laser and the spectrum range is 200-2700 cm-1 with a resolution (FWHM) of 6 cm-1. Multivariate analysis is applied for discrimination of E series from K series. By methods of principal components analysis (PCA) and Fisher discriminant analysis (FDA), a discrimination result with sensitivity of 90.91% and specificity of 95.12% is achieved. The corresponding receiver operating characteristic (ROC) is 0.99, indicting the accuracy of the predictive model. This result demonstrates the prospect of portable Raman spectrometer for rapid, non-destructive classification and discrimination of E series and K series samples of HPMC.

Declining Bias and Gender Wage Discrimination? A Meta-Regression Analysis

ERIC Educational Resources Information Center

Jarrell, Stephen B.; Stanley, T. D.

2004-01-01

The meta-regression analysis reveals that there is a strong tendency for discrimination estimates to fall and wage discrimination exist against the woman. The biasing effect of researchers' gender of not correcting for selection bias has weakened and changes in labor market have made it less important.

From Equal to Equivalent Pay: Salary Discrimination in Academia

ERIC Educational Resources Information Center

Greenfield, Ester

1977-01-01

Examines the federal statutes barring sex discrimination in employment and argues that the work of any two professors is comparable but not equal. Suggests using regression analysis to prove salary discrimination and discusses the legal justification for adopting regression analysis and the standard of comparable pay for comparable work.…

Perceived Discrimination and Health: A Meta-Analytic Review

ERIC Educational Resources Information Center

Pascoe, Elizabeth A.; Richman, Laura Smart

2009-01-01

Perceived discrimination has been studied with regard to its impact on several types of health effects. This meta-analysis provides a comprehensive account of the relationships between multiple forms of perceived discrimination and both mental and physical health outcomes. In addition, this meta-analysis examines potential mechanisms by which…

The platinum microelectrode/Nafion interface - An electrochemical impedance spectroscopic analysis of oxygen reduction kinetics and Nafion characteristics

NASA Technical Reports Server (NTRS)

Parthasarathy, Arvind; Dave, Bhasker; Srinivasan, Supramaniam; Appleby, John A.; Martin, Charles R.

1992-01-01

The objectives of this study were to use electrochemical impedance spectroscopy (EIS) to study the oxygen-reduction reaction under lower humidification conditions than previously studied. The EIS technique permits the discrimination of electrode kinetics of oxygen reduction, mass transport of O2 in the membrane, and the electrical characteristics of the membrane. Electrode-kinetic parameters for the oxygen-reduction reaction, corrosion current densities for Pt, and double-layer capacitances were calculated. The production of water due to electrochemical reduction of oxygen greatly influenced the EIS response and the electrode kinetics at the Pt/Nafion interface. From the finite-length Warburg behavior, a measure of the diffusion coefficient of oxygen in Nafion and diffusion-layer thickness was obtained. An analysis of the EIS data in the high-frequency domain yielded membrane and interfacial characteristics such as ionic conductivity of the membrane, membrane grain-boundary capacitance and resistance, and uncompensated resistance.

Chemometric classification of Chinese lager beers according to manufacturer based on data fusion of fluorescence, UV and visible spectroscopies.

PubMed

Tan, Jin; Li, Rong; Jiang, Zi-Tao

2015-10-01

We report an application of data fusion for chemometric classification of 135 canned samples of Chinese lager beers by manufacturer based on the combination of fluorescence, UV and visible spectroscopies. Right-angle synchronous fluorescence spectra (SFS) at three wavelength difference Δλ=30, 60 and 80 nm and visible spectra in the range 380-700 nm of undiluted beers were recorded. UV spectra in the range 240-400 nm of diluted beers were measured. A classification model was built using principal component analysis (PCA) and linear discriminant analysis (LDA). LDA with cross-validation showed that the data fusion could achieve 78.5-86.7% correct classification (sensitivity), while those rates using individual spectroscopies ranged from 42.2% to 70.4%. The results demonstrated that the fluorescence, UV and visible spectroscopies complemented each other, yielding higher synergic effect. Copyright © 2015 Elsevier Ltd. All rights reserved.

Examining the Psychometric Properties of the Family Accommodation Scale-Parent-Report (FAS-PR)

PubMed Central

Sapyta, Jeffrey; Garcia, Abbe; Freeman, Jennifer B.; Franklin, Martin E.; Foa, Edna; March, John

2011-01-01

Growing research has examined parental accommodation among the families of children with obsessive-compulsive disorder (OCD). However, these studies have utilized a parent-report (PR) version of a measure, the Family Accommodation Scale (FAS) that has never received proper psychometric validation. In turn, previously derived subscales have been developed via clinical rather than empirical evidence. This study aims to conduct a comprehensive psychometric analysis of the FAS-PR utilizing data collected from 96 youths with OCD. Exploratory factors analysis was conducted and revealed a 12-item scale yielding two separate, yet related subscales, Avoidance of Triggers (AT) and Involvement in Compulsions (IC). Subsequent analyses revealed good internal consistency and convergent and discriminant validity. These findings suggest that future research should seek to examine factors that may impact various facets to accommodation as well as the role these facets plays in predicting treatment outcome. Limitations are discussed. PMID:21743772

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

NASA Astrophysics Data System (ADS)

Akerib, D. S.; Alsum, S.; Araújo, H. M.; Bai, X.; Bailey, A. J.; Balajthy, J.; Beltrame, P.; Bernard, E. P.; Bernstein, A.; Biesiadzinski, T. P.; Boulton, E. M.; Brás, P.; Byram, D.; Cahn, S. B.; Carmona-Benitez, M. C.; Chan, C.; Currie, A.; Cutter, J. E.; Davison, T. J. R.; Dobi, A.; Dobson, J. E. Y.; Druszkiewicz, E.; Edwards, B. N.; Faham, C. H.; Fallon, S. R.; Fan, A.; Fiorucci, S.; Gaitskell, R. J.; Gehman, V. M.; Genovesi, J.; Ghag, C.; Gilchriese, M. G. D.; Hall, C. R.; Hanhardt, M.; Haselschwardt, S. J.; Hertel, S. A.; Hogan, D. P.; Horn, M.; Huang, D. Q.; Ignarra, C. M.; Jacobsen, R. G.; Ji, W.; Kamdin, K.; Kazkaz, K.; Khaitan, D.; Knoche, R.; Larsen, N. A.; Lee, C.; Lenardo, B. G.; Lesko, K. T.; Lindote, A.; Lopes, M. I.; Manalaysay, A.; Mannino, R. L.; Marzioni, M. F.; McKinsey, D. N.; Mei, D.-M.; Mock, J.; Moongweluwan, M.; Morad, J. A.; Murphy, A. St. J.; Nehrkorn, C.; Nelson, H. N.; Neves, F.; O'Sullivan, K.; Oliver-Mallory, K. C.; Palladino, K. J.; Pease, E. K.; Reichhart, L.; Rhyne, C.; Shaw, S.; Shutt, T. A.; Silva, C.; Solmaz, M.; Solovov, V. N.; Sorensen, P.; Sumner, T. J.; Szydagis, M.; Taylor, D. J.; Taylor, W. C.; Tennyson, B. P.; Terman, P. A.; Tiedt, D. R.; To, W. H.; Tripathi, M.; Tvrznikova, L.; Uvarov, S.; Velan, V.; Verbus, J. R.; Webb, R. C.; White, J. T.; Whitis, T. J.; Witherell, M. S.; Wolfs, F. L. H.; Xu, J.; Yazdani, K.; Young, S. K.; Zhang, C.; LUX Collaboration

2018-05-01

The LUX experiment has performed searches for dark-matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived from 1.4 ×104 kg days of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.

A general protocol for creating high-throughput screening assays for reaction yield and enantiomeric excess applied to hydrobenzoin

PubMed Central

Shabbir, Shagufta H.; Regan, Clinton J.; Anslyn, Eric V.

2009-01-01

A general approach to high-throughput screening of enantiomeric excess (ee) and concentration was developed by using indicator displacement assays (IDAs), and the protocol was then applied to the vicinal diol hydrobenzoin. The method involves the sequential utilization of what we define herein as screening, training, and analysis plates. Several enantioselective boronic acid-based receptors were screened by using 96-well plates, both for their ability to discriminate the enantiomers of hydrobenzoin and to find their optimal pairing with indicators resulting in the largest optical responses. The best receptor/indicator combination was then used to train an artificial neural network to determine concentration and ee. To prove the practicality of the developed protocol, analysis plates were created containing true unknown samples of hydrobenzoin generated by established Sharpless asymmetric dihydroxylation reactions, and the best ligand was correctly identified. PMID:19332790

Development and validation of the Alcohol Myopia Scale.

PubMed

Lac, Andrew; Berger, Dale E

2013-09-01

Alcohol myopia theory conceptualizes the ability of alcohol to narrow attention and how this demand on mental resources produces the impairments of self-inflation, relief, and excess. The current research was designed to develop and validate a scale based on this framework. People who were alcohol users rated items representing myopic experiences arising from drinking episodes in the past month. In Study 1 (N = 260), the preliminary 3-factor structure was supported by exploratory factor analysis. In Study 2 (N = 289), the 3-factor structure was substantiated with confirmatory factor analysis, and it was superior in fit to an empirically indefensible 1-factor structure. The final 14-item scale was evaluated with internal consistency reliability, discriminant validity, convergent validity, criterion validity, and incremental validity. The alcohol myopia scale (AMS) illuminates conceptual underpinnings of this theory and yields insights for understanding the tunnel vision that arises from intoxication.

Molecular recognition and self-assembly special feature: A general protocol for creating high-throughput screening assays for reaction yield and enantiomeric excess applied to hydrobenzoin.

PubMed

Shabbir, Shagufta H; Regan, Clinton J; Anslyn, Eric V

2009-06-30

A general approach to high-throughput screening of enantiomeric excess (ee) and concentration was developed by using indicator displacement assays (IDAs), and the protocol was then applied to the vicinal diol hydrobenzoin. The method involves the sequential utilization of what we define herein as screening, training, and analysis plates. Several enantioselective boronic acid-based receptors were screened by using 96-well plates, both for their ability to discriminate the enantiomers of hydrobenzoin and to find their optimal pairing with indicators resulting in the largest optical responses. The best receptor/indicator combination was then used to train an artificial neural network to determine concentration and ee. To prove the practicality of the developed protocol, analysis plates were created containing true unknown samples of hydrobenzoin generated by established Sharpless asymmetric dihydroxylation reactions, and the best ligand was correctly identified.

Cross-validating a bidimensional mathematics anxiety scale.

PubMed

Haiyan Bai

2011-03-01

The psychometric properties of a 14-item bidimensional Mathematics Anxiety Scale-Revised (MAS-R) were empirically cross-validated with two independent samples consisting of 647 secondary school students. An exploratory factor analysis on the scale yielded strong construct validity with a clear two-factor structure. The results from a confirmatory factor analysis indicated an excellent model-fit (χ(2) = 98.32, df = 62; normed fit index = .92, comparative fit index = .97; root mean square error of approximation = .04). The internal consistency (.85), test-retest reliability (.71), interfactor correlation (.26, p < .001), and positive discrimination power indicated that MAS-R is a psychometrically reliable and valid instrument for measuring mathematics anxiety. Math anxiety, as measured by MAS-R, correlated negatively with student achievement scores (r = -.38), suggesting that MAS-R may be a useful tool for classroom teachers and other educational personnel tasked with identifying students at risk of reduced math achievement because of anxiety.

Method for phosphorothioate antisense DNA sequencing by capillary electrophoresis with UV detection.

PubMed

Froim, D; Hopkins, C E; Belenky, A; Cohen, A S

1997-11-01

The progress of antisense DNA therapy demands development of reliable and convenient methods for sequencing short single-stranded oligonucleotides. A method of phosphorothioate antisense DNA sequencing analysis using UV detection coupled to capillary electrophoresis (CE) has been developed based on a modified chain termination sequencing method. The proposed method reduces the sequencing cost since it uses affordable CE-UV instrumentation and requires no labeling with minimal sample processing before analysis. Cycle sequencing with ThermoSequenase generates quantities of sequencing products that are readily detectable by UV. Discrimination of undesired components from sequencing products in the reaction mixture, previously accomplished by fluorescent or radioactive labeling, is now achieved by bringing concentrations of undesired components below the UV detection range which yields a 'clean', well defined sequence. UV detection coupled with CE offers additional conveniences for sequencing since it can be accomplished with commercially available CE-UV equipment and is readily amenable to automation.

Method for phosphorothioate antisense DNA sequencing by capillary electrophoresis with UV detection.

PubMed Central

Froim, D; Hopkins, C E; Belenky, A; Cohen, A S

1997-01-01

The progress of antisense DNA therapy demands development of reliable and convenient methods for sequencing short single-stranded oligonucleotides. A method of phosphorothioate antisense DNA sequencing analysis using UV detection coupled to capillary electrophoresis (CE) has been developed based on a modified chain termination sequencing method. The proposed method reduces the sequencing cost since it uses affordable CE-UV instrumentation and requires no labeling with minimal sample processing before analysis. Cycle sequencing with ThermoSequenase generates quantities of sequencing products that are readily detectable by UV. Discrimination of undesired components from sequencing products in the reaction mixture, previously accomplished by fluorescent or radioactive labeling, is now achieved by bringing concentrations of undesired components below the UV detection range which yields a 'clean', well defined sequence. UV detection coupled with CE offers additional conveniences for sequencing since it can be accomplished with commercially available CE-UV equipment and is readily amenable to automation. PMID:9336449

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

PubMed

Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

2015-01-01

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

Discrimination Learning in Paramecia (P. Caudatum)

ERIC Educational Resources Information Center

Armus, Harvard L.; Montgomery, Amber R.; Jellison, Jenny L.

2006-01-01

Previous attempts to condition a 1-celled organism, paramecium, by either classical or instrumental procedures, have yielded equivocal results. The present experiments were designed to determine whether the use of positive reinforcement provided by DC electrical stimulation at the cathode, which had previously been shown to be attractive to…

Hydrology team

NASA Technical Reports Server (NTRS)

Ragan, R.

1982-01-01

General problems faced by hydrologists when using historical records, real time data, statistical analysis, and system simulation in providing quantitative information on the temporal and spatial distribution of water are related to the limitations of these data. Major problem areas requiring multispectral imaging-based research to improve hydrology models involve: evapotranspiration rates and soil moisture dynamics for large areas; the three dimensional characteristics of bodies of water; flooding in wetlands; snow water equivalents; runoff and sediment yield from ungaged watersheds; storm rainfall; fluorescence and polarization of water and its contained substances; discriminating between sediment and chlorophyll in water; role of barrier island dynamics in coastal zone processes; the relationship between remotely measured surface roughness and hydraulic roughness of land surfaces and stream networks; and modeling the runoff process.

The magnifying glass - A feature space local expansion for visual analysis. [and image enhancement

NASA Technical Reports Server (NTRS)

Juday, R. D.

1981-01-01

The Magnifying Glass Transformation (MGT) technique is proposed, as a multichannel spectral operation yielding visual imagery which is enhanced in a specified spectral vicinity, guided by the statistics of training samples. An application example is that in which the discrimination among spectral neighbors within an interactive display may be increased without altering distant object appearances or overall interpretation. A direct histogram specification technique is applied to the channels within the multispectral image so that a subset of the spectral domain occupies an increased fraction of the domain. The transformation is carried out by obtaining the training information, establishing the condition of the covariance matrix, determining the influenced solid, and initializing the lookup table. Finally, the image is transformed.

Complete Hexose Isomer Identification with Mass Spectrometry

NASA Astrophysics Data System (ADS)

Nagy, Gabe; Pohl, Nicola L. B.

2015-04-01

The first analytical method is presented for the identification and absolute configuration determination of all 24 aldohexose and 2-ketohexose isomers, including the D and L enantiomers for allose, altrose, galactose, glucose, gulose, idose, mannose, talose, fructose, psicose, sorbose, and tagatose. Two unique fixed ligand kinetic method combinations were discovered to create significant enough energetic differences to achieve chiral discrimination among all 24 hexoses. Each of these 24 hexoses yields unique ratios of a specific pair of fragment ions that allows for simultaneous determination of identification and absolute configuration. This mass spectrometric-based methodology can be readily employed for accurate identification of any isolated monosaccharide from an unknown biological source. This work provides a key step towards the goal of complete de novo carbohydrate analysis.

Contextual influence on orientation discrimination of humans and responses of neurons in V1 of alert monkeys.

PubMed

Li, W; Thier, P; Wehrhahn, C

2000-02-01

We studied the effects of various patterns as contextual stimuli on human orientation discrimination, and on responses of neurons in V1 of alert monkeys. When a target line is presented along with various contextual stimuli (masks), human orientation discrimination is impaired. For most V1 neurons, responses elicited by a line in the receptive field (RF) center are suppressed by these contextual patterns. Orientation discrimination thresholds of human observers are elevated slightly when the target line is surrounded by orthogonal lines. For randomly oriented lines, thresholds are elevated further and even more so for lines parallel to the target. Correspondingly, responses of most V1 neurons to a line are suppressed. Although contextual lines inhibit the amplitude of orientation tuning functions of most V1 neurons, they do not systematically alter the tuning width. Elevation of human orientation discrimination thresholds decreases with increasing curvature of masking lines, so does the inhibition of V1 neuronal responses. A mask made of straight lines yields the strongest interference with human orientation discrimination and produces the strongest suppression of neuronal responses. Elevation of human orientation discrimination thresholds is highest when a mask covers only the immediate vicinity of the target line. Increasing the masking area results in less interference. On the contrary, suppression of neuronal responses in V1 increases with increasing mask size. Our data imply that contextual interference observed in human orientation discrimination is in part directly related to contextual inhibition of neuronal activity in V1. However, the finding that interference with orientation discrimination is weaker for larger masks suggests a figure-ground segregation process that is not located in V1.

Neural mechanisms of coarse-to-fine discrimination in the visual cortex.

PubMed

Purushothaman, Gopathy; Chen, Xin; Yampolsky, Dmitry; Casagrande, Vivien A

2014-12-01

Vision is a dynamic process that refines the spatial scale of analysis over time, as evidenced by a progressive improvement in the ability to detect and discriminate finer details. To understand coarse-to-fine discrimination, we studied the dynamics of spatial frequency (SF) response using reverse correlation in the primary visual cortex (V1) of the primate. In a majority of V1 cells studied, preferred SF either increased monotonically with time (group 1) or changed nonmonotonically, with an initial increase followed by a decrease (group 2). Monotonic shift in preferred SF occurred with or without an early suppression at low SFs. Late suppression at high SFs always accompanied nonmonotonic SF dynamics. Bayesian analysis showed that SF discrimination performance and best discriminable SF frequencies changed with time in different ways in the two groups of neurons. In group 1 neurons, SF discrimination performance peaked on both left and right flanks of the SF tuning curve at about the same time. In group 2 neurons, peak discrimination occurred on the right flank (high SFs) later than on the left flank (low SFs). Group 2 neurons were also better discriminators of high SFs. We examined the relationship between the time at which SF discrimination performance peaked on either flank of the SF tuning curve and the corresponding best discriminable SFs in both neuronal groups. This analysis showed that the population best discriminable SF increased with time in V1. These results suggest neural mechanisms for coarse-to-fine discrimination behavior and that this process originates in V1 or earlier. Copyright © 2014 the American Physiological Society.

Discrimination surfaces with application to region-specific brain asymmetry analysis.

PubMed

Martos, Gabriel; de Carvalho, Miguel

2018-05-20

Discrimination surfaces are here introduced as a diagnostic tool for localizing brain regions where discrimination between diseased and nondiseased participants is higher. To estimate discrimination surfaces, we introduce a Mann-Whitney type of statistic for random fields and present large-sample results characterizing its asymptotic behavior. Simulation results demonstrate that our estimator accurately recovers the true surface and corresponding interval of maximal discrimination. The empirical analysis suggests that in the anterior region of the brain, schizophrenic patients tend to present lower local asymmetry scores in comparison with participants in the control group. Copyright © 2018 John Wiley & Sons, Ltd.

Pulse-shape discrimination and energy resolution of a liquid-argon scintillator with xenon doping

NASA Astrophysics Data System (ADS)

Wahl, C. G.; Bernard, E. P.; Lippincott, W. H.; Nikkel, J. A.; Shin, Y.; McKinsey, D. N.

2014-06-01

Liquid-argon scintillation detectors are used in fundamental physics experiments and are being considered for security applications. Previous studies have suggested that the addition of small amounts of xenon dopant improves performance in light or signal yield, energy resolution, and particle discrimination. In this study, we investigate the detector response for xenon dopant concentrations from 9 ± 5 ppm to 1100 ± 500 ppm xenon (by weight) in 6 steps. The 3.14-liter detector uses tetraphenyl butadiene (TPB) wavelength shifter with dual photomultiplier tubes and is operated in single-phase mode. Gamma-ray-interaction signal yield of 4.0 ± 0.1 photoelectrons/keV improved to 5.0 ± 0.1 photoelectrons/keV with dopant. Energy resolution at 662 keV improved from (4.4 ± 0.2)% (σ) to (3.5 ± 0.2)% (σ) with dopant. Pulse-shape discrimination performance degraded greatly at the first addition of dopant, slightly improved with additional additions, then rapidly improved near the end of our dopant range, with performance becoming slightly better than pure argon at the highest tested dopant concentration. Some evidence of reduced neutron scintillation efficiency with increasing dopant concentration was observed. Finally, the waveform shape outside the TPB region is discussed, suggesting that the contribution to the waveform from xenon-produced light is primarily in the last portion of the slow component.

Bayesian exploration for intelligent identification of textures.

PubMed

Fishel, Jeremy A; Loeb, Gerald E

2012-01-01

In order to endow robots with human-like abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control, and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac), we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness). Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median = 5) and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other cognitive problems.

Bayesian Exploration for Intelligent Identification of Textures

PubMed Central

Fishel, Jeremy A.; Loeb, Gerald E.

2012-01-01

In order to endow robots with human-like abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control, and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac), we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness). Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median = 5) and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other cognitive problems. PMID:22783186

Comparison of cranial sex determination by discriminant analysis and logistic regression.

PubMed

Amores-Ampuero, Anabel; Alemán, Inmaculada

2016-04-05

Various methods have been proposed for estimating dimorphism. The objective of this study was to compare sex determination results from cranial measurements using discriminant analysis or logistic regression. The study sample comprised 130 individuals (70 males) of known sex, age, and cause of death from San José cemetery in Granada (Spain). Measurements of 19 neurocranial dimensions and 11 splanchnocranial dimensions were subjected to discriminant analysis and logistic regression, and the percentages of correct classification were compared between the sex functions obtained with each method. The discriminant capacity of the selected variables was evaluated with a cross-validation procedure. The percentage accuracy with discriminant analysis was 78.2% for the neurocranium (82.4% in females and 74.6% in males) and 73.7% for the splanchnocranium (79.6% in females and 68.8% in males). These percentages were higher with logistic regression analysis: 85.7% for the neurocranium (in both sexes) and 94.1% for the splanchnocranium (100% in females and 91.7% in males).

Classification accuracy on the family planning participation status using kernel discriminant analysis

NASA Astrophysics Data System (ADS)

Kurniawan, Dian; Suparti; Sugito

2018-05-01

Population growth in Indonesia has increased every year. According to the population census conducted by the Central Bureau of Statistics (BPS) in 2010, the population of Indonesia has reached 237.6 million people. Therefore, to control the population growth rate, the government hold Family Planning or Keluarga Berencana (KB) program for couples of childbearing age. The purpose of this program is to improve the health of mothers and children in order to manifest prosperous society by controlling births while ensuring control of population growth. The data used in this study is the updated family data of Semarang city in 2016 that conducted by National Family Planning Coordinating Board (BKKBN). From these data, classifiers with kernel discriminant analysis will be obtained, and also classification accuracy will be obtained from that method. The result of the analysis showed that normal kernel discriminant analysis gives 71.05 % classification accuracy with 28.95 % classification error. Whereas triweight kernel discriminant analysis gives 73.68 % classification accuracy with 26.32 % classification error. Using triweight kernel discriminant for data preprocessing of family planning participation of childbearing age couples in Semarang City of 2016 can be stated better than with normal kernel discriminant.

[Research on outlier detection methods for determination of oil yield in oil shales using near-infrared spectroscopy].

PubMed

Zhang, Huai-zhu; Lin, Jun; Zhang, Huai-Zhu

2014-06-01

In the present paper, the outlier detection methods for determination of oil yield in oil shale using near-infrared (NIR) diffuse reflection spectroscopy was studied. During the quantitative analysis with near-infrared spectroscopy, environmental change and operator error will both produce outliers. The presence of outliers will affect the overall distribution trend of samples and lead to the decrease in predictive capability. Thus, the detection of outliers are important for the construction of high-quality calibration models. The methods including principal component analysis-Mahalanobis distance (PCA-MD) and resampling by half-means (RHM) were applied to the discrimination and elimination of outliers in this work. The thresholds and confidences for MD and RHM were optimized using the performance of partial least squares (PLS) models constructed after the elimination of outliers, respectively. Compared with the model constructed with the data of full spectrum, the values of RMSEP of the models constructed with the application of PCA-MD with a threshold of a value equal to the sum of average and standard deviation of MD, RHM with the confidence level of 85%, and the combination of PCA-MD and RHM, were reduced by 48.3%, 27.5% and 44.8%, respectively. The predictive ability of the calibration model has been improved effectively.

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.

Radon backgrounds in the DEAP-1 liquid-argon-based Dark Matter detector

NASA Astrophysics Data System (ADS)

Amaudruz, P.-A.; Batygov, M.; Beltran, B.; Boudjemline, K.; Boulay, M. G.; Cai, B.; Caldwell, T.; Chen, M.; Chouinard, R.; Cleveland, B. T.; Contreras, D.; Dering, K.; Duncan, F.; Ford, R.; Gagnon, R.; Giuliani, F.; Gold, M.; Golovko, V. V.; Gorel, P.; Graham, K.; Grant, D. R.; Hakobyan, R.; Hallin, A. L.; Harvey, P.; Hearns, C.; Jillings, C. J.; Kuźniak, M.; Lawson, I.; Li, O.; Lidgard, J.; Liimatainen, P.; Lippincott, W. H.; Mathew, R.; McDonald, A. B.; McElroy, T.; McFarlane, K.; McKinsey, D.; Muir, A.; Nantais, C.; Nicolics, K.; Nikkel, J.; Noble, T.; O'Dwyer, E.; Olsen, K. S.; Ouellet, C.; Pasuthip, P.; Pollmann, T.; Rau, W.; Retiere, F.; Ronquest, M.; Skensved, P.; Sonley, T.; Tang, J.; Vázquez-Jáuregui, E.; Veloce, L.; Ward, M.

2015-03-01

The DEAP-1 7 kg single phase liquid argon scintillation detector was operated underground at SNOLAB in order to test the techniques and measure the backgrounds inherent to single phase detection, in support of the DEAP-3600 Dark Matter detector. Backgrounds in DEAP are controlled through material selection, construction techniques, pulse shape discrimination, and event reconstruction. This report details the analysis of background events observed in three iterations of the DEAP-1 detector, and the measures taken to reduce them. The 222 Rn decay rate in the liquid argon was measured to be between 16 and 26 μBq kg-1. We found that the background spectrum near the region of interest for Dark Matter detection in the DEAP-1 detector can be described considering events from three sources: radon daughters decaying on the surface of the active volume, the expected rate of electromagnetic events misidentified as nuclear recoils due to inefficiencies in the pulse shape discrimination, and leakage of events from outside the fiducial volume due to imperfect position reconstruction. These backgrounds statistically account for all observed events, and they will be strongly reduced in the DEAP-3600 detector due to its higher light yield and simpler geometry.

Psychometric Evaluation of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID).

PubMed

Duncan, Laura; Georgiades, Kathy; Wang, Li; Van Lieshout, Ryan J; MacMillan, Harriet L; Ferro, Mark A; Lipman, Ellen L; Szatmari, Peter; Bennett, Kathryn; Kata, Anna; Janus, Magdalena; Boyle, Michael H

2017-12-04

The goals of the study were to examine test-retest reliability, informant agreement and convergent and discriminant validity of nine DSM-IV-TR psychiatric disorders classified by parent and youth versions of the Mini International Neuropsychiatric Interview for Children and Adolescents (MINI-KID). Using samples drawn from the general population and child mental health outpatient clinics, 283 youth aged 9 to 18 years and their parents separately completed the MINI-KID with trained lay interviewers on two occasions 7 to 14 days apart. Test-retest reliability estimates based on kappa (κ) went from 0.33 to 0.79 across disorders, samples and informants. Parent-youth agreement on disorders was low (average κ = 0.20). Confirmatory factor analysis provided evidence supporting convergent and discriminant validity. The MINI-KID disorder classifications yielded estimates of test-retest reliability and validity comparable to other standardized diagnostic interviews in both general population and clinic samples. These findings, in addition to the brevity and low administration cost, make the MINI-KID a good candidate for use in epidemiological research and clinical practice. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Discriminating a deep defect from shallow acceptors in supercell calculations: gallium antisite in GaAs

NASA Astrophysics Data System (ADS)

Schultz, Peter

To make reliable first principles predictions of defect energies in semiconductors, it is crucial to discriminate between effective-mass-like defects--for which existing supercell methods fail--and deep defects--for which density functional theory calculations can yield reliable predictions of defect energy levels. The gallium antisite GaAs is often associated with the 78/203 meV shallow double acceptor in Ga-rich gallium arsenide. Within a framework of level occupation patterns, analyses of structure and spin stabilization can be used within a supercell approach to distinguish localized deep defect states from shallow acceptors such as BAs. This systematic analysis determines that the gallium antisite is inconsistent with a shallow state, and cannot be the 78/203 shallow double acceptor. The properties of the Ga antisite in GaAs are described, predicting that the Ga antisite is a deep double acceptor and has two donor states, one of which might be accidentally shallow. -- Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Company, for the U.S. Department of Energy's National Nuclear Security Administration under Contract DE-AC04-94AL85000.

Teacher stress and burnout: implications for school health personnel.

PubMed

Belcastro, P A; Gold, R S

1983-09-01

Recent literature indicates teachers experience considerable stress in the workplace, and that such stress is associated with an increased frequency of physical illnesses and somatic complaints. This study was conducted to identify the relationship between reported levels of stress and somatic complaints and selected illnesses. The Maslach Burnout Inventory and the Teacher Somatic Complaints and Illness Inventory were distributed to 428 teachers in public schools in Southern Illinois. The MBI yields data allowing classification of teachers into two groups according to degrees of work related stress. A discriminant analysis was performed to examine the ability to discriminate between these groups based on their reported patterns of somatic complaints and illnesses. More than 11% of those responding to the study were classified as burned out according to conservative criteria for classification. The conclusion that burnout represents a health risk to teachers in this study has implications for school health personnel. Since school health personnel have experience in educating people about physiological and psychological factors that threaten health, and have experience in motivating individuals to take positive action regarding their health, they can provide teachers with information and skills to cope with occupational stress.

Automatic segmentation of low-visibility moving objects through energy analyis of the local 3D spectrum

NASA Astrophysics Data System (ADS)

Nestares, Oscar; Miravet, Carlos; Santamaria, Javier; Fonolla Navarro, Rafael

1999-05-01

Automatic object segmentation in highly noisy image sequences, composed by a translating object over a background having a different motion, is achieved through joint motion-texture analysis. Local motion and/or texture is characterized by the energy of the local spatio-temporal spectrum, as different textures undergoing different translational motions display distinctive features in their 3D (x,y,t) spectra. Measurements of local spectrum energy are obtained using a bank of directional 3rd order Gaussian derivative filters in a multiresolution pyramid in space- time (10 directions, 3 resolution levels). These 30 energy measurements form a feature vector describing texture-motion for every pixel in the sequence. To improve discrimination capability and reduce computational cost, we automatically select those 4 features (channels) that best discriminate object from background, under the assumptions that the object is smaller than the background and has a different velocity or texture. In this way we reject features irrelevant or dominated by noise, that could yield wrong segmentation results. This method has been successfully applied to sequences with extremely low visibility and for objects that are even invisible for the eye in absence of motion.

The buffering role of social support on the associations among discrimination, mental health, and suicidality in a transgender sample

PubMed Central

Trujillo, Michael A.; Perrin, Paul B.; Sutter, Megan; Tabaac, Ariella; Benotsch, Eric G.

2017-01-01

INTRODUCTION Per the minority stress framework, trans individuals often experience psychological distress given the unique stress engendered by gender identity-related discrimination. Prior research has identified social support as particularly important for psychological distress and has suggested that social support may moderate this relationship. AIMS: The purpose of the current study was to explore the patterns of connections among discrimination, mental health, and suicidal ideation in trans individuals, and whether social support moderates these relationships. METHODS Participants (N = 78) completed measures of these constructs as part of a national online survey. RESULTS A series of simultaneous multiple regressions found that harassment/rejection discrimination was a unique positive predictor of mental health symptoms and suicidal ideation, with depression positively predicting suicidal ideation. A mediational model indicated that the association between harassment/rejection discrimination and suicidal ideation was fully mediated by depression. Three moderated meditational models were run, and one yielded a significant interaction, such that discrimination predicted suicidal ideation most strongly when participants had low social support from a significant other in comparison to moderate or high support. Further, conditional direct effects identified that discrimination led to ideation only for individuals with low support from friends or a significant other but not for those with moderate or high support. CONCLUSIONS Helping trans individuals cope with harassment and rejection, particularly by drawing on social support, may promote better mental health, which could help reduce suicidality in this population. PMID:29904324

The buffering role of social support on the associations among discrimination, mental health, and suicidality in a transgender sample.

PubMed

Trujillo, Michael A; Perrin, Paul B; Sutter, Megan; Tabaac, Ariella; Benotsch, Eric G

2017-01-01

Per the minority stress framework, trans individuals often experience psychological distress given the unique stress engendered by gender identity-related discrimination. Prior research has identified social support as particularly important for psychological distress and has suggested that social support may moderate this relationship. AIMS: The purpose of the current study was to explore the patterns of connections among discrimination, mental health, and suicidal ideation in trans individuals, and whether social support moderates these relationships. Participants ( N = 78) completed measures of these constructs as part of a national online survey. A series of simultaneous multiple regressions found that harassment/rejection discrimination was a unique positive predictor of mental health symptoms and suicidal ideation, with depression positively predicting suicidal ideation. A mediational model indicated that the association between harassment/rejection discrimination and suicidal ideation was fully mediated by depression. Three moderated meditational models were run, and one yielded a significant interaction, such that discrimination predicted suicidal ideation most strongly when participants had low social support from a significant other in comparison to moderate or high support. Further, conditional direct effects identified that discrimination led to ideation only for individuals with low support from friends or a significant other but not for those with moderate or high support. Helping trans individuals cope with harassment and rejection, particularly by drawing on social support, may promote better mental health, which could help reduce suicidality in this population.

[Comparison of Discriminant Analysis and Decision Trees for the Detection of Subclinical Keratoconus].

PubMed

Kleinhans, Sonja; Herrmann, Eva; Kohnen, Thomas; Bühren, Jens

2017-08-15

Background Iatrogenic keratectasia is one of the most dreaded complications of refractive surgery. In most cases, keratectasia develops after refractive surgery of eyes suffering from subclinical stages of keratoconus with few or no signs. Unfortunately, there has been no reliable procedure for the early detection of keratoconus. In this study, we used binary decision trees (recursive partitioning) to assess their suitability for discrimination between normal eyes and eyes with subclinical keratoconus. Patients and Methods The method of decision tree analysis was compared with discriminant analysis which has shown good results in previous studies. Input data were 32 eyes of 32 patients with newly diagnosed keratoconus in the contralateral eye and preoperative data of 10 eyes of 5 patients with keratectasia after laser in-situ keratomileusis (LASIK). The control group was made up of 245 normal eyes after LASIK and 12-month follow-up without any signs of iatrogenic keratectasia. Results Decision trees gave better accuracy and specificity than did discriminant analysis. The sensitivity of decision trees was lower than the sensitivity of discriminant analysis. Conclusion On the basis of the patient population of this study, decision trees did not prove to be superior to linear discriminant analysis for the detection of subclinical keratoconus. Georg Thieme Verlag KG Stuttgart · New York.

Multivariate geomorphic analysis of forest streams: Implications for assessment of land use impacts on channel condition

Treesearch

Richard. D. Wood-Smith; John M. Buffington

1996-01-01

Multivariate statistical analyses of geomorphic variables from 23 forest stream reaches in southeast Alaska result in successful discrimination between pristine streams and those disturbed by land management, specifically timber harvesting and associated road building. Results of discriminant function analysis indicate that a three-variable model discriminates 10...

Chemometric analysis for discrimination of extra virgin olive oils from whole and stoned olive pastes.

PubMed

De Luca, Michele; Restuccia, Donatella; Clodoveo, Maria Lisa; Puoci, Francesco; Ragno, Gaetano

2016-07-01

Chemometric discrimination of extra virgin olive oils (EVOO) from whole and stoned olive pastes was carried out by using Fourier transform infrared (FTIR) data and partial least squares-discriminant analysis (PLS1-DA) approach. Four Italian commercial EVOO brands, all in both whole and stoned version, were considered in this study. The adopted chemometric methodologies were able to describe the different chemical features in phenolic and volatile compounds contained in the two types of oil by using unspecific IR spectral information. Principal component analysis (PCA) was employed in cluster analysis to capture data patterns and to highlight differences between technological processes and EVOO brands. The PLS1-DA algorithm was used as supervised discriminant analysis to identify the different oil extraction procedures. Discriminant analysis was extended to the evaluation of possible adulteration by addition of aliquots of oil from whole paste to the most valuable oil from stoned olives. The statistical parameters from external validation of all the PLS models were very satisfactory, with low root mean square error of prediction (RMSEP) and relative error (RE%). Copyright © 2016 Elsevier Ltd. All rights reserved.

Agricultural resources investigations in northern Italy and southern France (Agreste Project)

NASA Technical Reports Server (NTRS)

1976-01-01

The author has identified the following significant results. The vegetation structure of rice was investigated and interpreted in dynamic terms as a significant factor governing the distribution of solar energy thoughout the canopy and therefore conditions the final yield. Radiometric characteristics of rice culture were described for various stages of development in relation to the vegetation structure in an attempt to establish correlations between data of total biomass and of grain yield. Qualitative classification results were encouraging although the discrimination achieved was far from complete.

Preliminary investigation on the relationship of Raman spectra of sheep meat with shear force and cooking loss.

PubMed

Schmidt, Heinar; Scheier, Rico; Hopkins, David L

2013-01-01

A prototype handheld Raman system was used as a rapid non-invasive optical device to measure raw sheep meat to estimate cooked meat tenderness and cooking loss. Raman measurements were conducted on m. longissimus thoracis et lumborum samples from two sheep flocks from two different origins which had been aged for five days at 3-4°C before deep freezing and further analysis. The Raman data of 140 samples were correlated with shear force and cooking loss data using PLS regression. Both sample origins could be discriminated and separate correlation models yielded better correlations than the joint correlation model. For shear force, R(2)=0.79 and R(2)=0.86 were obtained for the two sites. Results for cooking loss were comparable: separate models yielded R(2)=0.79 and R(2)=0.83 for the two sites. The results show the potential usefulness of Raman spectra which can be recorded during meat processing for the prediction of quality traits such as tenderness and cooking loss. Copyright © 2012 Elsevier Ltd. All rights reserved.

Rapid determination of chemical composition and classification of bamboo fractions using visible-near infrared spectroscopy coupled with multivariate data analysis.

PubMed

Yang, Zhong; Li, Kang; Zhang, Maomao; Xin, Donglin; Zhang, Junhua

2016-01-01

During conversion of bamboo into biofuels and chemicals, it is necessary to efficiently predict the chemical composition and digestibility of biomass. However, traditional methods for determination of lignocellulosic biomass composition are expensive and time consuming. In this work, a novel and fast method for quantitative and qualitative analysis of chemical composition and enzymatic digestibilities of juvenile bamboo and mature bamboo fractions (bamboo green, bamboo timber, bamboo yellow, bamboo node, and bamboo branch) using visible-near infrared spectra was evaluated. The developed partial least squares models yielded coefficients of determination in calibration of 0.88, 0.94, and 0.96, for cellulose, xylan, and lignin of bamboo fractions in raw spectra, respectively. After visible-near infrared spectra being pretreated, the corresponding coefficients of determination in calibration yielded by the developed partial least squares models are 0.994, 0.990, and 0.996, respectively. The score plots of principal component analysis of mature bamboo, juvenile bamboo, and different fractions of mature bamboo were obviously distinguished in raw spectra. Based on partial least squares discriminant analysis, the classification accuracies of mature bamboo, juvenile bamboo, and different fractions of bamboo (bamboo green, bamboo timber, bamboo yellow, and bamboo branch) all reached 100 %. In addition, high accuracies of evaluation of the enzymatic digestibilities of bamboo fractions after pretreatment with aqueous ammonia were also observed. The results showed the potential of visible-near infrared spectroscopy in combination with multivariate analysis in efficiently analyzing the chemical composition and hydrolysabilities of lignocellulosic biomass, such as bamboo fractions.

Support vector machine learning-based fMRI data group analysis.

PubMed

Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A

2007-07-15

To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.

Discrimination, Racial Identity, and Cytokine Levels Among African American Adolescents

PubMed Central

Brody, Gene H.; Yu, Tianyi; Miller, Gregory E.; Chen, Edith

2015-01-01

Purpose Low-grade inflammation, measured by circulating levels of cytokines, is a pathogenic mechanism for several chronic diseases of aging. Identifying factors related to inflammation among African American youths may yield insights into mechanisms underlying racial disparities in health. The purpose of the study was to determine whether (a) reported racial discrimination from ages 17 to 19 forecast heightened cytokine levels at age 22, and (b) this association is lower for youths with positive racial identities. Methods A longitudinal research design was used with a community sample of 160 African Americans who were 17 at the beginning of the study. Discrimination and racial identity were measured with questionnaires, and blood was drawn to measure basal cytokine levels. Ordinary least squares regression analyses were used to examine the hypotheses. Results After controlling for socioeconomic risk, life stress, depressive symptoms, and body mass index, racial discrimination (β = .307, p < .01), racial identity (β = −.179, p < .05), and their interaction (β = −.180, p < .05) forecast cytokine levels. Youths exposed to high levels of racial discrimination evinced elevated cytokine levels 3 years later. This association was not significant for young adults with positive racial identities. Conclusions High levels of interpersonal racial discrimination and the development of a positive racial identity operate jointly to determine low-grade inflammation levels that have been found to forecast chronic diseases of aging, such as coronary disease and stroke. PMID:25907649

Fair lineups are better than biased lineups and showups, but not because they increase underlying discriminability.

PubMed

Smith, Andrew M; Wells, Gary L; Lindsay, R C L; Penrod, Steven D

2017-04-01

Receiver Operating Characteristic (ROC) analysis has recently come in vogue for assessing the underlying discriminability and the applied utility of lineup procedures. Two primary assumptions underlie recommendations that ROC analysis be used to assess the applied utility of lineup procedures: (a) ROC analysis of lineups measures underlying discriminability, and (b) the procedure that produces superior underlying discriminability produces superior applied utility. These same assumptions underlie a recently derived diagnostic-feature detection theory, a theory of discriminability, intended to explain recent patterns observed in ROC comparisons of lineups. We demonstrate, however, that these assumptions are incorrect when ROC analysis is applied to lineups. We also demonstrate that a structural phenomenon of lineups, differential filler siphoning, and not the psychological phenomenon of diagnostic-feature detection, explains why lineups are superior to showups and why fair lineups are superior to biased lineups. In the process of our proofs, we show that computational simulations have assumed, unrealistically, that all witnesses share exactly the same decision criteria. When criterial variance is included in computational models, differential filler siphoning emerges. The result proves dissociation between ROC curves and underlying discriminability: Higher ROC curves for lineups than for showups and for fair than for biased lineups despite no increase in underlying discriminability. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Classification of EEG Signals Based on Pattern Recognition Approach.

PubMed

Amin, Hafeez Ullah; Mumtaz, Wajid; Subhani, Ahmad Rauf; Saad, Mohamad Naufal Mohamad; Malik, Aamir Saeed

2017-01-01

Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a "pattern recognition" approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature extraction such as, multi-resolution decompositions into detailed and approximate coefficients as well as relative wavelet energy were computed. Extracted relative wavelet energy features were normalized to zero mean and unit variance and then optimized using Fisher's discriminant ratio (FDR) and principal component analysis (PCA). A high density EEG dataset validated the proposed method (128-channels) by identifying two classifications: (1) EEG signals recorded during complex cognitive tasks using Raven's Advance Progressive Metric (RAPM) test; (2) EEG signals recorded during a baseline task (eyes open). Classifiers such as, K-nearest neighbors (KNN), Support Vector Machine (SVM), Multi-layer Perceptron (MLP), and Naïve Bayes (NB) were then employed. Outcomes yielded 99.11% accuracy via SVM classifier for coefficient approximations (A5) of low frequencies ranging from 0 to 3.90 Hz. Accuracy rates for detailed coefficients were 98.57 and 98.39% for SVM and KNN, respectively; and for detailed coefficients (D5) deriving from the sub-band range (3.90-7.81 Hz). Accuracy rates for MLP and NB classifiers were comparable at 97.11-89.63% and 91.60-81.07% for A5 and D5 coefficients, respectively. In addition, the proposed approach was also applied on public dataset for classification of two cognitive tasks and achieved comparable classification results, i.e., 93.33% accuracy with KNN. The proposed scheme yielded significantly higher classification performances using machine learning classifiers compared to extant quantitative feature extraction. These results suggest the proposed feature extraction method reliably classifies EEG signals recorded during cognitive tasks with a higher degree of accuracy.

Classification of EEG Signals Based on Pattern Recognition Approach

PubMed Central

Amin, Hafeez Ullah; Mumtaz, Wajid; Subhani, Ahmad Rauf; Saad, Mohamad Naufal Mohamad; Malik, Aamir Saeed

2017-01-01

Feature extraction is an important step in the process of electroencephalogram (EEG) signal classification. The authors propose a “pattern recognition” approach that discriminates EEG signals recorded during different cognitive conditions. Wavelet based feature extraction such as, multi-resolution decompositions into detailed and approximate coefficients as well as relative wavelet energy were computed. Extracted relative wavelet energy features were normalized to zero mean and unit variance and then optimized using Fisher's discriminant ratio (FDR) and principal component analysis (PCA). A high density EEG dataset validated the proposed method (128-channels) by identifying two classifications: (1) EEG signals recorded during complex cognitive tasks using Raven's Advance Progressive Metric (RAPM) test; (2) EEG signals recorded during a baseline task (eyes open). Classifiers such as, K-nearest neighbors (KNN), Support Vector Machine (SVM), Multi-layer Perceptron (MLP), and Naïve Bayes (NB) were then employed. Outcomes yielded 99.11% accuracy via SVM classifier for coefficient approximations (A5) of low frequencies ranging from 0 to 3.90 Hz. Accuracy rates for detailed coefficients were 98.57 and 98.39% for SVM and KNN, respectively; and for detailed coefficients (D5) deriving from the sub-band range (3.90–7.81 Hz). Accuracy rates for MLP and NB classifiers were comparable at 97.11–89.63% and 91.60–81.07% for A5 and D5 coefficients, respectively. In addition, the proposed approach was also applied on public dataset for classification of two cognitive tasks and achieved comparable classification results, i.e., 93.33% accuracy with KNN. The proposed scheme yielded significantly higher classification performances using machine learning classifiers compared to extant quantitative feature extraction. These results suggest the proposed feature extraction method reliably classifies EEG signals recorded during cognitive tasks with a higher degree of accuracy. PMID:29209190

Automatic Data Filter Customization Using a Genetic Algorithm

NASA Technical Reports Server (NTRS)

Mandrake, Lukas

2013-01-01

This work predicts whether a retrieval algorithm will usefully determine CO2 concentration from an input spectrum of GOSAT (Greenhouse Gases Observing Satellite). This was done to eliminate needless runtime on atmospheric soundings that would never yield useful results. A space of 50 dimensions was examined for predictive power on the final CO2 results. Retrieval algorithms are frequently expensive to run, and wasted effort defeats requirements and expends needless resources. This algorithm could be used to help predict and filter unneeded runs in any computationally expensive regime. Traditional methods such as the Fischer discriminant analysis and decision trees can attempt to predict whether a sounding will be properly processed. However, this work sought to detect a subsection of the dimensional space that can be simply filtered out to eliminate unwanted runs. LDAs (linear discriminant analyses) and other systems examine the entire data and judge a "best fit," giving equal weight to complex and problematic regions as well as simple, clear-cut regions. In this implementation, a genetic space of "left" and "right" thresholds outside of which all data are rejected was defined. These left/right pairs are created for each of the 50 input dimensions. A genetic algorithm then runs through countless potential filter settings using a JPL computer cluster, optimizing the tossed-out data s yield (proper vs. improper run removal) and number of points tossed. This solution is robust to an arbitrary decision boundary within the data and avoids the global optimization problem of whole-dataset fitting using LDA or decision trees. It filters out runs that would not have produced useful CO2 values to save needless computation. This would be an algorithmic preprocessing improvement to any computationally expensive system.

The intersectionality of discrimination attributes and bullying among youth: an applied latent class analysis.

PubMed

Garnett, Bernice Raveche; Masyn, Katherine E; Austin, S Bryn; Miller, Matthew; Williams, David R; Viswanath, Kasisomayajula

2014-08-01

Discrimination is commonly experienced among adolescents. However, little is known about the intersection of multiple attributes of discrimination and bullying. We used a latent class analysis (LCA) to illustrate the intersections of discrimination attributes and bullying, and to assess the associations of LCA membership to depressive symptoms, deliberate self harm and suicidal ideation among a sample of ethnically diverse adolescents. The data come from the 2006 Boston Youth Survey where students were asked whether they had experienced discrimination based on four attributes: race/ethnicity, immigration status, perceived sexual orientation and weight. They were also asked whether they had been bullied or assaulted for these attributes. A total of 965 (78%) students contributed to the LCA analytic sample (45% Non-Hispanic Black, 29% Hispanic, 58% Female). The LCA revealed that a 4-class solution had adequate relative and absolute fit. The 4-classes were characterized as: low discrimination (51%); racial discrimination (33%); sexual orientation discrimination (7%); racial and weight discrimination with high bullying (intersectional class) (7%). In multivariate models, compared to the low discrimination class, individuals in the sexual orientation discrimination class and the intersectional class had higher odds of engaging in deliberate self-harm. Students in the intersectional class also had higher odds of suicidal ideation. All three discrimination latent classes had significantly higher depressive symptoms compared to the low discrimination class. Multiple attributes of discrimination and bullying co-occur among adolescents. Research should consider the co-occurrence of bullying and discrimination.

Discriminant forest classification method and system

DOEpatents

Chen, Barry Y.; Hanley, William G.; Lemmond, Tracy D.; Hiller, Lawrence J.; Knapp, David A.; Mugge, Marshall J.

2012-11-06

A hybrid machine learning methodology and system for classification that combines classical random forest (RF) methodology with discriminant analysis (DA) techniques to provide enhanced classification capability. A DA technique which uses feature measurements of an object to predict its class membership, such as linear discriminant analysis (LDA) or Andersen-Bahadur linear discriminant technique (AB), is used to split the data at each node in each of its classification trees to train and grow the trees and the forest. When training is finished, a set of n DA-based decision trees of a discriminant forest is produced for use in predicting the classification of new samples of unknown class.

Efficiency of RAPD versus SSR markers for determining genetic diversity among popcorn lines.

PubMed

Leal, A A; Mangolin, C A; do Amaral, A T; Gonçalves, L S A; Scapim, C A; Mott, A S; Eloi, I B O; Cordovés, V; da Silva, M F P

2010-01-05

Using only one type of marker to quantify genetic diversity generates results that have been questioned in terms of reliability, when compared to the combined use of different markers. To compare the efficiency of the use of single versus multiple markers, we quantified genetic diversity among 10 S(7) inbred popcorn lines using both RAPD and SSR markers, and we evaluated how well these two types of markers discriminated the popcorn genotypes. These popcorn genotypes: "Yellow Pearl Popcorn" (P1-1 and P1-5), "Zélia" (P1-2 and P1-4), "Curagua" (P1-3), "IAC 112" (P9-1 and P9-2), "Avati Pichinga" (P9-3 and P9-5), and "Pisankalla" (P9-4) have different soil and climate adaptations. Using RAPD marker analysis, each primer yielded bands of variable intensities that were easily detected, as well as non-specific bands, which were discarded from the analysis. The nine primers used yielded 126 bands, of which 104 were classified as polymorphic, giving an average of 11.6 polymorphisms per primer. Using SSR procedures, the number of alleles per locus ranged from two to five, giving a total of 47 alleles for the 14 SSR loci. When comparing the groups formed using SSR and RAPD markers, there were similarities in the combinations of genotypes from the same genealogy. Correlation between genetic distances obtained through RAPD and SSR markers was relatively high (0.5453), indicating that both techniques are efficient for evaluating genetic diversity in the genotypes of popcorn that we evaluated, though RAPDs yielded more polymorphisms.

Lens-free microscopy of cerebrospinal fluid for the laboratory diagnosis of meningitis

NASA Astrophysics Data System (ADS)

Delacroix, Robin; Morel, Sophie Nhu An; Hervé, Lionel; Bordy, Thomas; Blandin, Pierre; Dinten, Jean-Marc; Drancourt, Michel; Allier, Cédric

2018-02-01

The cytology of the cerebrospinal fluid is traditionally performed by an operator (physician, biologist) by means of a conventional light microscope. The operator visually counts the leukocytes (white blood cells) present in a sample of cerebrospinal fluid (10 μl). It is a tedious job and the result is operator-dependent. Here in order to circumvent the limitations of manual counting, we approach the question of numeration of erythrocytes and leukocytes for the cytological diagnosis of meningitis by means of lens-free microscopy. In a first step, a prospective counts of leukocytes was performed by five different operators using conventional optical microscopy. The visual counting yielded an overall 16.7% misclassification of 72 cerebrospinal fluid specimens in meningitis/non-meningitis categories using a 10 leukocyte/μL cut-off. In a second step, the lens-free microscopy algorithm was adapted step-by-step for counting cerebrospinal fluid cells and discriminating leukocytes from erythrocytes. The optimization of the automatic lens-free counting was based on the prospective analysis of 215 cerebrospinal fluid specimens. The optimized algorithm yielded a 100% sensitivity and a 86% specificity compared to confirmed diagnostics. In a third step, a blind lens-free microscopic analysis of 116 cerebrospinal fluid specimens, including six cases of microbiology confirmed infectious meningitis, yielded a 100% sensitivity and a 79% specificity. Adapted lens-free microscopy is thus emerging as an operator-independent technique for the rapid numeration of leukocytes and erythrocytes in cerebrospinal fluid. In particular, this technique is well suited to the rapid diagnosis of meningitis at point-of-care laboratories.

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

Hull, G; Zaitseva, N; Cherepy, N

Efficient, readily-available, low-cost, high-energy neutron detectors can play a central role in detecting illicit nuclear weapons since neutrons are a strong indication for the presence of fissile material such as Plutonium and Highly-Enriched Uranium. The main challenge in detecting fast neutrons consists in the discrimination of the signal from the gamma radiation background. At present, the only well-investigated organic crystal scintillator for fast neutron detection, in a n/{gamma} mixed field, is stilbene, which while offering good pulse shape discrimination, is not widely used because of its limited availability and high cost. In this work we report the results of ourmore » studies made with a number of new organic crystals, which exhibit pulse shape discrimination for detection of fast neutrons. In particular 1,1,4,4-tetraphenyl-1,3-butadiene features a light yield higher than anthracene and a Figure of Merit (FOM) for the pulse shape discrimination better than stilbene. New crystals are good candidates for the low-cost solution growth method, thus representing promising organic scintillators for widespread deployment for high-energy neutron detection.« less

Using the Autism-spectrum quotient to discriminate Autism Spectrum Disorder from ADHD in adult patients with and without comorbid Substance Use Disorder.

PubMed

Sizoo, Bram B; van den Brink, Wim; Gorissen-van Eenige, Marielle; Koeter, Maarten W; van Wijngaarden-Cremers, Patricia J M; van der Gaag, Rutger Jan

2009-09-01

It is unknown whether the Autism-spectrum quotient (AQ) can discriminate between Autism Spectrum Disorder (ASD) and Attention Deficit and Hyperactivity Disorder (ADHD) with or without comorbid Substance Use Disorder (SUD). ANOVA's were used to analyse the mean AQ (sub)scores of 129 adults with ASD or ADHD. We applied receiver operating characteristic (ROC) computations to assess discriminant power. All but one of the mean AQ (sub)scores were significantly higher for adults with ASD compared to those with ADHD. The SUD status in general was not significantly associated with AQ (sub)scores. On the Social Skills subscale patients with ASD and comorbid SUD showed less impairment than those without SUD. The cut-off score 26 yielded 73% correct classifications. The clinical use of the AQ in differentiating between ASD and ADHD is limited.

Item validity vs. item discrimination index: a redundancy?

NASA Astrophysics Data System (ADS)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.

Orthogonal sparse linear discriminant analysis

NASA Astrophysics Data System (ADS)

Liu, Zhonghua; Liu, Gang; Pu, Jiexin; Wang, Xiaohong; Wang, Haijun

2018-03-01

Linear discriminant analysis (LDA) is a linear feature extraction approach, and it has received much attention. On the basis of LDA, researchers have done a lot of research work on it, and many variant versions of LDA were proposed. However, the inherent problem of LDA cannot be solved very well by the variant methods. The major disadvantages of the classical LDA are as follows. First, it is sensitive to outliers and noises. Second, only the global discriminant structure is preserved, while the local discriminant information is ignored. In this paper, we present a new orthogonal sparse linear discriminant analysis (OSLDA) algorithm. The k nearest neighbour graph is first constructed to preserve the locality discriminant information of sample points. Then, L2,1-norm constraint on the projection matrix is used to act as loss function, which can make the proposed method robust to outliers in data points. Extensive experiments have been performed on several standard public image databases, and the experiment results demonstrate the performance of the proposed OSLDA algorithm.

Fast classification of hazelnut cultivars through portable infrared spectroscopy and chemometrics

NASA Astrophysics Data System (ADS)

Manfredi, Marcello; Robotti, Elisa; Quasso, Fabio; Mazzucco, Eleonora; Calabrese, Giorgio; Marengo, Emilio

2018-01-01

The authentication and traceability of hazelnuts is very important for both the consumer and the food industry, to safeguard the protected varieties and the food quality. This study investigates the use of a portable FTIR spectrometer coupled to multivariate statistical analysis for the classification of raw hazelnuts. The method discriminates hazelnuts from different origins/cultivars based on differences of the signal intensities of their IR spectra. The multivariate classification methods, namely principal component analysis (PCA) followed by linear discriminant analysis (LDA) and partial least square discriminant analysis (PLS-DA), with or without variable selection, allowed a very good discrimination among the groups, with PLS-DA coupled to variable selection providing the best results. Due to the fast analysis, high sensitivity, simplicity and no sample preparation, the proposed analytical methodology could be successfully used to verify the cultivar of hazelnuts, and the analysis can be performed quickly and directly on site.

Analysis of laser printer and photocopier toners by spectral properties and chemometrics

NASA Astrophysics Data System (ADS)

Verma, Neha; Kumar, Raj; Sharma, Vishal

2018-05-01

The use of printers to generate falsified documents has become a common practice in today's world. The examination and identification of the printed matter in the suspected documents (civil or criminal cases) may provide important information about the authenticity of the document. In the present study, a total number of 100 black toner samples both from laser printers and photocopiers were examined using diffuse reflectance UV-Vis Spectroscopy. The present research is divided into two parts; visual discrimination and discrimination by using multivariate analysis. A comparison between qualitative and quantitative analysis showed that multivariate analysis (Principal component analysis) provides 99.59%pair-wise discriminating power for laser printer toners while 99.84% pair-wise discriminating power for photocopier toners. The overall results obtained confirm the applicability of UV-Vis spectroscopy and chemometrics, in the nondestructive analysis of toner printed documents while enhancing their evidential value for forensic applications.

VFMA: Topographic Analysis of Sensitivity Data From Full-Field Static Perimetry

PubMed Central

Weleber, Richard G.; Smith, Travis B.; Peters, Dawn; Chegarnov, Elvira N.; Gillespie, Scott P.; Francis, Peter J.; Gardiner, Stuart K.; Paetzold, Jens; Dietzsch, Janko; Schiefer, Ulrich; Johnson, Chris A.

2015-01-01

Purpose: To analyze static visual field sensitivity with topographic models of the hill of vision (HOV), and to characterize several visual function indices derived from the HOV volume. Methods: A software application, Visual Field Modeling and Analysis (VFMA), was developed for static perimetry data visualization and analysis. Three-dimensional HOV models were generated for 16 healthy subjects and 82 retinitis pigmentosa patients. Volumetric visual function indices, which are measures of quantity and comparable regardless of perimeter test pattern, were investigated. Cross-validation, reliability, and cross-sectional analyses were performed to assess this methodology and compare the volumetric indices to conventional mean sensitivity and mean deviation. Floor effects were evaluated by computer simulation. Results: Cross-validation yielded an overall R2 of 0.68 and index of agreement of 0.89, which were consistent among subject groups, indicating good accuracy. Volumetric and conventional indices were comparable in terms of test–retest variability and discriminability among subject groups. Simulated floor effects did not negatively impact the repeatability of any index, but large floor changes altered the discriminability for regional volumetric indices. Conclusions: VFMA is an effective tool for clinical and research analyses of static perimetry data. Topographic models of the HOV aid the visualization of field defects, and topographically derived indices quantify the magnitude and extent of visual field sensitivity. Translational Relevance: VFMA assists with the interpretation of visual field data from any perimetric device and any test location pattern. Topographic models and volumetric indices are suitable for diagnosis, monitoring of field loss, patient counseling, and endpoints in therapeutic trials. PMID:25938002

In Vitro Cell Death Discrimination and Screening Method by Simple and Cost-Effective Viability Analysis.

PubMed

Helm, Katharina; Beyreis, Marlena; Mayr, Christian; Ritter, Markus; Jakab, Martin; Kiesslich, Tobias; Plaetzer, Kristjan

2017-01-01

For in vitro cytotoxicity testing, discrimination of apoptosis and necrosis represents valuable information. Viability analysis performed at two different time points post treatment could serve such a purpose because the dynamics of metabolic activity of apoptotic and necrotic cells is different, i.e. a more rapid decline of cellular metabolism during necrosis whereas cellular metabolism is maintained during the entire execution phase of apoptosis. This study describes a straightforward approach to distinguish apoptosis and necrosis. A431 human epidermoid carcinoma cells were treated with different concentrations/doses of actinomycin D (Act-D), 4,5,6,7-tetrabromo-2-azabenzimidazole (TBB), Ro 31-8220, H2O2 and photodynamic treatment (PDT). The resazurin viability signal was recorded at 2 and 24 hrs post treatment. Apoptosis and necrosis were verified by measuring caspase 3/7 and membrane integrity. Calculation of the difference curve between the 2 and 24 hrs resazurin signals yields the following information: a positive difference signal indicates apoptosis (i.e. high metabolic activity at early time points and low signal at 24 hrs post treatment) while an early reduction of the viability signal indicates necrosis. For all treatments, this dose-dependent sequence of cellular responses could be confirmed by independent assays. Simple and cost-effective viability analysis provides reliable information about the dose ranges of a cytotoxic agent where apoptosis or necrosis occurs. This may serve as a starting point for further in-depth characterisation of cytotoxic treatments. © 2017 The Author(s)Published by S. Karger AG, Basel.

Patterns of Twitter Behavior Among Networks of Cannabis Dispensaries in California

PubMed Central

Chew, Robert F; Hsieh, Yuli P; Bieler, Gayle S; Bobashev, Georgiy V; Siege, Christopher; Zarkin, Gary A

2017-01-01

Background Twitter represents a social media platform through which medical cannabis dispensaries can rapidly promote and advertise a multitude of retail products. Yet, to date, no studies have systematically evaluated Twitter behavior among dispensaries and how these behaviors influence the formation of social networks. Objectives This study sought to characterize common cyberbehaviors and shared follower networks among dispensaries operating in two large cannabis markets in California. Methods From a targeted sample of 119 dispensaries in the San Francisco Bay Area and Greater Los Angeles, we collected metadata from the dispensary accounts using the Twitter API. For each city, we characterized the network structure of dispensaries based upon shared followers, then empirically derived communities with the Louvain modularity algorithm. Principal components factor analysis was employed to reduce 12 Twitter measures into a more parsimonious set of cyberbehavioral dimensions. Finally, quadratic discriminant analysis was implemented to verify the ability of the extracted dimensions to classify dispensaries into their derived communities. Results The modularity algorithm yielded three communities in each city with distinct network structures. The principal components factor analysis reduced the 12 cyberbehaviors into five dimensions that encompassed account age, posting frequency, referencing, hyperlinks, and user engagement among the dispensary accounts. In the quadratic discriminant analysis, the dimensions correctly classified 75% (46/61) of the communities in the San Francisco Bay Area and 71% (41/58) in Greater Los Angeles. Conclusions The most centralized and strongly connected dispensaries in both cities had newer accounts, higher daily activity, more frequent user engagement, and increased usage of embedded media, keywords, and hyperlinks. Measures derived from both network structure and cyberbehavioral dimensions can serve as key contextual indicators for the online surveillance of cannabis dispensaries and consumer markets over time. PMID:28676471

Stigma in the mental health workplace: perceptions of peer employees and clinicians.

PubMed

Stromwall, Layne K; Holley, Lynn C; Bashor, Kathy E

2011-08-01

Informed by a structural theory of workplace discrimination, mental health system employees' perceptions of mental health workplace stigma and discrimination against service recipients and peer employees were investigated. Fifty-one peer employees and 52 licensed behavioral health clinicians participated in an online survey. Independent variables were employee status (peer or clinician), gender, ethnicity, years of mental health employment, age, and workplace social inclusion of peer employees. Analysis of covariance on workplace discrimination against service recipients revealed that peer employees perceived more discrimination than clinicians and whites perceived more discrimination than employees of color (corrected model F = 9.743 [16, 87], P = .000, partial ŋ (2) = .644). Analysis of covariance on workplace discrimination against peer employees revealed that peer employees perceived more discrimination than clinicians (F = 4.593, [6, 97], P = .000, partial ŋ (2) = .223).

Microaggressions, Discrimination, and Phenotype among African Americans: A Latent Class Analysis of the Impact of Skin Tone and BMI.

PubMed

Keith, Verna M; Nguyen, Ann W; Taylor, Robert Joseph; Mouzon, Dawne M; Chatters, Linda M

2017-05-01

Data from the 2001-2003National Survey of American Life are used to investigate the effects of phenotype on everyday experiences with discrimination among African Americans (N=3343). Latent class analysis is used to identify four classes of discriminatory treatment: 1) low levels of discrimination, 2) disrespect and condescension, 3) character-based discrimination, and 4) high levels of discrimination. We then employ latent class multinomial logistic regression to evaluate the association between skin tone and body weight and these four classes of discrimination. Designating the low level discrimination class as the reference group, findings revealed that respondents with darker skin were more likely to be classified into the disrespect/condescension and the high level microaggression types. BMI was unrelated to the discrimination type, although there was a significant interaction effect between gender and BMI. BMI was strongly and positively associated with membership in the disrespect and condescension type among men but not among women. These findings indicate that skin tone and body weight are two phenotypic characteristics that influence the type and frequency of discrimination experienced by African Americans.

Real-time detection and discrimination of visual perception using electrocorticographic signals

NASA Astrophysics Data System (ADS)

Kapeller, C.; Ogawa, H.; Schalk, G.; Kunii, N.; Coon, W. G.; Scharinger, J.; Guger, C.; Kamada, K.

2018-06-01

Objective. Several neuroimaging studies have demonstrated that the ventral temporal cortex contains specialized regions that process visual stimuli. This study investigated the spatial and temporal dynamics of electrocorticographic (ECoG) responses to different types and colors of visual stimulation that were presented to four human participants, and demonstrated a real-time decoder that detects and discriminates responses to untrained natural images. Approach. ECoG signals from the participants were recorded while they were shown colored and greyscale versions of seven types of visual stimuli (images of faces, objects, bodies, line drawings, digits, and kanji and hiragana characters), resulting in 14 classes for discrimination (experiment I). Additionally, a real-time system asynchronously classified ECoG responses to faces, kanji and black screens presented via a monitor (experiment II), or to natural scenes (i.e. the face of an experimenter, natural images of faces and kanji, and a mirror) (experiment III). Outcome measures in all experiments included the discrimination performance across types based on broadband γ activity. Main results. Experiment I demonstrated an offline classification accuracy of 72.9% when discriminating among the seven types (without color separation). Further discrimination of grey versus colored images reached an accuracy of 67.1%. Discriminating all colors and types (14 classes) yielded an accuracy of 52.1%. In experiment II and III, the real-time decoder correctly detected 73.7% responses to face, kanji and black computer stimuli and 74.8% responses to presented natural scenes. Significance. Seven different types and their color information (either grey or color) could be detected and discriminated using broadband γ activity. Discrimination performance maximized for combined spatial-temporal information. The discrimination of stimulus color information provided the first ECoG-based evidence for color-related population-level cortical broadband γ responses in humans. Stimulus categories can be detected by their ECoG responses in real time within 500 ms with respect to stimulus onset.

Chemical Discrimination of Cortex Phellodendri amurensis and Cortex Phellodendri chinensis by Multivariate Analysis Approach.

PubMed

Sun, Hui; Wang, Huiyu; Zhang, Aihua; Yan, Guangli; Han, Ying; Li, Yuan; Wu, Xiuhong; Meng, Xiangcai; Wang, Xijun

2016-01-01

As herbal medicines have an important position in health care systems worldwide, their current assessment, and quality control are a major bottleneck. Cortex Phellodendri chinensis (CPC) and Cortex Phellodendri amurensis (CPA) are widely used in China, however, how to identify species of CPA and CPC has become urgent. In this study, multivariate analysis approach was performed to the investigation of chemical discrimination of CPA and CPC. Principal component analysis showed that two herbs could be separated clearly. The chemical markers such as berberine, palmatine, phellodendrine, magnoflorine, obacunone, and obaculactone were identified through the orthogonal partial least squared discriminant analysis, and were identified tentatively by the accurate mass of quadruple-time-of-flight mass spectrometry. A total of 29 components can be used as the chemical markers for discrimination of CPA and CPC. Of them, phellodenrine is significantly higher in CPC than that of CPA, whereas obacunone and obaculactone are significantly higher in CPA than that of CPC. The present study proves that multivariate analysis approach based chemical analysis greatly contributes to the investigation of CPA and CPC, and showed that the identified chemical markers as a whole should be used to discriminate the two herbal medicines, and simultaneously the results also provided chemical information for their quality assessment. Multivariate analysis approach was performed to the investigate the herbal medicineThe chemical markers were identified through multivariate analysis approachA total of 29 components can be used as the chemical markers. UPLC-Q/TOF-MS-based multivariate analysis method for the herbal medicine samples Abbreviations used: CPC: Cortex Phellodendri chinensis, CPA: Cortex Phellodendri amurensis, PCA: Principal component analysis, OPLS-DA: Orthogonal partial least squares discriminant analysis, BPI: Base peaks ion intensity.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy

NASA Astrophysics Data System (ADS)

Zhu, Ying; Tan, Tuck Lee

2016-04-01

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects.

The discrimination of honey origin using melissopalynology and Raman spectroscopy techniques coupled with multivariate analysis.

PubMed

Corvucci, Francesca; Nobili, Lara; Melucci, Dora; Grillenzoni, Francesca-Vittoria

2015-02-15

Honey traceability to food quality is required by consumers and food control institutions. Melissopalynologists traditionally use percentages of nectariferous pollens to discriminate the botanical origin and the entire pollen spectrum (presence/absence, type and quantities and association of some pollen types) to determinate the geographical origin of honeys. To improve melissopalynological routine analysis, principal components analysis (PCA) was used. A remarkable and innovative result was that the most significant pollens for the traditional discrimination of the botanical and geographical origin of honeys were the same as those individuated with the chemometric model. The reliability of assignments of samples to honey classes was estimated through explained variance (85%). This confirms that the chemometric model properly describes the melissopalynological data. With the aim to improve honey discrimination, FT-microRaman spectrography and multivariate analysis were also applied. Well performing PCA models and good agreement with known classes were achieved. Encouraging results were obtained for botanical discrimination. Copyright © 2014 Elsevier Ltd. All rights reserved.

Local kernel nonparametric discriminant analysis for adaptive extraction of complex structures

NASA Astrophysics Data System (ADS)

Li, Quanbao; Wei, Fajie; Zhou, Shenghan

2017-05-01

The linear discriminant analysis (LDA) is one of popular means for linear feature extraction. It usually performs well when the global data structure is consistent with the local data structure. Other frequently-used approaches of feature extraction usually require linear, independence, or large sample condition. However, in real world applications, these assumptions are not always satisfied or cannot be tested. In this paper, we introduce an adaptive method, local kernel nonparametric discriminant analysis (LKNDA), which integrates conventional discriminant analysis with nonparametric statistics. LKNDA is adept in identifying both complex nonlinear structures and the ad hoc rule. Six simulation cases demonstrate that LKNDA have both parametric and nonparametric algorithm advantages and higher classification accuracy. Quartic unilateral kernel function may provide better robustness of prediction than other functions. LKNDA gives an alternative solution for discriminant cases of complex nonlinear feature extraction or unknown feature extraction. At last, the application of LKNDA in the complex feature extraction of financial market activities is proposed.

L1-norm kernel discriminant analysis via Bayes error bound optimization for robust feature extraction.

PubMed

Zheng, Wenming; Lin, Zhouchen; Wang, Haixian

2014-04-01

A novel discriminant analysis criterion is derived in this paper under the theoretical framework of Bayes optimality. In contrast to the conventional Fisher's discriminant criterion, the major novelty of the proposed one is the use of L1 norm rather than L2 norm, which makes it less sensitive to the outliers. With the L1-norm discriminant criterion, we propose a new linear discriminant analysis (L1-LDA) method for linear feature extraction problem. To solve the L1-LDA optimization problem, we propose an efficient iterative algorithm, in which a novel surrogate convex function is introduced such that the optimization problem in each iteration is to simply solve a convex programming problem and a close-form solution is guaranteed to this problem. Moreover, we also generalize the L1-LDA method to deal with the nonlinear robust feature extraction problems via the use of kernel trick, and hereafter proposed the L1-norm kernel discriminant analysis (L1-KDA) method. Extensive experiments on simulated and real data sets are conducted to evaluate the effectiveness of the proposed method in comparing with the state-of-the-art methods.

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.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of LANDSAT digital data

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

Religious Discrimination Discourse in the Mono-Cultural School: The Case of Poland

ERIC Educational Resources Information Center

Anczyk, Adam; Grzymala-Moszczynska, Joanna

2018-01-01

The article forms an analysis of the religious discrimination discourse in Polish public schools, with special attention paid to the culturally specific, Polish understanding of the notion of religious discrimination. The introductory part presents the concept of religious discrimination as present in anti-discriminatory policies. The following…

Discrimination of surface wear on obsidian tools using LSCM and RelA: pilot study results (area-scale analysis of obsidian tool surfaces).

PubMed

Stemp, W James; Chung, Steven

2011-01-01

This pilot study tests the reliability of laser scanning confocal microscopy (LSCM) to quantitatively measure wear on experimental obsidian tools. To our knowledge, this is the first use of confocal microscopy to study wear on stone flakes made from an amorphous silicate like obsidian. Three-dimensional surface roughness or texture area scans on three obsidian flakes used on different contact materials (hide, shell, wood) were documented using the LSCM to determine whether the worn surfaces could be discriminated using area-scale analysis, specifically relative area (RelA). When coupled with the F-test, this scale-sensitive fractal analysis could not only discriminate the used from unused surfaces on individual tools, but was also capable of discriminating the wear histories of tools used on different contact materials. Results indicate that such discriminations occur at different scales. Confidence levels for the discriminations at different scales were established using the F-test (mean square ratios or MSRs). In instances where discrimination of surface roughness or texture was not possible above the established confidence level based on MSRs, photomicrographs and RelA assisted in hypothesizing why this was so. Copyright © 2011 Wiley Periodicals, Inc.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar

NASA Astrophysics Data System (ADS)

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-01

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm-1). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species.

Distractor Plausibility and Criterion Placement in Recognition

ERIC Educational Resources Information Center

Benjamin, Aaron S.; Bawa, Sameer

2004-01-01

To set an optimal decision criterion on a test of recognition, a subject must estimate the degree to which they can discriminate previously studied from unstudied stimuli. To do so accurately, the subject must assess not only their mastery of the material but also the extent to which the distractors yield mnemonic evidence that makes them…

Methods of rapid, early selection of poplar clones for maximum yield potential: a manual of procedures.

Treesearch

USDA FS

1982-01-01

Instructions, illustrated with examples and experimental results, are given for the controlled-environment propagation and selection of poplar clones. Greenhouse and growth-room culture of poplar stock plants and scions are described, and statistical techniques for discriminating among clones on the basis of growth variables are emphasized.

Factors that Affect Poverty Areas in North Sumatera Using Discriminant Analysis

NASA Astrophysics Data System (ADS)

Nasution, D. H.; Bangun, P.; Sitepu, H. R.

2018-04-01

In Indonesia, especially North Sumatera, the problem of poverty is one of the fundamental problems that become the focus of government both central and local government. Although the poverty rate decreased but the fact is there are many people who are poor. Poverty happens covers several aspects such as education, health, demographics, and also structural and cultural. This research will discuss about several factors such as population density, Unemployment Rate, GDP per capita ADHK, ADHB GDP per capita, economic growth and life expectancy that affect poverty in Indonesia. To determine the factors that most influence and differentiate the level of poverty of the Regency/City North Sumatra used discriminant analysis method. Discriminant analysis is one multivariate analysis technique are used to classify the data into a group based on the dependent variable and independent variable. Using discriminant analysis, it is evident that the factor affecting poverty is Unemployment Rate.

Trabecular Bone Strength Predictions of HR-pQCT and Individual Trabeculae Segmentation (ITS)-Based Plate and Rod Finite Element Model Discriminate Postmenopausal Vertebral Fractures

PubMed Central

Liu, X. Sherry; Wang, Ji; Zhou, Bin; Stein, Emily; Shi, Xiutao; Adams, Mark; Shane, Elizabeth; Guo, X. Edward

2013-01-01

While high-resolution peripheral quantitative computed tomography (HR-pQCT) has advanced clinical assessment of trabecular bone microstructure, nonlinear microstructural finite element (μFE) prediction of yield strength by HR-pQCT voxel model is impractical for clinical use due to its prohibitively high computational costs. The goal of this study was to develop an efficient HR-pQCT-based plate and rod (PR) modeling technique to fill the unmet clinical need for fast bone strength estimation. By using individual trabecula segmentation (ITS) technique to segment the trabecular structure into individual plates and rods, a patient-specific PR model was implemented by modeling each trabecular plate with multiple shell elements and each rod with a beam element. To validate this modeling technique, predictions by HR-pQCT PR model were compared with those of the registered high resolution μCT voxel model of 19 trabecular sub-volumes from human cadaveric tibiae samples. Both Young’s modulus and yield strength of HR-pQCT PR models strongly correlated with those of μCT voxel models (r2=0.91 and 0.86). Notably, the HR-pQCT PR models achieved major reductions in element number (>40-fold) and CPU time (>1,200-fold). Then, we applied PR model μFE analysis to HR-pQCT images of 60 postmenopausal women with (n=30) and without (n=30) a history of vertebral fracture. HR-pQCT PR model revealed significantly lower Young’s modulus and yield strength at the radius and tibia in fracture subjects compared to controls. Moreover, these mechanical measurements remained significantly lower in fracture subjects at both sites after adjustment for aBMD T-score at the ultradistal radius or total hip. In conclusion, we validated a novel HR-pQCT PR model of human trabecular bone against μCT voxel models and demonstrated its ability to discriminate vertebral fracture status in postmenopausal women. This accurate nonlinear μFE prediction of HR-pQCT PR model, which requires only seconds of desktop computer time, has tremendous promise for clinical assessment of bone strength. PMID:23456922

Predicting abuse potential of stimulants and other dopaminergic drugs: overview and recommendations.

PubMed

Huskinson, Sally L; Naylor, Jennifer E; Rowlett, James K; Freeman, Kevin B

2014-12-01

Examination of a drug's abuse potential at multiple levels of analysis (molecular/cellular action, whole-organism behavior, epidemiological data) is an essential component to regulating controlled substances under the Controlled Substances Act (CSA). We reviewed studies that examined several central nervous system (CNS) stimulants, focusing on those with primarily dopaminergic actions, in drug self-administration, drug discrimination, and physical dependence. For drug self-administration and drug discrimination, we distinguished between experiments conducted with rats and nonhuman primates (NHP) to highlight the common and unique attributes of each model in the assessment of abuse potential. Our review of drug self-administration studies suggests that this procedure is important in predicting abuse potential of dopaminergic compounds, but there were many false positives. We recommended that tests to determine how reinforcing a drug is relative to a known drug of abuse may be more predictive of abuse potential than tests that yield a binary, yes-or-no classification. Several false positives also occurred with drug discrimination. With this procedure, we recommended that future research follow a standard decision-tree approach that may require examining the drug being tested for abuse potential as the training stimulus. This approach would also allow several known drugs of abuse to be tested for substitution, and this may reduce false positives. Finally, we reviewed evidence of physical dependence with stimulants and discussed the feasibility of modeling these phenomena in nonhuman animals in a rational and practical fashion. This article is part of the Special Issue entitled 'CNS Stimulants'. Copyright © 2014 Elsevier Ltd. All rights reserved.

Mental Health Screening in Primary Care: A Comparison of 3 Brief Measures of Psychological Distress

PubMed Central

Cano, Annmarie; Sprafkin, Robert P.; Scaturo, Douglas J.; Lantinga, Larry J.; Fiese, Barbara H.; Brand, Frank

2001-01-01

Background: The current study compared 3 brief mental health screening measures in a sample of older patients in a primary care outpatient setting. Previous mental health screening research has been conducted primarily with younger patients, often with only 1 screening measure, thereby limiting the generalizability of findings. In addition, measures have not yet been compared in terms of their ability to discriminate between cases and noncases of psychiatric disorder. Method: One hundred thirty-four male patients attending their appointments at a primary care clinic in a Department of Veterans Affairs Medical Center participated in this study. Participants completed the General Health Questionnaire-12 (GHQ-12), the Symptom Checklist-10 (SCL-10), and the Primary Care Evaluation of Mental Disorders screening questionnaire and interview. Results: Receiver operating characteristic analysis yielded the optimum cutoff scores on each brief mental health screening measure and showed that all 3 measures discriminated well between cases and noncases of psychiatric disorders. The 3 measures performed slightly better in terms of discriminating between cases and noncases of mood or anxiety disorders than between cases and noncases of any psychiatric disorder. There were no significant differences between the measures' abilities to accurately identify cases and noncases of disorder. Conclusion: Primary care physicians are encouraged to use brief mental health screening measures with their patients, since many report symptoms of psychological distress and disorder. It is recommended that the SCL-10 and GHQ-12 be used to detect mood or anxiety disorders in patients such as these because of the accuracy and brevity of these measures. PMID:15014574

The Role of Remote Sensing in Assessing Forest Biomass in Appalachian South Carolina

NASA Technical Reports Server (NTRS)

Shain, W.; Nix, L.

1982-01-01

Information is presented on the use of color infrared aerial photographs and ground sampling methods to quantify standing forest biomass in Appalachian South Carolina. Local tree biomass equations are given and subsequent evaluation of stand density and size classes using remote sensing methods is presented. Methods of terrain analysis, environmental hazard rating, and subsequent determination of accessibility of forest biomass are discussed. Computer-based statistical analyses are used to expand individual cover-type specific ground sample data to area-wide cover type inventory figures based on aerial photographic interpretation and area measurement. Forest biomass data are presented for the study area in terms of discriminant size classes, merchantability limits, accessibility (as related to terrain and yield/harvest constraints), and potential environmental impact of harvest.

Apolipoprotein concentrations are elevated in malignant ovarian cyst fluids suggesting that lipoprotein metabolism is dysregulated in epithelial ovarian cancer.

PubMed

Podzielinski, Iwona; Saunders, Brook A; Kimbler, Kimberly D; Branscum, Adam J; Fung, Eric T; DePriest, Paul D; van Nagell, John R; Ueland, Frederick R; Baron, Andre T

2013-05-01

SELDI-TOF MS analysis of ovarian cyst fluids revealed that peaks m/z 8696 and 8825 discriminate malignant, borderline, and benign tumors. These peaks correspond to isoforms of apoA2. ELISA demonstrates that apoA1, A2, B, C2, C3, and E cyst fluid concentrations are uncorrelated and higher in malignant ovarian tumors, but only apoA2, apoE, and age are independent classifiers of malignant ovarian tumors, yielding 55.1% sensitivity, 95% specificity, and 88.1% accuracy to discern malignant from benign and borderline tumors. These data suggest that lipoprotein metabolism is dysregulated in ovarian cancer and that apoA2 and apoE warrant further investigation as ovarian tumor biomarkers.

Increased pulmonary alveolar-capillary permeability in patients at risk for adult respiratory distress syndrome

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

Tennenberg, S.D.; Jacobs, M.P.; Solomkin, J.S.

1987-04-01

Two methods for predicting adult respiratory distress syndrome (ARDS) were evaluated prospectively in a group of 81 multitrauma and sepsis patients considered at clinical high risk. A popular ARDS risk-scoring method, employing discriminant analysis equations (weighted risk criteria and oxygenation characteristics), yielded a predictive accuracy of 59% and a false-negative rate of 22%. Pulmonary alveolar-capillary permeability (PACP) was determined with a radioaerosol lung-scan technique in 23 of these 81 patients, representing a statistically similar subgroup. Lung scanning achieved a predictive accuracy of 71% (after excluding patients with unilateral pulmonary contusion) and gave no false-negatives. We propose a combination of clinicalmore » risk identification and functional determination of PACP to assess a patient's risk of developing ARDS.« less

Classifying Failing States

DTIC Science & Technology

2007-03-01

state failure, and Discriminant Analysis to classify states as Stable, Borderline, or Failing based on these indicators. Furthermore, each...nation’s discriminant function scores are used to determine their degree of instability. The methodology is applied to 200 countries for which open source...and go for a long walk. Finally, to my wonderful wife, who now knows more about Discriminant Analysis than any Legal Assistant on the planet, thank

Light yield in DarkSide-10: A prototype two-phase argon TPC for dark matter searches

NASA Astrophysics Data System (ADS)

Alexander, T.; Alton, D.; Arisaka, K.; Back, H. O.; Beltrame, P.; Benziger, J.; Bonfini, G.; Brigatti, A.; Brodsky, J.; Cadonati, L.; Calaprice, F.; Candela, A.; Cao, H.; Cavalcante, P.; Chavarria, A.; Chepurnov, A.; Cline, D.; Cocco, A. G.; Condon, C.; D'Angelo, D.; Davini, S.; De Haas, E.; Derbin, A.; Di Pietro, G.; Dratchnev, I.; Durben, D.; Empl, A.; Etenko, A.; Fan, A.; Fiorillo, G.; Fomenko, K.; Gabriele, F.; Galbiati, C.; Gazzana, S.; Ghag, C.; Ghiano, C.; Goretti, A.; Grandi, L.; Gromov, M.; Guan, M.; Guo, C.; Guray, G.; Hungerford, E. V.; Ianni, Al.; Ianni, An.; Kayunov, A.; Keeter, K.; Kendziora, C.; Kidner, S.; Kobychev, V.; Koh, G.; Korablev, D.; Korga, G.; Shields, E.; Li, P.; Loer, B.; Lombardi, P.; Love, C.; Ludhova, L.; Lukyanchenko, L.; Lund, A.; Lung, K.; Ma, Y.; Machulin, I.; Maricic, J.; Martoff, C. J.; Meng, Y.; Meroni, E.; Meyers, P. D.; Mohayai, T.; Montanari, D.; Montuschi, M.; Mosteiro, P.; Mount, B.; Muratova, V.; Nelson, A.; Nemtzow, A.; Nurakhov, N.; Orsini, M.; Ortica, F.; Pallavicini, M.; Pantic, E.; Parmeggiano, S.; Parsells, R.; Pelliccia, N.; Perasso, L.; Perfetto, F.; Pinsky, L.; Pocar, A.; Pordes, S.; Ranucci, G.; Razeto, A.; Romani, A.; Rossi, N.; Saggese, P.; Saldanha, R.; Salvo, C.; Sands, W.; Seigar, M.; Semenov, D.; Skorokhvatov, M.; Smirnov, O.; Sotnikov, A.; Sukhotin, S.; Suvorov, Y.; Tartaglia, R.; Tatarowicz, J.; Testera, G.; Teymourian, A.; Thompson, J.; Unzhakov, E.; Vogelaar, R. B.; Wang, H.; Westerdale, S.; Wojcik, M.; Wright, A.; Xu, J.; Yang, C.; Zavatarelli, S.; Zehfus, M.; Zhong, W.; Zuzel, G.

2013-09-01

As part of the DarkSide program of direct dark matter searches using two-phase argon TPCs, a prototype detector with an active volume containing 10 kg of liquid argon, DarkSide-10, was built and operated underground in the Gran Sasso National Laboratory in Italy. A critically important parameter for such devices is the scintillation light yield, as photon statistics limits the rejection of electron-recoil backgrounds by pulse shape discrimination. We have measured the light yield of DarkSide-10 using the readily-identifiable full-absorption peaks from gamma ray sources combined with single-photoelectron calibrations using low-occupancy laser pulses. For gamma lines of energies in the range 122-1275 keV, we get light yields averaging 8.887±0.003(stat)±0.444(sys) p.e./keVee. With additional purification, the light yield measured at 511 keV increased to 9.142±0.006(stat) p.e./keVee.

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images.

PubMed

Guo, Shengwen; Lai, Chunren; Wu, Congling; Cen, Guiyin

2017-01-01

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI-cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI-NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI-NC comparison. The best performances obtained by the SVM classifier using the essential features were 5-40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease.

A reduced number of mtSNPs saturates mitochondrial DNA haplotype diversity of worldwide population groups.

PubMed

Salas, Antonio; Amigo, Jorge

2010-05-03

The high levels of variation characterising the mitochondrial DNA (mtDNA) molecule are due ultimately to its high average mutation rate; moreover, mtDNA variation is deeply structured in different populations and ethnic groups. There is growing interest in selecting a reduced number of mtDNA single nucleotide polymorphisms (mtSNPs) that account for the maximum level of discrimination power in a given population. Applications of the selected mtSNP panel range from anthropologic and medical studies to forensic genetic casework. This study proposes a new simulation-based method that explores the ability of different mtSNP panels to yield the maximum levels of discrimination power. The method explores subsets of mtSNPs of different sizes randomly chosen from a preselected panel of mtSNPs based on frequency. More than 2,000 complete genomes representing three main continental human population groups (Africa, Europe, and Asia) and two admixed populations ("African-Americans" and "Hispanics") were collected from GenBank and the literature, and were used as training sets. Haplotype diversity was measured for each combination of mtSNP and compared with existing mtSNP panels available in the literature. The data indicates that only a reduced number of mtSNPs ranging from six to 22 are needed to account for 95% of the maximum haplotype diversity of a given population sample. However, only a small proportion of the best mtSNPs are shared between populations, indicating that there is not a perfect set of "universal" mtSNPs suitable for all population contexts. The discrimination power provided by these mtSNPs is much higher than the power of the mtSNP panels proposed in the literature to date. Some mtSNP combinations also yield high diversity values in admixed populations. The proposed computational approach for exploring combinations of mtSNPs that optimise the discrimination power of a given set of mtSNPs is more efficient than previous empirical approaches. In contrast to precedent findings, the results seem to indicate that only few mtSNPs are needed to reach high levels of discrimination power in a population, independently of its ancestral background.

A Reduced Number of mtSNPs Saturates Mitochondrial DNA Haplotype Diversity of Worldwide Population Groups

PubMed Central

Salas, Antonio; Amigo, Jorge

2010-01-01

Background The high levels of variation characterising the mitochondrial DNA (mtDNA) molecule are due ultimately to its high average mutation rate; moreover, mtDNA variation is deeply structured in different populations and ethnic groups. There is growing interest in selecting a reduced number of mtDNA single nucleotide polymorphisms (mtSNPs) that account for the maximum level of discrimination power in a given population. Applications of the selected mtSNP panel range from anthropologic and medical studies to forensic genetic casework. Methodology/Principal Findings This study proposes a new simulation-based method that explores the ability of different mtSNP panels to yield the maximum levels of discrimination power. The method explores subsets of mtSNPs of different sizes randomly chosen from a preselected panel of mtSNPs based on frequency. More than 2,000 complete genomes representing three main continental human population groups (Africa, Europe, and Asia) and two admixed populations (“African-Americans” and “Hispanics”) were collected from GenBank and the literature, and were used as training sets. Haplotype diversity was measured for each combination of mtSNP and compared with existing mtSNP panels available in the literature. The data indicates that only a reduced number of mtSNPs ranging from six to 22 are needed to account for 95% of the maximum haplotype diversity of a given population sample. However, only a small proportion of the best mtSNPs are shared between populations, indicating that there is not a perfect set of “universal” mtSNPs suitable for all population contexts. The discrimination power provided by these mtSNPs is much higher than the power of the mtSNP panels proposed in the literature to date. Some mtSNP combinations also yield high diversity values in admixed populations. Conclusions/Significance The proposed computational approach for exploring combinations of mtSNPs that optimise the discrimination power of a given set of mtSNPs is more efficient than previous empirical approaches. In contrast to precedent findings, the results seem to indicate that only few mtSNPs are needed to reach high levels of discrimination power in a population, independently of its ancestral background. PMID:20454657

Kin discrimination within honey bee (Apis mellifera) colonies: An analysis of the evidence.

PubMed

Breed, M D; Welch, C K; Cruz, R

1994-12-01

Compelling evolutionary arguments lead to the prediction that honey bee workers should discriminate between supersisters and half-sisters within colonies. We review the theoretical support for discrimination during swarming, queen rearing, feeding, and grooming. A survey of the data that tests whether such discrimination takes place shows that, despite substantial effort in a number of laboratories, there is no conclusive evidence for intracolony discrimination in any of the postulated contexts. The strongest suggestive data is in the critical context of queen rearing, but flaws in experimental design or analysis make the best available tests inconclusive. We present new data that shows that cues exist on which discriminations can be made among adult workers in nestmate recognition interactions and in feeding interactions, but our data does not differentiate between subfamily recognition and recognition associated with color phenotypes. We conclude that while selection may favor discrimination between supersisters and half-sisters, as a practical matter such discriminations play no role, or only a minor role, in the biology of the honey bee. Copyright © 1994. Published by Elsevier B.V.

Feature extraction with deep neural networks by a generalized discriminant analysis.

PubMed

Stuhlsatz, André; Lippel, Jens; Zielke, Thomas

2012-04-01

We present an approach to feature extraction that is a generalization of the classical linear discriminant analysis (LDA) on the basis of deep neural networks (DNNs). As for LDA, discriminative features generated from independent Gaussian class conditionals are assumed. This modeling has the advantages that the intrinsic dimensionality of the feature space is bounded by the number of classes and that the optimal discriminant function is linear. Unfortunately, linear transformations are insufficient to extract optimal discriminative features from arbitrarily distributed raw measurements. The generalized discriminant analysis (GerDA) proposed in this paper uses nonlinear transformations that are learnt by DNNs in a semisupervised fashion. We show that the feature extraction based on our approach displays excellent performance on real-world recognition and detection tasks, such as handwritten digit recognition and face detection. In a series of experiments, we evaluate GerDA features with respect to dimensionality reduction, visualization, classification, and detection. Moreover, we show that GerDA DNNs can preprocess truly high-dimensional input data to low-dimensional representations that facilitate accurate predictions even if simple linear predictors or measures of similarity are used.

Multi-class ERP-based BCI data analysis using a discriminant space self-organizing map.

PubMed

Onishi, Akinari; Natsume, Kiyohisa

2014-01-01

Emotional or non-emotional image stimulus is recently applied to event-related potential (ERP) based brain computer interfaces (BCI). Though the classification performance is over 80% in a single trial, a discrimination between those ERPs has not been considered. In this research we tried to clarify the discriminability of four-class ERP-based BCI target data elicited by desk, seal, spider images and letter intensifications. A conventional self organizing map (SOM) and newly proposed discriminant space SOM (ds-SOM) were applied, then the discriminabilites were visualized. We also classify all pairs of those ERPs by stepwise linear discriminant analysis (SWLDA) and verify the visualization of discriminabilities. As a result, the ds-SOM showed understandable visualization of the data with a shorter computational time than the traditional SOM. We also confirmed the clear boundary between the letter cluster and the other clusters. The result was coherent with the classification performances by SWLDA. The method might be helpful not only for developing a new BCI paradigm, but also for the big data analysis.

Differential experiences of discrimination among ethnoracially diverse persons experiencing mental illness and homelessness.

PubMed

Zerger, Suzanne; Bacon, Sarah; Corneau, Simon; Skosireva, Anna; McKenzie, Kwame; Gapka, Susan; O'Campo, Patricia; Sarang, Aseefa; Stergiopoulos, Vicky

2014-12-14

This mixed methods study explored the characteristics of and experiences with perceived discrimination in an ethnically diverse urban sample of adults experiencing homelessness and mental illness. Data were collected in Toronto, Ontario, as part of a 4-year national randomized field trial of the Housing First treatment model. Rates of perceived discrimination were captured from survey questions regarding perceived discrimination among 231 ethnoracially diverse participants with moderate mental health needs. The qualitative component included thirty six in-depth interviews which explored how individuals who bear these multiple identities of oppression navigate stigma and discrimination, and what affects their capacity to do so. Quantitative analysis revealed very high rates of perceived discrimination related to: homelessness/poverty (61.5%), race/ethnicity/skin colour (50.6%) and mental illness/substance use (43.7%). Immigrants and those who had been homeless three or more years reported higher perceived discrimination on all three domains. Analysis of qualitative interviews revealed three common themes related to navigating these experiences of discrimination among participants: 1) social distancing; 2) old and new labels/identities; and, 3) 'homeland' cultures. These study findings underscore poverty and homelessness as major sources of perceived discrimination, and expose underlying complexities in the navigation of multiple identities in responding to stigma and discrimination. Current Controlled Trials ISRCTN42520374 . Registered 18 August 2009.

Penalized discriminant analysis for the detection of wild-grown and cultivated Ganoderma lucidum using Fourier transform infrared spectroscopy.

PubMed

Zhu, Ying; Tan, Tuck Lee

2016-04-15

An effective and simple analytical method using Fourier transform infrared (FTIR) spectroscopy to distinguish wild-grown high-quality Ganoderma lucidum (G. lucidum) from cultivated one is of essential importance for its quality assurance and medicinal value estimation. Commonly used chemical and analytical methods using full spectrum are not so effective for the detection and interpretation due to the complex system of the herbal medicine. In this study, two penalized discriminant analysis models, penalized linear discriminant analysis (PLDA) and elastic net (Elnet),using FTIR spectroscopy have been explored for the purpose of discrimination and interpretation. The classification performances of the two penalized models have been compared with two widely used multivariate methods, principal component discriminant analysis (PCDA) and partial least squares discriminant analysis (PLSDA). The Elnet model involving a combination of L1 and L2 norm penalties enabled an automatic selection of a small number of informative spectral absorption bands and gave an excellent classification accuracy of 99% for discrimination between spectra of wild-grown and cultivated G. lucidum. Its classification performance was superior to that of the PLDA model in a pure L1 setting and outperformed the PCDA and PLSDA models using full wavelength. The well-performed selection of informative spectral features leads to substantial reduction in model complexity and improvement of classification accuracy, and it is particularly helpful for the quantitative interpretations of the major chemical constituents of G. lucidum regarding its anti-cancer effects. Copyright © 2016 Elsevier B.V. All rights reserved.

Discrimination, racial identity, and cytokine levels among African-American adolescents.

PubMed

Brody, Gene H; Yu, Tianyi; Miller, Gregory E; Chen, Edith

2015-05-01

Low-grade inflammation, measured by circulating levels of cytokines, is a pathogenic mechanism for several chronic diseases of aging. Identifying factors related to inflammation among African-American youths may yield insights into mechanisms underlying racial disparities in health. The purpose of the study was to determine whether (1) reported racial discrimination from ages 17-19 years forecasts heightened cytokine levels at the age of 22 years and (2) this association is lower for youths with positive racial identities. A longitudinal research design was used with a community sample of 160 African-Americans who were aged 17 years at the beginning of the study. Discrimination and racial identity were measured with questionnaires, and blood was drawn to measure basal cytokine levels. Ordinary least squares regression analyses were used to examine the hypotheses. After controlling for socioeconomic risk, life stress, depressive symptoms, and body mass index, racial discrimination (β = .307; p < .01), racial identity (β = -.179; p < .05), and their interaction (β = -.180; p < .05) forecast cytokine levels. Youths exposed to high levels of racial discrimination evinced elevated cytokine levels 3 years later. This association was not significant for young adults with positive racial identities. High levels of interpersonal racial discrimination and the development of a positive racial identity operate jointly to determine low-grade inflammation levels that have been found to forecast chronic diseases of aging, such as coronary disease and stroke. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Discriminant Analysis of Student Loan Applications

ERIC Educational Resources Information Center

Dyl, Edward A.; McGann, Anthony F.

1977-01-01

The use of discriminant analysis in identifying potentially "good" versus potentially "bad" student loans is explained. The technique is applied to a sample of 200 student loan applications at the University of Wyoming. (LBH)

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

Determination of five active compounds in Artemisia princeps and A. capillaris based on UPLC-DAD and discrimination of two species with multivariate analysis.

PubMed

Yang, Heejung; Lee, Dong Young; Jeon, Minji; Suh, Youngbae; Sung, Sang Hyun

2014-05-01

Five active compounds, chlorogenic acid, 3,5-di-O-caffeoylquinic acid, 4,5-di-O-caffeoylquinic acid, jaceosidin, and eupatilin, in Artemisia princeps (Compositae) were simultaneously determined by ultra-performance liquid chromatography connected to diode array detector. The morphological resemblance between A. princeps and A. capillaris makes it difficult to properly identify species properly. It occasionally leads to misuse or misapplication in Korean traditional medicine. In the study, the discrimination between A. princeps and A. capillaris was optimally performed by the developed validation method, which resulted in definitely a difference between two species. Also, it was developed the most reliable markers contributing to the discrimination of two species by the multivariate analysis methods, such as a principal component analysis and a partial least squares discrimination analysis.

Analysis of longitudinal diffusion-weighted images in healthy and pathological aging: An ADNI study.

PubMed

Kruggel, Frithjof; Masaki, Fumitaro; Solodkin, Ana

2017-02-15

The widely used framework of voxel-based morphometry for analyzing neuroimages is extended here to model longitudinal imaging data by exchanging the linear model with a linear mixed-effects model. The new approach is employed for analyzing a large longitudinal sample of 756 diffusion-weighted images acquired in 177 subjects of the Alzheimer's Disease Neuroimaging initiative (ADNI). While sample- and group-level results from both approaches are equivalent, the mixed-effect model yields information at the single subject level. Interestingly, the neurobiological relevance of the relevant parameter at the individual level describes specific differences associated with aging. In addition, our approach highlights white matter areas that reliably discriminate between patients with Alzheimer's disease and healthy controls with a predictive power of 0.99 and include the hippocampal alveus, the para-hippocampal white matter, the white matter of the posterior cingulate, and optic tracts. In this context, notably the classifier includes a sub-population of patients with minimal cognitive impairment into the pathological domain. Our classifier offers promising features for an accessible biomarker that predicts the risk of conversion to Alzheimer's disease. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how to apply/ADNI Acknowledgement List.pdf. Significance statement This study assesses neuro-degenerative processes in the brain's white matter as revealed by diffusion-weighted imaging, in order to discriminate healthy from pathological aging in a large sample of elderly subjects. The analysis of time-series examinations in a linear mixed effects model allowed the discrimination of population-based aging processes from individual determinants. We demonstrate that a simple classifier based on white matter imaging data is able to predict the conversion to Alzheimer's disease with a high predictive power. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Meta-analysis of field experiments shows no change in racial discrimination in hiring over time.

PubMed

Quillian, Lincoln; Pager, Devah; Hexel, Ole; Midtbøen, Arnfinn H

2017-10-10

This study investigates change over time in the level of hiring discrimination in US labor markets. We perform a meta-analysis of every available field experiment of hiring discrimination against African Americans or Latinos ( n = 28). Together, these studies represent 55,842 applications submitted for 26,326 positions. We focus on trends since 1989 ( n = 24 studies), when field experiments became more common and improved methodologically. Since 1989, whites receive on average 36% more callbacks than African Americans, and 24% more callbacks than Latinos. We observe no change in the level of hiring discrimination against African Americans over the past 25 years, although we find modest evidence of a decline in discrimination against Latinos. Accounting for applicant education, applicant gender, study method, occupational groups, and local labor market conditions does little to alter this result. Contrary to claims of declining discrimination in American society, our estimates suggest that levels of discrimination remain largely unchanged, at least at the point of hire.

Is it really organic?--multi-isotopic analysis as a tool to discriminate between organic and conventional plants.

PubMed

Laursen, K H; Mihailova, A; Kelly, S D; Epov, V N; Bérail, S; Schjoerring, J K; Donard, O F X; Larsen, E H; Pedentchouk, N; Marca-Bell, A D; Halekoh, U; Olesen, J E; Husted, S

2013-12-01

Novel procedures for analytical authentication of organic plant products are urgently needed. Here we present the first study encompassing stable isotopes of hydrogen, carbon, nitrogen, oxygen, magnesium and sulphur as well as compound-specific nitrogen and oxygen isotope analysis of nitrate for discrimination of organically and conventionally grown plants. The study was based on wheat, barley, faba bean and potato produced in rigorously controlled long-term field trials comprising 144 experimental plots. Nitrogen isotope analysis revealed the use of animal manure, but was unable to discriminate between plants that were fertilised with synthetic nitrogen fertilisers or green manures from atmospheric nitrogen fixing legumes. This limitation was bypassed using oxygen isotope analysis of nitrate in potato tubers, while hydrogen isotope analysis allowed complete discrimination of organic and conventional wheat and barley grains. It is concluded, that multi-isotopic analysis has the potential to disclose fraudulent substitutions of organic with conventionally cultivated plants. Copyright © 2013 Elsevier Ltd. All rights reserved.

Rapid direct analysis to discriminate geographic origin of extra virgin olive oils by flash gas chromatography electronic nose and chemometrics.

PubMed

Melucci, Dora; Bendini, Alessandra; Tesini, Federica; Barbieri, Sara; Zappi, Alessandro; Vichi, Stefania; Conte, Lanfranco; Gallina Toschi, Tullia

2016-08-01

At present, the geographical origin of extra virgin olive oils can be ensured by documented traceability, although chemical analysis may add information that is useful for possible confirmation. This preliminary study investigated the effectiveness of flash gas chromatography electronic nose and multivariate data analysis to perform rapid screening of commercial extra virgin olive oils characterized by a different geographical origin declared in the label. A comparison with solid phase micro extraction coupled to gas chromatography mass spectrometry was also performed. The new method is suitable to verify the geographic origin of extra virgin olive oils based on principal components analysis and discriminant analysis applied to the volatile profile of the headspace as a fingerprint. The selected variables were suitable in discriminating between "100% Italian" and "non-100% Italian" oils. Partial least squares discriminant analysis also allowed prediction of the degree of membership of unknown samples to the classes examined. Copyright © 2016. Published by Elsevier Ltd.

Sub-pattern based multi-manifold discriminant analysis for face recognition

NASA Astrophysics Data System (ADS)

Dai, Jiangyan; Guo, Changlu; Zhou, Wei; Shi, Yanjiao; Cong, Lin; Yi, Yugen

2018-04-01

In this paper, we present a Sub-pattern based Multi-manifold Discriminant Analysis (SpMMDA) algorithm for face recognition. Unlike existing Multi-manifold Discriminant Analysis (MMDA) approach which is based on holistic information of face image for recognition, SpMMDA operates on sub-images partitioned from the original face image and then extracts the discriminative local feature from the sub-images separately. Moreover, the structure information of different sub-images from the same face image is considered in the proposed method with the aim of further improve the recognition performance. Extensive experiments on three standard face databases (Extended YaleB, CMU PIE and AR) demonstrate that the proposed method is effective and outperforms some other sub-pattern based face recognition methods.

A Small Aptamer with Strong and Specific Recognition of the Triphosphate of ATP

PubMed Central

Sazani, Peter L.; Larralde, Rosa

2004-01-01

We report the in vitro selection of an RNA-based ATP aptamer with the ability to discriminate between adenosine ligands based on their 5‘ phosphorylation state. Previous selection of ATP aptamers yielded molecules that do not significantly discriminate between ligands at the 5‘ position. By applying a selective pressure that demands recognition of the 5‘ triphosphate, we obtained an aptamer that binds to ATP with a Kd of approximately 5 μM, and to AMP with a Kd of approximately 5.5 mM, a difference of 1100-fold. This aptamer demonstrates the ability of small RNAs to interact with negatively charged moieties. PMID:15237981

Multipolarization radar images for geologic mapping and vegetation discrimination

NASA Technical Reports Server (NTRS)

Evans, D. L.; Farr, T. G.; Ford, J. P.; Thompson, T. W.; Werner, C. L.

1986-01-01

NASA has developed an airborne SAR that simultaneously yields image data in four linear polarizations in L-band with 10-m resolution over a swath of about 10 km. Signal data are recorded both optically and digitally and annotated in each of the channels to facilitate completely automated digital correlation. Comparison of the relative intensities of the different polarizations furnishes discriminatory mapping information. Local intensity variations in like-polarization images result from topographic effects, while strong cross polarization responses denote the effects of vegetation cover and, in some cases, possible scattering from the subsurface. In each of the areas studied, multiple polarization data led to the discrimination and mapping of unique surface unit features.

Escherichia coli identification and strain discrimination using nanosecond laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Diedrich, Jonathan; Rehse, Steven J.; Palchaudhuri, Sunil

2007-04-01

Three strains of Escherichia coli, one strain of environmental mold, and one strain of Candida albicans yeast have been analyzed by laser-induced breakdown spectroscopy using nanosecond laser pulses. All microorganisms were analyzed while still alive and with no sample preparation. Nineteen atomic and ionic emission lines have been identified in the spectrum, which is dominated by calcium, magnesium, and sodium. A discriminant function analysis has been used to discriminate between the biotypes and E. coli strains. This analysis showed efficient discrimination between laser-induced breakdown spectroscopy spectra from different strains of a single bacteria species.

Gender Wage Inequality and Economic Growth: Is There Really a Puzzle?-A Comment.

PubMed

Schober, Thomas; Winter-Ebmer, Rudolf

2011-08-01

Seguino (2000) shows that gender wage discrimination in export-oriented semi-industrialized countries might be fostering investment and growth in general. While the original analysis does not have internationally comparable wage discrimination data, we replicate the analysis using data from a meta-study on gender wage discrimination and do not find any evidence that more discrimination might further economic growth-on the contrary: if anything the impact of gender inequality is negative for growth. Standing up for more gender equality-also in terms of wages-is good for equity considerations and at least not negative for growth.

A canonical discriminant analysis to study the association between milk fatty acids of ruminal origin and milk fat depression in dairy cows.

PubMed

Conte, G; Dimauro, C; Serra, A; Macciotta, N P P; Mele, M

2018-04-04

Although milk fat depression (MFD) has been observed and described since the beginning of the last century, all the molecular and biochemical mechanisms involved are still not completely understood. Some fatty acids (FA) originating during rumen biohydrogenation have been proposed as causative elements of MFD. However, contradictory results were obtained when studying the effect of single FA on MFD. An alternative could be the simultaneous evaluation of the effect of many FA using a multivariate approach. The aim of this study was to evaluate the relationship between individual milk FA of ruminal origin and MFD using canonical discriminant analysis, a multivariate technique able to distinguish 2 or more groups on the basis of a pool of variables. In a commercial dairy herd, a diet containing 26% starch on a DM basis induced an unintentional MFD syndrome in 14 cows out of 40. Milk yielded by these 14 animals showed a fat content lower than 50% of the ordinary value, whereas milk production and protein content were normal. The remaining 26 cows secreted typical milk fat content and therefore were considered the control group, even though they ate the same diet. The stepwise discriminant analysis selected 14 milk FA of ruminal origin most able to distinguish the 2 groups. This restricted pool of FA was used, as variables, in a run of the canonical discriminant analysis that was able to significantly discriminate between the 2 groups. Out of the 14 FA, 5 conjugated linoleic acid isomers (C18:2 trans-10,trans-12, C18:2 trans-8,trans-10, C18:2 trans-11,cis-13, C18:2 cis-9,cis-11, C18:2 cis-10,cis-12) and C15:0 iso were more related to the control group, whereas C18:2 trans-10,cis-12, C16:1 trans-6-7, C16:1 trans-9, C18:1 trans-6-8, C18:1 trans-9, C18:1 trans-10, C18:1 cis-11, and C18:3n-3 were positively associated with the MFD group, allowing a complete discrimination. On the basis of these results, we can conclude that (1) the shift of ruminal biohydrogenation from C18:1 trans-11 to C18:1 trans-10 seemed to be strongly associated with MFD; (2) at the same time, other C18:1 trans isomers showed a similar association; (3) on the contrary, conjugated linoleic acid isomers other than C18:2 trans-10,cis-12 seemed to be associated with a normal fat secretion. Results confirmed that MFD is the consequence of a combined effect of the outflow of many ruminal FA, which collectively affect mammary fat synthesis. Because the animals of the 2 groups were fed the same diet, these results suggested that factors other than diet are involved in the MFD syndrome. Feeding behavior (i.e., ability to select dietary ingredients in a total mixed ration), rumen environment and the composition of ruminal bacteria are additional factors able to modify the products of rumen biohydrogenation. Results of the present work confirmed that the multivariate approach can be a useful tool to evaluate a metabolic pathway that involves several parameters, providing interesting suggestions about the role of some FA involved in MFD. However, results about the MFD syndrome obtained in the present research require a deep molecular investigation to be confirmed. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Discriminant Analysis of Time Series in the Presence of Within-Group Spectral Variability.

PubMed

Krafty, Robert T

2016-07-01

Many studies record replicated time series epochs from different groups with the goal of using frequency domain properties to discriminate between the groups. In many applications, there exists variation in cyclical patterns from time series in the same group. Although a number of frequency domain methods for the discriminant analysis of time series have been explored, there is a dearth of models and methods that account for within-group spectral variability. This article proposes a model for groups of time series in which transfer functions are modeled as stochastic variables that can account for both between-group and within-group differences in spectra that are identified from individual replicates. An ensuing discriminant analysis of stochastic cepstra under this model is developed to obtain parsimonious measures of relative power that optimally separate groups in the presence of within-group spectral variability. The approach possess favorable properties in classifying new observations and can be consistently estimated through a simple discriminant analysis of a finite number of estimated cepstral coefficients. Benefits in accounting for within-group spectral variability are empirically illustrated in a simulation study and through an analysis of gait variability.

Discrimination of the rare medicinal plant Dendrobium officinale based on naringenin, bibenzyl, and polysaccharides.

PubMed

Chen, Xiaomei; Wang, Fangfei; Wang, Yunqiang; Li, Xuelan; Wang, Airong; Wang, Chunlan; Guo, Shunxing

2012-12-01

The aim of this study was to establish a method for discriminating Dendrobium officinale from four of its close relatives Dendrobium chrysanthum, Dendrobium crystallinum, Dendrobium aphyllum and Dendrobium devonianum based on chemical composition analysis. We analyzed 62 samples of 24 Dendrobium species. High performance liquid chromatography analysis confirmed that the four low molecular weight compounds 4',5,7-trihydroxyflavanone (naringenin), 3,4-dihydroxy-4',5-dime-thoxybibenzyl (DDB-2), 3',4-dihydroxy-3,5'-dimethoxybibenzyl (gigantol), and 4,4'-dihydroxy-3,3',5-trimethoxybibenzy (moscatilin), were common in the genus. The phenol-sulfuric acid method was used to quantify polysaccharides, and the monosaccharide composition of the polysaccharides was determined by gas chromatography. Stepwise discriminant analysis was used to differentiate among the five closely related species based on the chemical composition analysis. This proved to be a simple and accurate approach for discriminating among these species. The results also showed that the polysaccharide content, the amounts of the four low molecular weight compounds, and the mannose to glucose ratio, were important factors for species discriminant. Therefore, we propose that a chemical analysis based on quantification of naringenin, bibenzyl, and polysaccharides is effective for identifying D. officinale.

Alteration mapping at Goldfield, Nevada, by cluster and discriminant analysis of Landsat digital data. [mapping of hydrothermally altered volcanic rocks

NASA Technical Reports Server (NTRS)

Ballew, G.

1977-01-01

The ability of Landsat multispectral digital data to differentiate among 62 combinations of rock and alteration types at the Goldfield mining district of Western Nevada was investigated by using statistical techniques of cluster and discriminant analysis. Multivariate discriminant analysis was not effective in classifying each of the 62 groups, with classification results essentially the same whether data of four channels alone or combined with six ratios of channels were used. Bivariate plots of group means revealed a cluster of three groups including mill tailings, basalt and all other rock and alteration types. Automatic hierarchical clustering based on the fourth dimensional Mahalanobis distance between group means of 30 groups having five or more samples was performed using Johnson's HICLUS program. The results of the cluster analysis revealed hierarchies of mill tailings vs. natural materials, basalt vs. non-basalt, highly reflectant rocks vs. other rocks and exclusively unaltered rocks vs. predominantly altered rocks. The hierarchies were used to determine the order in which sets of multiple discriminant analyses were to be performed and the resulting discriminant functions were used to produce a map of geology and alteration which has an overall accuracy of 70 percent for discriminating exclusively altered rocks from predominantly altered rocks.

MATRIX DISCRIMINANT ANALYSIS WITH APPLICATION TO COLORIMETRIC SENSOR ARRAY DATA

PubMed Central

Suslick, Kenneth S.

2014-01-01

With the rapid development of nano-technology, a “colorimetric sensor array” (CSA) which is referred to as an optical electronic nose has been developed for the identification of toxicants. Unlike traditional sensors which rely on a single chemical interaction, CSA can measure multiple chemical interactions by using chemo-responsive dyes. The color changes of the chemo-responsive dyes are recorded before and after exposure to toxicants and serve as a template for classification. The color changes are digitalized in the form of a matrix with rows representing dye effects and columns representing the spectrum of colors. Thus, matrix-classification methods are highly desirable. In this article, we develop a novel classification method, matrix discriminant analysis (MDA), which is a generalization of linear discriminant analysis (LDA) for the data in matrix form. By incorporating the intrinsic matrix-structure of the data in discriminant analysis, the proposed method can improve CSA’s sensitivity and more importantly, specificity. A penalized MDA method, PMDA, is also introduced to further incorporate sparsity structure in discriminant function. Numerical studies suggest that the proposed MDA and PMDA methods outperform LDA and other competing discriminant methods for matrix predictors. The asymptotic consistency of MDA is also established. R code and data are available online as supplementary material. PMID:26783371

Proof of Principle for a Real-Time Pathogen Isolation Media Diagnostic: The Use of Laser-Induced Breakdown Spectroscopy to Discriminate Bacterial Pathogens and Antimicrobial-Resistant Staphylococcus aureus Strains Grown on Blood Agar

PubMed Central

Multari, Rosalie A.; Cremers, David A.; Bostian, Melissa L.; Dupre, Joanne M.

2013-01-01

Laser-Induced Breakdown Spectroscopy (LIBS) is a rapid, in situ, diagnostic technique in which light emissions from a laser plasma formed on the sample are used for analysis allowing automated analysis results to be available in seconds to minutes. This speed of analysis coupled with little or no sample preparation makes LIBS an attractive detection tool. In this study, it is demonstrated that LIBS can be utilized to discriminate both the bacterial species and strains of bacterial colonies grown on blood agar. A discrimination algorithm was created based on multivariate regression analysis of spectral data. The algorithm was deployed on a simulated LIBS instrument system to demonstrate discrimination capability using 6 species. Genetically altered Staphylococcus aureus strains grown on BA, including isogenic sets that differed only by the acquisition of mutations that increase fusidic acid or vancomycin resistance, were also discriminated. The algorithm successfully identified all thirteen cultures used in this study in a time period of 2 minutes. This work provides proof of principle for a LIBS instrumentation system that could be developed for the rapid discrimination of bacterial species and strains demonstrating relatively minor genomic alterations using data collected directly from pathogen isolation media. PMID:24109513

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars.

PubMed

Hu, Boran; Yue, Yaqing; Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W

2015-01-01

Proton nuclear magnetic resonance spectroscopy coupled multivariate analysis (1H NMR-PCA/PLS-DA) is an important tool for the discrimination of wine products. Although 1H NMR has been shown to discriminate wines of different cultivars, a grape genetic component of the discrimination has been inferred only from discrimination of cultivars of undefined genetic homology and in the presence of many confounding environmental factors. We aimed to confirm the influence of grape genotypes in the absence of those factors. We applied 1H NMR-PCA/PLS-DA and hierarchical cluster analysis (HCA) to wines from five, variously genetically-related grapevine (V. vinifera) cultivars; all grown similarly on the same site and vinified similarly. We also compared the semi-quantitative profiles of the discriminant metabolites of each cultivar with previously reported chemical analyses. The cultivars were clearly distinguishable and there was a general correlation between their grouping and their genetic homology as revealed by recent genomic studies. Between cultivars, the relative amounts of several of the cultivar-related discriminant metabolites conformed closely with reported chemical analyses. Differences in grape-derived metabolites associated with genetic differences alone are a major source of 1H NMR-based discrimination of wines and 1H NMR has the capacity to discriminate between very closely related cultivars. The study confirms that genetic variation among grape cultivars alone can account for the discrimination of wine by 1H NMR-PCA/PLS and indicates that 1H NMR spectra of wine of single grape cultivars may in future be used in tandem with hierarchical cluster analysis to elucidate genetic lineages and metabolomic relations of grapevine cultivars. In the absence of genetic information, for example, where predecessor varieties are no longer extant, this may be a particularly useful approach.

Credit scoring analysis using kernel discriminant

NASA Astrophysics Data System (ADS)

Widiharih, T.; Mukid, M. A.; Mustafid

2018-05-01

Credit scoring model is an important tool for reducing the risk of wrong decisions when granting credit facilities to applicants. This paper investigate the performance of kernel discriminant model in assessing customer credit risk. Kernel discriminant analysis is a non- parametric method which means that it does not require any assumptions about the probability distribution of the input. The main ingredient is a kernel that allows an efficient computation of Fisher discriminant. We use several kernel such as normal, epanechnikov, biweight, and triweight. The models accuracy was compared each other using data from a financial institution in Indonesia. The results show that kernel discriminant can be an alternative method that can be used to determine who is eligible for a credit loan. In the data we use, it shows that a normal kernel is relevant to be selected for credit scoring using kernel discriminant model. Sensitivity and specificity reach to 0.5556 and 0.5488 respectively.

Discriminant analysis of resting-state functional connectivity patterns on the Grassmann manifold

NASA Astrophysics Data System (ADS)

Fan, Yong; Liu, Yong; Jiang, Tianzi; Liu, Zhening; Hao, Yihui; Liu, Haihong

2010-03-01

The functional networks, extracted from fMRI images using independent component analysis, have been demonstrated informative for distinguishing brain states of cognitive functions and neurological diseases. In this paper, we propose a novel algorithm for discriminant analysis of functional networks encoded by spatial independent components. The functional networks of each individual are used as bases for a linear subspace, referred to as a functional connectivity pattern, which facilitates a comprehensive characterization of temporal signals of fMRI data. The functional connectivity patterns of different individuals are analyzed on the Grassmann manifold by adopting a principal angle based subspace distance. In conjunction with a support vector machine classifier, a forward component selection technique is proposed to select independent components for constructing the most discriminative functional connectivity pattern. The discriminant analysis method has been applied to an fMRI based schizophrenia study with 31 schizophrenia patients and 31 healthy individuals. The experimental results demonstrate that the proposed method not only achieves a promising classification performance for distinguishing schizophrenia patients from healthy controls, but also identifies discriminative functional networks that are informative for schizophrenia diagnosis.

Psychometric Properties of the Persian Version of the Social Anxiety - Acceptance and Action Questionnaire.

PubMed

Soltani, Esmail; Bahrainian, Seyed Abdolmajid; Masjedi Arani, Abbas; Farhoudian, Ali; Gachkar, Latif

2016-06-01

Social anxiety disorder is often related to specific impairment or distress in different areas of life, including occupational, social and family settings. The purpose of the present study was to examine the psychometric properties of the persian version of the social anxiety-acceptance and action questionnaire (SA-AAQ) in university students. In this descriptive cross-sectional study, 324 students from Shahid Beheshti University of Medical Sciences participated via the cluster sampling method during year 2015. Factor analysis by the principle component analysis method, internal consistency analysis, and convergent and divergent validity were conducted to examine the validity of the SA-AAQ. To calculate the reliability of the SA-AAQ, Cronbach's alpha and test-retest reliability were used. The results from factor analysis by principle component analysis method yielded three factors that were named acceptance, action and non-judging of experience. The three-factor solution explained 51.82% of the variance. Evidence for the internal consistency of SA-AAQ was obtained via calculating correlations between SA-AAQ and its subscales. Support for convergent and discriminant validity of the SA-AAQ via its correlations with the acceptance and action questionnaire - II, social interaction anxiety scale, cognitive fusion questionnaire, believability of anxious feelings and thoughts questionnaire, valued living questionnaire and WHOQOL- BREF was obtained. The reliability of the SA-AAQ via calculating Cronbach's alpha and test-retest coefficients yielded values of 0.84 and 0.84, respectively. The Iranian version of the SA-AAQ has acceptable levels of psychometric properties in university students. The SA-AAQ is a valid and reliable measure to be utilized in research investigations and therapeutic interventions.

Seismic Analysis of Three Bomb Explosions in Turkey

NASA Astrophysics Data System (ADS)

Necmioglu, O.; Semin, K. U.; Kocak, S.; Destici, C.; Teoman, U.; Ozel, N. M.

2016-12-01

Seismic analysis of three vehicle-installed bomb explosions occurred on 13 March 2016 in Ankara, 12 May 2016 in Diyarbakır and 9 July 2016 in Mardin have been conducted using data from the nearest stations (LOD, DYBB and MAZI) of the Boğaziçi University - Kandilli Observatory and Earthquake Research Institute's (KOERI) seismic network and compared with low-magnitude earthquakes in similar distance based on phase readings and frequency content. Amplitude spectra has been compared through Fourier transformation and earthquake-explosion frequency discrimination has been performed using various filter bands. Time-domain and spectral analysis have been performed using Geotool software provided by CTBTO. Local magnitude (ML) values have been calculated for each explosion by removing instrument-response and adding Wood-Anderson type instrument response. Approximate amount of explosives used in these explosions have been determined using empirical methods of Koper (2002). Preliminary results indicated that 16 tons TNT equivalent explosives have been used in 12 May 2016 Diyarbakır explosion, which is very much in accordance with the media reports claiming 15 tons of TNT. Our analysis for 9 July 2016 Mardin explosion matched the reported 5 tons of explosives. Results concerning 13 March 2016 Ankara explosion indicated that approximately 1,7 ton of TNT equivalent explosives were used in the attack whereas security and intelligence reports claimed 300 kg explosives as a combination of TNT, RDX and ammonium nitrate. The overestimated results obtained in our analysis for the Ankara explosion may be related due to i) high relative effectiveness factor of the RDX component of the explosive ii) inefficiency of Koper (2002) method in lower yields (since the method was developed using explosions with yields of 3-12 tons of TNT), iii) combination of both.

Psychometric Properties of the Persian Version of the Social Anxiety - Acceptance and Action Questionnaire

PubMed Central

Soltani, Esmail; Bahrainian, Seyed Abdolmajid; Masjedi Arani, Abbas; Farhoudian, Ali; Gachkar, Latif

2016-01-01

Background Social anxiety disorder is often related to specific impairment or distress in different areas of life, including occupational, social and family settings. Objective The purpose of the present study was to examine the psychometric properties of the persian version of the social anxiety-acceptance and action questionnaire (SA-AAQ) in university students. Materials and Methods In this descriptive cross-sectional study, 324 students from Shahid Beheshti University of Medical Sciences participated via the cluster sampling method during year 2015. Factor analysis by the principle component analysis method, internal consistency analysis, and convergent and divergent validity were conducted to examine the validity of the SA-AAQ. To calculate the reliability of the SA-AAQ, Cronbach’s alpha and test-retest reliability were used. Results The results from factor analysis by principle component analysis method yielded three factors that were named acceptance, action and non-judging of experience. The three-factor solution explained 51.82% of the variance. Evidence for the internal consistency of SA-AAQ was obtained via calculating correlations between SA-AAQ and its subscales. Support for convergent and discriminant validity of the SA-AAQ via its correlations with the acceptance and action questionnaire - II, social interaction anxiety scale, cognitive fusion questionnaire, believability of anxious feelings and thoughts questionnaire, valued living questionnaire and WHOQOL- BREF was obtained. The reliability of the SA-AAQ via calculating Cronbach’s alpha and test-retest coefficients yielded values of 0.84 and 0.84, respectively. Conclusions The Iranian version of the SA-AAQ has acceptable levels of psychometric properties in university students. The SA-AAQ is a valid and reliable measure to be utilized in research investigations and therapeutic interventions. PMID:27803719

Score-moment combined linear discrimination analysis (SMC-LDA) as an improved discrimination method.

PubMed

Han, Jintae; Chung, Hoeil; Han, Sung-Hwan; Yoon, Moon-Young

2007-01-01

A new discrimination method called the score-moment combined linear discrimination analysis (SMC-LDA) has been developed and its performance has been evaluated using three practical spectroscopic datasets. The key concept of SMC-LDA was to use not only the score from principal component analysis (PCA), but also the moment of the spectrum, as inputs for LDA to improve discrimination. Along with conventional score, moment is used in spectroscopic fields as an effective alternative for spectral feature representation. Three different approaches were considered. Initially, the score generated from PCA was projected onto a two-dimensional feature space by maximizing Fisher's criterion function (conventional PCA-LDA). Next, the same procedure was performed using only moment. Finally, both score and moment were utilized simultaneously for LDA. To evaluate discrimination performances, three different spectroscopic datasets were employed: (1) infrared (IR) spectra of normal and malignant stomach tissue, (2) near-infrared (NIR) spectra of diesel and light gas oil (LGO) and (3) Raman spectra of Chinese and Korean ginseng. For each case, the best discrimination results were achieved when both score and moment were used for LDA (SMC-LDA). Since the spectral representation character of moment was different from that of score, inclusion of both score and moment for LDA provided more diversified and descriptive information.

Fourier transform infrared spectroscopy combined with chemometrics for discrimination of Curcuma longa, Curcuma xanthorrhiza and Zingiber cassumunar.

PubMed

Rohaeti, Eti; Rafi, Mohamad; Syafitri, Utami Dyah; Heryanto, Rudi

2015-02-25

Turmeric (Curcuma longa), java turmeric (Curcuma xanthorrhiza) and cassumunar ginger (Zingiber cassumunar) are widely used in traditional Indonesian medicines (jamu). They have similar color for their rhizome and possess some similar uses, so it is possible to substitute one for the other. The identification and discrimination of these closely-related plants is a crucial task to ensure the quality of the raw materials. Therefore, an analytical method which is rapid, simple and accurate for discriminating these species using Fourier transform infrared spectroscopy (FTIR) combined with some chemometrics methods was developed. FTIR spectra were acquired in the mid-IR region (4000-400 cm(-1)). Standard normal variate, first and second order derivative spectra were compared for the spectral data. Principal component analysis (PCA) and canonical variate analysis (CVA) were used for the classification of the three species. Samples could be discriminated by visual analysis of the FTIR spectra by using their marker bands. Discrimination of the three species was also possible through the combination of the pre-processed FTIR spectra with PCA and CVA, in which CVA gave clearer discrimination. Subsequently, the developed method could be used for the identification and discrimination of the three closely-related plant species. Copyright © 2014 Elsevier B.V. All rights reserved.

An Analysis of the Association between Perceived Discrimination and Self-Reported Health among University Students in Southwest Florida

ERIC Educational Resources Information Center

McFarland, Renee L.

2013-01-01

The experience of discrimination is a complex phenomenon. At present, there are few studies that have captured the experience of discrimination on a predominately white university campus. This study was designed to investigate the association between perceived discrimination and self-reported health outcomes among university students in Southwest…

Recommendation for incorporation of a different lymph node scoring system in future AJCC N category for oral cancer.

PubMed

Lee, Ching-Chih; Su, Yu-Chieh; Hung, Shih-Kai; Chen, Po-Chun; Huang, Chung-I; Huang, Wei-Lun; Lin, Yu-Wei; Yang, Ching-Chieh

2017-10-26

To compare the prognostic value of 3 different lymph node scoring systems " log odds of positive nodes (LODDS), lymph node ratio (rN), and lymph node yield " in an effort to improve the staging of oral cancer. We identified 3958 oral cancer patients from Surveillance, Epidemiology, and End Results database from 2007 to 2013. In univariate analysis, LODDS, pN, rN, and lymph node yield were prognostic factors for 5-year disease-specific survival (DSS) and overall survival (OS). Multivariate analysis indicated that patients with LODDS 4 had worst 5-year DSS and OS. Stage migration occurred in pN1 and pN2 patients with LODDS 4. In pN1 patients, those with LODDS 4 had the worst 5-year DSS (41.2%) and OS (31.6%) than patients with pN1 and LODDS 2-3. In pN2 patients, those with LODDS4 had the worst 5-year DSS (34.5%) and OS (27.4%) than patients with pN2 and LODDS 2-3. The proposed staging system, which incorporates LODDS with AJCC pN, had better discriminability and prediction accuracy for predicting survival. We also noted that patients with LODDS 4 given adjuvant radiotherapy had better 5-year DSS and OS. The LODDS should be considered as a future candidate measurement for N category in oral cancer.

Using Assistive Technology Outcomes Research to Inform Policy Related to the Employment of Individuals with Disabilities

ERIC Educational Resources Information Center

Mendelsohn, Steven; Edyburn, Dave L.; Rust, Kathy L.; Schwanke, Todd D.; Smith, Roger O.

2008-01-01

We know that work is recognized as a central component of life for individuals with and without disabilities. It yields many physical and psychological benefits to the individual while simultaneously contributing numerous benefits to society. Lawmakers have enacted a plethora of laws designed to prevent discrimination, provide incentives for…

Summary of Seismic Discrimination and Explosion Yield Determination Research

DTIC Science & Technology

1978-11-01

measured and nuemrically simulated displacements .. ........... ... 56 21 Comparison of experimental and numerically simulated source functions expressed...as RVP transforms ...... ..................... 5 22 Comparison of measured and predicted displace- ments for Test 1 ..... .............. ... 57 23...Comparison of measured and predicted displace- ments for the cratering shot (Test 8) . . . . 59 24 The vertical displacement from the complete two

Relationships between tree height and carbon isotope discrimination

Treesearch

Nate G. McDowell; Barbara J. Bond; Lee T. Dickman; Michael G. Ryan; David Whitehead

2011-01-01

Understanding how tree size impacts leaf- and crown-level gas exchange is essential to predicting forest yields and carbon and water budgets. The stable carbon isotope ratio of organic matter has been used to examine the relationship of gas exchange to tree size for a host of species because it carries a temporally integrated signature of foliar photosynthesis and...

Lexico-Semantic Structure and the Word-Frequency Effect in Recognition Memory

ERIC Educational Resources Information Center

Monaco, Joseph D.; Abbott, L. F.; Kahana, Michael J.

2007-01-01

The word-frequency effect (WFE) in recognition memory refers to the finding that more rare words are better recognized than more common words. We demonstrate that a familiarity-discrimination model operating on data from a semantic word-association space yields a robust WFE in data on both hit rates and false-alarm rates. Our modeling results…

Diagnosis of human malignancies using laser-induced breakdown spectroscopy in combination with chemometric methods

NASA Astrophysics Data System (ADS)

Chen, Xue; Li, Xiaohui; Yu, Xin; Chen, Deying; Liu, Aichun

2018-01-01

Diagnosis of malignancies is a challenging clinical issue. In this work, we present quick and robust diagnosis and discrimination of lymphoma and multiple myeloma (MM) using laser-induced breakdown spectroscopy (LIBS) conducted on human serum samples, in combination with chemometric methods. The serum samples collected from lymphoma and MM cancer patients and healthy controls were deposited on filter papers and ablated with a pulsed 1064 nm Nd:YAG laser. 24 atomic lines of Ca, Na, K, H, O, and N were selected for malignancy diagnosis. Principal component analysis (PCA), linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), and k nearest neighbors (kNN) classification were applied to build the malignancy diagnosis and discrimination models. The performances of the models were evaluated using 10-fold cross validation. The discrimination accuracy, confusion matrix and receiver operating characteristic (ROC) curves were obtained. The values of area under the ROC curve (AUC), sensitivity and specificity at the cut-points were determined. The kNN model exhibits the best performances with overall discrimination accuracy of 96.0%. Distinct discrimination between malignancies and healthy controls has been achieved with AUC, sensitivity and specificity for healthy controls all approaching 1. For lymphoma, the best discrimination performance values are AUC = 0.990, sensitivity = 0.970 and specificity = 0.956. For MM, the corresponding values are AUC = 0.986, sensitivity = 0.892 and specificity = 0.994. The results show that the serum-LIBS technique can serve as a quick, less invasive and robust method for diagnosis and discrimination of human malignancies.

MO-F-CAMPUS-I-04: Characterization of Fan Beam Coded Aperture Coherent Scatter Spectral Imaging Methods for Differentiation of Normal and Neoplastic Breast Structures

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

Morris, R; Albanese, K; Lakshmanan, M

Purpose: This study intends to characterize the spectral and spatial resolution limits of various fan beam geometries for differentiation of normal and neoplastic breast structures via coded aperture coherent scatter spectral imaging techniques. In previous studies, pencil beam raster scanning methods using coherent scatter computed tomography and selected volume tomography have yielded excellent results for tumor discrimination. However, these methods don’t readily conform to clinical constraints; primarily prolonged scan times and excessive dose to the patient. Here, we refine a fan beam coded aperture coherent scatter imaging system to characterize the tradeoffs between dose, scan time and image quality formore » breast tumor discrimination. Methods: An X-ray tube (125kVp, 400mAs) illuminated the sample with collimated fan beams of varying widths (3mm to 25mm). Scatter data was collected via two linear-array energy-sensitive detectors oriented parallel and perpendicular to the beam plane. An iterative reconstruction algorithm yields images of the sample’s spatial distribution and respective spectral data for each location. To model in-vivo tumor analysis, surgically resected breast tumor samples were used in conjunction with lard, which has a form factor comparable to adipose (fat). Results: Quantitative analysis with current setup geometry indicated optimal performance for beams up to 10mm wide, with wider beams producing poorer spatial resolution. Scan time for a fixed volume was reduced by a factor of 6 when scanned with a 10mm fan beam compared to a 1.5mm pencil beam. Conclusion: The study demonstrates the utility of fan beam coherent scatter spectral imaging for differentiation of normal and neoplastic breast tissues has successfully reduced dose and scan times whilst sufficiently preserving spectral and spatial resolution. Future work to alter the coded aperture and detector geometries could potentially allow the use of even wider fans, thereby making coded aperture coherent scatter imaging a clinically viable method for breast cancer detection. United States Department of Homeland Security; Duke University Medical Center - Department of Radiology; Carl E Ravin Advanced Imaging Laboratories; Duke University Medical Physics Graduate Program.« less

Cascaded systems analysis of noise and detectability in dual-energy cone-beam CT

PubMed Central

Gang, Grace J.; Zbijewski, Wojciech; Webster Stayman, J.; Siewerdsen, Jeffrey H.

2012-01-01

Purpose: Dual-energy computed tomography and dual-energy cone-beam computed tomography (DE-CBCT) are promising modalities for applications ranging from vascular to breast, renal, hepatic, and musculoskeletal imaging. Accordingly, the optimization of imaging techniques for such applications would benefit significantly from a general theoretical description of image quality that properly incorporates factors of acquisition, reconstruction, and tissue decomposition in DE tomography. This work reports a cascaded systems analysis model that includes the Poisson statistics of x rays (quantum noise), detector model (flat-panel detectors), anatomical background, image reconstruction (filtered backprojection), DE decomposition (weighted subtraction), and simple observer models to yield a task-based framework for DE technique optimization. Methods: The theoretical framework extends previous modeling of DE projection radiography and CBCT. Signal and noise transfer characteristics are propagated through physical and mathematical stages of image formation and reconstruction. Dual-energy decomposition was modeled according to weighted subtraction of low- and high-energy images to yield the 3D DE noise-power spectrum (NPS) and noise-equivalent quanta (NEQ), which, in combination with observer models and the imaging task, yields the dual-energy detectability index (d′). Model calculations were validated with NPS and NEQ measurements from an experimental imaging bench simulating the geometry of a dedicated musculoskeletal extremities scanner. Imaging techniques, including kVp pair and dose allocation, were optimized using d′ as an objective function for three example imaging tasks: (1) kidney stone discrimination; (2) iodine vs bone in a uniform, soft-tissue background; and (3) soft tissue tumor detection on power-law anatomical background. Results: Theoretical calculations of DE NPS and NEQ demonstrated good agreement with experimental measurements over a broad range of imaging conditions. Optimization results suggest a lower fraction of total dose imparted by the low-energy acquisition, a finding consistent with previous literature. The selection of optimal kVp pair reveals the combined effect of both quantum noise and contrast in the kidney stone discrimination and soft-tissue tumor detection tasks, whereas the K-edge effect of iodine was the dominant factor in determining kVp pairs in the iodine vs bone task. The soft-tissue tumor task illustrated the benefit of dual-energy imaging in eliminating anatomical background noise and improving detectability beyond that achievable by single-energy scans. Conclusions: This work established a task-based theoretical framework that is predictive of DE image quality. The model can be utilized in optimizing a broad range of parameters in image acquisition, reconstruction, and decomposition, providing a useful tool for maximizing DE-CBCT image quality and reducing dose. PMID:22894440

Psychometric properties of a Chinese asthma quality of life questionnaire.

PubMed

Wang, Ningqun; Huang, Xiaobo; Chen, Wenqiang; Zhang, Xiaomei; Zhang, Yongsheng; Chen, Yujing

2017-12-01

To assess the acceptability, reliability, validity, and responsiveness of the Chinese Asthma Quality of Life Questionnaire (C-AQLQ) in a sample of Chinese asthma patients. The C-AQLQ and Short Form 36 Health Survey (SF-36) scales were administered to patients at baseline and 3 months later. Asthma severity condition and lung function were evaluated. Necessary data were gathered to assess the psychometric properties such as the feasibility, internal consistency, test-retest reliability, structural validity, discriminant validity, convergent validity, and responsiveness of the C-AQLQ. One hundred and thirty-seven patients completed the investigation. The Cronbach's alpha coefficient for the total scale was 0.96. Factor analysis yielded five factors that generally corresponded to the five proposed subscales. Patients with mild asthma reported higher scores than patients with moderate/severe asthma on all subscales other than environmental stimuli. Lung function measurement and the asthma severity score correlated significantly with domains of the C-AQOL but with fewer domains of the SF-36. The questionnaire detected within-subject changes in patients' asthma status during follow-up. Results indicated preliminary support that the C-AQLQ is a reliable, valid, discriminating, and responsive measure of quality of life in Chinese asthma patients. It is more sensitive than the generic SF-36 in detecting differences in asthma severity.

A Search for WIMP Dark Matter Using an Optimized Chi-square Technique on the Final Data from the Cryogenic Dark Matter Search Experiment (CDMS II)

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

Manungu Kiveni, Joseph

2012-12-01

This dissertation describes the results of a WIMP search using CDMS II data sets accumulated at the Soudan Underground Laboratory in Minnesota. Results from the original analysis of these data were published in 2009; two events were observed in the signal region with an expected leakage of 0.9 events. Further investigation revealed an issue with the ionization-pulse reconstruction algorithm leading to a software upgrade and a subsequent reanalysis of the data. As part of the reanalysis, I performed an advanced discrimination technique to better distinguish (potential) signal events from backgrounds using a 5-dimensional chi-square method. This dataanalysis technique combines themore » event information recorded for each WIMP-search event to derive a backgrounddiscrimination parameter capable of reducing the expected background to less than one event, while maintaining high efficiency for signal events. Furthermore, optimizing the cut positions of this 5-dimensional chi-square parameter for the 14 viable germanium detectors yields an improved expected sensitivity to WIMP interactions relative to previous CDMS results. This dissertation describes my improved (and optimized) discrimination technique and the results obtained from a blind application to the reanalyzed CDMS II WIMP-search data.« less

CONCENTRIC DECILE SEGMENTATION OF WHITE AND HYPOPIGMENTED AREAS IN DERMOSCOPY IMAGES OF SKIN LESIONS ALLOWS DISCRIMINATION OF MALIGNANT MELANOMA

PubMed Central

Dalal, Ankur; Moss, Randy H.; Stanley, R. Joe; Stoecker, William V.; Gupta, Kapil; Calcara, David A.; Xu, Jin; Shrestha, Bijaya; Drugge, Rhett; Malters, Joseph M.; Perry, Lindall A.

2011-01-01

Dermoscopy, also known as dermatoscopy or epiluminescence microscopy (ELM), permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. White areas, prominent in early malignant melanoma and melanoma in situ, contribute to early detection of these lesions. An adaptive detection method has been investigated to identify white and hypopigmented areas based on lesion histogram statistics. Using the Euclidean distance transform, the lesion is segmented in concentric deciles. Overlays of the white areas on the lesion deciles are determined. Calculated features of automatically detected white areas include lesion decile ratios, normalized number of white areas, absolute and relative size of largest white area, relative size of all white areas, and white area eccentricity, dispersion, and irregularity. Using a back-propagation neural network, the white area statistics yield over 95% diagnostic accuracy of melanomas from benign nevi. White and hypopigmented areas in melanomas tend to be central or paracentral. The four most powerful features on multivariate analysis are lesion decile ratios. Automatic detection of white and hypopigmented areas in melanoma can be accomplished using lesion statistics. A neural network can achieve good discrimination of melanomas from benign nevi using these areas. Lesion decile ratios are useful white area features. PMID:21074971

The Invariance Hypothesis Implies Domain-Specific Regions in Visual Cortex

PubMed Central

Leibo, Joel Z.; Liao, Qianli; Anselmi, Fabio; Poggio, Tomaso

2015-01-01

Is visual cortex made up of general-purpose information processing machinery, or does it consist of a collection of specialized modules? If prior knowledge, acquired from learning a set of objects is only transferable to new objects that share properties with the old, then the recognition system’s optimal organization must be one containing specialized modules for different object classes. Our analysis starts from a premise we call the invariance hypothesis: that the computational goal of the ventral stream is to compute an invariant-to-transformations and discriminative signature for recognition. The key condition enabling approximate transfer of invariance without sacrificing discriminability turns out to be that the learned and novel objects transform similarly. This implies that the optimal recognition system must contain subsystems trained only with data from similarly-transforming objects and suggests a novel interpretation of domain-specific regions like the fusiform face area (FFA). Furthermore, we can define an index of transformation-compatibility, computable from videos, that can be combined with information about the statistics of natural vision to yield predictions for which object categories ought to have domain-specific regions in agreement with the available data. The result is a unifying account linking the large literature on view-based recognition with the wealth of experimental evidence concerning domain-specific regions. PMID:26496457

Psychometric properties of the French versions of the Perceived Stress Scale.

PubMed

Lesage, Francois-Xavier; Berjot, Sophie; Deschamps, Frederic

2012-06-01

This study was conducted to examine the psychometric properties of the French versions of the Perceived Stress Scale (PSS) and to compare the appropriateness of the three versions of this scale (14 items, 10 items, or 4 items) in a sample of workers. Five hundred and one workers were randomly selected in several occupational health care centers of the North of France during 2010. Participants completed a questionnaire including demographic variables and the PSS. The psychometric properties of this scale were analyzed: internal consistency, factorial structure, and discriminative sensibility. For the PSS-14 and PSS-10, the Exploratory Factor Analysis (EFA) provided a two-factor structure, corresponding to the positively and negatively worded items. Those two factors were significantly correlated (r = 0.43 and 0.50, respectively). For the PSS-4, the EFA yielded a one-factor structure. The reliability was high for all three versions of the PSS (Cronbach's α values ranged from 0.73 to 0.84). The results concerning the effects of age, gender, marital, parental and occupational statuses showed that the 10-item version had the best discriminative sensibility. The findings confirmed satisfactory psychometric properties of all the three French versions of the PSS. We recommend the use of the PSS-10 in research settings because of its good psychometric properties.

Lipolysis, lipid peroxidation, and color characteristics of Serrano Hams from Duroc and large white pigs during dry-curing.

PubMed

del Olmo, Ana; Calzada, Javier; Nuñez, Manuel

2013-11-01

Lipolysis, lipid peroxidation, and colorimetric characteristics of Serrano hams from Duroc and Large White pigs along a 15-mo curing period were investigated. Physicochemical parameters of both types of hams evolved similarly during curing. Twelve of 13 free fatty acids (FFAs) increased during curing, eicosatrienoic acid being the only exception. Linoleic, stearic, and arachidonic acids and the minor heptadecanoic acid reached lower concentrations, and the rest of minor FFAs higher concentrations, in Duroc hams than in Large White hams. The index measuring the early stage of lipid peroxidation declined from month 5 onwards, indicating that the phenomenon had been completed by month 5, while the index of the secondary stage of lipid peroxidation increased with curing time. Higher values were found for the 1st index in Duroc hams. Curing affected color parameters. Lightness decreased and redness increased in both types of hams, while yellowness decreased only in Duroc hams. Lower redness values were found for Duroc hams. Major differences in color parameters were found between muscles. Principal components analysis of FFAs yielded 2 main principal components. The 1st factor, correlated with all FFAs excepting eicosatrienoic acid, allowed discrimination between curing times. The 2nd factor, correlated with eicosatrienoic acid, permitted discrimination between breeds. © 2013 Institute of Food Technologists®

In silico analysis of decomposed reflectances of C3 and C4 plants aiming at the effective assessment of crop needs

NASA Astrophysics Data System (ADS)

Baranoski, Gladimir V. G.; Van Leeuwen, Spencer; Chen, Tenn F.

2017-04-01

By separating the surface and subsurface components of foliar hyperspectral signatures using polarization optics, it is possible to enhance the remote discrimination of different plant species and optimize the assessment of different factors associated with their health status. These initiatives, in turn, can lead to higher crop yield and lower environmental impact. It is important to consider, however, that the main varieties of crops, represented by C3 (e.g., soy) and C4 (e.g., maize) plants, have markedly distinct morphological characteristics. Accordingly, the influence of these characteristics on their interactions with impinging light may affect the selection of optimal probe wavelengths for specific applications making use of combined hyperspectral and polarization measurements. In this paper, we compare the sensitivity of the total (including surface and subsurface components) and subsurface reflectance responses of C3 and C4 plants to different spectral and geometrical light incidence conditions. This investigation is supported by measured biophysical data and predictive light transport simulations. The results of our comparisons indicate that the total and subsurface reflectance responses of C3 and C4 plants depict well-defined patterns of sensitivity for varying illumination conditions. We believe that these patterns should be considered in the design of high-fidelity crop discrimination and monitoring procedures.

DNA barcoding in Atlantic Forest plants: What is the best marker for Sapotaceae species identification?

PubMed Central

Vivas, Caio Vinicius; Moraes, Ramiris César Souza; Alves-Araújo, Anderson; Alves, Marccus; Mariano-Neto, Eduardo; van den Berg, Cássio; Gaiotto, Fernanda Amato

2014-01-01

The Atlantic Forest is a phytogeographic domain with a high rate of endemism and large species diversity. The Sapotaceae is a botanical family for which species identification in the Atlantic Forest is difficult. An approach that facilitates species identification in the Sapotaceae is urgently needed because this family includes threatened species and valuable timber species. In this context, DNA barcoding could provide an important tool for identifying species in the Atlantic Forest. In this work, we evaluated four plant barcode markers (matK, rbcL, trnH-psbA and the nuclear ribosomal internal transcribed spacer region - ITS) in 80 samples from 26 species of Sapotaceae that occur in the Atlantic Forest. ITS yielded the highest average interspecific distance (0.122), followed by trnH-psbA (0.019), matK (0.008) and rbcL (0.002). For species discrimination, ITS provided the best results, followed by matK, trnH-psbA and rbcL. Furthermore, the combined analysis of two, three or four markers did not result in higher rates of discrimination than obtained with ITS alone. These results indicate that the ITS region is the best option for molecular identification of Sapotaceae species from the Atlantic Forest. PMID:25505841

Mercury speciation with fluorescent gold nanocluster as a probe.

PubMed

Yang, Jian-Yu; Yang, Ting; Wang, Xiao-Yan; Chen, Ming-Li; Yu, Yong-Liang; Wang, Jian-Hua

2018-05-11

Fluorescent nanoparticles are widely used for sensing biologically significant species. However, it is rarely reported for the discrimination or speciation of metal species. In this work, we report for the first time the speciation of mercury (Hg 2+ ) and methylmercury (CH 3 Hg + ) by taking advantage of the fluorescence feature of folic acid-capped gold nanoclusters (FA-AuNCs). FA-Au NCs exhibit an average size of 2.08±0.15 nm and a maximum emission at λ ex /λ em = 280/440 nm with a quantum yield of 27.3%. It is interesting that Hg 2+ causes a significant quench on the fluorescence of FA-Au NCs, whereas CH 3 Hg + leads to a remarkable fluorescence enhancement. Based on this discriminative fluorescent response between Hg 2+ and CH 3 Hg + , a novel nanosensor for the speciation of CH 3 Hg + and Hg 2+ was developed, providing limits of detection (LOD) of 28 nM for Hg 2+ and 25 nM for CH 3 Hg + within 100-1000 nM. This sensing system is highly selective to mercury. Its practical applications were further demonstrated by the analysis of CH 3 Hg + and the speciation of mercury (CH 3 Hg + and Hg 2+ ) in environmental water and fish samples.

Customizing national models for a medical center's population to rapidly identify patients at high risk of 30-day all-cause hospital readmission following a heart failure hospitalization.

PubMed

Cox, Zachary L; Lai, Pikki; Lewis, Connie M; Lindenfeld, JoAnn; Collins, Sean P; Lenihan, Daniel J

2018-05-28

Nationally-derived models predicting 30-day readmissions following heart failure (HF) hospitalizations yield insufficient discrimination for institutional use. Develop a customized readmission risk model from Medicare-employed and institutionally-customized risk factors and compare the performance against national models in a medical center. Medicare patients age ≥ 65 years hospitalized for HF (n = 1,454) were studied in a derivation cohort and in a separate validation cohort (n = 243). All 30-day hospital readmissions were documented. The primary outcome was risk discrimination (c-statistic) compared to national models. A customized model demonstrated improved discrimination (c-statistic 0.72; 95% CI 0.69 - 0.74) compared to national models (c-statistics of 0.60 and 0.61) with a c-statistic of 0.63 in the validation cohort. Compared to national models, a customized model demonstrated superior readmission risk profiling by distinguishing a high-risk (38.3%) from a low-risk (9.4%) quartile. A customized model improved readmission risk discrimination from HF hospitalizations compared to national models. Copyright © 2018 Elsevier Inc. All rights reserved.

Improved Discrimination of Visual Stimuli Following Repetitive Transcranial Magnetic Stimulation

PubMed Central

Waterston, Michael L.; Pack, Christopher C.

2010-01-01

Background Repetitive transcranial magnetic stimulation (rTMS) at certain frequencies increases thresholds for motor-evoked potentials and phosphenes following stimulation of cortex. Consequently rTMS is often assumed to introduce a “virtual lesion” in stimulated brain regions, with correspondingly diminished behavioral performance. Methodology/Principal Findings Here we investigated the effects of rTMS to visual cortex on subjects' ability to perform visual psychophysical tasks. Contrary to expectations of a visual deficit, we find that rTMS often improves the discrimination of visual features. For coarse orientation tasks, discrimination of a static stimulus improved consistently following theta-burst stimulation of the occipital lobe. Using a reaction-time task, we found that these improvements occurred throughout the visual field and lasted beyond one hour post-rTMS. Low-frequency (1 Hz) stimulation yielded similar improvements. In contrast, we did not find consistent effects of rTMS on performance in a fine orientation discrimination task. Conclusions/Significance Overall our results suggest that rTMS generally improves or has no effect on visual acuity, with the nature of the effect depending on the type of stimulation and the task. We interpret our results in the context of an ideal-observer model of visual perception. PMID:20442776

Sparse network-based models for patient classification using fMRI

PubMed Central

Rosa, Maria J.; Portugal, Liana; Hahn, Tim; Fallgatter, Andreas J.; Garrido, Marta I.; Shawe-Taylor, John; Mourao-Miranda, Janaina

2015-01-01

Pattern recognition applied to whole-brain neuroimaging data, such as functional Magnetic Resonance Imaging (fMRI), has proved successful at discriminating psychiatric patients from healthy participants. However, predictive patterns obtained from whole-brain voxel-based features are difficult to interpret in terms of the underlying neurobiology. Many psychiatric disorders, such as depression and schizophrenia, are thought to be brain connectivity disorders. Therefore, pattern recognition based on network models might provide deeper insights and potentially more powerful predictions than whole-brain voxel-based approaches. Here, we build a novel sparse network-based discriminative modeling framework, based on Gaussian graphical models and L1-norm regularized linear Support Vector Machines (SVM). In addition, the proposed framework is optimized in terms of both predictive power and reproducibility/stability of the patterns. Our approach aims to provide better pattern interpretation than voxel-based whole-brain approaches by yielding stable brain connectivity patterns that underlie discriminative changes in brain function between the groups. We illustrate our technique by classifying patients with major depressive disorder (MDD) and healthy participants, in two (event- and block-related) fMRI datasets acquired while participants performed a gender discrimination and emotional task, respectively, during the visualization of emotional valent faces. PMID:25463459

Sex estimation from sternal measurements using multidetector computed tomography.

PubMed

Ekizoglu, Oguzhan; Hocaoglu, Elif; Inci, Ercan; Bilgili, Mustafa Gokhan; Solmaz, Dilek; Erdil, Irem; Can, Ismail Ozgur

2014-12-01

We aimed to show the utility and reliability of sternal morphometric analysis for sex estimation.Sex estimation is a very important step in forensic identification. Skeletal surveys are main methods for sex estimation studies. Morphometric analysis of sternum may provide high accuracy rated data in sex discrimination. In this study, morphometric analysis of sternum was evaluated in 1 mm chest computed tomography scans for sex estimation. Four hundred forty 3 subjects (202 female, 241 male, mean age: 44 ± 8.1 [distribution: 30-60 year old]) were included the study. Manubrium length (ML), mesosternum length (2L), Sternebra 1 (S1W), and Sternebra 3 (S3W) width were measured and also sternal index (SI) was calculated. Differences between genders were evaluated by student t-test. Predictive factors of sex were determined by discrimination analysis and receiver operating characteristic (ROC) analysis. Male sternal measurement values are significantly higher than females (P < 0.001) while SI is significantly low in males (P < 0.001). In discrimination analysis, MSL has high accuracy rate with 80.2% in females and 80.9% in males. MSL also has the best sensitivity (75.9%) and specificity (87.6%) values. Accuracy rates were above 80% in 3 stepwise discrimination analysis for both sexes. Stepwise 1 (ML, MSL, S1W, S3W) has the highest accuracy rate in stepwise discrimination analysis with 86.1% in females and 83.8% in males. Our study showed that morphometric computed tomography analysis of sternum might provide important information for sex estimation.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Noise-robust unsupervised spike sorting based on discriminative subspace learning with outlier handling

NASA Astrophysics Data System (ADS)

Keshtkaran, Mohammad Reza; Yang, Zhi

2017-06-01

Objective. Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. Most of the feature extraction and dimensionality reduction techniques that have been used for spike sorting give a projection subspace which is not necessarily the most discriminative one. Therefore, the clusters which appear inherently separable in some discriminative subspace may overlap if projected using conventional feature extraction approaches leading to a poor sorting accuracy especially when the noise level is high. In this paper, we propose a noise-robust and unsupervised spike sorting algorithm based on learning discriminative spike features for clustering. Approach. The proposed algorithm uses discriminative subspace learning to extract low dimensional and most discriminative features from the spike waveforms and perform clustering with automatic detection of the number of the clusters. The core part of the algorithm involves iterative subspace selection using linear discriminant analysis and clustering using Gaussian mixture model with outlier detection. A statistical test in the discriminative subspace is proposed to automatically detect the number of the clusters. Main results. Comparative results on publicly available simulated and real in vivo datasets demonstrate that our algorithm achieves substantially improved cluster distinction leading to higher sorting accuracy and more reliable detection of clusters which are highly overlapping and not detectable using conventional feature extraction techniques such as principal component analysis or wavelets. Significance. By providing more accurate information about the activity of more number of individual neurons with high robustness to neural noise and outliers, the proposed unsupervised spike sorting algorithm facilitates more detailed and accurate analysis of single- and multi-unit activities in neuroscience and brain machine interface studies.

Principal Component Clustering Approach to Teaching Quality Discriminant Analysis

ERIC Educational Resources Information Center

Xian, Sidong; Xia, Haibo; Yin, Yubo; Zhai, Zhansheng; Shang, Yan

2016-01-01

Teaching quality is the lifeline of the higher education. Many universities have made some effective achievement about evaluating the teaching quality. In this paper, we establish the Students' evaluation of teaching (SET) discriminant analysis model and algorithm based on principal component clustering analysis. Additionally, we classify the SET…

The Coopersmith Self-Esteem Inventory in an Adult Sample.

ERIC Educational Resources Information Center

Noller, Patricia; Shugm, David

1988-01-01

The reliability and validity of the Self-Esteem Inventory developed by S. C. Coopersmith (1975) were evaluated via item-total correlation, discriminant analysis, factor analysis, and analysis of variance of data for 352 Australian adults. The instrument had high internal consistency and discriminated well between subjects with high and low…

Metabolic fingerprinting of Cannabis sativa L., cannabinoids and terpenoids for chemotaxonomic and drug standardization purposes.

PubMed

Fischedick, Justin Thomas; Hazekamp, Arno; Erkelens, Tjalling; Choi, Young Hae; Verpoorte, Rob

2010-12-01

Cannabis sativa L. is an important medicinal plant. In order to develop cannabis plant material as a medicinal product quality control and clear chemotaxonomic discrimination between varieties is a necessity. Therefore in this study 11 cannabis varieties were grown under the same environmental conditions. Chemical analysis of cannabis plant material used a gas chromatography flame ionization detection method that was validated for quantitative analysis of cannabis monoterpenoids, sesquiterpenoids, and cannabinoids. Quantitative data was analyzed using principal component analysis to determine which compounds are most important in discriminating cannabis varieties. In total 36 compounds were identified and quantified in the 11 varieties. Using principal component analysis each cannabis variety could be chemically discriminated. This methodology is useful for both chemotaxonomic discrimination of cannabis varieties and quality control of plant material. Copyright © 2010 Elsevier Ltd. All rights reserved.

Don't ask for fair treatment? A gender analysis of ethnic discrimination, response to discrimination, and self-rated health among marriage migrants in South Korea.

PubMed

Kim, Yugyun; Son, Inseo; Wie, Dainn; Muntaner, Carles; Kim, Hyunwoo; Kim, Seung-Sup

2016-07-19

Ethnic discrimination is increasingly common nowadays in South Korea with the influx of migrants. Despite the growing body of evidences suggests that ethnic discrimination negatively impacts health, only few researches have been conducted on the association between ethnic discrimination and health outcomes among marriage migrants in Korea. This study sought to examine how ethnic discrimination and response to the discrimination are related to self-rated health and whether the association differs by victim's gender. We conducted two-step analysis using cross-sectional dataset from the 'National Survey of Multicultural Families 2012'. First, we examined the association between perceived ethnic discrimination and self-rated health among 14,406 marriage migrants in Korea. Second, among the marriage migrants who experienced ethnic discrimination (n=5,880), we examined how response to discrimination (i.e., whether or not asking for fair treatment) is related to poor self-rated health. All analyses were conducted after being stratified by the migrant's gender. This research found the significant association between ethnic discrimination and poor self-rated health among female marriage migrants (OR: 1.53, 95 % CI: 1.32, 1.76), but not among male marriage migrants (OR: 1.16, 95 % CI: 0.81, 1.66). In the restricted analysis with marriage migrants who experienced ethnic discrimination, compared to the group who did not ask for fair treatment, female marriage migrants who asked for fair treatment were more likely to report poor self-rated health (OR: 1.21, 95 % CI: 0.98, 1.50); however, male marriage migrants who asked for fair treatment were less likely to report poor self-rated health (OR: 0.65, 95 % CI: 0.36, 1.04) although both were not statistically significant. This is the first study to investigate gender difference in the association between response to ethnic discrimination and self-rated health in South Korea. We discussed that gender may play an important role in the association between response to discrimination and self-rated health among marriage migrants in Korea. In order to prevent discrimination which could endanger the health of ethnic minorities including marriage migrants, relevant policies are needed.

Correlative feature analysis of FFDM images

NASA Astrophysics Data System (ADS)

Yuan, Yading; Giger, Maryellen L.; Li, Hui; Sennett, Charlene

2008-03-01

Identifying the corresponding image pair of a lesion is an essential step for combining information from different views of the lesion to improve the diagnostic ability of both radiologists and CAD systems. Because of the non-rigidity of the breasts and the 2D projective property of mammograms, this task is not trivial. In this study, we present a computerized framework that differentiates the corresponding images from different views of a lesion from non-corresponding ones. A dual-stage segmentation method, which employs an initial radial gradient index(RGI) based segmentation and an active contour model, was initially applied to extract mass lesions from the surrounding tissues. Then various lesion features were automatically extracted from each of the two views of each lesion to quantify the characteristics of margin, shape, size, texture and context of the lesion, as well as its distance to nipple. We employed a two-step method to select an effective subset of features, and combined it with a BANN to obtain a discriminant score, which yielded an estimate of the probability that the two images are of the same physical lesion. ROC analysis was used to evaluate the performance of the individual features and the selected feature subset in the task of distinguishing between corresponding and non-corresponding pairs. By using a FFDM database with 124 corresponding image pairs and 35 non-corresponding pairs, the distance feature yielded an AUC (area under the ROC curve) of 0.8 with leave-one-out evaluation by lesion, and the feature subset, which includes distance feature, lesion size and lesion contrast, yielded an AUC of 0.86. The improvement by using multiple features was statistically significant as compared to single feature performance. (p<0.001)

Discrimination of cultivation ages and cultivars of ginseng leaves using Fourier transform infrared spectroscopy combined with multivariate analysis

PubMed Central

Kwon, Yong-Kook; Ahn, Myung Suk; Park, Jong Suk; Liu, Jang Ryol; In, Dong Su; Min, Byung Whan; Kim, Suk Weon

2013-01-01

To determine whether Fourier transform (FT)-IR spectral analysis combined with multivariate analysis of whole-cell extracts from ginseng leaves can be applied as a high-throughput discrimination system of cultivation ages and cultivars, a total of total 480 leaf samples belonging to 12 categories corresponding to four different cultivars (Yunpung, Kumpung, Chunpung, and an open-pollinated variety) and three different cultivation ages (1 yr, 2 yr, and 3 yr) were subjected to FT-IR. The spectral data were analyzed by principal component analysis and partial least squares-discriminant analysis. A dendrogram based on hierarchical clustering analysis of the FT-IR spectral data on ginseng leaves showed that leaf samples were initially segregated into three groups in a cultivation age-dependent manner. Then, within the same cultivation age group, leaf samples were clustered into four subgroups in a cultivar-dependent manner. The overall prediction accuracy for discrimination of cultivars and cultivation ages was 94.8% in a cross-validation test. These results clearly show that the FT-IR spectra combined with multivariate analysis from ginseng leaves can be applied as an alternative tool for discriminating of ginseng cultivars and cultivation ages. Therefore, we suggest that this result could be used as a rapid and reliable F1 hybrid seed-screening tool for accelerating the conventional breeding of ginseng. PMID:24558311

Graphical methods for the sensitivity analysis in discriminant analysis

DOE PAGES

Kim, Youngil; Anderson-Cook, Christine M.; Dae-Heung, Jang

2015-09-30

Similar to regression, many measures to detect influential data points in discriminant analysis have been developed. Many follow similar principles as the diagnostic measures used in linear regression in the context of discriminant analysis. Here we focus on the impact on the predicted classification posterior probability when a data point is omitted. The new method is intuitive and easily interpretative compared to existing methods. We also propose a graphical display to show the individual movement of the posterior probability of other data points when a specific data point is omitted. This enables the summaries to capture the overall pattern ofmore » the change.« less

Results on Neutrinoless Double-β Decay of Ge76 from Phase I of the GERDA Experiment

NASA Astrophysics Data System (ADS)

Agostini, M.; Allardt, M.; Andreotti, E.; Bakalyarov, A. M.; Balata, M.; Barabanov, I.; Barnabé Heider, M.; Barros, N.; Baudis, L.; Bauer, C.; Becerici-Schmidt, N.; Bellotti, E.; Belogurov, S.; Belyaev, S. T.; Benato, G.; Bettini, A.; Bezrukov, L.; Bode, T.; Brudanin, V.; Brugnera, R.; Budjáš, D.; Caldwell, A.; Cattadori, C.; Chernogorov, A.; Cossavella, F.; Demidova, E. V.; Domula, A.; Egorov, V.; Falkenstein, R.; Ferella, A.; Freund, K.; Frodyma, N.; Gangapshev, A.; Garfagnini, A.; Gotti, C.; Grabmayr, P.; Gurentsov, V.; Gusev, K.; Guthikonda, K. K.; Hampel, W.; Hegai, A.; Heisel, M.; Hemmer, S.; Heusser, G.; Hofmann, W.; Hult, M.; Inzhechik, L. V.; Ioannucci, L.; Janicskó Csáthy, J.; Jochum, J.; Junker, M.; Kihm, T.; Kirpichnikov, I. V.; Kirsch, A.; Klimenko, A.; Knöpfle, K. T.; Kochetov, O.; Kornoukhov, V. N.; Kuzminov, V. V.; Laubenstein, M.; Lazzaro, A.; Lebedev, V. I.; Lehnert, B.; Liao, H. Y.; Lindner, M.; Lippi, I.; Liu, X.; Lubashevskiy, A.; Lubsandorzhiev, B.; Lutter, G.; Macolino, C.; Machado, A. A.; Majorovits, B.; Maneschg, W.; Misiaszek, M.; Nemchenok, I.; Nisi, S.; O'Shaughnessy, C.; Pandola, L.; Pelczar, K.; Pessina, G.; Pullia, A.; Riboldi, S.; Rumyantseva, N.; Sada, C.; Salathe, M.; Schmitt, C.; Schreiner, J.; Schulz, O.; Schwingenheuer, B.; Schönert, S.; Shevchik, E.; Shirchenko, M.; Simgen, H.; Smolnikov, A.; Stanco, L.; Strecker, H.; Tarka, M.; Ur, C. A.; Vasenko, A. A.; Volynets, O.; von Sturm, K.; Wagner, V.; Walter, M.; Wegmann, A.; Wester, T.; Wojcik, M.; Yanovich, E.; Zavarise, P.; Zhitnikov, I.; Zhukov, S. V.; Zinatulina, D.; Zuber, K.; Zuzel, G.

2013-09-01

Neutrinoless double beta decay is a process that violates lepton number conservation. It is predicted to occur in extensions of the standard model of particle physics. This Letter reports the results from phase I of the Germanium Detector Array (GERDA) experiment at the Gran Sasso Laboratory (Italy) searching for neutrinoless double beta decay of the isotope Ge76. Data considered in the present analysis have been collected between November 2011 and May 2013 with a total exposure of 21.6 kg yr. A blind analysis is performed. The background index is about 1×10-2counts/(keVkgyr) after pulse shape discrimination. No signal is observed and a lower limit is derived for the half-life of neutrinoless double beta decay of Ge76, T1/20ν>2.1×1025yr (90% C.L.). The combination with the results from the previous experiments with Ge76 yields T1/20ν>3.0×1025yr (90% C.L.).

Private healthcare quality: applying a SERVQUAL model.

PubMed

Butt, Mohsin Muhammad; de Run, Ernest Cyril

2010-01-01

This paper seeks to develop and test the SERVQUAL model scale for measuring Malaysian private health service quality. The study consists of 340 randomly selected participants visiting a private healthcare facility during a three-month data collection period. Data were analyzed using means, correlations, principal component and confirmatory factor analysis to establish the modified SERVQUAL scale's reliability, underlying dimensionality and convergent, discriminant validity. Results indicate a moderate negative quality gap for overall Malaysian private healthcare service quality. Results also indicate a moderate negative quality gap on each service quality scale dimension. However, scale development analysis yielded excellent results, which can be used in wider healthcare policy and practice. Respondents were skewed towards a younger population, causing concern that the results might not represent all Malaysian age groups. The study's major contribution is that it offers a way to assess private healthcare service quality. Second, it successfully develops a scale that can be used to measure health service quality in Malaysian contexts.

Calibration, event reconstruction, data analysis and limits calculation for the LUX dark matter experiment

DOE PAGES

Akerib, DS; Alsum, S; Araújo, HM; ...

2018-01-05

The LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Craniometric analysis of European Upper Palaeolithic and Mesolithic samples supports discontinuity at the Late Glacial Maximum

PubMed Central

Brewster, Ciarán; Meiklejohn, Christopher; von Cramon-Taubadel, Noreen; Pinhasi, Ron

2014-01-01

The Last Glacial Maximum (LGM) represents the most significant climatic event since the emergence of anatomically modern humans (AMH). In Europe, the LGM may have played a role in changing morphological features as a result of adaptive and stochastic processes. We use craniometric data to examine morphological diversity in pre- and post-LGM specimens. Craniometric variation is assessed across four periods—pre-LGM, late glacial, Early Holocene and Middle Holocene—using a large, well-dated, dataset. Our results show significant differences across the four periods, using a MANOVA on size-adjusted cranial measurements. A discriminant function analysis shows separation between pre-LGM and later groups. Analyses repeated on a subsample, controlled for time and location, yield similar results. The results are largely influenced by facial measurements and are most consistent with neutral demographic processes. These findings suggest that the LGM had a major impact on AMH populations in Europe prior to the Neolithic. PMID:24912847

Use of a porous silicon-gold plasmonic nanostructure to enhance serum peptide signals in MALDI-TOF analysis.

PubMed

Li, Xiao; Tan, Jie; Yu, Jiekai; Feng, Jiandong; Pan, Aiwu; Zheng, Shu; Wu, Jianmin

2014-11-07

Small peptides in serum are potential biomarkers for the diagnosis of cancer and other diseases. The identification of peptide biomarkers in human plasma/serum has become an area of high interest in medical research. However, the direct analysis of peptides in serum samples using mass spectrometry is challenging due to the low concentration of peptides and the high abundance of high-molecular-weight proteins in serum, the latter of which causes severe signal suppression. Herein, we reported that porous semiconductor-noble metal hybrid nanostructures can both eliminate the interference from large proteins in serum samples and significantly enhance the matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) yields of peptides captured on the nanostructure. Serum peptide fingerprints with high fidelity can be acquired rapidly, and successful discrimination of colorectal cancer patients based on peptide fingerprints is demonstrated. Copyright © 2014 Elsevier B.V. All rights reserved.

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

DOE PAGES

Akerib, D. S.; Alsum, S.; Araújo, H. M.; ...

2018-05-31

Here, the LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Psychometric Properties of the Cyberbullying Test, a Screening Instrument to Measure Cybervictimization, Cyberaggression, and Cyberobservation.

PubMed

Garaigordobil, Maite

2015-08-19

The purpose of the study was to analyze the psychometric properties of the Cyberbullying Test. The sample included 3,026 participants from the Basque Country (northern Spain), aged 12 to 18 years. Results confirmed high internal consistency and moderate temporal stability. Exploratory factor analysis yielded three moderately correlated factors (cyberobserver, cyberaggressor, and cybervictim). Confirmatory factor analysis ratified adequate model fit of the three factors. Convergent and discriminant validity were confirmed: (a) cybervictims use a variety of conflict resolution strategies, scoring high in neuroticism, openness, antisocial behavior, emotional attention, school-academic problems, shyness-withdrawal, psychopathological disorders, anxiety, and psychosomatic complaints, and low in agreeableness, responsibility, self-esteem, and social adjustment and (b) cyberaggressors use many aggressive conflict resolution strategies, scoring high in neuroticism, antisocial behavior, school-academic problems, psychopathological and psychosomatic disorders, and low in empathy, agreeableness, responsibility, emotion regulation, and social adjustment. The study confirms the test's reliability and validity. © The Author(s) 2015.

mec-associated dru typing in the epidemiological analysis of ST239 MRSA in Malaysia.

PubMed

Ghaznavi-Rad, E; Goering, R V; Nor Shamsudin, M; Weng, P L; Sekawi, Z; Tavakol, M; van Belkum, A; Neela, V

2011-11-01

The usefulness of mec-associated dru typing in the epidemiological analysis of methicillin-resistant Staphylococcus aureus (MRSA) isolated in Malaysia was investigated and compared with pulsed-field gel electrophoresis (PFGE), multilocus sequence typing (MLST), and spa and SCCmec typing. The isolates studied included all MRSA types in Malaysia. Multilocus sequence type ST188 and ST1 isolates were highly clonal by all typing methods. However, the dru typing of ST239 isolates produced the clearest discrimination between SCCmec IIIa and III isolates, yielding more subtypes than any other method. Evaluation of the discriminatory power for each method identified dru typing and PFGE as the most discriminatory, with Simpson's index of diversity (SID) values over 89%, including an isolate which was non-typeable by spa, but dru-typed as dt13j. The discriminatory ability of dru typing, especially with closely related MRSA ST239 strains (e.g., Brazilian and Hungarian), underscores its utility as a tool for the epidemiological investigation of MRSA.

Calibration, event reconstruction, data analysis, and limit calculation for the LUX dark matter experiment

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

Akerib, D. S.; Alsum, S.; Araújo, H. M.

Here, the LUX experiment has performed searches for dark matter particles scattering elastically on xenon nuclei, leading to stringent upper limits on the nuclear scattering cross sections for dark matter. Here, for results derived frommore » $${1.4}\\times 10^{4}\\;\\mathrm{kg\\,days}$$ of target exposure in 2013, details of the calibration, event-reconstruction, modeling, and statistical tests that underlie the results are presented. Detector performance is characterized, including measured efficiencies, stability of response, position resolution, and discrimination between electron- and nuclear-recoil populations. Models are developed for the drift field, optical properties, background populations, the electron- and nuclear-recoil responses, and the absolute rate of low-energy background events. Innovations in the analysis include in situ measurement of the photomultipliers' response to xenon scintillation photons, verification of fiducial mass with a low-energy internal calibration source, and new empirical models for low-energy signal yield based on large-sample, in situ calibrations.« less

Forensic analysis of printing inks using tandem Laser Induced Breakdown Spectroscopy and Laser Ablation Inductively Coupled Plasma Mass Spectrometry

NASA Astrophysics Data System (ADS)

Subedi, Kiran; Trejos, Tatiana; Almirall, José

2015-01-01

Elemental analysis, using either LA-ICP-MS or LIBS, can be used for the chemical characterization of materials of forensic interest to discriminate between source materials originating from different sources and also for the association of materials known to originate from the same source. In this study, a tandem LIBS/LA-ICP-MS system that combines the benefits of both LIBS and LA-ICP-MS was evaluated for the characterization of samples of printing inks (toners, inkjets, intaglio and offset.). The performance of both laser sampling methods is presented. A subset of 9 black laser toners, 10 colored (CMYK) inkjet samples, 12 colored (CMYK) offset samples and 12 intaglio inks originating from different manufacturing sources were analyzed to evaluate the discrimination capability of the tandem method. These samples were selected because they presented a very similar elemental profile by LA-ICP-MS. Although typical discrimination between different ink sources is found to be > 99% for a variety of inks when only LA-ICP-MS was used for the analysis, additional discrimination was achieved by combining the elemental results from the LIBS analysis to the LA-ICP-MS analysis in the tandem technique, enhancing the overall discrimination capability of the individual laser ablation methods. The LIBS measurements of the Ca, Fe, K and Si signals, in particular, improved the discrimination for this specific set of different ink samples previously shown to exhibit very similar LA-ICP-MS elemental profiles. The combination of these two techniques in a single setup resulted in better discrimination of the printing inks with two distinct fingerprint spectra, providing information from atomic/ionic emissions and isotopic composition (m/z) for each ink sample.

Optical redox ratio differentiates early tissue transformations in DMBA-induced hamster oral carcinogenesis based on autofluorescence spectroscopy coupled with multivariate analysis

NASA Astrophysics Data System (ADS)

Sethupathi, R.; Gurushankar, K.; Krishnakumar, N.

2016-11-01

Fluorescence intensity measurements have the potential to facilitate the diagnoses of many pathological conditions. The changes in fluorescence intensity may be influenced by factors such as tissue architectures, endogenous fluorophores, cellular metabolism and light penetration depth in tissue. Two of the most diagnostically important endogenous fluorophores are reduced nicotinamide dinucleotide (NADH) and flavin adenine dinucleotide (FAD), which can be used to monitor dramatic metabolic changes in cells and tissues. The goal of this study is to investigate changes in the endogenous fluorophore emission and to quantify metabolic changes in the redox state of various tissue transformation conditions with respect to control tissues in dimethyl benz[a] anthracene (DMBA)-induced hamster oral carcinogenesis for measuring emission spectrum at 320 nm excitation. In the present study, collagen, NADH and FAD emission of well-differentiated squamous cell carcinoma (WDSCC) showed decreased intensity at ~385 nm, ~450 nm and ~520 nm compared to hyperplasia, dysplasia and control tissues. Furthermore, a significant decrease in the optical redox ratio is observed in WDSCC tissues, which indicates an increased metabolic activity compared to the control tissues. Moreover, the principal component linear discriminant analysis (PC-LDA) algorithm together with the leave-one-out cross-validation (LOOCV) method yield an overall diagnostic sensitivity of 77.7% and a specificity of 88.8% in the classification of control, hyperplasia, dysplasia and WDSCC tissues, respectively. The results from this study demonstrated that fluorescence-based tissue analysis combined with PC-LDA has tremendous potential for the effective discrimination of control from neoplastic tissues; furthermore it also detects early neoplastic changes prior to definite morphologic alteration.

Staff preparedness for providing palliative and end-of-life care in long-term care homes: Instrument development and validation.

PubMed

Chan, Helen Yl; Chun, Gloria Km; Man, C W; Leung, Edward Mf

2018-05-01

Although much attention has been on integrating the palliative care approach into services of long-term care homes for older people living with frailty and progressive diseases, little is known about the staff preparedness for these new initiatives. The present study aimed to develop and test the psychometric properties of an instrument for measuring care home staff preparedness in providing palliative and end-of-life care. A 16-item instrument, covering perceived knowledge, skill and psychological readiness, was developed. A total of 247 staff members of different ranks from four care homes participated in the study. Exploratory factor analysis using the principal component analysis extraction method with varimax rotation was carried out for initial validation. Known group comparison was carried out to examine its discriminant validity. Reliability of the instrument was assessed based on test-retest reliability of a subsample of 20 participants and the Cronbach's alpha of the items. Exploratory factor analysis showed that the instrument yielded a three-factor solution, which cumulatively accounted for 68.5% of the total variance. Three subscales, namely, willingness, capability and resilience, showed high internal consistency and test-retest reliability. It also showed good discriminant validity between staff members of professional and non-professional groups. This is a brief, valid and reliable scale for measuring care home staff preparedness for providing palliative and end-of-life care. It can be used to identify their concerns and training needs in providing palliative and end-of-life care, and as an outcome measure to evaluate the effects of interventional studies for capacity building in this regard. Geriatr Gerontol Int 2018; 18: 745-749. © 2018 Japan Geriatrics Society.

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.

The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses

PubMed Central

2010-01-01

Background Proton Magnetic Resonance (MR) Spectroscopy (MRS) is a widely available technique for those clinical centres equipped with MR scanners. Unlike the rest of MR-based techniques, MRS yields not images but spectra of metabolites in the tissues. In pathological situations, the MRS profile changes and this has been particularly described for brain tumours. However, radiologists are frequently not familiar to the interpretation of MRS data and for this reason, the usefulness of decision-support systems (DSS) in MRS data analysis has been explored. Results This work presents the INTERPRET DSS version 3.0, analysing the improvements made from its first release in 2002. Version 3.0 is aimed to be a program that 1st, can be easily used with any new case from any MR scanner manufacturer and 2nd, improves the initial analysis capabilities of the first version. The main improvements are an embedded database, user accounts, more diagnostic discrimination capabilities and the possibility to analyse data acquired under additional data acquisition conditions. Other improvements include a customisable graphical user interface (GUI). Most diagnostic problems included have been addressed through a pattern-recognition based approach, in which classifiers based on linear discriminant analysis (LDA) were trained and tested. Conclusions The INTERPRET DSS 3.0 allows radiologists, medical physicists, biochemists or, generally speaking, any person with a minimum knowledge of what an MR spectrum is, to enter their own SV raw data, acquired at 1.5 T, and to analyse them. The system is expected to help in the categorisation of MR Spectra from abnormal brain masses. PMID:21114820

Large-scale optimization-based classification models in medicine and biology.

PubMed

Lee, Eva K

2007-06-01

We present novel optimization-based classification models that are general purpose and suitable for developing predictive rules for large heterogeneous biological and medical data sets. Our predictive model simultaneously incorporates (1) the ability to classify any number of distinct groups; (2) the ability to incorporate heterogeneous types of attributes as input; (3) a high-dimensional data transformation that eliminates noise and errors in biological data; (4) the ability to incorporate constraints to limit the rate of misclassification, and a reserved-judgment region that provides a safeguard against over-training (which tends to lead to high misclassification rates from the resulting predictive rule); and (5) successive multi-stage classification capability to handle data points placed in the reserved-judgment region. To illustrate the power and flexibility of the classification model and solution engine, and its multi-group prediction capability, application of the predictive model to a broad class of biological and medical problems is described. Applications include: the differential diagnosis of the type of erythemato-squamous diseases; predicting presence/absence of heart disease; genomic analysis and prediction of aberrant CpG island meythlation in human cancer; discriminant analysis of motility and morphology data in human lung carcinoma; prediction of ultrasonic cell disruption for drug delivery; identification of tumor shape and volume in treatment of sarcoma; discriminant analysis of biomarkers for prediction of early atherosclerois; fingerprinting of native and angiogenic microvascular networks for early diagnosis of diabetes, aging, macular degeneracy and tumor metastasis; prediction of protein localization sites; and pattern recognition of satellite images in classification of soil types. In all these applications, the predictive model yields correct classification rates ranging from 80 to 100%. This provides motivation for pursuing its use as a medical diagnostic, monitoring and decision-making tool.

Reduced Data Dualscale Entropy Analysis of HRV Signals for Improved Congestive Heart Failure Detection

NASA Astrophysics Data System (ADS)

Kuntamalla, Srinivas; Lekkala, Ram Gopal Reddy

2014-10-01

Heart rate variability (HRV) is an important dynamic variable of the cardiovascular system, which operates on multiple time scales. In this study, Multiscale entropy (MSE) analysis is applied to HRV signals taken from Physiobank to discriminate Congestive Heart Failure (CHF) patients from healthy young and elderly subjects. The discrimination power of the MSE method is decreased as the amount of the data reduces and the lowest amount of the data at which there is a clear discrimination between CHF and normal subjects is found to be 4000 samples. Further, this method failed to discriminate CHF from healthy elderly subjects. In view of this, the Reduced Data Dualscale Entropy Analysis method is proposed to reduce the data size required (as low as 500 samples) for clearly discriminating the CHF patients from young and elderly subjects with only two scales. Further, an easy to interpret index is derived using this new approach for the diagnosis of CHF. This index shows 100 % accuracy and correlates well with the pathophysiology of heart failure.

Metabolomic assessment reveals an elevated level of glucosinolate content in CaCl₂ treated broccoli microgreens.

PubMed

Sun, Jianghao; Kou, Liping; Geng, Ping; Huang, Huilian; Yang, Tianbao; Luo, Yaguang; Chen, Pei

2015-02-18

Preharvest calcium application has been shown to increase broccoli microgreen yield and extend shelf life. In this study, we investigated the effect of calcium application on its metabolome using ultra-high-performance liquid chromatography with mass spectrometry. The data collected were analyzed using principal component analysis and orthogonal projection to latent structural discriminate analysis. Chemical composition comparison shows that glucosinolates, a very important group of phytochemicals, are the major compounds enhanced by preharvest treatment with 10 mM calcium chloride (CaCl2). Aliphatic glucosinolates (glucoerucin, glucoiberin, glucoiberverin, glucoraphanin, pentyl glucosinolate, and hexyl glucosinolate) and indolic glucosinolates (glucobrassicin, neoglucobrassicin, and 4-hydroxyglucobrassicin) were increased significantly in the CaCl2 treated microgreens using metabolomic approaches. Targeted glucosinolate analysis using the ISO 9167-1 method was further employed to confirm the findings. Results indicate that glucosinolates can be considered as a class of compounds that are responsible for the difference between two groups and a higher glucosinolate level was found in CaCl2 treated groups at each time point after harvest in comparison with the control group.

Thermal effusivity measurement of conventional and organic coffee oils via photopyroelectric technique.

PubMed

Bedoya, A; Gordillo-Delgado, F; Cruz-Santillana, Y E; Plazas, J; Marin, E

2017-12-01

In this work, oil samples extracted from organic and conventional coffee beans were studied. A fatty acids profile analysis was done using gas chromatography and physicochemical analysis of density and acidity index to verify the oil purity. Additionally, Mid-Infrared Fourier Transform Photoacoustic Spectroscopy (FTIR-PAS) aided by Principal Component Analysis (PCA) was used to identify differences between the intensities of the absorption bands related to functional groups. Thermal effusivity values between 592±3 and 610±4Ws 1/2 m -2 K -1 were measured using the photopyroelectric technique in a front detection configuration. The acidity index was between 1.11 and 1.27% and the density changed between 0.921 and 0.94g/mL. These variables, as well as the extraction yield between 12,6 and 14,4%, showed a similar behavior than that observed for the thermal effusivity, demonstrating that this parameter can be used as a criterion for discrimination between oil samples extracted from organic and conventional coffee beans. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dimensionality Reduction Through Classifier Ensembles

NASA Technical Reports Server (NTRS)

Oza, Nikunj C.; Tumer, Kagan; Norwig, Peter (Technical Monitor)

1999-01-01

In data mining, one often needs to analyze datasets with a very large number of attributes. Performing machine learning directly on such data sets is often impractical because of extensive run times, excessive complexity of the fitted model (often leading to overfitting), and the well-known "curse of dimensionality." In practice, to avoid such problems, feature selection and/or extraction are often used to reduce data dimensionality prior to the learning step. However, existing feature selection/extraction algorithms either evaluate features by their effectiveness across the entire data set or simply disregard class information altogether (e.g., principal component analysis). Furthermore, feature extraction algorithms such as principal components analysis create new features that are often meaningless to human users. In this article, we present input decimation, a method that provides "feature subsets" that are selected for their ability to discriminate among the classes. These features are subsequently used in ensembles of classifiers, yielding results superior to single classifiers, ensembles that use the full set of features, and ensembles based on principal component analysis on both real and synthetic datasets.

The Use of DNA Barcoding in Identification and Conservation of Rosewood (Dalbergia spp.)

PubMed Central

Hartvig, Ida; Czako, Mihaly; Kjær, Erik Dahl; Nielsen, Lene Rostgaard; Theilade, Ida

2015-01-01

The genus Dalbergia contains many valuable timber species threatened by illegal logging and deforestation, but knowledge on distributions and threats is often limited and accurate species identification difficult. The aim of this study was to apply DNA barcoding methods to support conservation efforts of Dalbergia species in Indochina. We used the recommended rbcL, matK and ITS barcoding markers on 95 samples covering 31 species of Dalbergia, and tested their discrimination ability with both traditional distance-based as well as different model-based machine learning methods. We specifically tested whether the markers could be used to solve taxonomic confusion concerning the timber species Dalbergia oliveri, and to identify the CITES-listed Dalbergia cochinchinensis. We also applied the barcoding markers to 14 samples of unknown identity. In general, we found that the barcoding markers discriminated among Dalbergia species with high accuracy. We found that ITS yielded the single highest discrimination rate (100%), but due to difficulties in obtaining high-quality sequences from degraded material, the better overall choice for Dalbergia seems to be the standard rbcL+matK barcode, as this yielded discrimination rates close to 90% and amplified well. The distance-based method TaxonDNA showed the highest identification rates overall, although a more complete specimen sampling is needed to conclude on the best analytic method. We found strong support for a monophyletic Dalbergia oliveri and encourage that this name is used consistently in Indochina. The CITES-listed Dalbergia cochinchinensis was successfully identified, and a species-specific assay can be developed from the data generated in this study for the identification of illegally traded timber. We suggest that the use of DNA barcoding is integrated into the work flow during floristic studies and at national herbaria in the region, as this could significantly increase the number of identified specimens and improve knowledge about species distributions. PMID:26375850

Broadband seismology and the detection and verification of underground nuclear explosions

NASA Astrophysics Data System (ADS)

Tinker, Mark Andrew

1997-10-01

On September 24, 1996, President Clinton signed the Comprehensive Test Ban Treaty (CTBT), which bans the testing of all nuclear weapons thereby limiting their future development. Seismology is the primary tool used for the detection and identification of underground explosions and thus, will play a key role in monitoring a CTBT. The detection and identification of low yield explosions requires seismic stations at regional distances (<1500 km). However, because the regional wavefield propagates within the extremely heterogeneous crustal waveguide, the seismic waveforms are also very complicated. Therefore, it is necessary to have a solid understanding of how the phases used in regional discriminants develop within different tectonic regimes. Thus, the development of the seismic phases Pn and Lg, which compose the seismic discriminant Pn/Lg, within the western U.S. from the Non-Proliferation Experiment are evaluated. The most fundamental discriminant is event location as 90% of all seismic sources occur too deep within the earth to be unnatural. France resumed its nuclear testing program after a four year moratorium and conducted six tests during a five month period starting in September of 1995. Using teleseismic data, a joint hypocenter determination algorithm was used to determine the hypocenters of these six explosions. One of the most important problems in monitoring a CTBT is the detection and location of small seismic events. Although seismic arrays have become the central tool for event detection, in the context of a global monitoring treaty, there will be some dependence on sparse regional networks of three-component broadband seismic stations to detect low yield explosions. However, the full power of the data has not been utilized, namely using phases other than P and S. Therefore, the information in the surface wavetrain is used to improve the locations of small seismic events recorded on a sparse network in Bolivia. Finally, as a discrimination example in a complex region, P to S ratios are used to determine source parameters of the Msb{w} 8.3 deep Bolivia earthquake.

Characteristics of acoustic wave from atmospheric nuclear explosions conducted at the USSR Test Sites

NASA Astrophysics Data System (ADS)

Sokolova, Inna

2015-04-01

Availability of the acoustic wave on the record of microbarograph is one of discriminate signs of atmospheric (surface layer of atmosphere) and contact explosions. Nowadays there is large number of air wave records from chemical explosions recorded by the IMS infrasound stations installed during recent decade. But there is small number of air wave records from nuclear explosions as air and contact nuclear explosions had been conducted since 1945 to 1962, before the Limited Test Ban Treaty was signed in 1963 (the treaty banning nuclear weapon tests in the atmosphere, in outer space and under water) by the Great Britain, USSR and USA. That time there was small number of installed microbarographs. First infrasound stations in the USSR appeared in 1954, and by the moment of the USSR collapse the network consisted of 25 infrasound stations, 3 of which were located on Kazakhstan territory - in Kurchatov (East Kazakhstan), in Borovoye Observatory (North Kazakhstan) and Talgar Observatory (Northern Tien Shan). The microbarograph of Talgar Observatory was installed in 1962 and recorded large number of air nuclear explosions conducted at Semipalatinsk Test Site and Novaya Zemlya Test Site. The epicentral distance to the STS was ~700 km, and to Novaya Zemlya Test Site ~3500 km. The historical analog records of the microbarograph were analyzed on the availability of the acoustic wave. The selected records were digitized, the database of acoustic signals from nuclear explosions was created. In addition, acoustic signals from atmospheric nuclear explosions conducted at the USSR Test Sites were recorded by analogue broadband seismic stations at wide range of epicentral distances, 300-3600 km. These signals coincide well by its form and spectral content with records of microbarographs and can be used for monitoring tasks and discrimination in places where infrasound observations are absent. Nuclear explosions which records contained acoustic wave were from 0.03 to 30 kt yield for the STS, and from 8.3 to 25 Mt yield for Novaya Zemlya Test Site region. The peculiarities of the wave pattern and spectral content of the acoustic wave records, and relation regularities of acoustic wave amplitude and periods with explosion yield and distance were investigated. The created database can be applied in different monitoring tasks, such as infrasound stations calibration, discrimination of nuclear explosions, precision of nuclear explosions parameters, determination of the explosion yield etc.

UXO Detection and Characterization using new Berkeley UXO Discriminator (BUD)

NASA Astrophysics Data System (ADS)

Gasperikova, E.; Morrison, H. F.; Smith, J. T.; Becker, A.

2006-05-01

An optimally designed active electromagnetic system (AEM), Berkeley UXO Discriminator, BUD, has been developed for detection and characterization of UXO in the 20 mm to 150 mm size range. The system incorporates three orthogonal transmitters, and eight pairs of differenced receivers. The transmitter-receiver assembly together with the acquisition box, as well as the battery power and GPS receiver, is mounted on a small cart to assure system mobility. BUD not only detects the object itself but also quantitatively determines its size, shape, orientation, and metal content (ferrous or non-ferrous, mixed metals). Moreover, the principal polarizabilities and size of a metallic target can be determined from a single position of the BUD platform. The search for UXO is a two-step process. The object must first be detected and its location determined then the parameters of the object must be defined. A satisfactory classification scheme is one that determines the principal dipole polarizabilities of a target. While UXO objects have a single major polarizability (principal moment) coincident with the long axis of the object and two equal transverse polarizabilities, the scrap metal has all three principal moments entirely different. This description of the inherent polarizabilities of a target is a major advance in discriminating UXO from irregular scrap metal. Our results clearly show that BUD can resolve the intrinsic polarizabilities of a target and that there are very clear distinctions between symmetric intact UXO and irregular scrap metal. Target properties are determined by an inversion algorithm, which at any given time inverts the response to yield the location (x, y, z) of the target, its attitude and its principal polarizabilities (yielding an apparent aspect ratio). Signal-to-noise estimates (or measurements) are interpreted in this inversion to yield error estimates on the location, attitude and polarizabilities. This inversion at a succession of times provides the polarizabilities as a function of time, which can in turn yield the size, true aspect ratio and estimates of the conductivity and permeability of the target. The accuracy of these property estimates depends on the time window over which the polarizability measurements, and their accuracies, are known. Initial tests at a local site over a variety of test objects and inert UXOs showed excellent detection and characterization results within the predicted size-depth range. This research was funded by the U.S. Department of Defense under ESTCP Project # UX-0437.

Is Auditory Discrimination Mature by Middle Childhood? A Study Using Time-Frequency Analysis of Mismatch Responses from 7 Years to Adulthood

ERIC Educational Resources Information Center

Bishop, Dorothy V. M.; Hardiman, Mervyn J.; Barry, Johanna G.

2011-01-01

Behavioural and electrophysiological studies give differing impressions of when auditory discrimination is mature. Ability to discriminate frequency and speech contrasts reaches adult levels only around 12 years of age, yet an electrophysiological index of auditory discrimination, the mismatch negativity (MMN), is reported to be as large in…

Variations in students' perceived reasons for, sources of, and forms of in-school discrimination: A latent class analysis.

PubMed

Byrd, Christy M; Carter Andrews, Dorinda J

2016-08-01

Although there exists a healthy body of literature related to discrimination in schools, this research has primarily focused on racial or ethnic discrimination as perceived and experienced by students of color. Few studies examine students' perceptions of discrimination from a variety of sources, such as adults and peers, their descriptions of the discrimination, or the frequency of discrimination in the learning environment. Middle and high school students in a Midwestern school district (N=1468) completed surveys identifying whether they experienced discrimination from seven sources (e.g., peers, teachers, administrators), for seven reasons (e.g., gender, race/ethnicity, religion), and in eight forms (e.g., punished more frequently, called names, excluded from social groups). The sample was 52% White, 15% Black/African American, 14% Multiracial, and 17% Other. Latent class analysis was used to cluster individuals based on reported sources of, reasons for, and forms of discrimination. Four clusters were found, and ANOVAs were used to test for differences between clusters on perceptions of school climate, relationships with teachers, perceptions that the school was a "good school," and engagement. The Low Discrimination cluster experienced the best outcomes, whereas an intersectional cluster experienced the most discrimination and the worst outcomes. The results confirm existing research on the negative effects of discrimination. Additionally, the paper adds to the literature by highlighting the importance of an intersectional approach to examining students' perceptions of in-school discrimination. Copyright © 2016 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

How do biological systems discriminate among physically similar ions?

PubMed

Diamond, J M

1975-10-01

This paper reviews the history of understanding how biological systems can discriminate so strikingly among physically similar ions, especially alkali cations. Appreciation of qualitative regularities ("permitted sequences") and quantitative regularities ("selectivity isotherms") in ion selectivity grew first from studies of ion exchangers and glass electrodes, then of biological systems such as enzymes and cell membranes, and most recently of lipid bilayers doped with model pores and carriers. Discrimination of ions depends on both electrostatic and steric forces. "Black-box" studies on intact biological membranes have in some cases yielded molecular clues to the structure of the actual biological pores and carriers. Major current problems involve the extraction of these molecules; how to do it, what to do when it is achieved, and how (and if) it is relevant to the central problems of membrane function. Further advances are expected soon from studies of rate barriers within membranes, of voltage-dependent ("excitable") conducting channels, and of increasingly complex model systems and biological membranes.

When Love Meets Hate: The Relationship Between State Policies on Gay and Lesbian Rights and Hate Crime Incidence

PubMed Central

Levy, Brian L.; Levy, Denise L.

2016-01-01

Do public policies on gay and lesbian rights affect the incidence of hate crimes based on sexual orientation? We propose that legal inequalities increase hate crimes because they provide discursive opportunities for bias, discrimination, and violence. Legal equality, however, will reduce violence. Using annual panel data from 2000 to 2012, a period of substantial policy change, we analyze how three state policies affect reported hate crimes: same-sex partnerships, employment non-discrimination, and hate crime laws. Hate crime and employment non-discrimination laws that include sexual orientation reduce hate crime incidence. Partnership recognition increases reported hate crimes, though it may not increase actual crime incidence. Because incidence is spatially correlated, policy changes in one state yield spillover benefits in other states. These results provide some of the first quantitative evidence that public policies affect hate crimes based on sexual orientation. Findings confirm the roles of institutional heterosexism and discursive opportunities in producing hate crimes. PMID:27886725

N-(2-Ethylhexyl)carbazole: A New Fluorophore Highly Suitable as a Monomolecular Liquid Scintillator.

PubMed

Montbarbon, Eva; Sguerra, Fabien; Bertrand, Guillaume H V; Magnier, Élodie; Coulon, Romain; Pansu, Robert B; Hamel, Matthieu

2016-08-16

The synthesis, photophysical properties, and applications in scintillation counting of N-(2-ethylhexyl)carbazole (EHCz) are reported. This molecule displays all of the required characteristics for an efficient liquid scintillator (emission wavelength, scintillation yield), and can be used without any extra fluorophores. Thus, its scintillation properties are discussed, as well as its fast neutron/gamma discrimination. For the latter application, the material is compared with the traditional liquid scintillator BC-501 A, and other liquid fluorescent molecules classically used as scintillation solvents, such as xylene, pseudocumene (PC), linear alkylbenzenes (LAB), diisopropylnaphthalene (DIN), 1-methylnaphthalene (1-MeNapht), and 4-isopropylbiphenyl (iPrBiph). For the first time, an excimeric form of a molecule has been advantageously used in scintillation counting. A moderate discrimination between fast neutrons and gamma rays was observed in bulk EHCz, with an apparent neutron/gamma discrimination potential half of that of BC-501 A. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

When love meets hate: The relationship between state policies on gay and lesbian rights and hate crime incidence.

PubMed

Levy, Brian L; Levy, Denise L

2017-01-01

Do public policies on gay and lesbian rights affect the incidence of hate crimes based on sexual orientation? We propose that legal inequalities increase hate crimes because they provide discursive opportunities for bias, discrimination, and violence. Legal equality, however, will reduce violence. Using annual panel data from 2000 to 2012, a period of substantial policy change, we analyze how three state policies affect reported hate crimes: same-sex partnerships, employment non-discrimination, and hate crime laws. Hate crime and employment non-discrimination laws that include sexual orientation reduce hate crime incidence. Partnership recognition increases reported hate crimes, though it may not increase actual crime incidence. Because incidence is spatially correlated, policy changes in one state yield spillover benefits in other states. These results provide some of the first quantitative evidence that public policies affect hate crimes based on sexual orientation. Findings confirm the roles of institutional heterosexism and discursive opportunities in producing hate crimes. Copyright © 2016 Elsevier Inc. All rights reserved.

Bat Species Comparisons Based on External Morphology: A Test of Traditional versus Geometric Morphometric Approaches

PubMed Central

Schmieder, Daniela A.; Benítez, Hugo A.; Borissov, Ivailo M.; Fruciano, Carmelo

2015-01-01

External morphology is commonly used to identify bats as well as to investigate flight and foraging behavior, typically relying on simple length and area measures or ratios. However, geometric morphometrics is increasingly used in the biological sciences to analyse variation in shape and discriminate among species and populations. Here we compare the ability of traditional versus geometric morphometric methods in discriminating between closely related bat species – in this case European horseshoe bats (Rhinolophidae, Chiroptera) – based on morphology of the wing, body and tail. In addition to comparing morphometric methods, we used geometric morphometrics to detect interspecies differences as shape changes. Geometric morphometrics yielded improved species discrimination relative to traditional methods. The predicted shape for the variation along the between group principal components revealed that the largest differences between species lay in the extent to which the wing reaches in the direction of the head. This strong trend in interspecific shape variation is associated with size, which we interpret as an evolutionary allometry pattern. PMID:25965335

Effects of Perceived Discrimination on Depressive Symptoms Among Black Men Residing in the United States: A Meta-Analysis

PubMed Central

Britt-Spells, Angelitta M.; Slebodnik, Maribeth; Sands, Laura P.; Rollock, David

2016-01-01

Research reports that perceived discrimination is positively associated with depressive symptoms. The literature is limited when examining this relationship among Black men. This meta-analysis systematically examines the current literature and investigates the relationship of perceived discrimination on depressive symptoms among Black men residing in the United States. Using a random-effects model, study findings indicate a positive association between perceived discrimination and depressive symptoms among Black men (r = .29). Several potential moderators were also examined in this study; however, there were no significant moderation effects detected. Recommendations and implications for future research and practice are discussed. PMID:26742988

Gender Wage Inequality and Economic Growth: Is There Really a Puzzle?—A Comment

PubMed Central

Schober, Thomas; Winter-Ebmer, Rudolf

2011-01-01

Summary Seguino (2000) shows that gender wage discrimination in export-oriented semi-industrialized countries might be fostering investment and growth in general. While the original analysis does not have internationally comparable wage discrimination data, we replicate the analysis using data from a meta-study on gender wage discrimination and do not find any evidence that more discrimination might further economic growth—on the contrary: if anything the impact of gender inequality is negative for growth. Standing up for more gender equality—also in terms of wages—is good for equity considerations and at least not negative for growth. PMID:21857765

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®

Patterns of metal composition and biological condition and their association in male common carp across an environmental contaminant gradient in Lake Mead National Recreation Area, Nevada and Arizona, USA

USGS Publications Warehouse

Patino, R.; Rosen, Michael R.; Orsak, E.L.; Goodbred, S.L.; May, T.W.; Alvarez, David; Echols, K.R.; Wieser, C.M.; Ruessler, S.; Torres, L.

2012-01-01

There is a contaminant gradient in Lake Mead National Recreation Area (LMNRA) that is partly driven by municipal and industrial runoff and wastewater inputs via Las Vegas Wash (LVW). Adult male common carp (Cyprinus carpio; 10 fish/site) were collected from LVW, Las Vegas Bay (receiving LVW flow), Overton Arm (OA, upstream reference), and Willow Beach (WB, downstream) in March 2008. Discriminant function analysis was used to describe differences in metal concentrations and biological condition of fish collected from the four study sites, and canonical correlation analysis was used to evaluate the association between metal and biological traits. Metal concentrations were determined in whole-body extracts. Of 63 metals screened, those initially used in the statistical analysis were Ag, As, Ba, Cd, Co, Fe, Hg, Pb, Se, Zn. Biological variables analyzed included total length (TL), Fulton's condition factor, gonadosomatic index (GSI), hematocrit (Hct), and plasma estradiol-17?? and 11-ketotestosterone (11kt) concentrations. Analysis of metal composition and biological condition both yielded strong discrimination of fish by site (respective canonical model, p< 0.0001). Compared to OA, pairwise Mahalanobis distances between group means were WB < LVB < LVW for metal concentrations and LVB < WB < LVW for biological traits. Respective primary drivers for these separations were Ag, As, Ba, Hg, Pb, Se and Zn; and TL, GSI, 11kt, and Hct. Canonical correlation analysis using the latter variable sets showed they are significantly associated (p<0.0003); with As, Ba, Hg, and Zn, and TL, 11kt, and Hct being the primary contributors to the association. In conclusion, male carp collected along a contaminant gradient in LMNRA have distinct, collection site-dependent metal and morpho-physiological profiles that are significantly associated with each other. These associations suggest that fish health and reproductive condition (as measured by the biological variables evaluated in this study) are influenced by levels of certain metals in the Lake Mead environment. ?? 2011.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

PubMed

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

Effects of measurement errors on psychometric measurements in ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis, and linear discriminant analysis.

PubMed

Liu, Yan; Salvendy, Gavriel

2009-05-01

This paper aims to demonstrate the effects of measurement errors on psychometric measurements in ergonomics studies. A variety of sources can cause random measurement errors in ergonomics studies and these errors can distort virtually every statistic computed and lead investigators to erroneous conclusions. The effects of measurement errors on five most widely used statistical analysis tools have been discussed and illustrated: correlation; ANOVA; linear regression; factor analysis; linear discriminant analysis. It has been shown that measurement errors can greatly attenuate correlations between variables, reduce statistical power of ANOVA, distort (overestimate, underestimate or even change the sign of) regression coefficients, underrate the explanation contributions of the most important factors in factor analysis and depreciate the significance of discriminant function and discrimination abilities of individual variables in discrimination analysis. The discussions will be restricted to subjective scales and survey methods and their reliability estimates. Other methods applied in ergonomics research, such as physical and electrophysiological measurements and chemical and biomedical analysis methods, also have issues of measurement errors, but they are beyond the scope of this paper. As there has been increasing interest in the development and testing of theories in ergonomics research, it has become very important for ergonomics researchers to understand the effects of measurement errors on their experiment results, which the authors believe is very critical to research progress in theory development and cumulative knowledge in the ergonomics field.

Discrimination of lymphoma using laser-induced breakdown spectroscopy conducted on whole blood samples

PubMed Central

Chen, Xue; Li, Xiaohui; Yang, Sibo; Yu, Xin; Liu, Aichun

2018-01-01

Lymphoma is a significant cancer that affects the human lymphatic and hematopoietic systems. In this work, discrimination of lymphoma using laser-induced breakdown spectroscopy (LIBS) conducted on whole blood samples is presented. The whole blood samples collected from lymphoma patients and healthy controls are deposited onto standard quantitative filter papers and ablated with a 1064 nm Q-switched Nd:YAG laser. 16 atomic and ionic emission lines of calcium (Ca), iron (Fe), magnesium (Mg), potassium (K) and sodium (Na) are selected to discriminate the cancer disease. Chemometric methods, including principal component analysis (PCA), linear discriminant analysis (LDA) classification, and k nearest neighbor (kNN) classification are used to build the discrimination models. Both LDA and kNN models have achieved very good discrimination performances for lymphoma, with an accuracy of over 99.7%, a sensitivity of over 0.996, and a specificity of over 0.997. These results demonstrate that the whole-blood-based LIBS technique in combination with chemometric methods can serve as a fast, less invasive, and accurate method for detection and discrimination of human malignancies. PMID:29541503

Lithium Alkaline Halides—Next Generation of Dual Mode Scintillators

NASA Astrophysics Data System (ADS)

Soundara-Pandian, L.; Hawrami, R.; Glodo, J.; Ariesanti, E.; van Loef, E. V.; Shah, K.

2016-04-01

We report on a new family of scintillators - Lithium alkaline halides, developed based on the alkaline halides by introducing lithium for dual mode gamma-neutron detection. Many different compositions were grown, among which LiSr2I5 (LSI), LiCa2I5 (LCI), LiSr2Br5 (LSB) activated with divalent Europium show good gamma and neutron detection properties. LSI shows the main emission at 497 nm under X-ray excitation. It also shows good proportionality, which in combination with the light yield as high as 60000 photons/MeV, results in an energy resolution of 3.5% at 662 keV. The electron or gamma equivalent energy (GEE) of the thermal neutron peak due to the 6Li neutron capture is 4.1 MeV, which amounts to a very high neutron light yield of 245000 photons. The decay times for neutrons are faster compared to that for gamma-rays, hence we achieved good pulse shape discrimination (PSD) between gamma and neutron events. Our initial studies on the effects of Eu concentration on the properties of LSI show that 3%-4% Eu concentration is optimal for the best performance in terms of gamma and neutron light yields and pulse shape discrimination. LCI shows the main emission at 475 nm under X-ray excitation and a very high gamma light yield of 90000 photons/MeV. The measured energy resolution is 6% at 662 keV. The electron equivalent energy for neutron detection has been measured to be around 3 MeV, which gives a neutron light yield of 270 000 photons. The measured decay times for neutrons are faster compared to gamma decays and the PSD between the gamma-rays and neutrons is not as good as LSI. LSB shows two emissions at 410 and 475 nm under X-ray excitation. The measured light yield is 32000 ph/MeV gamma-ray with an energy resolution of 6% at 662 keV. The electron equivalent energy of the 6Li capture peak was measured to be 3.3 MeV.

Analysis and Classification of Entering Freshmen Mathematic Students Using Multiple Discriminate Function Analysis.

ERIC Educational Resources Information Center

Ahrens, Steve

Predictor variables that could be used effectively to place entering freshmen methematics students into courses of instruction in mathematics were investigated at West Virginia University. Multiple discriminant analysis was used with nearly 6,000 student records collected over a three-year period, and a series of predictive equations were…

Aberrant functional connectivity for diagnosis of major depressive disorder: a discriminant analysis.

PubMed

Cao, Longlong; Guo, Shuixia; Xue, Zhimin; Hu, Yong; Liu, Haihong; Mwansisya, Tumbwene E; Pu, Weidan; Yang, Bo; Liu, Chang; Feng, Jianfeng; Chen, Eric Y H; Liu, Zhening

2014-02-01

Aberrant brain functional connectivity patterns have been reported in major depressive disorder (MDD). It is unknown whether they can be used in discriminant analysis for diagnosis of MDD. In the present study we examined the efficiency of discriminant analysis of MDD by individualized computer-assisted diagnosis. Based on resting-state functional magnetic resonance imaging data, a new approach was adopted to investigate functional connectivity changes in 39 MDD patients and 37 well-matched healthy controls. By using the proposed feature selection method, we identified significant altered functional connections in patients. They were subsequently applied to our analysis as discriminant features using a support vector machine classification method. Furthermore, the relative contribution of functional connectivity was estimated. After subset selection of high-dimension features, the support vector machine classifier reached up to approximately 84% with leave-one-out training during the discrimination process. Through summarizing the classification contribution of functional connectivities, we obtained four obvious contribution modules: inferior orbitofrontal module, supramarginal gyrus module, inferior parietal lobule-posterior cingulated gyrus module and middle temporal gyrus-inferior temporal gyrus module. The experimental results demonstrated that the proposed method is effective in discriminating MDD patients from healthy controls. Functional connectivities might be useful as new biomarkers to assist clinicians in computer auxiliary diagnosis of MDD. © 2013 The Authors. Psychiatry and Clinical Neurosciences © 2013 Japanese Society of Psychiatry and Neurology.

Corona discharge radical emission spectroscopy: a multi-channel detector with nose-type function for discrimination analysis.

PubMed

Tian, Yunfei; Wu, Peng; Wu, Xi; Jiang, Xiaoming; Xu, Kailai; Hou, Xiandeng

2013-04-21

A simple and economical multi-channel optical sensor using corona discharge radical emission spectroscopy is developed and explored as an optical nose for discrimination analysis of volatile organic compounds, wines, and even isomers.

Harassment and discrimination in medical training: a systematic review and meta-analysis.

PubMed

Fnais, Naif; Soobiah, Charlene; Chen, Maggie Hong; Lillie, Erin; Perrier, Laure; Tashkhandi, Mariam; Straus, Sharon E; Mamdani, Muhammad; Al-Omran, Mohammed; Tricco, Andrea C

2014-05-01

Harassment and discrimination include a wide range of behaviors that medical trainees perceive as being humiliating, hostile, or abusive. To understand the significance of such mistreatment and to explore potential preventive strategies, the authors conducted a systematic review and meta-analysis to examine the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. In 2011, the authors identified relevant studies by searching MEDLINE and EMBASE, scanning reference lists of relevant studies, and contacting experts. They included studies that reported the prevalence, risk factors, and sources of harassment and discrimination among medical trainees. Two reviewers independently screened all articles and abstracted study and participant characteristics and study results. The authors assessed the methodological quality in individual studies using the Newcastle-Ottawa Scale. They also conducted a meta-analysis. The authors included 57 cross-sectional and 2 cohort studies in their review. The meta-analysis of 51 studies demonstrated that 59.4% of medical trainees had experienced at least one form of harassment or discrimination during their training (95% confidence interval [CI]: 52.0%-66.7%). Verbal harassment was the most commonly cited form of harassment (prevalence: 63.0%; 95% CI: 54.8%-71.2%). Consultants were the most commonly cited source of harassment and discrimination, followed by patients or patients' families (34.4% and 21.9%, respectively). This review demonstrates the surprisingly high prevalence of harassment and discrimination among medical trainees that has not declined over time. The authors recommend both drafting policies and promoting cultural change within academic institutions to prevent future abuse.

Item analysis of examinations in the Faculty of Medicine of Tunis.

PubMed

Hermi, Amene; Achour, Wafa

2016-04-01

Introduction Item analysis is the process of collecting, summarizing and using information from students' responses to assess test items' quality. This study used this approach to evaluate the quality of items and examinations given in the Faculty of Medicine of Tunis (FMT).    Methods This study concerned the examinations of 2012-2013 (principal session). It analyzed 3138 items from 66 examinations, of which, 46 were multidisciplinary (187 disciplines). A total of 2515 students took the examinations. "AnItem.xls" file was used for the analysis that focused on difficulty, discrimination and internal consistency.  Results Mean difficulty for all examinations was optimum (mean difficulty index: 0.59). Majority of items (89.17%) were either easy or of acceptable difficulty. Mean discrimination for all examinations was moderate (mean item discrimination coefficient: 0.28) with poor discrimination in 23.62% of items. Maximal discrimination occurred with disciplines of difficulty index between 0.4-0.6. « Ideal » items represented 27.02%. Mean internal consistency for all examinations was acceptable (Cronbach's alpha: 0.79). Disciplines with nonacceptable internal consistency (68.45%) contained a maximum of 33 items (each one) and a positive correlation between their alpha and the number of their questions. Distributions were mostly (72.73%) platykurtic and negatively asymmetric (89.39%). First year of studies had the best parameters. Conclusion Our examinations had an acceptable internal consistency, and a good level of difficulty and discrimination. They tended to facility and discriminated basically students of medium level. Item analysis is useful as a guide to item writers to improve the overall quality of questions in the future.

Detection of Genetically Modified Sugarcane by Using Terahertz Spectroscopy and Chemometrics

NASA Astrophysics Data System (ADS)

Liu, J.; Xie, H.; Zha, B.; Ding, W.; Luo, J.; Hu, C.

2018-03-01

A methodology is proposed to identify genetically modified sugarcane from non-genetically modified sugarcane by using terahertz spectroscopy and chemometrics techniques, including linear discriminant analysis (LDA), support vector machine-discriminant analysis (SVM-DA), and partial least squares-discriminant analysis (PLS-DA). The classification rate of the above mentioned methods is compared, and different types of preprocessing are considered. According to the experimental results, the best option is PLS-DA, with an identification rate of 98%. The results indicated that THz spectroscopy and chemometrics techniques are a powerful tool to identify genetically modified and non-genetically modified sugarcane.

Double displacement: An improved bioorthogonal reaction strategy for templated nucleic acid detection.

PubMed

Kleinbaum, Daniel J; Miller, Gregory P; Kool, Eric T

2010-06-16

Quenched autoligation probes have been employed previously in a target-templated nonenzymatic ligation strategy for detecting nucleic acids in cells by fluorescence. A common source of background signal in such probes is the undesired reaction with water and other cellular nucleophiles. Here, we describe a new class of self-ligating probes, double displacement (DD) probes, that rely on two displacement reactions to fully unquench a nearby fluorophore. Three potential double displacement architectures, all possessing two fluorescence quencher/leaving groups (dabsylate groups), were synthesized and evaluated for templated reaction with nucleophile (phosphorothioate) probes both in vitro and in intact bacterial cells. All three DD probe designs provided substantially better initial quenching than a single-Dabsyl control. In isothermal templated reactions in vitro, double displacement probes yielded considerably lower background signal than previous single displacement probes; investigation into the mechanism revealed that one dabsylate acts as a sacrificial leaving group, reacting nonspecifically with water, but yielding little signal because another quencher group remains. Templated reaction with the specific nucleophile probe is required to activate a signal. The double displacement probes provided a ca. 80-fold turn-on signal and yielded a 2-4-fold improvement in signal/background over single Dabsyl probes. The best-performing probe architecture was demonstrated in a two-color, FRET-based two-allele discrimination system in vitro and was shown to be capable of discriminating between two closely related species of bacteria differing by a single nucleotide at an rRNA target site.

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.

The discrimination of geoforensic trace material from close proximity locations by organic profiling using HPLC and plant wax marker analysis by GC.

PubMed

McCulloch, G; Dawson, L A; Ross, J M; Morgan, R M

2018-07-01

There is a need to develop a wider empirical research base to expand the scope for utilising the organic fraction of soil in forensic geoscience, and to demonstrate the capability of the analytical techniques used in forensic geoscience to discriminate samples at close proximity locations. The determination of wax markers from soil samples by GC analysis has been used extensively in court and is known to be effective in discriminating samples from different land use types. A new HPLC method for the analysis of the organic fraction of forensic sediment samples has also been shown recently to add value in conjunction with existing inorganic techniques for the discrimination of samples derived from close proximity locations. This study compares the ability of these two organic techniques to discriminate samples derived from close proximity locations and finds the GC technique to provide good discrimination at this scale, providing quantification of known compounds, whilst the HPLC technique offered a shorter and simpler sample preparation method and provided very good discrimination between groups of samples of different provenance in most cases. The use of both data sets together gave further improved accuracy rates in some cases, suggesting that a combined organic approach can provide added benefits in certain case scenarios and crime reconstruction contexts. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Classification of cucumber green mottle mosaic virus (CGMMV) infected watermelon seeds using Raman spectroscopy

NASA Astrophysics Data System (ADS)

Lee, Hoonsoo; Lim, Hyoun-Sub; Cho, Byoung-Kwan

2016-05-01

The Cucumber Green Mottle Mosaic Virus (CGMMV) is a globally distributed plant virus. CGMMV-infected plants exhibit severe mosaic symptoms, discoloration, and deformation. Therefore, rapid and early detection of CGMMV infected seeds is very important for preventing disease damage and yield losses. Raman spectroscopy was investigated in this study as a potential tool for rapid, accurate, and nondestructive detection of infected seeds. Raman spectra of healthy and infected seeds were acquired in the 400 cm-1 to 1800 cm-1 wavenumber range and an algorithm based on partial least-squares discriminant analysis was developed to classify infected and healthy seeds. The classification model's accuracies for calibration and prediction data sets were 100% and 86%, respectively. Results showed that the Raman spectroscopic technique has good potential for nondestructive detection of virus-infected seeds.

Raman spectroscopic characterization of urine of normal and cervical cancer subjects

NASA Astrophysics Data System (ADS)

Pappu, Raja; Prakasarao, Aruna; Dornadula, Koteeswaran; Singaravelu, Ganesan

2017-02-01

Cervical cancer is the fourth most common malignancy in female worldwide; the present method for diagnosis is the biopsy, Pap smear, colposcopy etc. To overcome the drawbacks of diagnosis an alternative technique is required, optical spectroscopy is a new technique where the discrimination of normal and cancer subjects provides valuable potential information in the diagnostic oncology at an early stage. Raman peaks in the spectra suggest interesting differences in various bio molecules. In this regard, non invasive optical detection of cervical cancer using urine samples by Raman Spectroscopy combined with LDA diagnostic algorithm yields an accuracy of 100% for original and cross validated group respectively. As the results were appreciable it is necessary to carry out the analysis for more number of samples to explore the facts hidden at different stages during the development of cervical cancer.

PROSPECT - A precision oscillation and spectrum experiment

NASA Astrophysics Data System (ADS)

Langford, T. J.; PROSPECT Collaboration

2015-08-01

Segmented antineutrino detectors placed near a compact research reactor provide an excellent opportunity to probe short-baseline neutrino oscillations and precisely measure the reactor antineutrino spectrum. Close proximity to a reactor combined with minimal overburden yield a high background environment that must be managed through shielding and detector technology. PROSPECT is a new experimental effort to detect reactor antineutrinos from the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory, managed by UT Battelle for the U.S. Department of Energy. The detector will use novel lithium-loaded liquid scintillator capable of neutron/gamma pulse shape discrimination and neutron capture tagging. These enhancements improve the ability to identify neutrino inverse-beta decays (IBD) and reject background events in analysis. Results from these efforts will be covered along with their implications for an oscillation search and a precision spectrum measurement.

P300 Chinese input system based on Bayesian LDA.

PubMed

Jin, Jing; Allison, Brendan Z; Brunner, Clemens; Wang, Bei; Wang, Xingyu; Zhang, Jianhua; Neuper, Christa; Pfurtscheller, Gert

2010-02-01

A brain-computer interface (BCI) is a new communication channel between humans and computers that translates brain activity into recognizable command and control signals. Attended events can evoke P300 potentials in the electroencephalogram. Hence, the P300 has been used in BCI systems to spell, control cursors or robotic devices, and other tasks. This paper introduces a novel P300 BCI to communicate Chinese characters. To improve classification accuracy, an optimization algorithm (particle swarm optimization, PSO) is used for channel selection (i.e., identifying the best electrode configuration). The effects of different electrode configurations on classification accuracy were tested by Bayesian linear discriminant analysis offline. The offline results from 11 subjects show that this new P300 BCI can effectively communicate Chinese characters and that the features extracted from the electrodes obtained by PSO yield good performance.

Housing anxiety and multiple geographies in post-tsunami Sri Lanka.

PubMed

Boano, Camillo

2009-10-01

Tsunami intervention has been an extraordinary and unprecedented relief and recovery operation. This article underlines the complexities posed by shelter and housing intervention in post-tsunami Sri Lanka, revealing a pragmatic, reductionist approach to shelter and housing reconstruction in a contested and fragmented environment. Competition, housing anxiety and buffer zone implementation have resulted in compulsory villagisation inland, stirring feelings of discrimination and tension, and becoming major obstacles to equitable rebuilding of houses and livelihoods. A new tsunami geography has been imposed on an already vulnerable conflict-based geography, in which shelter has been conceived as a mono-dimensional artefact. An analysis of the process and outcomes of temporary and permanent post-tsunami housing programmes yields information about the extent to which shelter policies and programmes serve not only physical needs but 'higher order' objectives for a comprehensive and sustainable recovery plan.

Real-time image annotation by manifold-based biased Fisher discriminant analysis

NASA Astrophysics Data System (ADS)

Ji, Rongrong; Yao, Hongxun; Wang, Jicheng; Sun, Xiaoshuai; Liu, Xianming

2008-01-01

Automatic Linguistic Annotation is a promising solution to bridge the semantic gap in content-based image retrieval. However, two crucial issues are not well addressed in state-of-art annotation algorithms: 1. The Small Sample Size (3S) problem in keyword classifier/model learning; 2. Most of annotation algorithms can not extend to real-time online usage due to their low computational efficiencies. This paper presents a novel Manifold-based Biased Fisher Discriminant Analysis (MBFDA) algorithm to address these two issues by transductive semantic learning and keyword filtering. To address the 3S problem, Co-Training based Manifold learning is adopted for keyword model construction. To achieve real-time annotation, a Bias Fisher Discriminant Analysis (BFDA) based semantic feature reduction algorithm is presented for keyword confidence discrimination and semantic feature reduction. Different from all existing annotation methods, MBFDA views image annotation from a novel Eigen semantic feature (which corresponds to keywords) selection aspect. As demonstrated in experiments, our manifold-based biased Fisher discriminant analysis annotation algorithm outperforms classical and state-of-art annotation methods (1.K-NN Expansion; 2.One-to-All SVM; 3.PWC-SVM) in both computational time and annotation accuracy with a large margin.

Application of discriminant analysis-based model for prediction of risk of low back disorders due to workplace design in industrial jobs.

PubMed

Ganga, G M D; Esposto, K F; Braatz, D

2012-01-01

The occupational exposure limits of different risk factors for development of low back disorders (LBDs) have not yet been established. One of the main problems in setting such guidelines is the limited understanding of how different risk factors for LBDs interact in causing injury, since the nature and mechanism of these disorders are relatively unknown phenomena. Industrial ergonomists' role becomes further complicated because the potential risk factors that may contribute towards the onset of LBDs interact in a complex manner, which makes it difficult to discriminate in detail among the jobs that place workers at high or low risk of LBDs. The purpose of this paper was to develop a comparative study between predictions based on the neural network-based model proposed by Zurada, Karwowski & Marras (1997) and a linear discriminant analysis model, for making predictions about industrial jobs according to their potential risk of low back disorders due to workplace design. The results obtained through applying the discriminant analysis-based model proved that it is as effective as the neural network-based model. Moreover, the discriminant analysis-based model proved to be more advantageous regarding cost and time savings for future data gathering.

Spatial-temporal discriminant analysis for ERP-based brain-computer interface.

PubMed

Zhang, Yu; Zhou, Guoxu; Zhao, Qibin; Jin, Jing; Wang, Xingyu; Cichocki, Andrzej

2013-03-01

Linear discriminant analysis (LDA) has been widely adopted to classify event-related potential (ERP) in brain-computer interface (BCI). Good classification performance of the ERP-based BCI usually requires sufficient data recordings for effective training of the LDA classifier, and hence a long system calibration time which however may depress the system practicability and cause the users resistance to the BCI system. In this study, we introduce a spatial-temporal discriminant analysis (STDA) to ERP classification. As a multiway extension of the LDA, the STDA method tries to maximize the discriminant information between target and nontarget classes through finding two projection matrices from spatial and temporal dimensions collaboratively, which reduces effectively the feature dimensionality in the discriminant analysis, and hence decreases significantly the number of required training samples. The proposed STDA method was validated with dataset II of the BCI Competition III and dataset recorded from our own experiments, and compared to the state-of-the-art algorithms for ERP classification. Online experiments were additionally implemented for the validation. The superior classification performance in using few training samples shows that the STDA is effective to reduce the system calibration time and improve the classification accuracy, thereby enhancing the practicability of ERP-based BCI.

Ebony and Ivory: Relationship between African American Young Women's Skin Color and Ratings of Self and Peers

ERIC Educational Resources Information Center

Nassar-McMillan, Sylvia; McFall-Roberts, Ebuni; Flowers, Claudia; Garrett, Michael T.

2006-01-01

Many individuals face discrimination because of their skin color; however, skin color of African American young adults has not been studied in detail. This study examines relationships between skin color and perceptions among African American college women. The study yielded a positive correlation between personal values and self-rated skin color …

Sex Estimation From Sternal Measurements Using Multidetector Computed Tomography

PubMed Central

Ekizoglu, Oguzhan; Hocaoglu, Elif; Inci, Ercan; Bilgili, Mustafa Gokhan; Solmaz, Dilek; Erdil, Irem; Can, Ismail Ozgur

2014-01-01

Abstract We aimed to show the utility and reliability of sternal morphometric analysis for sex estimation. Sex estimation is a very important step in forensic identification. Skeletal surveys are main methods for sex estimation studies. Morphometric analysis of sternum may provide high accuracy rated data in sex discrimination. In this study, morphometric analysis of sternum was evaluated in 1 mm chest computed tomography scans for sex estimation. Four hundred forty 3 subjects (202 female, 241 male, mean age: 44 ± 8.1 [distribution: 30–60 year old]) were included the study. Manubrium length (ML), mesosternum length (2L), Sternebra 1 (S1W), and Sternebra 3 (S3W) width were measured and also sternal index (SI) was calculated. Differences between genders were evaluated by student t-test. Predictive factors of sex were determined by discrimination analysis and receiver operating characteristic (ROC) analysis. Male sternal measurement values are significantly higher than females (P < 0.001) while SI is significantly low in males (P < 0.001). In discrimination analysis, MSL has high accuracy rate with 80.2% in females and 80.9% in males. MSL also has the best sensitivity (75.9%) and specificity (87.6%) values. Accuracy rates were above 80% in 3 stepwise discrimination analysis for both sexes. Stepwise 1 (ML, MSL, S1W, S3W) has the highest accuracy rate in stepwise discrimination analysis with 86.1% in females and 83.8% in males. Our study showed that morphometric computed tomography analysis of sternum might provide important information for sex estimation. PMID:25501090

Taking Advantage of Disorder: Small-Molecule Organic Glasses for Radiation Detection and Particle Discrimination

DOE PAGES

Carlson, Joseph S.; Marleau, Peter; Zarkesh, Ryan A.; ...

2017-06-20

A series of fluorescent silyl-fluorene molecules were synthesized and studied with respect to their photophysical properties and response toward ionizing neutron and gamma-ray radiation. Optically transparent and stable organic glasses were prepared from these materials using a bulk melt-casting procedure. The prepared organic glass monoliths provided fluorescence quantum yields and radiation detection properties exceeding the highest-performing benchmark materials such as solution-grown trans-stilbene crystals. Co-melts based on blends of two different glass-forming compounds were prepared with the goal of enhancing the stability of the amorphous state. Accelerated aging experiments on co-melt mixtures ranging from 0% to 100% of each component indicatedmore » improved resistance to recrystallization in the glass blends, able to remain fully amorphous for >1 month at 60 °C. Secondary dopants comprising singlet fluorophores or iridium organometallic compounds provided further improved detection efficiency, as evaluated by light yield and neutron/gamma particle discrimination measurements. As a result, optimized singlet and triplet doping levels were determined to be 0.05 wt % 1,4-bis(2-methylstyryl)benzene singlet fluorophore and 0.28 wt % Ir 3+, respectively.« less