States' Accommodations Policies and Development of Alternate Assessments Based on Modified Achievement Standards: A Discriminant Analysis

ERIC Educational Resources Information Center

Lazarus, Sheryl S.; Cormier, Damien C.; Thurlow, Martha L.

2011-01-01

The characteristics of a state's accommodations policy may affect a state's decision about whether to develop an alternate assessment based on modified achievement standards (AA-MAS). A very restrictive accommodations policy may make it more difficult for some students to participate in the state's regular assessment used for accountability…

Optical Spectroscopic Analysis for the Discrimination of Extra-Virgin Olive Oil.

PubMed

McReynolds, Naomi; Auñón Garcia, Juan M; Guengerich, Zoe; Smith, Terry K; Dholakia, Kishan

2016-11-01

We demonstrate the ability to discriminate between five brands of commercially available extra-virgin olive oil (EVOO) using Raman spectroscopy or fluorescence spectroscopy. Data was taken on both a 'bulk optics' free space system and on a compact handheld device, each capable of taking both Raman and fluorescence data. With the compact Raman device we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach illustrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. The main challenge with this technique is that oxidation of EVOO causes a shift in the Raman signal over time. It would therefore be necessary to retrain the database regularly. We demonstrate preliminary data to address this issue, which may enable successful discrimination over time. We show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency. © The Author(s) 2016.

A test of the perceived norms model to explain drinking patterns among university student athletes.

PubMed

Thombs, D L

2000-09-01

The author tested the ability of perceived drinking norms to discriminate among drinking patterns in a sample of National Collegiate Athletic Association (NCAA) Division I student athletes. He used an anonymous questionnaire to assess 297 athletes, representing 18 teams, at a public university in the Midwest. Alcohol use patterns showed considerable variation, with many athletes (37.1%) abstaining during their season of competition. A discriminant function analysis revealed that higher levels of alcohol involvement are disproportionately found among athletes who began drinking regularly at an early age. Perceived drinking norms were less important in the discrimination of student athlete drinker groups. Women and those with higher grade point averages were somewhat more likely to refrain from in-season drinking than other survey respondents.

Discriminating Characteristics of Tectonic and Human-Induced Seismicity

NASA Astrophysics Data System (ADS)

Zaliapin, I. V.; Ben-Zion, Y.

2015-12-01

We analyze statistical features of background and clustered subpopulations of earthquakes in different regions in an effort to distinguish between human-induced and natural seismicity. Analysis of "end-member" areas known to be dominated by human-induced earthquakes (the Geyser geothermal field in northern California and TauTona gold mine in South Africa) and regular tectonic activity (the San Jacinto fault zone in southern California and Coso region excluding the Coso geothermal field in eastern central California) reveals several distinguishing characteristics. Induced seismicity is shown to have (i) higher rate of background events (both absolute and relative to the total rate), (ii) faster temporal offspring decay, (iii) higher intensity of repeating events, (iv) larger proportion of small clusters, and (v) larger spatial separation between parent and offspring, compared to regular tectonic activity. These differences also successfully discriminate seismicity within the Coso and Salton Sea geothermal fields in California before and after the expansion of geothermal production during the 1980s.

A Novel Graph Constructor for Semisupervised Discriminant Analysis: Combined Low-Rank and k-Nearest Neighbor Graph

PubMed Central

Pan, Yongke; Niu, Wenjia

2017-01-01

Semisupervised Discriminant Analysis (SDA) is a semisupervised dimensionality reduction algorithm, which can easily resolve the out-of-sample problem. Relative works usually focus on the geometric relationships of data points, which are not obvious, to enhance the performance of SDA. Different from these relative works, the regularized graph construction is researched here, which is important in the graph-based semisupervised learning methods. In this paper, we propose a novel graph for Semisupervised Discriminant Analysis, which is called combined low-rank and k-nearest neighbor (LRKNN) graph. In our LRKNN graph, we map the data to the LR feature space and then the kNN is adopted to satisfy the algorithmic requirements of SDA. Since the low-rank representation can capture the global structure and the k-nearest neighbor algorithm can maximally preserve the local geometrical structure of the data, the LRKNN graph can significantly improve the performance of SDA. Extensive experiments on several real-world databases show that the proposed LRKNN graph is an efficient graph constructor, which can largely outperform other commonly used baselines. PMID:28316616

Dual mechanisms in the perceptual processing of click train temporal regularity.

PubMed

Phillips, Dennis P; Dingle, Rachel N; Hall, Susan E; Jang, Moragh

2012-07-01

Two experiments measured human sensitivity to temporal jitter in 25-click trains with inter-click intervals (ICIs) between 5 and 100 ms. In a naturalistic experiment using wideband clicks, jitter thresholds were a nonmonotonic function of ICI, peaking for ICIs near 40-60 ms. In a subsequent experiment, clicks were high-passed and presented against a low-frequency noise masker. Jitter threshold vs ICI functions lost the positive slope over short ICIs but retained the negative slope at long ICIs. The same behavior was seen in click rate discrimination tasks. Different processes mediate regularity analysis for click trains with ICIs above and below 40-60 ms.

Qualitative and quantitative evaluation of a local lymph node assay based on ex vivo interleukin-2 production.

PubMed

Azam, Philippe; Peiffer, Jean-Luc; Ourlin, Jean-Claude; Bonnet, Pierre-Antoine; Tissier, Marie-Hélène; Vian, Laurence; Fabre, Isabelle

2005-01-15

The local lymph node assay (LLNA) is a regular method for the detection of sensitizing chemicals in mice which measures the incorporation of tritiated thymidine in lymph node cells. We have evaluated an alternative to this method based on the interleukin-2 (IL-2) production of lymph node cells. At the mRNA level, no change in the IL-2 gene expression level was detected by real-time PCR analysis. At the protein level, various experimental conditions were checked in order to improve the irritant versus sensitizer discrimination with a restricted set of prototypic compounds. In particular, the use of phytohemagglutinin A (PHA) in an ex vivo cell culture step showed an improvement of both signal and discrimination. In these optimised conditions, a panel of irritants and potency-graded sensitizers was used to assess the performance of the modified method. IFN-gamma production was used as a positive control. For each compound, a dose-response was performed and stimulation indexes (SI) were determined. Effective concentrations (EC) for each sensitizers were then extracted and compared to the literature data of the regular LLNA. The IL-2-based LLNA showed similar performances at both qualitative and quantitative levels compared to regular LLNA.

Optical spectroscopic analysis for the discrimination of extra-virgin olive-oil (Conference Presentation)

NASA Astrophysics Data System (ADS)

McReynolds, Naomi; Auñón Garcia, Juan M.; Guengerich, Zoe; Smith, Terry K.; Dholakia, Kishan

2017-02-01

We present an optical spectroscopic technique, making use of both Raman signals and fluorescence spectroscopy, for the identification of five brands of commercially available extra-virgin olive-oil (EVOO). We demonstrate our technique on both a `bulk-optics' free-space system and a compact device. Using the compact device, which is capable of recording both Raman and fluorescence signals, we achieved an average sensitivity and specificity of 98.4% and 99.6% for discrimination, respectively. Our approach demonstrates that both Raman and fluorescence spectroscopy can be used for portable discrimination of EVOOs which obviates the need to use centralised laboratories and opens up the prospect of in-field testing. This technique may enable detection of EVOO that has undergone counterfeiting or adulteration. One of the main challenges facing Raman spectroscopy for use in quality control of EVOOs is that the oxidation of EVOO, which naturally occurs due to aging, causes shifts in Raman spectra with time, which implies regular retraining would be necessary. We present a potential method of analysis to minimize the effect that aging has on discrimination efficiency; we show that by discarding the first principal component, which contains information on the variations due to oxidation, we can improve discrimination efficiency thus improving the robustness of our technique.

Sex Partnership and Self-Efficacy Influence Depression in Chinese Transgender Women: A Cross-Sectional Study

PubMed Central

Yang, Xiaoshi; Wang, Lie; Hao, Chun; Gu, Yuan; Song, Wei; Wang, Jian; Chang, Margaret M.; Zhao, Qun

2015-01-01

Background Transgender women often suffer from transition-related discrimination and loss of social support due to their gender transition, which may pose considerable psychological challenges and may lead to a high prevalence of depression in this population. Increased self-efficacy may combat the adverse effects of gender transition on depression. However, few available studies have investigated the protective effect of self-efficacy on depression among transgender women, and there is a scarcity of research describing the mental health of Chinese transgender women. This study aims to describe the prevalence of depression among Chinese transgender women and to explore the associated factors. Methods A cross-sectional study was conducted in Shenyang, Liaoning Province of China by convenience sampling from January 2014 to July 2014. Two hundred and nine Chinese transgender women were interviewed face-to-face with questionnaires that covered topics including the Zung Self-Rating Depression Scale (SDS), demographic characteristics, transition status, sex partnership, perceived transgender-related discrimination, the Multidimensional Scale of Perceived Social Support (MSPSS) and the adapted General Self-efficacy Scale (GSES). A hierarchical multiple regression analysis was performed to explore the factors associated with SDS scores. Results The prevalence of depression among transgender women was 45.35%. Transgender women with regular partners or casual partners exhibited higher SDS scores than those without regular partners or casual partners. Regression analyses showed that sex partnership explained most (16.6%) of the total variance in depression scores. Self-efficacy was negatively associated with depression. Conclusions Chinese transgender women experienced high levels of depression. Depression was best predicted by whether transgender women had a regular partner or a casual partner rather than transgender-related discrimination and transition status. Moreover, self-efficacy had positive effects on attenuating depression due to gender transition. Therefore, interventions should focus on improving the sense of self-efficacy among these women to enable them to cope with depression and to determine risky sex partnership characteristics, especially for regular and casual partners. PMID:26367265

Sex Partnership and Self-Efficacy Influence Depression in Chinese Transgender Women: A Cross-Sectional Study.

PubMed

Yang, Xiaoshi; Wang, Lie; Hao, Chun; Gu, Yuan; Song, Wei; Wang, Jian; Chang, Margaret M; Zhao, Qun

2015-01-01

Transgender women often suffer from transition-related discrimination and loss of social support due to their gender transition, which may pose considerable psychological challenges and may lead to a high prevalence of depression in this population. Increased self-efficacy may combat the adverse effects of gender transition on depression. However, few available studies have investigated the protective effect of self-efficacy on depression among transgender women, and there is a scarcity of research describing the mental health of Chinese transgender women. This study aims to describe the prevalence of depression among Chinese transgender women and to explore the associated factors. A cross-sectional study was conducted in Shenyang, Liaoning Province of China by convenience sampling from January 2014 to July 2014. Two hundred and nine Chinese transgender women were interviewed face-to-face with questionnaires that covered topics including the Zung Self-Rating Depression Scale (SDS), demographic characteristics, transition status, sex partnership, perceived transgender-related discrimination, the Multidimensional Scale of Perceived Social Support (MSPSS) and the adapted General Self-efficacy Scale (GSES). A hierarchical multiple regression analysis was performed to explore the factors associated with SDS scores. The prevalence of depression among transgender women was 45.35%. Transgender women with regular partners or casual partners exhibited higher SDS scores than those without regular partners or casual partners. Regression analyses showed that sex partnership explained most (16.6%) of the total variance in depression scores. Self-efficacy was negatively associated with depression. Chinese transgender women experienced high levels of depression. Depression was best predicted by whether transgender women had a regular partner or a casual partner rather than transgender-related discrimination and transition status. Moreover, self-efficacy had positive effects on attenuating depression due to gender transition. Therefore, interventions should focus on improving the sense of self-efficacy among these women to enable them to cope with depression and to determine risky sex partnership characteristics, especially for regular and casual partners.

The SRI-WEFA Soviet Econometric Model: Phase One Documentation

DTIC Science & Technology

1975-03-01

established prices. We also have an estimated equation for an end-use residual category which conceptually includes state grain reserves, other undis...forecasting. An important virtue of the econometric discipline is that it requires one first to conceptualize and estimate regularities of behavior...any de- scriptive analysis. Within the framwork of an econometric model, the analyst is able to discriminate among these "special events

Weighted Discriminative Dictionary Learning based on Low-rank Representation

NASA Astrophysics Data System (ADS)

Chang, Heyou; Zheng, Hao

2017-01-01

Low-rank representation has been widely used in the field of pattern classification, especially when both training and testing images are corrupted with large noise. Dictionary plays an important role in low-rank representation. With respect to the semantic dictionary, the optimal representation matrix should be block-diagonal. However, traditional low-rank representation based dictionary learning methods cannot effectively exploit the discriminative information between data and dictionary. To address this problem, this paper proposed weighted discriminative dictionary learning based on low-rank representation, where a weighted representation regularization term is constructed. The regularization associates label information of both training samples and dictionary atoms, and encourages to generate a discriminative representation with class-wise block-diagonal structure, which can further improve the classification performance where both training and testing images are corrupted with large noise. Experimental results demonstrate advantages of the proposed method over the state-of-the-art methods.

Inflammatory Asthma Phenotype Discrimination Using an Electronic Nose Breath Analyzer.

PubMed

Plaza, V; Crespo, A; Giner, J; Merino, J L; Ramos-Barbón, D; Mateus, E F; Torrego, A; Cosio, B G; Agustí, A; Sibila, O

2015-01-01

Patients with persistent asthma have different inflammatory phenotypes. The electronic nose is a new technology capable of distinguishing volatile organic compound (VOC) breath-prints in exhaled breath. The aim of the study was to investigate the capacity of electronic nose breath-print analysis to discriminate between different inflammatory asthma phenotypes (eosinophilic, neutrophilic, paucigranulocytic) determined by induced sputum in patients with persistent asthma. Fifty-two patients with persistent asthma were consecutively included in a cross-sectional proof-of-concept study. Inflammatory asthma phenotypes (eosinophilic, neutrophilic and paucigranulocytic) were recognized by inflammatory cell counts in induced sputum. VOC breath-prints were analyzed using the electronic nose Cyranose 320 and assessed by discriminant analysis on principal component reduction, resulting in cross-validated accuracy values. Receiver operating characteristic (ROC) curves were calculated. VOC breath-prints were different in eosinophilic asthmatics compared with both neutrophilic asthmatics (accuracy 73%; P=.008; area under ROC, 0.92) and paucigranulocytic asthmatics (accuracy 74%; P=.004; area under ROC, 0.79). Likewise, neutrophilic and paucigranulocytic breath-prints were also different (accuracy 89%; P=.001; area under ROC, 0.88). An electronic nose can discriminate inflammatory phenotypes in patients with persistent asthma in a regular clinical setting. ClinicalTrials.gov identifier: NCT02026336.

TV watching, soap opera and happiness.

PubMed

Lu, L; Argyle, M

1993-09-01

One hundred and fourteen subjects reported the amount of time they spent watching television in general, and soap opera in particular. They also completed scales measuring happiness and other personality variables, such as extraversion and cooperativeness. In the multiple regression analysis, having controlled for the demographic variables, watching TV was related to unhappiness, whereas watching soap opera was related to happiness. Discriminant analysis showed that females, higher happiness and extraversion distinguished regular soap watchers (who nevertheless watched little TV in general) from irregular soap watchers (who nevertheless watched a lot of TV in general).

Alert management for home healthcare based on home automation analysis.

PubMed

Truong, T T; de Lamotte, F; Diguet, J-Ph; Said-Hocine, F

2010-01-01

Rising healthcare for elder and disabled people can be controlled by offering people autonomy at home by means of information technology. In this paper, we present an original and sensorless alert management solution which performs multimedia and home automation service discrimination and extracts highly regular home activities as sensors for alert management. The results of simulation data, based on real context, allow us to evaluate our approach before application to real data.

Quality Evaluation and Chemical Markers Screening of Salvia miltiorrhiza Bge. (Danshen) Based on HPLC Fingerprints and HPLC-MSn Coupled with Chemometrics.

PubMed

Liang, Wenyi; Chen, Wenjing; Wu, Lingfang; Li, Shi; Qi, Qi; Cui, Yaping; Liang, Linjin; Ye, Ting; Zhang, Lanzhen

2017-03-17

Danshen, the dried root of Salvia miltiorrhiza Bge., is a widely used commercially available herbal drug, and unstable quality of different samples is a current issue. This study focused on a comprehensive and systematic method combining fingerprints and chemical identification with chemometrics for discrimination and quality assessment of Danshen samples. Twenty-five samples were analyzed by HPLC-PAD and HPLC-MS n . Forty-nine components were identified and characteristic fragmentation regularities were summarized for further interpretation of bioactive components. Chemometric analysis was employed to differentiate samples and clarify the quality differences of Danshen including hierarchical cluster analysis, principal component analysis, and partial least squares discriminant analysis. Consistent results were that the samples were divided into three categories which reflected the difference in quality of Danshen samples. By analyzing the reasons for sample classification, it was revealed that the processing method had a more obvious impact on sample classification than the geographical origin, it induced the different content of bioactive compounds and finally lead to different qualities. Cryptotanshinone, trijuganone B, and 15,16-dihydrotanshinone I were screened out as markers to distinguish samples by different processing methods. The developed strategy could provide a reference for evaluation and discrimination of other traditional herbal medicines.

Learning Robust and Discriminative Subspace With Low-Rank Constraints.

PubMed

Li, Sheng; Fu, Yun

2016-11-01

In this paper, we aim at learning robust and discriminative subspaces from noisy data. Subspace learning is widely used in extracting discriminative features for classification. However, when data are contaminated with severe noise, the performance of most existing subspace learning methods would be limited. Recent advances in low-rank modeling provide effective solutions for removing noise or outliers contained in sample sets, which motivates us to take advantage of low-rank constraints in order to exploit robust and discriminative subspace for classification. In particular, we present a discriminative subspace learning method called the supervised regularization-based robust subspace (SRRS) approach, by incorporating the low-rank constraint. SRRS seeks low-rank representations from the noisy data, and learns a discriminative subspace from the recovered clean data jointly. A supervised regularization function is designed to make use of the class label information, and therefore to enhance the discriminability of subspace. Our approach is formulated as a constrained rank-minimization problem. We design an inexact augmented Lagrange multiplier optimization algorithm to solve it. Unlike the existing sparse representation and low-rank learning methods, our approach learns a low-dimensional subspace from recovered data, and explicitly incorporates the supervised information. Our approach and some baselines are evaluated on the COIL-100, ALOI, Extended YaleB, FERET, AR, and KinFace databases. The experimental results demonstrate the effectiveness of our approach, especially when the data contain considerable noise or variations.

Size-distribution analysis of macromolecules by sedimentation velocity ultracentrifugation and lamm equation modeling.

PubMed

Schuck, P

2000-03-01

A new method for the size-distribution analysis of polymers by sedimentation velocity analytical ultracentrifugation is described. It exploits the ability of Lamm equation modeling to discriminate between the spreading of the sedimentation boundary arising from sample heterogeneity and from diffusion. Finite element solutions of the Lamm equation for a large number of discrete noninteracting species are combined with maximum entropy regularization to represent a continuous size-distribution. As in the program CONTIN, the parameter governing the regularization constraint is adjusted by variance analysis to a predefined confidence level. Estimates of the partial specific volume and the frictional ratio of the macromolecules are used to calculate the diffusion coefficients, resulting in relatively high-resolution sedimentation coefficient distributions c(s) or molar mass distributions c(M). It can be applied to interference optical data that exhibit systematic noise components, and it does not require solution or solvent plateaus to be established. More details on the size-distribution can be obtained than from van Holde-Weischet analysis. The sensitivity to the values of the regularization parameter and to the shape parameters is explored with the help of simulated sedimentation data of discrete and continuous model size distributions, and by applications to experimental data of continuous and discrete protein mixtures.

Linear Discriminant Analysis Achieves High Classification Accuracy for the BOLD fMRI Response to Naturalistic Movie Stimuli

PubMed Central

Mandelkow, Hendrik; de Zwart, Jacco A.; Duyn, Jeff H.

2016-01-01

Naturalistic stimuli like movies evoke complex perceptual processes, which are of great interest in the study of human cognition by functional MRI (fMRI). However, conventional fMRI analysis based on statistical parametric mapping (SPM) and the general linear model (GLM) is hampered by a lack of accurate parametric models of the BOLD response to complex stimuli. In this situation, statistical machine-learning methods, a.k.a. multivariate pattern analysis (MVPA), have received growing attention for their ability to generate stimulus response models in a data-driven fashion. However, machine-learning methods typically require large amounts of training data as well as computational resources. In the past, this has largely limited their application to fMRI experiments involving small sets of stimulus categories and small regions of interest in the brain. By contrast, the present study compares several classification algorithms known as Nearest Neighbor (NN), Gaussian Naïve Bayes (GNB), and (regularized) Linear Discriminant Analysis (LDA) in terms of their classification accuracy in discriminating the global fMRI response patterns evoked by a large number of naturalistic visual stimuli presented as a movie. Results show that LDA regularized by principal component analysis (PCA) achieved high classification accuracies, above 90% on average for single fMRI volumes acquired 2 s apart during a 300 s movie (chance level 0.7% = 2 s/300 s). The largest source of classification errors were autocorrelations in the BOLD signal compounded by the similarity of consecutive stimuli. All classifiers performed best when given input features from a large region of interest comprising around 25% of the voxels that responded significantly to the visual stimulus. Consistent with this, the most informative principal components represented widespread distributions of co-activated brain regions that were similar between subjects and may represent functional networks. In light of these results, the combination of naturalistic movie stimuli and classification analysis in fMRI experiments may prove to be a sensitive tool for the assessment of changes in natural cognitive processes under experimental manipulation. PMID:27065832

Volcano plots in analyzing differential expressions with mRNA microarrays.

PubMed

Li, Wentian

2012-12-01

A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.

Evaluation of drinking quality of groundwater through multivariate techniques in urban area.

PubMed

Das, Madhumita; Kumar, A; Mohapatra, M; Muduli, S D

2010-07-01

Groundwater is a major source of drinking water in urban areas. Because of the growing threat of debasing water quality due to urbanization and development, monitoring water quality is a prerequisite to ensure its suitability for use in drinking. But analysis of a large number of properties and parameter to parameter basis evaluation of water quality is not feasible in a regular interval. Multivariate techniques could streamline the data without much loss of information to a reasonably manageable data set. In this study, using principal component analysis, 11 relevant properties of 58 water samples were grouped into three statistical factors. Discriminant analysis identified "pH influence" as the most distinguished factor and pH, Fe, and NO₃⁻ as the most discriminating variables and could be treated as water quality indicators. These were utilized to classify the sampling sites into homogeneous clusters that reflect location-wise importance of specific indicator/s for use to monitor drinking water quality in the whole study area.

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.

Kernel-Based Discriminant Techniques for Educational Placement

ERIC Educational Resources Information Center

Lin, Miao-hsiang; Huang, Su-yun; Chang, Yuan-chin

2004-01-01

This article considers the problem of educational placement. Several discriminant techniques are applied to a data set from a survey project of science ability. A profile vector for each student consists of five science-educational indicators. The students are intended to be placed into three reference groups: advanced, regular, and remedial.…

Kernel Partial Least Squares for Nonlinear Regression and Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Clancy, Daniel (Technical Monitor)

2002-01-01

This paper summarizes recent results on applying the method of partial least squares (PLS) in a reproducing kernel Hilbert space (RKHS). A previously proposed kernel PLS regression model was proven to be competitive with other regularized regression methods in RKHS. The family of nonlinear kernel-based PLS models is extended by considering the kernel PLS method for discrimination. Theoretical and experimental results on a two-class discrimination problem indicate usefulness of the method.

Mixture of Segmenters with Discriminative Spatial Regularization and Sparse Weight Selection*

PubMed Central

Chen, Ting; Rangarajan, Anand; Eisenschenk, Stephan J.

2011-01-01

This paper presents a novel segmentation algorithm which automatically learns the combination of weak segmenters and builds a strong one based on the assumption that the locally weighted combination varies w.r.t. both the weak segmenters and the training images. We learn the weighted combination during the training stage using a discriminative spatial regularization which depends on training set labels. A closed form solution to the cost function is derived for this approach. In the testing stage, a sparse regularization scheme is imposed to avoid overfitting. To the best of our knowledge, such a segmentation technique has never been reported in literature and we empirically show that it significantly improves on the performances of the weak segmenters. After showcasing the performance of the algorithm in the context of atlas-based segmentation, we present comparisons to the existing weak segmenter combination strategies on a hippocampal data set. PMID:22003748

On the validity of time-dependent AUC estimators.

PubMed

Schmid, Matthias; Kestler, Hans A; Potapov, Sergej

2015-01-01

Recent developments in molecular biology have led to the massive discovery of new marker candidates for the prediction of patient survival. To evaluate the predictive value of these markers, statistical tools for measuring the performance of survival models are needed. We consider estimators of discrimination measures, which are a popular approach to evaluate survival predictions in biomarker studies. Estimators of discrimination measures are usually based on regularity assumptions such as the proportional hazards assumption. Based on two sets of molecular data and a simulation study, we show that violations of the regularity assumptions may lead to over-optimistic estimates of prediction accuracy and may therefore result in biased conclusions regarding the clinical utility of new biomarkers. In particular, we demonstrate that biased medical decision making is possible even if statistical checks indicate that all regularity assumptions are satisfied. © The Author 2013. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

General subspace learning with corrupted training data via graph embedding.

PubMed

Bao, Bing-Kun; Liu, Guangcan; Hong, Richang; Yan, Shuicheng; Xu, Changsheng

2013-11-01

We address the following subspace learning problem: supposing we are given a set of labeled, corrupted training data points, how to learn the underlying subspace, which contains three components: an intrinsic subspace that captures certain desired properties of a data set, a penalty subspace that fits the undesired properties of the data, and an error container that models the gross corruptions possibly existing in the data. Given a set of data points, these three components can be learned by solving a nuclear norm regularized optimization problem, which is convex and can be efficiently solved in polynomial time. Using the method as a tool, we propose a new discriminant analysis (i.e., supervised subspace learning) algorithm called Corruptions Tolerant Discriminant Analysis (CTDA), in which the intrinsic subspace is used to capture the features with high within-class similarity, the penalty subspace takes the role of modeling the undesired features with high between-class similarity, and the error container takes charge of fitting the possible corruptions in the data. We show that CTDA can well handle the gross corruptions possibly existing in the training data, whereas previous linear discriminant analysis algorithms arguably fail in such a setting. Extensive experiments conducted on two benchmark human face data sets and one object recognition data set show that CTDA outperforms the related algorithms.

Espresso beverages of pure origin coffee: mineral characterization, contribution for mineral intake and geographical discrimination.

PubMed

Oliveira, Marta; Ramos, Sandra; Delerue-Matos, Cristina; Morais, Simone

2015-06-15

Espresso coffee beverages prepared from pure origin roasted ground coffees from the major world growing regions (Brazil, Ethiopia, Colombia, India, Mexico, Honduras, Guatemala, Papua New Guinea, Kenya, Cuba, Timor, Mussulo and China) were characterized and compared in terms of their mineral content. Regular consumption of one cup of espresso contributes to a daily mineral intake varying from 0.002% (sodium; Central America) to 8.73% (potassium; Asia). The mineral profiles of the espresso beverages revealed significant inter- and intra-continental differences. South American pure origin coffees are on average richer in the analyzed elements except for calcium, while samples from Central America have generally lower mineral amounts (except for manganese). Manganese displayed significant differences (p<0.05) among the countries of each characterized continent. Intercontinental and inter-country discrimination between the major world coffee producers were achieved by applying canonical discriminant analysis. Manganese and calcium were found to be the best chemical descriptors for origin. Copyright © 2015 Elsevier Ltd. All rights reserved.

Auditory Stimulus Processing and Task Learning Are Adequate in Dyslexia, but Benefits from Regularities Are Reduced

ERIC Educational Resources Information Center

Daikhin, Luba; Raviv, Ofri; Ahissar, Merav

2017-01-01

Purpose: The reading deficit for people with dyslexia is typically associated with linguistic, memory, and perceptual-discrimination difficulties, whose relation to reading impairment is disputed. We proposed that automatic detection and usage of serial sound regularities for individuals with dyslexia is impaired (anchoring deficit hypothesis),…

Gait characteristics and their discriminative power in geriatric patients with and without cognitive impairment.

PubMed

Kikkert, Lisette H J; Vuillerme, Nicolas; van Campen, Jos P; Appels, Bregje A; Hortobágyi, Tibor; Lamoth, Claudine J C

2017-08-15

A detailed gait analysis (e.g., measures related to speed, self-affinity, stability, and variability) can help to unravel the underlying causes of gait dysfunction, and identify cognitive impairment. However, because geriatric patients present with multiple conditions that also affect gait, results from healthy old adults cannot easily be extrapolated to geriatric patients. Hence, we (1) quantified gait outcomes based on dynamical systems theory, and (2) determined their discriminative power in three groups: healthy old adults, geriatric patients with- and geriatric patients without cognitive impairment. For the present cross-sectional study, 25 healthy old adults recruited from community (65 ± 5.5 years), and 70 geriatric patients with (n = 39) and without (n = 31) cognitive impairment from the geriatric dayclinic of the MC Slotervaart hospital in Amsterdam (80 ± 6.6 years) were included. Participants walked for 3 min during single- and dual-tasking at self-selected speed while 3D trunk accelerations were registered with an IPod touch G4. We quantified 23 gait outcomes that reflect multiple gait aspects. A multivariate model was built using Partial Least Square- Discriminant Analysis (PLS-DA) that best modelled participant group from gait outcomes. For single-task walking, the PLS-DA model consisted of 4 Latent Variables that explained 63 and 41% of the variance in gait outcomes and group, respectively. Outcomes related to speed, regularity, predictability, and stability of trunk accelerations revealed with the highest discriminative power (VIP > 1). A high proportion of healthy old adults (96 and 93% for single- and dual-task, respectively) was correctly classified based on the gait outcomes. The discrimination of geriatric patients with and without cognitive impairment was poor, with 57% (single-task) and 64% (dual-task) of the patients misclassified. While geriatric patients vs. healthy old adults walked slower, and less regular, predictable, and stable, we found no differences in gait between geriatric patients with and without cognitive impairment. The effects of multiple comorbidities on geriatric patients' gait possibly causes a 'floor-effect', with no room for further deterioration when patients develop cognitive impairment. An accurate identification of cognitive status thus necessitates a multifactorial approach.

Use of intonation contours for speech recognition in noise by cochlear implant recipients.

PubMed

Meister, Hartmut; Landwehr, Markus; Pyschny, Verena; Grugel, Linda; Walger, Martin

2011-05-01

The corruption of intonation contours has detrimental effects on sentence-based speech recognition in normal-hearing listeners Binns and Culling [(2007). J. Acoust. Soc. Am. 122, 1765-1776]. This paper examines whether this finding also applies to cochlear implant (CI) recipients. The subjects' F0-discrimination and speech perception in the presence of noise were measured, using sentences with regular and inverted F0-contours. The results revealed that speech recognition for regular contours was significantly better than for inverted contours. This difference was related to the subjects' F0-discrimination providing further evidence that the perception of intonation patterns is important for the CI-mediated speech recognition in noise.

Ensemble Recordings in Awake Rats: Achieving Behavioral Regularity during Multimodal Stimulus Processing and Discriminative Learning

ERIC Educational Resources Information Center

Lee, Eunjeong; Oliveira-Ferreira, Ana I.; de Water, Ed; Gerritsen, Hans; Bakker, Mattijs C.; Kalwij, Jan A. W.; van Goudoever, Tjerk; Buster, Wietze H.; Pennartz, Cyriel M. A.

2009-01-01

To meet an increasing need to examine the neurophysiological underpinnings of behavior in rats, we developed a behavioral system for studying sensory processing, attention and discrimination learning in rats while recording firing patterns of neurons in one or more brain areas of interest. Because neuronal activity is sensitive to variations in…

Observations on the State of Indigenous Human Rights in Light of the UN Declaration on the Rights of Indigenous Peoples: Guatemala

ERIC Educational Resources Information Center

Cultural Survival, 2008

2008-01-01

Since the 1996 Peace Accords ended the Guatemalan civil war, the country has made strides to legally recognize the rights of its indigenous peoples and has criminalized racial discrimination. However, political exclusion, discrimination, and economic marginalization of indigenous peoples still regularly occur due to the lack of resources and…

Obtaining sparse distributions in 2D inverse problems.

PubMed

Reci, A; Sederman, A J; Gladden, L F

2017-08-01

The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L 1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L 1 regularization to a class of inverse problems; relaxation-relaxation, T 1 -T 2 , and diffusion-relaxation, D-T 2 , correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks. We introduce a robust algorithm for solving the L 1 regularization problem and provide a guide to implementing it, including the choice of the amount of regularization used and the assignment of error estimates. We then show experimentally that L 1 regularization has significant advantages over both the Non-Negative Least Squares (NNLS) algorithm and Tikhonov regularization. It is shown that the L 1 regularization algorithm stably recovers a distribution at a signal to noise ratio<20 and that it resolves relaxation time constants and diffusion coefficients differing by as little as 10%. The enhanced resolving capability is used to measure the inter and intra particle concentrations of a mixture of hexane and dodecane present within porous silica beads immersed within a bulk liquid phase; neither NNLS nor Tikhonov regularization are able to provide this resolution. This experimental study shows that the approach enables discrimination between different chemical species when direct spectroscopic discrimination is impossible, and hence measurement of chemical composition within porous media, such as catalysts or rocks, is possible while still being stable to high levels of noise. Copyright © 2017. Published by Elsevier Inc.

Obtaining sparse distributions in 2D inverse problems

NASA Astrophysics Data System (ADS)

Reci, A.; Sederman, A. J.; Gladden, L. F.

2017-08-01

The mathematics of inverse problems has relevance across numerous estimation problems in science and engineering. L1 regularization has attracted recent attention in reconstructing the system properties in the case of sparse inverse problems; i.e., when the true property sought is not adequately described by a continuous distribution, in particular in Compressed Sensing image reconstruction. In this work, we focus on the application of L1 regularization to a class of inverse problems; relaxation-relaxation, T1-T2, and diffusion-relaxation, D-T2, correlation experiments in NMR, which have found widespread applications in a number of areas including probing surface interactions in catalysis and characterizing fluid composition and pore structures in rocks. We introduce a robust algorithm for solving the L1 regularization problem and provide a guide to implementing it, including the choice of the amount of regularization used and the assignment of error estimates. We then show experimentally that L1 regularization has significant advantages over both the Non-Negative Least Squares (NNLS) algorithm and Tikhonov regularization. It is shown that the L1 regularization algorithm stably recovers a distribution at a signal to noise ratio < 20 and that it resolves relaxation time constants and diffusion coefficients differing by as little as 10%. The enhanced resolving capability is used to measure the inter and intra particle concentrations of a mixture of hexane and dodecane present within porous silica beads immersed within a bulk liquid phase; neither NNLS nor Tikhonov regularization are able to provide this resolution. This experimental study shows that the approach enables discrimination between different chemical species when direct spectroscopic discrimination is impossible, and hence measurement of chemical composition within porous media, such as catalysts or rocks, is possible while still being stable to high levels of noise.

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.

Cross-label Suppression: a Discriminative and Fast Dictionary Learning with Group Regularization.

PubMed

Wang, Xiudong; Gu, Yuantao

2017-05-10

This paper addresses image classification through learning a compact and discriminative dictionary efficiently. Given a structured dictionary with each atom (columns in the dictionary matrix) related to some label, we propose crosslabel suppression constraint to enlarge the difference among representations for different classes. Meanwhile, we introduce group regularization to enforce representations to preserve label properties of original samples, meaning the representations for the same class are encouraged to be similar. Upon the cross-label suppression, we don't resort to frequently-used `0-norm or `1- norm for coding, and obtain computational efficiency without losing the discriminative power for categorization. Moreover, two simple classification schemes are also developed to take full advantage of the learnt dictionary. Extensive experiments on six data sets including face recognition, object categorization, scene classification, texture recognition and sport action categorization are conducted, and the results show that the proposed approach can outperform lots of recently presented dictionary algorithms on both recognition accuracy and computational efficiency.

[Advances in clustered regularly interspaced short palindromic repeats--a review].

PubMed

Wang, Lili; He, Jin; Wang, Jieping

2011-08-01

The recently discovered Clustered Regularly Interspaced Short Palindromic Repeat (CRISPRs) can protect bacteria and archaea with adaptive and heritable defense systems against the invasion of phage- and plasmid- associated mobile genetic elements. Here, we review the structure, diversity, mechanism of interference and self versus non-self discrimination of CRISPR systems. We also discuss the potential applications of this novel interference system.

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.

Fast learning of simple perceptual discriminations reduces brain activation in working memory and in high-level auditory regions.

PubMed

Daikhin, Luba; Ahissar, Merav

2015-07-01

Introducing simple stimulus regularities facilitates learning of both simple and complex tasks. This facilitation may reflect an implicit change in the strategies used to solve the task when successful predictions regarding incoming stimuli can be formed. We studied the modifications in brain activity associated with fast perceptual learning based on regularity detection. We administered a two-tone frequency discrimination task and measured brain activation (fMRI) under two conditions: with and without a repeated reference tone. Although participants could not explicitly tell the difference between these two conditions, the introduced regularity affected both performance and the pattern of brain activation. The "No-Reference" condition induced a larger activation in frontoparietal areas known to be part of the working memory network. However, only the condition with a reference showed fast learning, which was accompanied by a reduction of activity in two regions: the left intraparietal area, involved in stimulus retention, and the posterior superior-temporal area, involved in representing auditory regularities. We propose that this joint reduction reflects a reduction in the need for online storage of the compared tones. We further suggest that this change reflects an implicit strategic shift "backwards" from reliance mainly on working memory networks in the "No-Reference" condition to increased reliance on detected regularities stored in high-level auditory networks.

Variations in the Intragene Methylation Profiles Hallmark Induced Pluripotency

PubMed Central

Druzhkov, Pavel; Zolotykh, Nikolay; Meyerov, Iosif; Alsaedi, Ahmed; Shutova, Maria; Ivanchenko, Mikhail; Zaikin, Alexey

2015-01-01

We demonstrate the potential of differentiating embryonic and induced pluripotent stem cells by the regularized linear and decision tree machine learning classification algorithms, based on a number of intragene methylation measures. The resulting average accuracy of classification has been proven to be above 95%, which overcomes the earlier achievements. We propose a constructive and transparent method of feature selection based on classifier accuracy. Enrichment analysis reveals statistically meaningful presence of stemness group and cancer discriminating genes among the selected best classifying features. These findings stimulate the further research on the functional consequences of these differences in methylation patterns. The presented approach can be broadly used to discriminate the cells of different phenotype or in different state by their methylation profiles, identify groups of genes constituting multifeature classifiers, and assess enrichment of these groups by the sets of genes with a functionality of interest. PMID:26618180

Acute moderate exercise improves mnemonic discrimination in young adults.

PubMed

Suwabe, Kazuya; Hyodo, Kazuki; Byun, Kyeongho; Ochi, Genta; Yassa, Michael A; Soya, Hideaki

2017-03-01

Increasing evidence suggests that regular moderate exercise increases neurogenesis in the dentate gyrus (DG) of the hippocampus and improves memory functions in both humans and animals. The DG is known to play a role in pattern separation, which is the ability to discriminate among similar experiences, a fundamental component of episodic memory. While long-term voluntary exercise improves pattern separation, there is little evidence of alterations in DG function after an acute exercise session. Our previous studies showing acute moderate exercise-enhanced DG activation in rats, and acute moderate exercise-enhanced prefrontal activation and executive function in humans, led us to postulate that acute moderate exercise may also activate the hippocampus, including more specifically the DG, thus improving pattern separation. We thus investigated the effects of a 10-min moderate exercise (50% V̇O 2peak ) session, the recommended intensity for health promotion, on mnemonic discrimination (a behavioral index of pattern separation) in young adults. An acute bout of moderate exercise improved mnemonic discrimination performance in high similarity lures. These results support our hypothesis that acute moderate exercise improves DG-mediated pattern separation in humans, proposing a useful human acute-exercise model for analyzing the neuronal substrate underlying acute and regular exercise-enhanced episodic memory based on the hippocampus. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Acute Moderate Exercise Improves Mnemonic Discrimination in Young Adults

PubMed Central

Suwabe, Kazuya; Hyodo, Kazuki; Byun, Kyeongho; Ochi, Genta; Yassa, Michael A.; Soya, Hideaki

2018-01-01

Increasing evidence suggests that regular moderate exercise increases neurogenesis in the dentate gyrus (DG) of the hippocampus and improves memory functions in both humans and animals. The DG is known to play a role in pattern separation, which is the ability to discriminate among similar experiences, a fundamental component of episodic memory. While long-term voluntary exercise improves pattern separation, there is little evidence of alterations in DG function after an acute exercise session. Our previous studies showing acute moderate exercise-enhanced DG activation in rats, and acute moderate exercise-enhanced prefrontal activation and executive function in humans, led us to postulate that acute moderate exercise may also activate the hippocampus, including more specifically the DG, thus improving pattern separation. We thus investigated the effects of a 10-min moderate exercise (50% V̇O2peak) session, the recommended intensity for health promotion, on mnemonic discrimination (a behavioral index of pattern separation) in young adults. An acute bout of moderate exercise improved mnemonic discrimination performance in high similarity lures. These results support our hypothesis that acute moderate exercise improves DG-mediated pattern separation in humans, proposing a useful human acute-exercise model for analyzing the neuronal substrate underlying acute and regular exercise-enhanced episodic memory based on the hippocampus. PMID:27997992

Automatic face naming by learning discriminative affinity matrices from weakly labeled images.

PubMed

Xiao, Shijie; Xu, Dong; Wu, Jianxin

2015-10-01

Given a collection of images, where each image contains several faces and is associated with a few names in the corresponding caption, the goal of face naming is to infer the correct name for each face. In this paper, we propose two new methods to effectively solve this problem by learning two discriminative affinity matrices from these weakly labeled images. We first propose a new method called regularized low-rank representation by effectively utilizing weakly supervised information to learn a low-rank reconstruction coefficient matrix while exploring multiple subspace structures of the data. Specifically, by introducing a specially designed regularizer to the low-rank representation method, we penalize the corresponding reconstruction coefficients related to the situations where a face is reconstructed by using face images from other subjects or by using itself. With the inferred reconstruction coefficient matrix, a discriminative affinity matrix can be obtained. Moreover, we also develop a new distance metric learning method called ambiguously supervised structural metric learning by using weakly supervised information to seek a discriminative distance metric. Hence, another discriminative affinity matrix can be obtained using the similarity matrix (i.e., the kernel matrix) based on the Mahalanobis distances of the data. Observing that these two affinity matrices contain complementary information, we further combine them to obtain a fused affinity matrix, based on which we develop a new iterative scheme to infer the name of each face. Comprehensive experiments demonstrate the effectiveness of our approach.

Weight Discrimination and Unhealthy Eating-related Behaviors

PubMed Central

Sutin, Angelina; Robinson, Eric; Daly, Michael; Terracciano, Antonio

2016-01-01

Individuals with obesity often experience unfair treatment because of their body weight. Such experiences are associated with binge eating, but less is known about its association with other eating-related behaviors and whether these relations are specific to discrimination based on weight or extend to other attributions for discrimination. The present research uses a large national sample (N=5,129) to examine whether weight discrimination is associated with diet and meal rhythmicity, in addition to overeating, and whether these associations generalize to nine other attributions for discrimination. We found that in addition to overeating, weight discrimination was associated with more frequent consumption of convenience foods and less regular meal timing. These associations were generally similar across sex, age, and race. Discrimination based on ancestry, gender, age, religion, and physical disability were also associated with overeating, which suggests that overeating may be a general coping response to discrimination. Unfair treatment because of body weight is associated with unhealthy eating-related behaviors, which may be one pathway through which weight discrimination increases risk for weight gain and obesity. PMID:26877216

Weight discrimination and unhealthy eating-related behaviors.

PubMed

Sutin, Angelina; Robinson, Eric; Daly, Michael; Terracciano, Antonio

2016-07-01

Individuals with obesity often experience unfair treatment because of their body weight. Such experiences are associated with binge eating, but less is known about its association with other eating-related behaviors and whether these relations are specific to discrimination based on weight or extend to other attributions for discrimination. The present research uses a large national sample (N = 5129) to examine whether weight discrimination is associated with diet and meal rhythmicity, in addition to overeating, and whether these associations generalize to nine other attributions for discrimination. We found that in addition to overeating, weight discrimination was associated with more frequent consumption of convenience foods and less regular meal timing. These associations were generally similar across sex, age, and race. Discrimination based on ancestry, gender, age, religion, and physical disability were also associated with overeating, which suggests that overeating may be a general coping response to discrimination. Unfair treatment because of body weight is associated with unhealthy eating-related behaviors, which may be one pathway through which weight discrimination increases risk for weight gain and obesity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Discovery of human urinary biomarkers of aronia-citrus juice intake by HPLC-q-TOF-based metabolomic approach.

PubMed

Llorach, Rafael; Medina, Sonia; García-Viguera, Cristina; Zafrilla, Pilar; Abellán, José; Jauregui, Olga; Tomás-Barberán, Francisco A; Gil-Izquierdo, Angel; Andrés-Lacueva, Cristina

2014-06-01

Metabolomics has emerged in the field of food and nutrition sciences as a powerful tool for doing profiling approaches. In this context, HPLC-q-TOF-based metabolomics approach was applied to unveil changes in the urinary metabolome in human subjects (n = 51, 23 men and 28 women) after regular aronia-citrus juice (AC-juice) intake (250 mL/day) during 16 weeks compared to individuals given a placebo beverage. Samples were analyzed by HPLC-q-TOF followed by multivariate data analysis (orthogonal signal filtering-partial least square discriminant analysis) that discriminated relevant mass features related to AC-juice intake. The results showed that biomarkers of AC-juice intake including metabolites coming from metabolism of food components as proline betaine, ferulic acid, and two unknown mercapturate derivatives were identified. Discovery of new biomarkers of food intake will help in the building up of the food metabolome and facilitate future insights into the mechanisms of action of dietary components in population health. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Manifold regularized discriminative nonnegative matrix factorization with fast gradient descent.

PubMed

Guan, Naiyang; Tao, Dacheng; Luo, Zhigang; Yuan, Bo

2011-07-01

Nonnegative matrix factorization (NMF) has become a popular data-representation method and has been widely used in image processing and pattern-recognition problems. This is because the learned bases can be interpreted as a natural parts-based representation of data and this interpretation is consistent with the psychological intuition of combining parts to form a whole. For practical classification tasks, however, NMF ignores both the local geometry of data and the discriminative information of different classes. In addition, existing research results show that the learned basis is unnecessarily parts-based because there is neither explicit nor implicit constraint to ensure the representation parts-based. In this paper, we introduce the manifold regularization and the margin maximization to NMF and obtain the manifold regularized discriminative NMF (MD-NMF) to overcome the aforementioned problems. The multiplicative update rule (MUR) can be applied to optimizing MD-NMF, but it converges slowly. In this paper, we propose a fast gradient descent (FGD) to optimize MD-NMF. FGD contains a Newton method that searches the optimal step length, and thus, FGD converges much faster than MUR. In addition, FGD includes MUR as a special case and can be applied to optimizing NMF and its variants. For a problem with 165 samples in R(1600), FGD converges in 28 s, while MUR requires 282 s. We also apply FGD in a variant of MD-NMF and experimental results confirm its efficiency. Experimental results on several face image datasets suggest the effectiveness of MD-NMF.

Statistical learning and auditory processing in children with music training: An ERP study.

PubMed

Mandikal Vasuki, Pragati Rao; Sharma, Mridula; Ibrahim, Ronny; Arciuli, Joanne

2017-07-01

The question whether musical training is associated with enhanced auditory and cognitive abilities in children is of considerable interest. In the present study, we compared children with music training versus those without music training across a range of auditory and cognitive measures, including the ability to detect implicitly statistical regularities in input (statistical learning). Statistical learning of regularities embedded in auditory and visual stimuli was measured in musically trained and age-matched untrained children between the ages of 9-11years. In addition to collecting behavioural measures, we recorded electrophysiological measures to obtain an online measure of segmentation during the statistical learning tasks. Musically trained children showed better performance on melody discrimination, rhythm discrimination, frequency discrimination, and auditory statistical learning. Furthermore, grand-averaged ERPs showed that triplet onset (initial stimulus) elicited larger responses in the musically trained children during both auditory and visual statistical learning tasks. In addition, children's music skills were associated with performance on auditory and visual behavioural statistical learning tasks. Our data suggests that individual differences in musical skills are associated with children's ability to detect regularities. The ERP data suggest that musical training is associated with better encoding of both auditory and visual stimuli. Although causality must be explored in further research, these results may have implications for developing music-based remediation strategies for children with learning impairments. Copyright © 2017 International Federation of Clinical Neurophysiology. Published by Elsevier B.V. All rights reserved.

Harvest locations of goose barnacles can be successfully discriminated using trace elemental signatures

NASA Astrophysics Data System (ADS)

Albuquerque, Rui; Queiroga, Henrique; Swearer, Stephen E.; Calado, Ricardo; Leandro, Sérgio M.

2016-06-01

European Union regulations state that consumers must be rightfully informed about the provenance of fishery products to prevent fraudulent practices. However, mislabeling of the geographical origin is a common practice. It is therefore paramount to develop forensic methods that allow all players involved in the supply chain to accurately trace the origin of seafood. In this study, trace elemental signatures (TES) of the goose barnacle Pollicipes pollicipes, collected from ten sites along the Portuguese coast, were employed to discriminate individual’s origin. Barium (Ba), boron (B), cadmium (Cd), chromium (Cr), lithium (Li), magnesium (Mg), manganese (Mn), phosphorous (P), lead (Pb), strontium (Sr) and zinc (Zn) - were quantified using Inductively Coupled Plasma-Mass Spectrometry (ICP-MS). Significant differences were recorded among locations for all elements. A regularized discriminant analysis (RDA) revealed that 83% of all individuals were correctly assigned. This study shows TES can be a reliable tool to confirm the geographic origin of goose barnacles at fine spatial resolution. Although additional studies are required to ascertain the reliability of TES on cooked specimens and the temporal stability of the signature, the approach holds great promise for the management of goose barnacles fisheries, enforcement of conservation policies and assurance in accurate labeling.

Emotional responses to Hindustani raga music: the role of musical structure

PubMed Central

Mathur, Avantika; Vijayakumar, Suhas H.; Chakrabarti, Bhismadev; Singh, Nandini C.

2015-01-01

In Indian classical music, ragas constitute specific combinations of tonic intervals potentially capable of evoking distinct emotions. A raga composition is typically presented in two modes, namely, alaap and gat. Alaap is the note by note delineation of a raga bound by a slow tempo, but not bound by a rhythmic cycle. Gat on the other hand is rendered at a faster tempo and follows a rhythmic cycle. Our primary objective was to (1) discriminate the emotions experienced across alaap and gat of ragas, (2) investigate the association of tonic intervals, tempo and rhythmic regularity with emotional response. 122 participants rated their experienced emotion across alaap and gat of 12 ragas. Analysis of the emotional responses revealed that (1) ragas elicit distinct emotions across the two presentation modes, and (2) specific tonic intervals are robust predictors of emotional response. Specifically, our results showed that the ‘minor second’ is a direct predictor of negative valence. (3) Tonality determines the emotion experienced for a raga where as rhythmic regularity and tempo modulate levels of arousal. Our findings provide new insights into the emotional response to Indian ragas and the impact of tempo, rhythmic regularity and tonality on it. PMID:25983702

Emotional responses to Hindustani raga music: the role of musical structure.

PubMed

Mathur, Avantika; Vijayakumar, Suhas H; Chakrabarti, Bhismadev; Singh, Nandini C

2015-01-01

In Indian classical music, ragas constitute specific combinations of tonic intervals potentially capable of evoking distinct emotions. A raga composition is typically presented in two modes, namely, alaap and gat. Alaap is the note by note delineation of a raga bound by a slow tempo, but not bound by a rhythmic cycle. Gat on the other hand is rendered at a faster tempo and follows a rhythmic cycle. Our primary objective was to (1) discriminate the emotions experienced across alaap and gat of ragas, (2) investigate the association of tonic intervals, tempo and rhythmic regularity with emotional response. 122 participants rated their experienced emotion across alaap and gat of 12 ragas. Analysis of the emotional responses revealed that (1) ragas elicit distinct emotions across the two presentation modes, and (2) specific tonic intervals are robust predictors of emotional response. Specifically, our results showed that the 'minor second' is a direct predictor of negative valence. (3) Tonality determines the emotion experienced for a raga where as rhythmic regularity and tempo modulate levels of arousal. Our findings provide new insights into the emotional response to Indian ragas and the impact of tempo, rhythmic regularity and tonality on it.

POLLUTION DETECTION DOGS: PROOF OF CONCEPT

EPA Science Inventory

Dogs have been used extensively in law enforcement and military applications to detect narcotics and explosives for over thirty years. Dogs are regularly used in arson investigations to detect accelerants since they are much more accurate at discriminating between accelerants an...

Attention checklist: a rating scale for mildly mentally handicapped adolescents.

PubMed

Das, J P; Melnyk, L

1989-06-01

A check list for attentional deficits without reference to hyperactive behavior observed in the classroom was constructed, and teachers' ratings were factor analyzed. The check-list rating was compared to a widely used rating scale for attention deficit-hyperactive disorder (AD-HD), the Abbreviated Conners Rating Scale. Both scales were given to 15 teachers to rate 100 mildly mentally handicapped adolescent students. Analysis showed that 33% of the mentally handicapped students were rated above 1.5 on the Conners Scale, which is the cut-off for hyperactivity. This is much higher than the prevalence of hyperactivity in regular classrooms. The two sets of ratings correlated strongly (.84). Check-list items were grouped under one factor explaining 70.7% of variance and so are recommended for use in discriminating attentional deficit in mentally handicapped as well as in regular class students. The high correlation with ratings on the Conners Scale suggests that AD-HD is a unitary syndrome with attention being most problematic for children labeled hyperactive.

Avoiding overstating the strength of forensic evidence: Shrunk likelihood ratios/Bayes factors.

PubMed

Morrison, Geoffrey Stewart; Poh, Norman

2018-05-01

When strength of forensic evidence is quantified using sample data and statistical models, a concern may be raised as to whether the output of a model overestimates the strength of evidence. This is particularly the case when the amount of sample data is small, and hence sampling variability is high. This concern is related to concern about precision. This paper describes, explores, and tests three procedures which shrink the value of the likelihood ratio or Bayes factor toward the neutral value of one. The procedures are: (1) a Bayesian procedure with uninformative priors, (2) use of empirical lower and upper bounds (ELUB), and (3) a novel form of regularized logistic regression. As a benchmark, they are compared with linear discriminant analysis, and in some instances with non-regularized logistic regression. The behaviours of the procedures are explored using Monte Carlo simulated data, and tested on real data from comparisons of voice recordings, face images, and glass fragments. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

Gap Shape Classification using Landscape Indices and Multivariate Statistics

PubMed Central

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-01-01

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

Gap Shape Classification using Landscape Indices and Multivariate Statistics.

PubMed

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-11-30

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

Laser-Induced Breakdown Spectroscopy (LIBS) for spectral characterization of regular coffee beans and luwak coffee bean

NASA Astrophysics Data System (ADS)

Nufiqurakhmah, Nufiqurakhmah; Nasution, Aulia; Suyanto, Hery

2016-11-01

Luwak (civet) coffee refers to a type of coffee, where the cherries have been priorly digested and then defecated by a civet (Paradoxurus Hermaphroditus), a catlike animals typically habited in Indonesia. Luwak will only selectively select ripe cherries, and digesting them by enzymatic fermentation in its digestive system. The defecated beans is then removed and cleaned from the feces. It is regarded as the world's most expensive coffee, Traditionally the quality of the coffee is subjectively determined by a tester. This research is motivated by the needs to study and develop quantitative parameters in determining the quality of coffee bean, which are more objective to measure the quality of coffee products. LIBS technique was used to identify the elemental contents of coffee beans based on its spectral characteristics in the range 200-900 nm. Samples of green beans from variant of arabica and robusta, either regular and luwak, were collected from 5 plantations in East Java. From the recorded spectra, intensity ratio of nitrogen (N), hydrogen (H), and oxygen (O) as essential elements in coffee is applied. In general, values extracted from luwak coffee bean is higher with increases 0.03% - 79.93%. A Discriminant Function Analysis (DFA) also applied to identify marker elements that characterize the regular and luwak beans. Elements of Ca, W, Sr, Mg, and H are the ones used to differentiate the regular and luwak beans from arabica variant, while Ca and W are the ones used to differentiate the regular and luwak beans of robusta variant.

Longitudinal Discriminant Analysis of Hemoglobin Level for Predicting Preeclampsia

PubMed Central

Nasiri, Malihe; Faghihzadeh, Soghrat; Alavi Majd, Hamid; Zayeri, Farid; Kariman, Noorosadat; Safavi Ardebili, Nastaran

2015-01-01

Background: Preeclampsia is one of the most serious complications during pregnancy with important effects on health of mother and fetus that causes maternal and fetal morbidity and mortality. This study was performed to evaluate whether high levels of hemoglobin may increase the risk of preeclampsia. Objectives: The present study aimed to predict preeclampsia by the hemoglobin profiles through longitudinal discriminant analysis and comparing the error rate of discrimination in longitudinal and cross sectional data. Patients and Methods: In a prospective cohort study from October 2010 to July 2011, 650 pregnant women referred to the prenatal clinic of Milad Hospital in Tehran were evaluated in 3 stages. The hemoglobin level of each woman was measured in the first, second, and third trimester of pregnancy by an expert technician. The subjects were followed up to delivery and preeclampsia was the main outcome under study. The covariance pattern and linear-mixed effects models are common methods that were applied for discriminant analysis of longitudinal data. Also Student t, Mann-Whitney U, and chi-square tests were used for comparing the demographic and clinical characteristics between two groups. Statistical analyses were performed using the SAS software version 9.1. Results: The prevalence rate of preeclampsia was 7.2% (47 women). The women with preeclampsia had a higher mean of hemoglobin values and the difference was 0.46 g/dL (P = 0.003). Also the mean of hemoglobin in the first trimester was higher than that of the second trimester, and was lower than that of the third trimester and the differences were significant (P = 0.015 and P < 0.001, respectively). The sensitivity for longitudinal data and cross-sectional data in three trimesters was 90%, 67%, 72%, and 54% and the specificity was 88%, 55%, 63%, and 50%, respectively. Conclusions: The levels of hemoglobin can be used to predict preeclampsia and monitoring the pregnant women and its regular measure in 3 trimesters help us to identify women at risk for preeclampsia. PMID:26019901

Regularization of Instantaneous Frequency Attribute Computations

NASA Astrophysics Data System (ADS)

Yedlin, M. J.; Margrave, G. F.; Van Vorst, D. G.; Ben Horin, Y.

2014-12-01

We compare two different methods of computation of a temporally local frequency:1) A stabilized instantaneous frequency using the theory of the analytic signal.2) A temporally variant centroid (or dominant) frequency estimated from a time-frequency decomposition.The first method derives from Taner et al (1979) as modified by Fomel (2007) and utilizes the derivative of the instantaneous phase of the analytic signal. The second method computes the power centroid (Cohen, 1995) of the time-frequency spectrum, obtained using either the Gabor or Stockwell Transform. Common to both methods is the necessity of division by a diagonal matrix, which requires appropriate regularization.We modify Fomel's (2007) method by explicitly penalizing the roughness of the estimate. Following Farquharson and Oldenburg (2004), we employ both the L curve and GCV methods to obtain the smoothest model that fits the data in the L2 norm.Using synthetic data, quarry blast, earthquakes and the DPRK tests, our results suggest that the optimal method depends on the data. One of the main applications for this work is the discrimination between blast events and earthquakesFomel, Sergey. " Local seismic attributes." , Geophysics, 72.3 (2007): A29-A33.Cohen, Leon. " Time frequency analysis theory and applications." USA: Prentice Hall, (1995).Farquharson, Colin G., and Douglas W. Oldenburg. "A comparison of automatic techniques for estimating the regularization parameter in non-linear inverse problems." Geophysical Journal International 156.3 (2004): 411-425.Taner, M. Turhan, Fulton Koehler, and R. E. Sheriff. " Complex seismic trace analysis." Geophysics, 44.6 (1979): 1041-1063.

Harvest locations of goose barnacles can be successfully discriminated using trace elemental signatures

PubMed Central

Albuquerque, Rui; Queiroga, Henrique; Swearer, Stephen E.; Calado, Ricardo; Leandro, Sérgio M.

2016-01-01

European Union regulations state that consumers must be rightfully informed about the provenance of fishery products to prevent fraudulent practices. However, mislabeling of the geographical origin is a common practice. It is therefore paramount to develop forensic methods that allow all players involved in the supply chain to accurately trace the origin of seafood. In this study, trace elemental signatures (TES) of the goose barnacle Pollicipes pollicipes, collected from ten sites along the Portuguese coast, were employed to discriminate individual’s origin. Barium (Ba), boron (B), cadmium (Cd), chromium (Cr), lithium (Li), magnesium (Mg), manganese (Mn), phosphorous (P), lead (Pb), strontium (Sr) and zinc (Zn) - were quantified using Inductively Coupled Plasma−Mass Spectrometry (ICP-MS). Significant differences were recorded among locations for all elements. A regularized discriminant analysis (RDA) revealed that 83% of all individuals were correctly assigned. This study shows TES can be a reliable tool to confirm the geographic origin of goose barnacles at fine spatial resolution. Although additional studies are required to ascertain the reliability of TES on cooked specimens and the temporal stability of the signature, the approach holds great promise for the management of goose barnacles fisheries, enforcement of conservation policies and assurance in accurate labeling. PMID:27292413

Seafloor monitoring west of Helgoland (German Bight, North Sea) using the acoustic ground discrimination system RoxAnn

NASA Astrophysics Data System (ADS)

Hass, H. Christian; Mielck, Finn; Fiorentino, Dario; Papenmeier, Svenja; Holler, Peter; Bartholomä, Alexander

2017-04-01

Marine habitats of shelf seas are in constant dynamic change and therefore need regular assessment particularly in areas of special interest. In this study, the single-beam acoustic ground discrimination system RoxAnn served to assess seafloor hardness and roughness, and combine these parameters into one variable expressed as RGB (red green blue) color code followed by k-means fuzzy cluster analysis (FCA). The data were collected at a monitoring site west of the island of Helgoland (German Bight, SE North Sea) in the course of four surveys between September 2011 and November 2014. The study area has complex characteristics varying from outcropping bedrock to sandy and muddy sectors with mostly gradual transitions. RoxAnn data enabled to discriminate all seafloor types that were suggested by ground-truth information (seafloor samples, video). The area appears to be quite stable overall; sediment import (including fluid mud) was detected only from the NW. Although hard substrates (boulders, bedrock) are clearly identified, the signal can be modified by inclination and biocover. Manually, six RoxAnn zones were identified; for the FCA, only three classes are suggested. The latter classification based on `hard' boundaries would suffice for stakeholder issues, but the former classification based on `soft' boundaries is preferred to meet state-of-the-art scientific objectives.

USING CANINES IN SOURCE DETECTION OF INDOOR AIR POLLUTANTS

EPA Science Inventory

Dogs have been used extensively in law enforcement and military applications to detect narcotics and explosives for over thirty years. Dogs are regularly used in arson investigations to detect accelerants since they are much more accurate at discriminating between accelerants an...

Electrophysiological evidence for a specific neural correlate of musical violation expectation in primary-school children.

PubMed

James, Clara E; Cereghetti, Donato M; Roullet Tribes, Elodie; Oechslin, Mathias S

2015-01-01

The majority of studies on music processing in children used simple musical stimuli. Here, primary schoolchildren judged the appropriateness of musical closure in expressive polyphone music, while high-density electroencephalography was recorded. Stimuli ended either regularly or contained refined in-key harmonic transgressions at closure. The children discriminated the transgressions well above chance. Regular and transgressed endings evoked opposite scalp voltage configurations peaking around 400ms after stimulus onset with bilateral frontal negativity for regular and centro-posterior negativity (CPN) for transgressed endings. A positive correlation could be established between strength of the CPN response and rater sensitivity (d-prime). We also investigated whether the capacity to discriminate the transgressions was supported by auditory domain specific or general cognitive mechanisms, and found that working memory capacity predicted transgression discrimination. Latency and distribution of the CPN are reminiscent of the N400, typically observed in response to semantic incongruities in language. Therefore our observation is intriguing, as the CPN occurred here within an intra-musical context, without any symbols referring to the external world. Moreover, the harmonic in-key transgressions that we implemented may be considered syntactical as they transgress structural rules. Such structural incongruities in music are typically followed by an early right anterior negativity (ERAN) and an N5, but not so here. Putative contributive sources of the CPN were localized in left pre-motor, mid-posterior cingulate and superior parietal regions of the brain that can be linked to integration processing. These results suggest that, at least in children, processing of syntax and meaning may coincide in complex intra-musical contexts. Copyright © 2014 Elsevier Inc. All rights reserved.

Patients’ perceptions of discrimination during hospitalization

PubMed Central

Hudelson, Patricia; Kolly, Véronique; Perneger, Thomas

2009-01-01

Abstract Objective  To identify sources of perceived discrimination during hospitalization and examine the relationship of perceived discrimination to patient and hospital stay characteristics, and to patient ratings of care. Background  Patient experiences of discrimination within the health‐care system are associated with delays in care seeking, non‐adherence to medical advice and poorer health status. Most research to date has focused on race and ethnicity‐based discrimination, and few studies have included hospitalized patients. Methods  Questions about patients’ experiences of discrimination were added to a regular patient opinion survey conducted at the Geneva University Hospitals. Participants were 1537 adult residents of Switzerland discharged from the hospital between 15 February and 15 March 2007. Results  A total of 171 (11.1%) respondents reported at least one source of discrimination. Most (93, 54.4%) reported a single cause of discrimination. The most frequent causes of discrimination were language, age, nationality and having a disease that is viewed negatively by others. Fifteen percentage of non‐European respondents reported at least one of the following types of discrimination: language, nationality, religion and skin colour. Reporting discrimination from any cause was associated with higher Picker Patient Experience problem scores, and patients who reported discrimination were less likely to describe their care as very good or excellent and less likely to recommend the hospital to others. Conclusions  Patient experiences of discrimination during hospitalization are relatively frequent and are associated with lower patient ratings of care. Collection of data on patient experiences of discrimination may contribute to the development of interventions aimed at ensuring respectful, quality care for all patients. PMID:19788555

Discriminative Relational Topic Models.

PubMed

Chen, Ning; Zhu, Jun; Xia, Fei; Zhang, Bo

2015-05-01

Relational topic models (RTMs) provide a probabilistic generative process to describe both the link structure and document contents for document networks, and they have shown promise on predicting network structures and discovering latent topic representations. However, existing RTMs have limitations in both the restricted model expressiveness and incapability of dealing with imbalanced network data. To expand the scope and improve the inference accuracy of RTMs, this paper presents three extensions: 1) unlike the common link likelihood with a diagonal weight matrix that allows the-same-topic interactions only, we generalize it to use a full weight matrix that captures all pairwise topic interactions and is applicable to asymmetric networks; 2) instead of doing standard Bayesian inference, we perform regularized Bayesian inference (RegBayes) with a regularization parameter to deal with the imbalanced link structure issue in real networks and improve the discriminative ability of learned latent representations; and 3) instead of doing variational approximation with strict mean-field assumptions, we present collapsed Gibbs sampling algorithms for the generalized relational topic models by exploring data augmentation without making restricting assumptions. Under the generic RegBayes framework, we carefully investigate two popular discriminative loss functions, namely, the logistic log-loss and the max-margin hinge loss. Experimental results on several real network datasets demonstrate the significance of these extensions on improving prediction performance.

Surface micromachined counter-meshing gears discrimination device

DOEpatents

Polosky, Marc A.; Garcia, Ernest J.; Allen, James J.

2000-12-12

A surface micromachined Counter-Meshing Gears (CMG) discrimination device which functions as a mechanically coded lock. Each of two CMG has a first portion of its perimeter devoted to continuous driving teeth that mesh with respective pinion gears. Each EMG also has a second portion of its perimeter devoted to regularly spaced discrimination gear teeth that extend outwardly on at least one of three levels of the CMG. The discrimination gear teeth are designed so as to pass each other without interference only if the correct sequence of partial rotations of the CMG occurs in response to a coded series of rotations from the pinion gears. A 24 bit code is normally input to unlock the device. Once unlocked, the device provides a path for an energy or information signal to pass through the device. The device is designed to immediately lock up if any portion of the 24 bit code is incorrect.

Exploring Discrimination and Mental Health Disparities Faced By Black Sexual Minority Women Using a Minority Stress Framework.

PubMed

Calabrese, Sarah K; Meyer, Ilan H; Overstreet, Nicole M; Haile, Rahwa; Hansen, Nathan B

2015-09-01

Black sexual minority women are triply marginalized due to their race, gender, and sexual orientation. We compared three dimensions of discrimination-frequency (regularity of occurrences), scope (number of types of discriminatory acts experienced), and number of bases (number of social statuses to which discrimination was attributed)-and self-reported mental health (depressive symptoms, psychological well-being, and social well-being) between 64 Black sexual minority women and each of two groups sharing two of three marginalized statuses: (a) 67 White sexual minority women and (b) 67 Black sexual minority men. Black sexual minority women reported greater discrimination frequency, scope, and number of bases and poorer psychological and social well-being than White sexual minority women and more discrimination bases, a higher level of depressive symptoms, and poorer social well-being than Black sexual minority men. We then tested and contrasted dimensions of discrimination as mediators between social status (race or gender) and mental health outcomes. Discrimination frequency and scope mediated the association between race and mental health, with a stronger effect via frequency among sexual minority women. Number of discrimination bases mediated the association between gender and mental health among Black sexual minorities. Future research and clinical practice would benefit from considering Black sexual minority women's mental health in a multidimensional minority stress context.

Accurate mask-based spatially regularized correlation filter for visual tracking

NASA Astrophysics Data System (ADS)

Gu, Xiaodong; Xu, Xinping

2017-01-01

Recently, discriminative correlation filter (DCF)-based trackers have achieved extremely successful results in many competitions and benchmarks. These methods utilize a periodic assumption of the training samples to efficiently learn a classifier. However, this assumption will produce unwanted boundary effects, which severely degrade the tracking performance. Correlation filters with limited boundaries and spatially regularized DCFs were proposed to reduce boundary effects. However, their methods used the fixed mask or predesigned weights function, respectively, which was unsuitable for large appearance variation. We propose an accurate mask-based spatially regularized correlation filter for visual tracking. Our augmented objective can reduce the boundary effect even in large appearance variation. In our algorithm, the masking matrix is converted into the regularized function that acts on the correlation filter in frequency domain, which makes the algorithm fast convergence. Our online tracking algorithm performs favorably against state-of-the-art trackers on OTB-2015 Benchmark in terms of efficiency, accuracy, and robustness.

29 CFR 1625.3 - Employment agency.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 29 Labor 4 2013-07-01 2013-07-01 false Employment agency. 1625.3 Section 1625.3 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION AGE DISCRIMINATION IN EMPLOYMENT ACT Interpretations § 1625.3 Employment agency. (a) As long as an employment agency regularly procures employees for...

29 CFR 1625.3 - Employment agency.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 29 Labor 4 2012-07-01 2012-07-01 false Employment agency. 1625.3 Section 1625.3 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION AGE DISCRIMINATION IN EMPLOYMENT ACT Interpretations § 1625.3 Employment agency. (a) As long as an employment agency regularly procures employees for...

29 CFR 1625.3 - Employment agency.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 29 Labor 4 2010-07-01 2010-07-01 false Employment agency. 1625.3 Section 1625.3 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION AGE DISCRIMINATION IN EMPLOYMENT ACT Interpretations § 1625.3 Employment agency. (a) As long as an employment agency regularly procures employees for...

29 CFR 1625.3 - Employment agency.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 29 Labor 4 2011-07-01 2011-07-01 false Employment agency. 1625.3 Section 1625.3 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION AGE DISCRIMINATION IN EMPLOYMENT ACT Interpretations § 1625.3 Employment agency. (a) As long as an employment agency regularly procures employees for...

29 CFR 1625.3 - Employment agency.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 29 Labor 4 2014-07-01 2014-07-01 false Employment agency. 1625.3 Section 1625.3 Labor Regulations Relating to Labor (Continued) EQUAL EMPLOYMENT OPPORTUNITY COMMISSION AGE DISCRIMINATION IN EMPLOYMENT ACT Interpretations § 1625.3 Employment agency. (a) As long as an employment agency regularly procures employees for...

Game Related Statistics Discriminating Between Starters and Nonstarters Players in Women’S National Basketball Association League (WNBA)

PubMed Central

Gòmez, Miguel-Ángel; Lorenzo, Alberto; Ortega, Enrique; Sampaio, Jaime; Ibàñez, Sergio-José

2009-01-01

The aim of the present study was to identify the game-related statistics that allow discriminating between starters and nonstarter players in women’s basketball when related to winning or losing games and best or worst teams. The sample comprised all 216 regular season games from the 2005 Women’s National Basketball Association League (WNBA). The game-related statistics included were 2- and 3- point field-goals (both successful and unsuccessful), free-throws (both successful and unsuccessful), defensive and offensive rebounds, assists, blocks, fouls, steals, turnovers and minutes played. Results from multivariate analysis showed that when best teams won, the discriminant game-related statistics were successful 2-point field-goals (SC = 0.47), successful free-throws (SC = 0.44), fouls (SC = -0.41), assists (SC = 0.37), and defensive rebounds (SC = 0.37). When the worst teams won, the discriminant game-related statistics were successful 2-point field- goals (SC = 0.37), successful free-throws (SC = 0.45), assists (SC = 0.58), and steals (SC = 0.35). The results showed that the successful 2-point field-goals, successful free-throws and the assists were the most powerful variables discriminating between starters and nonstarters. These specific characteristics helped to point out the importance of starters’ players shooting and passing ability during competitions. Key points The players’ game-related statistical profile varied according to team status, game outcome and team quality in women’s basketball. The results of this work help to point out the different player’s performance described in women’s basketball compared with men’s basketball. The results obtained enhance the importance of starters and nonstarters contribution to team’s performance in different game contexts. Results showed the power of successful 2-point field-goals, successful free-throws and assists discriminating between starters and nonstarters in all the analyses. PMID:24149538

Government and African Control of Education in the Bechuanaland Protectorate, 1928-48.

ERIC Educational Resources Information Center

Mgadla, P. T.

1995-01-01

Presents an in-depth portrait of the British government's educational policy in the Bechuanaland protectorate. The government systematized the primary school syllabus, regularized payment and training of teachers, and established cattle post schools. However, blatant discrimination favored support of European schools over African and little…

Adolescents Discriminate between Types of Smokers and Related Risks

ERIC Educational Resources Information Center

Rubinstein, Mark L.; Halpern-Felsher, Bonnie L.; Thompson, Pamela J.; Millstein, Susan G.

2003-01-01

Many studies concerning cigarette smoking and smoking-related outcomes among adolescents use categories such as "casual" or "regular" smoker to define different types of smokers. It is not clear whether adolescents themselves differentiate between different types of smokers. The present study sought to examine whether and how adolescents…

Assessment of sperm hyperactivated motility and acrosome reaction can discriminate the use of spermatozoa for conventional in vitro fertilisation or intracytoplasmic sperm injection: preliminary results.

PubMed

Wiser, A; Sachar, S; Ghetler, Y; Shulman, A; Breitbart, H

2014-04-01

Basic semen analysis is insufficient for determining the fertility potential. The aim of this study was to determine if hyperactivated motility (HAM) and acrosome reaction (AR) can be useful tests for evaluating semen quality during male infertility evaluations and to help the clinician decide whether regular insemination or intracytoplasmic sperm injection (ICSI) is preferable during in vitro fertilisation. A prospective study was conducted. Patients with normal sperm according to World Health Organization guidelines who underwent IVF treatment and planned regular insemination were asked to participate. A portion of sperm sample was evaluated for HAM and AR on day of ovum pick up. In HAM assessment, 93.3% of patients with increased HAM had a high fertilisation rate compared with 64% in the group without increased HAM (P = 0.059). For the AR evaluation, 91.7% of samples with a low rate of spontaneous AR had a high fertilisation rate compared with 39.3% in the group with a high rate of spontaneous AR (P = 0.004). © 2013 Blackwell Verlag GmbH.

Within-subject template estimation for unbiased longitudinal image analysis.

PubMed

Reuter, Martin; Schmansky, Nicholas J; Rosas, H Diana; Fischl, Bruce

2012-07-16

Longitudinal image analysis has become increasingly important in clinical studies of normal aging and neurodegenerative disorders. Furthermore, there is a growing appreciation of the potential utility of longitudinally acquired structural images and reliable image processing to evaluate disease modifying therapies. Challenges have been related to the variability that is inherent in the available cross-sectional processing tools, to the introduction of bias in longitudinal processing and to potential over-regularization. In this paper we introduce a novel longitudinal image processing framework, based on unbiased, robust, within-subject template creation, for automatic surface reconstruction and segmentation of brain MRI of arbitrarily many time points. We demonstrate that it is essential to treat all input images exactly the same as removing only interpolation asymmetries is not sufficient to remove processing bias. We successfully reduce variability and avoid over-regularization by initializing the processing in each time point with common information from the subject template. The presented results show a significant increase in precision and discrimination power while preserving the ability to detect large anatomical deviations; as such they hold great potential in clinical applications, e.g. allowing for smaller sample sizes or shorter trials to establish disease specific biomarkers or to quantify drug effects. Copyright © 2012 Elsevier Inc. All rights reserved.

Dispersion entropy for the analysis of resting-state MEG regularity in Alzheimer's disease.

PubMed

Azami, Hamed; Rostaghi, Mostafa; Fernandez, Alberto; Escudero, Javier

2016-08-01

Alzheimer's disease (AD) is a progressive degenerative brain disorder affecting memory, thinking, behaviour and emotion. It is the most common form of dementia and a big social problem in western societies. The analysis of brain activity may help to diagnose this disease. Changes in entropy methods have been reported useful in research studies to characterize AD. We have recently proposed dispersion entropy (DisEn) as a very fast and powerful tool to quantify the irregularity of time series. The aim of this paper is to evaluate the ability of DisEn, in comparison with fuzzy entropy (FuzEn), sample entropy (SampEn), and permutation entropy (PerEn), to discriminate 36 AD patients from 26 elderly control subjects using resting-state magnetoencephalogram (MEG) signals. The results obtained by DisEn, FuzEn, and SampEn, unlike PerEn, show that the AD patients' signals are more regular than controls' time series. The p-values obtained by DisEn, FuzEn, SampEn, and PerEn based methods demonstrate the superiority of DisEn over PerEn, SampEn, and PerEn. Moreover, the computation time for the newly proposed DisEn-based method is noticeably less than for the FuzEn, SampEn, and PerEn based approaches.

Semi-supervised vibration-based classification and condition monitoring of compressors

NASA Astrophysics Data System (ADS)

Potočnik, Primož; Govekar, Edvard

2017-09-01

Semi-supervised vibration-based classification and condition monitoring of the reciprocating compressors installed in refrigeration appliances is proposed in this paper. The method addresses the problem of industrial condition monitoring where prior class definitions are often not available or difficult to obtain from local experts. The proposed method combines feature extraction, principal component analysis, and statistical analysis for the extraction of initial class representatives, and compares the capability of various classification methods, including discriminant analysis (DA), neural networks (NN), support vector machines (SVM), and extreme learning machines (ELM). The use of the method is demonstrated on a case study which was based on industrially acquired vibration measurements of reciprocating compressors during the production of refrigeration appliances. The paper presents a comparative qualitative analysis of the applied classifiers, confirming the good performance of several nonlinear classifiers. If the model parameters are properly selected, then very good classification performance can be obtained from NN trained by Bayesian regularization, SVM and ELM classifiers. The method can be effectively applied for the industrial condition monitoring of compressors.

Learners' perceptions of learners regarded as having a homosexual orientation in an independent secondary school environment.

PubMed

Mostert, Hendrik P; Myburgh, Chris; Poggenpoel, Marie

2012-10-04

In schools today discrimination based on sexual orientation takes place on a regular basis. This form of discrimination leads to aggression towards learners perceived to be homosexual, as well as towards those with a homosexual orientation. For more than 15 years South Africa has been a democratic country with laws that protect learners who have a homosexual orientation. Nevertheless, aggression and discrimination towards these learners still occur in schools. Aggression often leads to verbal and physical bullying of the victims by perpetrators. The objectives of this research were to explore and describe Grade 11 learners' experiences of aggression towards learners perceived to be homosexual as well as those with a homosexual orientation in an independent secondary school environment. The research design was qualitative, exploratory, descriptive and contextual in nature. The data for this investigation consisted of essays based on a published newspaper photograph, phenomenological group interviews, observations and field notes. Tesch's method of data analysis was used, and an independent coder assisted. Three themes were identified, discussed and supported by a literature control: that learners experience that it is right and acceptable to have a homosexual orientation; that they experience ambivalence towards homosexual orientation of learners; and experienced feelings that it is wrong to have a homosexual orientation. Recommended guidelines are provided to address aggression towards learners perceived to be homosexual and those with a homosexual orientation.

Phantom experiments using soft-prior regularization EIT for breast cancer imaging.

PubMed

Murphy, Ethan K; Mahara, Aditya; Wu, Xiaotian; Halter, Ryan J

2017-06-01

A soft-prior regularization (SR) electrical impedance tomography (EIT) technique for breast cancer imaging is described, which shows an ability to accurately reconstruct tumor/inclusion conductivity values within a dense breast model investigated using a cylindrical and a breast-shaped tank. The SR-EIT method relies on knowing the spatial location of a suspicious lesion initially detected from a second imaging modality. Standard approaches (using Laplace smoothing and total variation regularization) without prior structural information are unable to accurately reconstruct or detect the tumors. The soft-prior approach represents a very significant improvement to these standard approaches, and has the potential to improve conventional imaging techniques, such as automated whole breast ultrasound (AWB-US), by providing electrical property information of suspicious lesions to improve AWB-US's ability to discriminate benign from cancerous lesions. Specifically, the best soft-regularization technique found average absolute tumor/inclusion errors of 0.015 S m -1 for the cylindrical test and 0.055 S m -1 and 0.080 S m -1 for the breast-shaped tank for 1.8 cm and 2.5 cm inclusions, respectively. The standard approaches were statistically unable to distinguish the tumor from the mammary gland tissue. An analysis of false tumors (benign suspicious lesions) provides extra insight into the potential and challenges EIT has for providing clinically relevant information. The ability to obtain accurate conductivity values of a suspicious lesion (>1.8 cm) detected from another modality (e.g. AWB-US) could significantly reduce false positives and result in a clinically important technology.

Manifold regularized multitask learning for semi-supervised multilabel image classification.

PubMed

Luo, Yong; Tao, Dacheng; Geng, Bo; Xu, Chao; Maybank, Stephen J

2013-02-01

It is a significant challenge to classify images with multiple labels by using only a small number of labeled samples. One option is to learn a binary classifier for each label and use manifold regularization to improve the classification performance by exploring the underlying geometric structure of the data distribution. However, such an approach does not perform well in practice when images from multiple concepts are represented by high-dimensional visual features. Thus, manifold regularization is insufficient to control the model complexity. In this paper, we propose a manifold regularized multitask learning (MRMTL) algorithm. MRMTL learns a discriminative subspace shared by multiple classification tasks by exploiting the common structure of these tasks. It effectively controls the model complexity because different tasks limit one another's search volume, and the manifold regularization ensures that the functions in the shared hypothesis space are smooth along the data manifold. We conduct extensive experiments, on the PASCAL VOC'07 dataset with 20 classes and the MIR dataset with 38 classes, by comparing MRMTL with popular image classification algorithms. The results suggest that MRMTL is effective for image classification.

Women in the University of Chicago. Report of the Committee on University Women.

ERIC Educational Resources Information Center

Chicago Univ., IL.

Part 1 of this report on the status of women at the University of Chicago deals with women on the regular teaching faculties, their numbers and locations, potential pools of faculty women, recruitment procedures, promotions and reappointments, cases of alleged discrimination, nepotism, work patterns, reported satisfactions and dissatisfactions,…

Developmental Trajectories of Conduct Problems and Hyperactivity from Ages 2 to 10

ERIC Educational Resources Information Center

Shaw, Daniel S.; Lacourse, Eric; Nagin, Daniel S.

2005-01-01

Background: Conduct problems (CP) and hyperactivity/attention problems (HAP) are thought to covary with regularity, yet few studies have examined their co-occurrence or risk factors that discriminate their trajectories beginning in early childhood. Method: The present study sought to advance our understanding of this issue by examining separate…

Sleep and wake phase of heart beat dynamics by artificial insymmetrised patterns

NASA Astrophysics Data System (ADS)

Dudkowska, A.; Makowiec, D.

2004-05-01

In order to determine differences between healthy patients and patients with congestive heart failure we apply the artificial insymmetrised pattern (AIP) method. The AIP method by exploring a human eye ability to extract regularities and read symmetries in a dot pattern, serves a tool for qualitative discrimination of heart rate states.

Embracing and Harnessing Diversity in the US Workforce: What Have We Learned?

ERIC Educational Resources Information Center

Pope, Mark

2012-01-01

Cultural diversity in the US includes race, ethnicity, gender, disability, age, sexual orientation, religion, and other aspects of culture. American ethnic and racial minorities currently account for 31% of the US population, and growing. Their career development issues include the barriers they regularly encounter, such as discrimination;…

Identification of Which High Risk Youth Smoke Cigarettes Regularly.

ERIC Educational Resources Information Center

Sussman, Steve; And Others

This study investigated whether or not high or low risk youths differed on previous items discriminative of problem-prone youth, particularly problem-prone attitudes and preferences, and social and environmental smoking. In addition, the study examined whether high or low use youths differed on items related to a health orientation including…

Sex Discrimination in Education: Newsletter. Vol. 1, Nos. 1 and 2, Oct.-Dec., 1975.

ERIC Educational Resources Information Center

Michigan Univ., Ann Arbor. Dept. of Psychology.

This new bimonthly publication attempts to respond to the intent of the Women's Educational Equity Act (1974) which includes provisions for support of research and corrective programs geared toward elimination of sex stereotyping in textbooks and curricular materials. Regular features include sections on issues, categories and periodicals, print…

Antipsychotics side effects' influence on stigma of mental illness: focus group study results.

PubMed

Novak, Lan; Svab, Vesna

2009-03-01

Little research was done on the influence of antipsychotics' side effects on stigma of mental illness. An overview of studies shows that people with mental illness state that because of medication side effects they feel discriminated in the field of employment, observe worsening of family relations and tend to skip or discontinue their regular medication. It is difficult to discriminate between stigmatizing effects of antipsychotics and other stigma related factors such as illness symptoms. A focus group of ten patients with schizophrenia or schizoaffective disorder with severe and remitting mental illness treated with antipsychotic medication was conducted to obtain their personal views on how side effects of antipsychotic drugs affect their everyday lives and contribute to the stigmatization because of mental illness. The patients felt most stigmatized in areas of employment and occupation. They repeatedly skipped or discontinued regular medication due to side effects. Their families supported them throughout treatment and recovery despite problems associated with psychotropic medication. Medication induced stigma affects patients' lives in substantial ways and therefore merits further research, part of which is the patients' personal experience.

Health-related quality of life in young adults in education, employment, or training: development of the Japanese version of Pediatric Quality of Life Inventory (PedsQL) Generic Core Scales Young Adult Version.

PubMed

Kaneko, Mei; Sato, Iori; Soejima, Takafumi; Kamibeppu, Kiyoko

2014-09-01

The purpose of the study is to develop a Japanese version of the Pediatric Quality of Life Inventory (PedsQL) Generic Core Scales Young Adult Version (PedsQL-YA-J) and determine the feasibility, reliability, and validity of the scales. Translation equivalence and content validity were verified using back-translation and cognitive debriefing tests. A total of 428 young adults recruited from one university, two vocational schools, or five companies completed questionnaires. We determined questionnaire feasibility, internal consistency, and test-retest reliability; checked concurrent validity against the Center for Epidemiologic Studies Depression Scale (CES-D); determined convergent and discriminant validity with the Medical Outcome Study 36-item Short Form Health Survey (SF-36); described known-groups validity with regard to subjective symptoms, illness or injury requiring regular medical visits, and depression; and verified factorial validity. All scales were internally consistent (Cronbach's coefficient alpha = 0.77-0.86); test-retest reliability was acceptable (intraclass correlation coefficient = 0.57-0.69); and all scales were concurrently valid with depression (Pearson's correlation coefficient = 0.43-0.57). The scales convergent and discriminant validity with the SF-36 and CES-D were acceptable. Evaluation of known-groups validity confirmed that the Physical Functioning scale was sensitive for subjective symptoms, the Emotional Functioning scale for depression, and the Work/School Functioning scale for illness or injury requiring regular medical visits. Exploratory factor analysis found a six-factor structure consistent with the assumed structure (cumulative proportion = 57.0%). The PedsQL-YA-J is suitable for assessing health-related quality of life in young adults in education, employment, or training, and for clinical trials and epidemiological research.

Quantitative imaging of aggregated emulsions.

PubMed

Penfold, Robert; Watson, Andrew D; Mackie, Alan R; Hibberd, David J

2006-02-28

Noise reduction, restoration, and segmentation methods are developed for the quantitative structural analysis in three dimensions of aggregated oil-in-water emulsion systems imaged by fluorescence confocal laser scanning microscopy. Mindful of typical industrial formulations, the methods are demonstrated for concentrated (30% volume fraction) and polydisperse emulsions. Following a regularized deconvolution step using an analytic optical transfer function and appropriate binary thresholding, novel application of the Euclidean distance map provides effective discrimination of closely clustered emulsion droplets with size variation over at least 1 order of magnitude. The a priori assumption of spherical nonintersecting objects provides crucial information to combat the ill-posed inverse problem presented by locating individual particles. Position coordinates and size estimates are recovered with sufficient precision to permit quantitative study of static geometrical features. In particular, aggregate morphology is characterized by a novel void distribution measure based on the generalized Apollonius problem. This is also compared with conventional Voronoi/Delauney analysis.

Exploring Discrimination and Mental Health Disparities Faced By Black Sexual Minority Women Using a Minority Stress Framework

PubMed Central

Calabrese, Sarah K.; Meyer, Ilan H.; Overstreet, Nicole M.; Haile, Rahwa; Hansen, Nathan B.

2015-01-01

Black sexual minority women are triply marginalized due to their race, gender, and sexual orientation. We compared three dimensions of discrimination—frequency (regularity of occurrences), scope (number of types of discriminatory acts experienced), and number of bases (number of social statuses to which discrimination was attributed)—and self-reported mental health (depressive symptoms, psychological well-being, and social well-being) between 64 Black sexual minority women and each of two groups sharing two of three marginalized statuses: (a) 67 White sexual minority women and (b) 67 Black sexual minority men. Black sexual minority women reported greater discrimination frequency, scope, and number of bases and poorer psychological and social well-being than White sexual minority women and more discrimination bases, a higher level of depressive symptoms, and poorer social well-being than Black sexual minority men. We then tested and contrasted dimensions of discrimination as mediators between social status (race or gender) and mental health outcomes. Discrimination frequency and scope mediated the association between race and mental health, with a stronger effect via frequency among sexual minority women. Number of discrimination bases mediated the association between gender and mental health among Black sexual minorities. Future research and clinical practice would benefit from considering Black sexual minority women's mental health in a multidimensional minority stress context. PMID:26424904

Reverberations of Racism and Sexism Through the Subjective Sexualities of Undergraduate Women of Color.

PubMed

Zucker, Alyssa N; Fitz, Caroline C; Bay-Cheng, Laina Y

2016-01-01

Young women of color (among others) face both subtle and overt discrimination on a regular basis, but few studies have examined relations between discrimination and sexual outcomes using quantitative tools. We surveyed 154 self-identified undergraduate women of color to examine connections between race- and sex-based discrimination and subjective sexual well-being (i.e., condom use self-efficacy and sexual life satisfaction) and also tested whether sexual autonomy mediated these relations. When examined individually, each form of discrimination was related negatively to condom use self-efficacy and sexual life satisfaction, such that as women reported more discrimination, they reported poorer sexual well-being. However, when examining both racism and sexism as joint predictors, only racism remained significant and there were no racism × sexism interaction effects. In a path model, sexual autonomy mediated the relation between racism and each measure of subjective sexual well-being; racism was negatively related to sexual autonomy, which in turn was positively related to both condom use self-efficacy and sexual life satisfaction. These findings are consistent with the broader literature on the negative impact of discrimination on various aspects of mental and physical health. They also reinforce the position that redressing social inequality is a vital component of promoting individual health.

Exploring Game Performance in the National Basketball Association Using Player Tracking Data

PubMed Central

Calleja-González, Julio; Jiménez Sáiz, Sergio; Schelling i del Alcázar, Xavi; Balciunas, Mindaugas

2015-01-01

Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams. PMID:26171606

Exploring Game Performance in the National Basketball Association Using Player Tracking Data.

PubMed

Sampaio, Jaime; McGarry, Tim; Calleja-González, Julio; Jiménez Sáiz, Sergio; Schelling I Del Alcázar, Xavi; Balciunas, Mindaugas

2015-01-01

Recent player tracking technology provides new information about basketball game performance. The aim of this study was to (i) compare the game performances of all-star and non all-star basketball players from the National Basketball Association (NBA), and (ii) describe the different basketball game performance profiles based on the different game roles. Archival data were obtained from all 2013-2014 regular season games (n = 1230). The variables analyzed included the points per game, minutes played and the game actions recorded by the player tracking system. To accomplish the first aim, the performance per minute of play was analyzed using a descriptive discriminant analysis to identify which variables best predict the all-star and non all-star playing categories. The all-star players showed slower velocities in defense and performed better in elbow touches, defensive rebounds, close touches, close points and pull-up points, possibly due to optimized attention processes that are key for perceiving the required appropriate environmental information. The second aim was addressed using a k-means cluster analysis, with the aim of creating maximal different performance profile groupings. Afterwards, a descriptive discriminant analysis identified which variables best predict the different playing clusters. The results identified different playing profile of performers, particularly related to the game roles of scoring, passing, defensive and all-round game behavior. Coaching staffs may apply this information to different players, while accounting for individual differences and functional variability, to optimize practice planning and, consequently, the game performances of individuals and teams.

On the Regularities of the Polar Profiles of Proteins Related to Ebola Virus Infection and their Functional Domains.

PubMed

Polanco, Carlos; Samaniego Mendoza, José Lino; Buhse, Thomas; Uversky, Vladimir N; Bañuelos Chao, Ingrid Paola; Bañuelos Cedano, Marcela Angola; Tavera, Fernando Michel; Tavera, Daniel Michel; Falconi, Manuel; Ponce de León, Abelardo Vela

2018-03-06

The number of fatalities and economic losses caused by the Ebola virus infection across the planet culminated in the havoc that occurred between August and November 2014. However, little is known about the molecular protein profile of this devastating virus. This work represents a thorough bioinformatics analysis of the regularities of charge distribution (polar profiles) in two groups of proteins and their functional domains associated with Ebola virus disease: Ebola virus proteins and Human proteins interacting with Ebola virus. Our analysis reveals that a fragment exists in each of these proteins-one named the "functional domain"-with the polar profile similar to the polar profile of the protein that contains it. Each protein is formed by a group of short sub-sequences, where each fragment has a different and distinctive polar profile and where the polar profile between adjacent short sub-sequences changes orderly and gradually to coincide with the polar profile of the whole protein. When using the charge distribution as a metric, it was observed that it effectively discriminates the proteins from their functional domains. As a counterexample, the same test was applied to a set of synthetic proteins built for that purpose, revealing that any of the regularities reported here for the Ebola virus proteins and human proteins interacting with Ebola virus were not present in the synthetic proteins. Our results indicate that the polar profile of each protein studied and its corresponding functional domain are similar. Thus, when building each protein from its functional domai-adding one amino acid at a time and plotting each time its polar profile-it was observed that the resulting graphs can be divided into groups with similar polar profiles.

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…

Bell miner provisioning calls are more similar among relatives and are used by helpers at the nest to bias their effort towards kin

PubMed Central

McDonald, Paul G.; Wright, Jonathan

2011-01-01

Kin selection predicts that helpers in cooperative systems should preferentially aid relatives to maximize fitness. In family-based groups, this can be accomplished simply by assisting all group members. In more complex societies, where large numbers of kin and non-kin regularly interact, more sophisticated kin-recognition mechanisms are needed. Bell miners (Manorina melanophrys) are just such a system where individuals regularly interact with both kin and non-kin within large colonies. Despite this complexity, individual helpers of both sexes facultatively work harder when provisioning the young of closer genetic relatedness. We investigated the mechanism by which such adaptive discrimination occurs by assessing genetic kinship influences on the structure of more than 1900 provisioning vocalizations of 185 miners. These ‘mew’ calls showed a significant, positive linear increase in call similarity with increasing genetic relatedness, most especially in comparisons between male helpers and the breeding male. Furthermore, individual helping effort was more heavily influenced by call similarity to breeding males than to genetic relatedness, as predicted if call similarity is indeed the rule-of-thumb used to discriminate kin in this system. Individual mew call structure appeared to be inflexible and innate, providing an effective mechanism by which helpers can assess their relatedness to any individual. This provides, to our knowledge, the first example of a mechanism for fine-scale kin discrimination in a complex avian society. PMID:21450738

Clustering performances in the NBA according to players' anthropometric attributes and playing experience.

PubMed

Zhang, Shaoliang; Lorenzo, Alberto; Gómez, Miguel-Angel; Mateus, Nuno; Gonçalves, Bruno; Sampaio, Jaime

2018-04-20

The aim of this study was: (i) to group basketball players into similar clusters based on a combination of anthropometric characteristics and playing experience; and (ii) explore the distribution of players (included starters and non-starters) from different levels of teams within the obtained clusters. The game-related statistics from 699 regular season balanced games were analyzed using a two-step cluster model and a discriminant analysis. The clustering process allowed identifying five different player profiles: Top height and weight (HW) with low experience, TopHW-LowE; Middle HW with middle experience, MiddleHW-MiddleE; Middle HW with top experience, MiddleHW-TopE; Low HW with low experience, LowHW-LowE; Low HW with middle experience, LowHW-MiddleE. Discriminant analysis showed that TopHW-LowE group was highlighted by two-point field goals made and missed, offensive and defensive rebounds, blocks, and personal fouls; whereas the LowHW-LowE group made fewest passes and touches. The players from weaker teams were mostly distributed in LowHW-LowE group, whereas players from stronger teams were mainly grouped in LowHW-MiddleE group; and players that participated in the finals were allocated in the MiddleHW-MiddleE group. These results provide alternative references for basketball staff concerning the process of evaluating performance.

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…

Filling the blanks in temporal intervals: the type of filling influences perceived duration and discrimination performance

PubMed Central

Horr, Ninja K.; Di Luca, Massimiliano

2015-01-01

In this work we investigate how judgments of perceived duration are influenced by the properties of the signals that define the intervals. Participants compared two auditory intervals that could be any combination of the following four types: intervals filled with continuous tones (filled intervals), intervals filled with regularly-timed short tones (isochronous intervals), intervals filled with irregularly-timed short tones (anisochronous intervals), and intervals demarcated by two short tones (empty intervals). Results indicate that the type of intervals to be compared affects discrimination performance and induces distortions in perceived duration. In particular, we find that duration judgments are most precise when comparing two isochronous and two continuous intervals, while the comparison of two anisochronous intervals leads to the worst performance. Moreover, we determined that the magnitude of the distortions in perceived duration (an effect akin to the filled duration illusion) is higher for tone sequences (no matter whether isochronous or anisochronous) than for continuous tones. Further analysis of how duration distortions depend on the type of filling suggests that distortions are not only due to the perceived duration of the two individual intervals, but they may also be due to the comparison of two different filling types. PMID:25717310

Neighborhood Discriminant Hashing for Large-Scale Image Retrieval.

PubMed

Tang, Jinhui; Li, Zechao; Wang, Meng; Zhao, Ruizhen

2015-09-01

With the proliferation of large-scale community-contributed images, hashing-based approximate nearest neighbor search in huge databases has aroused considerable interest from the fields of computer vision and multimedia in recent years because of its computational and memory efficiency. In this paper, we propose a novel hashing method named neighborhood discriminant hashing (NDH) (for short) to implement approximate similarity search. Different from the previous work, we propose to learn a discriminant hashing function by exploiting local discriminative information, i.e., the labels of a sample can be inherited from the neighbor samples it selects. The hashing function is expected to be orthogonal to avoid redundancy in the learned hashing bits as much as possible, while an information theoretic regularization is jointly exploited using maximum entropy principle. As a consequence, the learned hashing function is compact and nonredundant among bits, while each bit is highly informative. Extensive experiments are carried out on four publicly available data sets and the comparison results demonstrate the outperforming performance of the proposed NDH method over state-of-the-art hashing techniques.

Using New Models to Analyze Complex Regularities of the World: Commentary on Musso et al. (2013)

ERIC Educational Resources Information Center

Nokelainen, Petri; Silander, Tomi

2014-01-01

This commentary to the recent article by Musso et al. (2013) discusses issues related to model fitting, comparison of classification accuracy of generative and discriminative models, and two (or more) cultures of data modeling. We start by questioning the extremely high classification accuracy with an empirical data from a complex domain. There is…

Special Needs Characteristics of Children with Emotional and Behavioral Disorders that Affect Inclusion in Regular Education

ERIC Educational Resources Information Center

Stoutjesdijk, Regina; Scholte, Evert M.; Swaab, Hanna

2012-01-01

The aim of this study is to determine the discriminating special needs characteristics of children with emotional and behavioral disorders (EBD) that predict restrictiveness of placement in special education. The focus is on dynamic factors instead of static factors. To this end, 235 children with EBD in special schools and 111 children with EBD…

"I Don't Have Time to Be This Busy." Exploring the Concerns of Secondary School Teachers Towards Inclusive Education

ERIC Educational Resources Information Center

Round, Penny N.; Subban, Pearl K.; Sharma, Umesh

2016-01-01

The trend towards inclusion in mainstream Australian schools has seen the numbers of students with disabilities educated in regular schools grow significantly. This trend has been supported by legislation such as the Disability Discrimination Act and the Education Standards. For inclusion to be successful, a number of factors are vital and teacher…

Examination of a social problem-solving intervention to treat selective mutism.

PubMed

O'Reilly, Mark; McNally, Deirdre; Sigafoos, Jeff; Lancioni, Giulio E; Green, Vanessa; Edrisinha, Chaturi; Machalicek, Wendy; Sorrells, Audrey; Lang, Russell; Didden, Robert

2008-03-01

The authors examined the use of a social problem-solving intervention to treat selective mutism with 2 sisters in an elementary school setting. Both girls were taught to answer teacher questions in front of their classroom peers during regular classroom instruction. Each girl received individualized instruction from a therapist and was taught to discriminate salient social cues, select an appropriate social response, perform the response, and evaluate her performance. The girls generalized the skills to their respective regular classrooms and maintained the skills for up to 3 months after the removal of the intervention. Experimental control was demonstrated using a multiple baseline design across participants. Limitations of this study and issues for future research are discussed.

A Unified Fisher's Ratio Learning Method for Spatial Filter Optimization.

PubMed

Li, Xinyang; Guan, Cuntai; Zhang, Haihong; Ang, Kai Keng

To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.To detect the mental task of interest, spatial filtering has been widely used to enhance the spatial resolution of electroencephalography (EEG). However, the effectiveness of spatial filtering is undermined due to the significant nonstationarity of EEG. Based on regularization, most of the conventional stationary spatial filter design methods address the nonstationarity at the cost of the interclass discrimination. Moreover, spatial filter optimization is inconsistent with feature extraction when EEG covariance matrices could not be jointly diagonalized due to the regularization. In this paper, we propose a novel framework for a spatial filter design. With Fisher's ratio in feature space directly used as the objective function, the spatial filter optimization is unified with feature extraction. Given its ratio form, the selection of the regularization parameter could be avoided. We evaluate the proposed method on a binary motor imagery data set of 16 subjects, who performed the calibration and test sessions on different days. The experimental results show that the proposed method yields improvement in classification performance for both single broadband and filter bank settings compared with conventional nonunified methods. We also provide a systematic attempt to compare different objective functions in modeling data nonstationarity with simulation studies.

Obesity discrimination: the role of physical appearance, personal ideology, and anti-fat prejudice.

PubMed

O'Brien, K S; Latner, J D; Ebneter, D; Hunter, J A

2013-03-01

Self-report measures of anti-fat prejudice are regularly used by the field, however, there is no research showing a relationship between explicit measures of anti-fat prejudice and the behavioral manifestation of them; obesity discrimination. The present study examined whether a recently developed measure of anti-fat prejudice, the universal measure of bias (UMB), along with other correlates of prejudicial attitudes and beliefs (that is, authoritarianism, social dominance orientation; SDO, physical appearance investment) predict obesity discrimination. Under the guise of a personnel selection task, participants (n=102) gave assessments of obese and non-obese females applying for a managerial position across a number of selection criteria (for example, starting salary, likelihood of selecting). Participants viewed resumes that had attached either a photo of a pre-bariatric surgery obese female (body mass index (BMI)=38-41) or a photo of the same female post-bariatric surgery (BMI=22-24). Participants also completed measures of anti-fat prejudice (UMB) authoritarianism, SDO, physical appearance evaluation and orientation. Obesity discrimination was displayed across all selection criteria. Higher UMB subscale scores (distance and negative judgement), authoritarianism, physical appearance evaluation and orientation were associated with greater obesity discrimination. In regression models, UMB 'distance' was a predictor of obesity discrimination for perceived leadership potential, starting salary, and overall employability. UMB 'negative judgement' predicted discrimination for starting salary; and authoritarianism predicted likelihood of selecting an obese applicant and candidate ranking. Finally, physical appearance evaluation and appearance orientation predicted obesity discrimination for predicted career success and leadership potential, respectively. Self-report measures of prejudice act as surrogates for discrimination, but there has been no empirical support for the validity of explicit measures of anti-fat prejudice. Here, the UMB, authoritarianism, and physical appearance investment predicted obesity discrimination. The present results provide support for the use of these measures by researchers seeking to assess, understand, and reduce anti-fat prejudice and discrimination.

Caffeine use disorder: An item-response theory analysis of proposed DSM-5 criteria.

PubMed

Ágoston, Csilla; Urbán, Róbert; Richman, Mara J; Demetrovics, Zsolt

2018-06-01

Caffeine is a common psychoactive substance with a documented addictive potential. Caffeine withdrawal has been included in the Diagnostic and Statistical Manual of Mental Disorders (DSM-5), but caffeine use disorder (CUD) is considered to be a condition for further study. The aim of the current study is (1) to test the psychometric properties of the Caffeine Use Disorder Questionnaire (CUDQ) by using a confirmatory factor analysis and an item response theory (IRT) approach, (2) to compare IRT models with varying numbers of parameters and models with or without caffeine consumption criteria, and (3) to examine if the total daily caffeine consumption and the use of different caffeinated products can predict the magnitude of CUD symptomatology. A cross-sectional study was conducted on an adult sample (N = 2259). Participants answered several questions regarding their caffeine consumption habits and completed the CUDQ, which incorporates the nine proposed criteria of the DSM-5 as well as one additional item regarding the suffering caused by the symptoms. Factor analyses demonstrated the unidimensionality of the CUDQ. The suffering criterion had the highest discriminative value at a higher degree of latent trait. The criterion of failure to fulfill obligations and social/interpersonal problems discriminate only at the higher value of CUD latent factor, while endorsement the consumption of more caffeine or longer than intended and craving criteria were discriminative at a lower level of CUD. Total daily caffeine intake was related to a higher level of CUD. Daily coffee, energy drink, and cola intake as dummy variables were associated with the presence of more CUD symptoms, while daily tea consumption as a dummy variable was related to less CUD symptoms. Regular smoking was associated with more CUD symptoms, which was explained by a larger caffeine consumption. The IRT approach helped to determine which CUD symptoms indicate more severity and have a greater discriminative value. The level of CUD is influenced by the type and quantity of caffeine consumption. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sparse graph regularization for robust crop mapping using hyperspectral remotely sensed imagery with very few in situ data

NASA Astrophysics Data System (ADS)

Xue, Zhaohui; Du, Peijun; Li, Jun; Su, Hongjun

2017-02-01

The generally limited availability of training data relative to the usually high data dimension pose a great challenge to accurate classification of hyperspectral imagery, especially for identifying crops characterized with highly correlated spectra. However, traditional parametric classification models are problematic due to the need of non-singular class-specific covariance matrices. In this research, a novel sparse graph regularization (SGR) method is presented, aiming at robust crop mapping using hyperspectral imagery with very few in situ data. The core of SGR lies in propagating labels from known data to unknown, which is triggered by: (1) the fraction matrix generated for the large unknown data by using an effective sparse representation algorithm with respect to the few training data serving as the dictionary; (2) the prediction function estimated for the few training data by formulating a regularization model based on sparse graph. Then, the labels of large unknown data can be obtained by maximizing the posterior probability distribution based on the two ingredients. SGR is more discriminative, data-adaptive, robust to noise, and efficient, which is unique with regard to previously proposed approaches and has high potentials in discriminating crops, especially when facing insufficient training data and high-dimensional spectral space. The study area is located at Zhangye basin in the middle reaches of Heihe watershed, Gansu, China, where eight crop types were mapped with Compact Airborne Spectrographic Imager (CASI) and Shortwave Infrared Airborne Spectrogrpahic Imager (SASI) hyperspectral data. Experimental results demonstrate that the proposed method significantly outperforms other traditional and state-of-the-art methods.

Subtypes of Reading Disability in a Shallow Orthography: A Double Dissociation between Accuracy-Disabled and Rate-Disabled Readers of Hebrew

ERIC Educational Resources Information Center

Shany, Michal; Share, David L.

2011-01-01

Whereas most English language sub-typing schemes for dyslexia (e.g., Castles & Coltheart, "1993") have focused on reading accuracy for words varying in regularity, such an approach may have limited utility for reading disability sub-typing beyond English in which fluency rather than accuracy is the key discriminator of developmental and individual…

Group B Streptococcus Vaginal Carriage in Pregnant Women as Deciphered by Clustered Regularly Interspaced Short Palindromic Repeat Analysis.

PubMed

Beauruelle, Clemence; Pastuszka, Adeline; Mereghetti, Laurent; Lanotte, Philippe

2018-06-01

We evaluated the diversity of group B Streptococcus (GBS) vaginal carriage populations in pregnant women. For this purpose, we studied each isolate present in a primary culture of a vaginal swab using a new approach based on clustered regularly interspaced short palindromic repeats (CRISPR) locus analysis. To evaluate the CRISPR array composition rapidly, a restriction fragment length polymorphism (RFLP) analysis was performed. For each different pattern observed, the CRISPR array was sequenced and capsular typing and multilocus sequence typing (MLST) were performed. A total of 970 isolates from 10 women were analyzed by CRISPR-RFLP. Each woman carrying GBS isolates presented one to five specific "personal" patterns. Five women showed similar isolates with specific and unique restriction patterns, suggesting the carriage of a single GBS clone. Different patterns were observed among isolates from the other five women. For three of these, CRISPR locus sequencing highlighted low levels of internal modifications in the locus backbone, whereas there were high levels of modifications for the last two women, suggesting the carriage of two different clones. These two clones were closely related, having the same ancestral spacer(s), the same capsular type and, in one case, the same ST, but showed different antibiotic resistance patterns in pairs. Eight of 10 women were colonized by a single GBS clone, while two of them were colonized by two strains, leading to a risk of selection of more-virulent and/or more-resistant clones during antibiotic prophylaxis. This CRISPR analysis made it possible to separate isolates belonging to a single capsular type and sequence type, highlighting the greater discriminating power of this approach. Copyright © 2018 American Society for Microbiology.

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

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.

The effect of dehydroepiandrosterone (DHEA) on recognition memory decision processes and discrimination in postmenopausal women.

PubMed

Hirshman, Elliot; Wells, Ellen; Wierman, Margaret E; Anderson, Benjamin; Butler, Andrew; Senholzi, Meredith; Fisher, Julia

2003-03-01

In this article, the theoretical distinction between recognition memory decision and discrimination processes is used to explore the effect of dehydroepiandrosterone (DHEA) in postmenopausal women. DHEA is an adrenal steroid that diminishes with aging. It has enhanced memory in laboratory animals. An 8-week placebo-controlled, double-blind experiment in which 30 women (ages 39-70) received a 50-mg/day oral dose of DHEA for 4 weeks demonstrated that DHEA made subjects more conservative (i.e., less likely to call test items "old") in their recognition memory decisions and enhanced recognition memory discrimination for items presented briefly. The former result may reflect an empirical regularity (Hirshman, 1995) in which recent strong memory experiences make participants more conservative. The latter result may reflect the effect of DHEA on visual perception, with consequent effects on memory. These results suggest the methodological importance of focusing on decision processes when examining the effects of hormones on memory.

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

[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.

Adaptation of the Haloarcula hispanica CRISPR-Cas system to a purified virus strictly requires a priming process

PubMed Central

Li, Ming; Wang, Rui; Zhao, Dahe; Xiang, Hua

2014-01-01

The clustered regularly interspaced short palindromic repeat (CRISPR)-Cas system mediates adaptive immunity against foreign nucleic acids in prokaryotes. However, efficient adaptation of a native CRISPR to purified viruses has only been observed for the type II-A system from a Streptococcus thermophilus industry strain, and rarely reported for laboratory strains. Here, we provide a second native system showing efficient adaptation. Infected by a newly isolated virus HHPV-2, Haloarcula hispanica type I-B CRISPR system acquired spacers discriminatively from viral sequences. Unexpectedly, in addition to Cas1, Cas2 and Cas4, this process also requires Cas3 and at least partial Cascade proteins, which are involved in interference and/or CRISPR RNA maturation. Intriguingly, a preexisting spacer partially matching a viral sequence is also required, and spacer acquisition from upstream and downstream sequences of its target sequence (i.e. priming protospacer) shows different strand bias. These evidences strongly indicate that adaptation in this system strictly requires a priming process. This requirement, if validated also true for other CRISPR systems as implied by our bioinformatic analysis, may help to explain failures to observe efficient adaptation to purified viruses in many laboratory strains, and the discrimination mechanism at the adaptation level that has confused scientists for years. PMID:24265226

Multilinear Graph Embedding: Representation and Regularization for Images.

PubMed

Chen, Yi-Lei; Hsu, Chiou-Ting

2014-02-01

Given a set of images, finding a compact and discriminative representation is still a big challenge especially when multiple latent factors are hidden in the way of data generation. To represent multifactor images, although multilinear models are widely used to parameterize the data, most methods are based on high-order singular value decomposition (HOSVD), which preserves global statistics but interprets local variations inadequately. To this end, we propose a novel method, called multilinear graph embedding (MGE), as well as its kernelization MKGE to leverage the manifold learning techniques into multilinear models. Our method theoretically links the linear, nonlinear, and multilinear dimensionality reduction. We also show that the supervised MGE encodes informative image priors for image regularization, provided that an image is represented as a high-order tensor. From our experiments on face and gait recognition, the superior performance demonstrates that MGE better represents multifactor images than classic methods, including HOSVD and its variants. In addition, the significant improvement in image (or tensor) completion validates the potential of MGE for image regularization.

Isotopic Discrimination During Leaf Litter Decomposition

NASA Astrophysics Data System (ADS)

Ngao, J.; Rubino, M.

2006-12-01

Methods involving stable isotopes have been successfully applied since decades in various research fields. Tracing 13C natural abundance in ecosystem compartments greatly enhanced the understanding of the C fluxes in the plant-soil-atmosphere C exchanges when compartments present different C isotopic signatures (i.e. atmospheric CO2 vs photosynthetic leaves, C3 vs C4; etc.). However, the assumption that no isotopic discrimination occurs during respiration is commonly made in numbers of C isotope-based ecological studies. Furthermore, verifications of such assumption are sparse and not enough reliable. The aim of our study is to assess the potential isotopic discrimination that may occur during litter decomposition. Leaf litter from an Arbutus unedo (L.) stand (Tolfa, Italy) was incubated in 1L jars, under constant laboratory conditions (i.e. 25 ° C and 135% WC). During the entire incubation period, gravimetric mass loss, litter respiration rates and the isotopic composition of respired CO2 are monitored at regular intervals. Data from 7 months of incubation will be presented and discussed. After two months, the litter mass loss averaged 16% of initial dry mass. During the same time-period, the respiration rate decreased significantly by 58% of the initial respiration rate. Isotopic compositions of respired CO2 ranged between -27.95‰ and - 25.69‰. Mean values did not differ significantly among the sampling days, in spite of an apparent enrichment in 13C of respired CO2 with time. The significance of these isotopic enrichment will be determined at a longer time scale. They may reveal both/either a direct microbial discrimination during respiration processes and/or a use of different litter compounds as C source along time. Further chemical and compound-specific isotopic analysis of dry matter will be performed in order to clarify these hypotheses. This work is part of the "ALICE" project, funded by the European Union's Marie Curie Fellowship Actions that aims to implement an advanced laser spectrometry technology to measure the isotopic composition in respired CO2. The laser spectrometer will be used to investigate the isotopic discrimination during soil respiration, in laboratory and field studies.

Clustered Regularly Interspaced Short Palindromic Repeats Are emm Type-Specific in Highly Prevalent Group A Streptococci.

PubMed

Zheng, Po-Xing; Chan, Yuen-Chi; Chiou, Chien-Shun; Chiang-Ni, Chuan; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong

2015-01-01

Clustered regularly interspaced short palindromic repeats (CRISPR) are the bacterial adaptive immune system against foreign nucleic acids. Given the variable nature of CRISPR, it could be a good marker for molecular epidemiology. Group A streptococcus is one of the major human pathogens. It has two CRISPR loci, including CRISPR01 and CRISPR02. The aim of this study was to analyze the distribution of CRISPR-associated gene cassettes (cas) and CRISPR arrays in highly prevalent emm types. The cas cassette and CRISPR array in two CRISPR loci were analyzed in a total of 332 strains, including emm1, emm3, emm4, emm12, and emm28 strains. The CRISPR type was defined by the spacer content of each CRISPR array. All strains had at least one cas cassette or CRISPR array. More than 90% of the spacers were found in one emm type, specifically. Comparing the consistency between emm and CRISPR types by Simpson's index of diversity and the adjusted Wallace coefficient, CRISPR01 type was concordant to emm type, and CRISPR02 showed unidirectional congruence to emm type, suggesting that at least for the majority of isolates causing infection in high income countries, the emm type can be inferred from CRISPR analysis, which can further discriminate isolates sharing the same emm type.

Random forests in non-invasive sensorimotor rhythm brain-computer interfaces: a practical and convenient non-linear classifier.

PubMed

Steyrl, David; Scherer, Reinhold; Faller, Josef; Müller-Putz, Gernot R

2016-02-01

There is general agreement in the brain-computer interface (BCI) community that although non-linear classifiers can provide better results in some cases, linear classifiers are preferable. Particularly, as non-linear classifiers often involve a number of parameters that must be carefully chosen. However, new non-linear classifiers were developed over the last decade. One of them is the random forest (RF) classifier. Although popular in other fields of science, RFs are not common in BCI research. In this work, we address three open questions regarding RFs in sensorimotor rhythm (SMR) BCIs: parametrization, online applicability, and performance compared to regularized linear discriminant analysis (LDA). We found that the performance of RF is constant over a large range of parameter values. We demonstrate - for the first time - that RFs are applicable online in SMR-BCIs. Further, we show in an offline BCI simulation that RFs statistically significantly outperform regularized LDA by about 3%. These results confirm that RFs are practical and convenient non-linear classifiers for SMR-BCIs. Taking into account further properties of RFs, such as independence from feature distributions, maximum margin behavior, multiclass and advanced data mining capabilities, we argue that RFs should be taken into consideration for future BCIs.

Study on nondestructive discrimination of genuine and counterfeit wild ginsengs using NIRS

NASA Astrophysics Data System (ADS)

Lu, Q.; Fan, Y.; Peng, Z.; Ding, H.; Gao, H.

2012-07-01

A new approach for the nondestructive discrimination between genuine wild ginsengs and the counterfeit ones by near infrared spectroscopy (NIRS) was developed. Both discriminant analysis and back propagation artificial neural network (BP-ANN) were applied to the model establishment for discrimination. Optimal modeling wavelengths were determined based on the anomalous spectral information of counterfeit samples. Through principal component analysis (PCA) of various wild ginseng samples, genuine and counterfeit, the cumulative percentages of variance of the principal components were obtained, serving as a reference for principal component (PC) factor determination. Discriminant analysis achieved an identification ratio of 88.46%. With sample' truth values as its outputs, a three-layer BP-ANN model was built, which yielded a higher discrimination accuracy of 100%. The overall results sufficiently demonstrate that NIRS combined with BP-ANN classification algorithm performs better on ginseng discrimination than discriminant analysis, and can be used as a rapid and nondestructive method for the detection of counterfeit wild ginsengs in food and pharmaceutical industry.

Discrimination of fast click-series produced by tagged Risso's dolphins (Grampus griseus) for echolocation or communication.

PubMed

Arranz, P; DeRuiter, S L; Stimpert, A K; Neves, S; Friedlaender, A S; Goldbogen, J A; Visser, F; Calambokidis, J; Southall, B L; Tyack, P L

2016-09-15

Early studies that categorized odontocete pulsed sounds had few means of discriminating signals used for biosonar-based foraging from those used for communication. This capability to identify the function of sounds is important for understanding and interpreting behavior; it is also essential for monitoring and mitigating potential disturbance from human activities. Archival tags were placed on free-ranging Grampus griseus to quantify and discriminate between pulsed sounds used for echolocation-based foraging and those used for communication. Two types of rapid click-series pulsed sounds, buzzes and burst pulses, were identified as produced by the tagged dolphins and classified using a Gaussian mixture model based on their duration, association with jerk (i.e. rapid change of acceleration) and temporal association with click trains. Buzzes followed regular echolocation clicks and coincided with a strong jerk signal from accelerometers on the tag. They consisted of series averaging 359±210 clicks (mean±s.d.) with an increasing repetition rate and relatively low amplitude. Burst pulses consisted of relatively short click series averaging 45±54 clicks with decreasing repetition rate and longer inter-click interval that were less likely to be associated with regular echolocation and the jerk signal. These results suggest that the longer, relatively lower amplitude, jerk-associated buzzes are used in this species to capture prey, mostly during the bottom phase of foraging dives, as seen in other odontocetes. In contrast, the shorter, isolated burst pulses that are generally emitted by the dolphins while at or near the surface are used outside of a direct, known foraging context. © 2016. Published by The Company of Biologists Ltd.

Stigma, agency and recovery amongst people with severe mental illness.

PubMed

Whitley, Rob; Campbell, Rosalyn Denise

2014-04-01

Evidence suggests that people with a severe mental illness still suffer high levels of stigma and discrimination. However little is known about how people with a severe mental illness manage such stigma. As such, the overall aim of this study is to document and analyze behavioral and psychological strategies of stigma management and control in a sample of people in recovery from a severe mental illness. To meet this aim, we conducted a five-year (2008-2012) qualitative longitudinal study in Washington D.C. Participants were recruited from small-scale congregate housing units ('recovery communities') for people in recovery, provided by a public mental health agency. We conducted regular focus groups at these communities, augmented by in-depth participant observation. Analysis was propelled by the grounded theory approach. A key finding of this study is that stigma and discrimination were not perceived as commonly experienced problems by participants. Instead, stigma and discrimination were perceived as omnipresent potential problems to which participants remained eternally vigilant, taking various preventive measures. Most notable among these measures was a concerted and self-conscious effort to behave and look 'normal'; through dress, appearance, conduct and demeanor. In this endeavor, participants possessed and deployed a considered degree of agency to prevent, avoid or preempt stigma and discrimination. These efforts appeared to have a strong semiotic dimension, as participants reported their developing 'normality' (and increased agentic power) was tangible proof of their ongoing recovery. Participants also routinely discussed severe mental illness in normative terms, noting its similarity to physical illnesses such as diabetes, or to generic mental health problems experienced by all. These behavioral and psychological strategies of normalization appeared to be consolidated within the recovery communities, which provided physical shelter and highly-valued peer support. This fostered participants' ability to face and embrace the outside world with confidence, pride and dignity. Copyright © 2014 Elsevier Ltd. All rights reserved.

Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast

PubMed Central

Oh, Eun-Yeong; Lerwill, Melinda F.; Brachtel, Elena F.; Jones, Nicholas C.; Knoblauch, Nicholas W.; Montaser-Kouhsari, Laleh; Johnson, Nicole B.; Rao, Luigi K. F.; Faulkner-Jones, Beverly; Wilbur, David C.; Schnitt, Stuart J.; Beck, Andrew H.

2014-01-01

The categorization of intraductal proliferative lesions of the breast based on routine light microscopic examination of histopathologic sections is in many cases challenging, even for experienced pathologists. The development of computational tools to aid pathologists in the characterization of these lesions would have great diagnostic and clinical value. As a first step to address this issue, we evaluated the ability of computational image analysis to accurately classify DCIS and UDH and to stratify nuclear grade within DCIS. Using 116 breast biopsies diagnosed as DCIS or UDH from the Massachusetts General Hospital (MGH), we developed a computational method to extract 392 features corresponding to the mean and standard deviation in nuclear size and shape, intensity, and texture across 8 color channels. We used L1-regularized logistic regression to build classification models to discriminate DCIS from UDH. The top-performing model contained 22 active features and achieved an AUC of 0.95 in cross-validation on the MGH data-set. We applied this model to an external validation set of 51 breast biopsies diagnosed as DCIS or UDH from the Beth Israel Deaconess Medical Center, and the model achieved an AUC of 0.86. The top-performing model contained active features from all color-spaces and from the three classes of features (morphology, intensity, and texture), suggesting the value of each for prediction. We built models to stratify grade within DCIS and obtained strong performance for stratifying low nuclear grade vs. high nuclear grade DCIS (AUC = 0.98 in cross-validation) with only moderate performance for discriminating low nuclear grade vs. intermediate nuclear grade and intermediate nuclear grade vs. high nuclear grade DCIS (AUC = 0.83 and 0.69, respectively). These data show that computational pathology models can robustly discriminate benign from malignant intraductal proliferative lesions of the breast and may aid pathologists in the diagnosis and classification of these lesions. PMID:25490766

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

The role of multisensory interplay in enabling temporal expectations.

PubMed

Ball, Felix; Michels, Lara E; Thiele, Carsten; Noesselt, Toemme

2018-01-01

Temporal regularities can guide our attention to focus on a particular moment in time and to be especially vigilant just then. Previous research provided evidence for the influence of temporal expectation on perceptual processing in unisensory auditory, visual, and tactile contexts. However, in real life we are often exposed to a complex and continuous stream of multisensory events. Here we tested - in a series of experiments - whether temporal expectations can enhance perception in multisensory contexts and whether this enhancement differs from enhancements in unisensory contexts. Our discrimination paradigm contained near-threshold targets (subject-specific 75% discrimination accuracy) embedded in a sequence of distractors. The likelihood of target occurrence (early or late) was manipulated block-wise. Furthermore, we tested whether spatial and modality-specific target uncertainty (i.e. predictable vs. unpredictable target position or modality) would affect temporal expectation (TE) measured with perceptual sensitivity (d ' ) and response times (RT). In all our experiments, hidden temporal regularities improved performance for expected multisensory targets. Moreover, multisensory performance was unaffected by spatial and modality-specific uncertainty, whereas unisensory TE effects on d ' but not RT were modulated by spatial and modality-specific uncertainty. Additionally, the size of the temporal expectation effect, i.e. the increase in perceptual sensitivity and decrease of RT, scaled linearly with the likelihood of expected targets. Finally, temporal expectation effects were unaffected by varying target position within the stream. Together, our results strongly suggest that participants quickly adapt to novel temporal contexts, that they benefit from multisensory (relative to unisensory) stimulation and that multisensory benefits are maximal if the stimulus-driven uncertainty is highest. We propose that enhanced informational content (i.e. multisensory stimulation) enables the robust extraction of temporal regularities which in turn boost (uni-)sensory representations. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

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.

A latent class analysis of underage problem drinking: evidence from a community sample of 16-20 year olds.

PubMed

Reboussin, Beth A; Song, Eun-Young; Shrestha, Anshu; Lohman, Kurt K; Wolfson, Mark

2006-07-27

The aim of this paper is to shed light on the nature of underage problem drinking by using an empirically based method to characterize the variation in patterns of drinking in a community sample of underage drinkers. A total of 4056 16-20-year-old current drinkers from 212 communities in the US were surveyed by telephone as part of the National Evaluation of the Enforcing Underage Drinking Laws (EUDL) Program. Latent class models were used to create homogenous groups of drinkers with similar drinking patterns defined by multiple indicators of drinking behaviors and alcohol-related problems. Two types of underage problem drinkers were identified; risky drinkers (30%) and regular drinkers (27%). The most prominent behaviors among both types of underage problem drinkers were binge drinking and getting drunk. Being male, other drug use, early onset drinking and beliefs about friends drinking and getting drunk were all associated with an increased risk of being a problem drinker after adjustment for other factors. Beliefs that most friends drink and current marijuana use were the strongest predictors of both risky problem drinking (OR=4.0; 95% CI=3.1, 5.1 and OR=4.0; 95% CI=2.8, 5.6, respectively) and regular problem drinking (OR=10.8; 95% CI=7.0, 16.7 and OR=10.2; 95% CI=6.9, 15.2). Young adulthood (ages 18-20) was significantly associated with regular problem drinking but not risky problem drinking. The belief that most friends get drunk weekly was the strongest discriminator of risky and regular problem drinking patterns (OR=5.3; 95% CI=3.9, 7.1). These findings suggest that underage problem drinking is most strongly characterized by heavy drinking behaviors which can emerge in late adolescence and underscores its association with perceptions regarding friends drinking behaviors and illicit drug use.

A latent class analysis of underage problem drinking: Evidence from a community sample of 16−20 year olds

PubMed Central

Reboussin, Beth A.; Song, Eun-Young; Shrestha, Anshu; Lohman, Kurt K.; Wolfson, Mark

2008-01-01

The aim of this paper is to shed light on the nature of underage problem drinking by using an empirically based method to characterize the variation in patterns of drinking in a community sample of underage drinkers. A total of 4056 16−20-year-old current drinkers from 212 communities in the US were surveyed by telephone as part of the National Evaluation of the Enforcing Underage Drinking Laws (EUDL) Program. Latent class models were used to create homogenous groups of drinkers with similar drinking patterns defined by multiple indicators of drinking behaviors and alcohol-related problems. Two types of underage problem drinkers were identified; risky drinkers (30%) and regular drinkers (27%). The most prominent behaviors among both types of underage problem drinkers were binge drinking and getting drunk. Being male, other drug use, early onset drinking and beliefs about friends drinking and getting drunk were all associated with an increased risk of being a problem drinker after adjustment for other factors. Beliefs that most friends drink and current marijuana use were the strongest predictors of both risky problem drinking (OR = 4.0; 95% CI = 3.1, 5.1 and OR = 4.0; 95% CI = 2.8, 5.6, respectively) and regular problem drinking (OR = 10.8; 95% CI = 7.0, 16.7 and OR = 10.2; 95% CI = 6.9, 15.2). Young adulthood (ages 18−20) was significantly associated with regular problem drinking but not risky problem drinking. The belief that most friends get drunk weekly was the strongest discriminator of risky and regular problem drinking patterns (OR = 5.3; 95% CI = 3.9, 7.1). These findings suggest that underage problem drinking is most strongly characterized by heavy drinking behaviors which can emerge in late adolescence and underscores its association with perceptions regarding friends drinking behaviors and illicit drug use. PMID:16359829

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.

Regularized Generalized Canonical Correlation Analysis

ERIC Educational Resources Information Center

Tenenhaus, Arthur; Tenenhaus, Michel

2011-01-01

Regularized generalized canonical correlation analysis (RGCCA) is a generalization of regularized canonical correlation analysis to three or more sets of variables. It constitutes a general framework for many multi-block data analysis methods. It combines the power of multi-block data analysis methods (maximization of well identified criteria) and…

Determining origin in a migratory marine vertebrate: a novel method to integrate stable isotopes and satellite tracking

USGS Publications Warehouse

Vander Zanden, Hannah B.; Tucker, Anton D.; Hart, Kristen M.; Lamont, Margaret M.; Fujisaki, Ikuko; Addison, David S.; Mansfield, Katherine L.; Phillips, Katrina F.; Wunder, Michael B.; Bowen, Gabriel J.; Pajuelo, Mariela; Bolten, Alan B.; Bjorndal, Karen A.

2015-01-01

Stable isotope analysis is a useful tool to track animal movements in both terrestrial and marine environments. These intrinsic markers are assimilated through the diet and may exhibit spatial gradients as a result of biogeochemical processes at the base of the food web. In the marine environment, maps to predict the spatial distribution of stable isotopes are limited, and thus determining geographic origin has been reliant upon integrating satellite telemetry and stable isotope data. Migratory sea turtles regularly move between foraging and reproductive areas. Whereas most nesting populations can be easily accessed and regularly monitored, little is known about the demographic trends in foraging populations. The purpose of the present study was to examine migration patterns of loggerhead nesting aggregations in the Gulf of Mexico (GoM), where sea turtles have been historically understudied. Two methods of geographic assignment using stable isotope values in known-origin samples from satellite telemetry were compared: 1) a nominal approach through discriminant analysis and 2) a novel continuous-surface approach using bivariate carbon and nitrogen isoscapes (isotopic landscapes) developed for this study. Tissue samples for stable isotope analysis were obtained from 60 satellite-tracked individuals at five nesting beaches within the GoM. Both methodological approaches for assignment resulted in high accuracy of foraging area determination, though each has advantages and disadvantages. The nominal approach is more appropriate when defined boundaries are necessary, but up to 42% of the individuals could not be considered in this approach. All individuals can be included in the continuous-surface approach, and individual results can be aggregated to identify geographic hotspots of foraging area use, though the accuracy rate was lower than nominal assignment. The methodological validation provides a foundation for future sea turtle studies in the region to inexpensively determine geographic origin for large numbers of untracked individuals. Regular monitoring of sea turtle nesting aggregations with stable isotope sampling can be used to fill critical data gaps regarding habitat use and migration patterns. Probabilistic assignment to origin with isoscapes has not been previously used in the marine environment, but the methods presented here could also be applied to other migratory marine species.

Determining origin in a migratory marine vertebrate: a novel method to integrate stable isotopes and satellite tracking.

PubMed

Zanden, Hannah B Vander; Tucker, Anton D; Hart, Kristen M; Lamont, Margaret M; Fuisaki, Ikuko; Addison, David; Mansfield, Katherine L; Phillips, Katrina F; Wunder, Michael B; Bowen, Gabriel J; Pajuelo, Mariela; Bolten, Alan B; Bjorndal, Karen A

2015-03-01

Stable isotope analysis is a useful tool to track animal movements in both terrestrial and marine environments. These intrinsic markers are assimilated through the diet and may exhibit spatial gradients as a result of biogeochemical processes at the base of the food web. In the marine environment, maps to predict the spatial distribution of stable isotopes are limited, and thus determining geographic origin has been reliant upon integrating satellite telemetry and stable isotope data. Migratory sea turtles regularly move between foraging and reproductive areas. Whereas most nesting populations can be easily accessed and regularly monitored, little is known about the demographic trends in foraging populations. The purpose of the present study was to examine migration patterns of loggerhead nesting aggregations in the Gulf of Mexico (GoM), where sea turtles have been historically understudied. Two methods of geographic assignment using stable isotope values in known-origin samples from satellite telemetry were compared: (1) a nominal approach through discriminant analysis and (2) a novel continuous-surface approach using bivariate carbon and nitrogen isoscapes (isotopic landscapes) developed for this study. Tissue samples for stable isotope analysis were obtained from 60 satellite-tracked individuals at five nesting beaches within the GoM. Both methodological approaches for assignment resulted in high accuracy of foraging area determination, though each has advantages and disadvantages. The nominal approach is more appropriate when defined boundaries are necessary, but up to 42% of the individuals could not be considered in this approach. All individuals can be included in the continuous-surface approach, and individual results can be aggregated to identify geographic hotspots of foraging area use, though the accuracy rate was lower than nominal assignment. The methodological validation provides a foundation for future sea turtle studies in the region to inexpensively determine geographic origin for large numbers of untracked individuals. Regular monitoring of sea turtle nesting aggregations with stable isotope sampling can be used to fill critical data gaps regarding habitat use and migration patterns. Probabilistic assignment to origin with isoscapes has not been previously used in the marine environment, but the methods presented here could also be applied to other migratory marine species.

Discrimination and Health among Lesbian, Gay, Bisexual and Trans People in Puerto Rico.

PubMed

Rodríguez-Díaz, Carlos E; Jovet-Toledo, Gerardo G; Vélez-Vega, Carmen M; Ortiz-Sánchez, Edgardo J; Santiago-Rodríguez, Edda I; Vargas-Molina, Ricardo L; Rodríguez Madera, Sheilla L; Mulinelli-Rodríguez, José J

2016-09-01

To identify the experiences of discrimination among and the perceived priorities for the health of lesbian, gay, bisexual, and trans (LGBT) people in Puerto Rico (PR). Data were collected during the 2013 LGBT Pride Parade in San Juan, using a brief self-administered survey that included questions on sociodemographic characteristics, the disclosure of sexual orientation/gender identity, experiences of discrimination, experiences while receiving social and health services, and perceived healthcare priorities and needs. Most participants reported that they had disclosed their sexual orientation to at least one person. Discrimination due to sexual orientation/gender identity was most frequently reported to have occurred in school settings. At least 25% of the sample reported regular or negative experiences based on sexual orientation/gender identity when receiving government services and when looking for support from relatives. HIV/AIDS, mental health, and sexual health were identified as healthcare priorities. In bivariate analyses, mental health services and aging were the priorities most frequently reported among older participants. HIV/AIDS was the main priority only for gay men; sexual health was the main priority for bisexuals; and mental health was the main priority for lesbians. Most participants reported that their preferred modalities for health service provision were support groups and health education. The experiences of discrimination among LGBT people in PR were consistent across age groups and sexual orientation/gender identity. Policies and interventions to address discrimination in different settings are necessary. The findings also suggest the need to prioritize HIV services among gay men and to address mental and sexual health needs among lesbian and bisexual people.

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…

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

Sparse Covariance Matrix Estimation by DCA-Based Algorithms.

PubMed

Phan, Duy Nhat; Le Thi, Hoai An; Dinh, Tao Pham

2017-11-01

This letter proposes a novel approach using the [Formula: see text]-norm regularization for the sparse covariance matrix estimation (SCME) problem. The objective function of SCME problem is composed of a nonconvex part and the [Formula: see text] term, which is discontinuous and difficult to tackle. Appropriate DC (difference of convex functions) approximations of [Formula: see text]-norm are used that result in approximation SCME problems that are still nonconvex. DC programming and DCA (DC algorithm), powerful tools in nonconvex programming framework, are investigated. Two DC formulations are proposed and corresponding DCA schemes developed. Two applications of the SCME problem that are considered are classification via sparse quadratic discriminant analysis and portfolio optimization. A careful empirical experiment is performed through simulated and real data sets to study the performance of the proposed algorithms. Numerical results showed their efficiency and their superiority compared with seven state-of-the-art methods.

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.

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...

Surface enhanced Raman spectroscopy (SERS) for the discrimination of Arthrobacter strains based on variations in cell surface composition.

PubMed

Stephen, Kate E; Homrighausen, Darren; DePalma, Glen; Nakatsu, Cindy H; Irudayaraj, Joseph

2012-09-21

Surface enhanced Raman spectroscopy (SERS) is a rapid and highly sensitive spectroscopic technique that has the potential to measure chemical changes in bacterial cell surface in response to environmental changes. The objective of this study was to determine whether SERS had sufficient resolution to differentiate closely related bacteria within a genus grown on solid and liquid medium, and a single Arthrobacter strain grown in multiple chromate concentrations. Fourteen closely related Arthrobacter strains, based on their 16S rRNA gene sequences, were used in this study. After performing principal component analysis in conjunction with Linear Discriminant Analysis, we used a novel, adapted cross-validation method, which more faithfully models the classification of spectra. All fourteen strains could be classified with up to 97% accuracy. The hierarchical trees comparing SERS spectra from the liquid and solid media datasets were different. Additionally, hierarchical trees created from the Raman data were different from those obtained using 16S rRNA gene sequences (a phylogenetic measure). A single bacterial strain grown on solid media culture with three different chromate levels also showed significant spectral distinction at discrete points identified by the new Elastic Net regularized regression method demonstrating the ability of SERS to detect environmentally induced changes in cell surface composition. This study demonstrates that SERS is effective in distinguishing between a large number of very closely related Arthrobacter strains and could be a valuable tool for rapid monitoring and characterization of phenotypic variations in a single population in response to environmental conditions.

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

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

Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography.

PubMed

Gang, Grace J; Siewerdsen, Jeffrey H; Stayman, J Webster

2017-12-01

This paper presents a joint optimization of dynamic fluence field modulation (FFM) and regularization in quadratic penalized-likelihood reconstruction that maximizes a task-based imaging performance metric. We adopted a task-driven imaging framework for prospective designs of the imaging parameters. A maxi-min objective function was adopted to maximize the minimum detectability index ( ) throughout the image. The optimization algorithm alternates between FFM (represented by low-dimensional basis functions) and local regularization (including the regularization strength and directional penalty weights). The task-driven approach was compared with three FFM strategies commonly proposed for FBP reconstruction (as well as a task-driven TCM strategy) for a discrimination task in an abdomen phantom. The task-driven FFM assigned more fluence to less attenuating anteroposterior views and yielded approximately constant fluence behind the object. The optimal regularization was almost uniform throughout image. Furthermore, the task-driven FFM strategy redistribute fluence across detector elements in order to prescribe more fluence to the more attenuating central region of the phantom. Compared with all strategies, the task-driven FFM strategy not only improved minimum by at least 17.8%, but yielded higher over a large area inside the object. The optimal FFM was highly dependent on the amount of regularization, indicating the importance of a joint optimization. Sample reconstructions of simulated data generally support the performance estimates based on computed . The improvements in detectability show the potential of the task-driven imaging framework to improve imaging performance at a fixed dose, or, equivalently, to provide a similar level of performance at reduced dose.

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.

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

Moradi, Hamid; Murugkar, Sangeeta; Ahmad, Abrar

Purpose: To improve classification by reducing batch effect in samples from the ovarian carcinoma cell lines A2780s (parental wild type) and A2780cp (cisplatin cross-radio-resistant), before, right after, and 24 hours after irradiation to 10Gy. Methods: Spectra were acquired with a home built confocal Raman microscope in 3 distinct runs of six samples: unirradiated s&cp (control pair), then 0h and 24h after irradiation. The Raman spectra were noise reduced, then background subtracted with SMIRF algorithm. ∼35 cell spectra were collected from each sample in 1024 channels from 700cm-1 to 1618cm-1. The spectra were analyzed by regularized multiclass LDA. For feature reductionmore » the spectra were grouped into 3 overlapping group pairs: s-cp, 0Gy–10Gy0h and 0Gy10–Gy24h. The three features, the three differences of the mean spectra were mapped to the analysis sub-space by the inverse regularized covariance matrix. The batch effect noticeably confounded the dose and time effect. Results: To remove the batch effect, the 2+2=4D subspace extended by the covariance matrix of the means of the 0Gy control groups was subtracted from the spectra of each sample. Repeating the analysis on the spectra with the control group variability removed, the batch effect was dramatically reduced in the dose and time directions enabling sharp linear discrimination. The cell type classification also improved. Conclusions: We identified a efficient batch effect removal technique crucial to the applicability of Raman microscopy to radiosensitivity studies both on cell cultures and potential clinical diagnostic applications.« 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.

Increased sensitivity to age-related differences in brain functional connectivity during continuous multiple object tracking compared to resting-state.

PubMed

Dørum, Erlend S; Kaufmann, Tobias; Alnæs, Dag; Andreassen, Ole A; Richard, Geneviève; Kolskår, Knut K; Nordvik, Jan Egil; Westlye, Lars T

2017-03-01

Age-related differences in cognitive agility vary greatly between individuals and cognitive functions. This heterogeneity is partly mirrored in individual differences in brain network connectivity as revealed using resting-state functional magnetic resonance imaging (fMRI), suggesting potential imaging biomarkers for age-related cognitive decline. However, although convenient in its simplicity, the resting state is essentially an unconstrained paradigm with minimal experimental control. Here, based on the conception that the magnitude and characteristics of age-related differences in brain connectivity is dependent on cognitive context and effort, we tested the hypothesis that experimentally increasing cognitive load boosts the sensitivity to age and changes the discriminative network configurations. To this end, we obtained fMRI data from younger (n=25, mean age 24.16±5.11) and older (n=22, mean age 65.09±7.53) healthy adults during rest and two load levels of continuous multiple object tracking (MOT). Brain network nodes and their time-series were estimated using independent component analysis (ICA) and dual regression, and the edges in the brain networks were defined as the regularized partial temporal correlations between each of the node pairs at the individual level. Using machine learning based on a cross-validated regularized linear discriminant analysis (rLDA) we attempted to classify groups and cognitive load from the full set of edge-wise functional connectivity indices. While group classification using resting-state data was highly above chance (approx. 70% accuracy), functional connectivity (FC) obtained during MOT strongly increased classification performance, with 82% accuracy for the young and 95% accuracy for the old group at the highest load level. Further, machine learning revealed stronger differentiation between rest and task in young compared to older individuals, supporting the notion of network dedifferentiation in cognitive aging. Task-modulation in edgewise FC was primarily observed between attention- and sensorimotor networks; with decreased negative correlations between attention- and default mode networks in older adults. These results demonstrate that the magnitude and configuration of age-related differences in brain functional connectivity are partly dependent on cognitive context and load, which emphasizes the importance of assessing brain connectivity differences across a range of cognitive contexts beyond the resting-state. Copyright © 2017 Elsevier Inc. All rights reserved.

A pilot study to determine whether combinations of objectively measured activity parameters can be used to differentiate between mixed states, mania, and bipolar depression.

PubMed

Scott, Jan; Vaaler, Arne E; Fasmer, Ole Bernt; Morken, Gunnar; Krane-Gartiser, Karoline

2017-12-01

Until recently, actigraphy studies in bipolar disorders focused on sleep rather than daytime activity in mania or depression, and have failed to analyse mixed episodes separately. Furthermore, even those studies that assessed activity parameters reported only mean levels rather than complexity or predictability of activity. We identified cases presenting in one of three acute phases of bipolar disorder and examined whether the application of non-linear dynamic models to the description of objectively measured activity can be used to predict case classification. The sample comprised 34 adults who were hospitalized with an acute episode of mania (n = 16), bipolar depression (n = 12), or a mixed state (n = 6), who agreed to wear an actiwatch for a continuous period of 24 h. Mean level, variability, regularity, entropy, and predictability of activity were recorded for a defined 64-min active morning and active evening period. Discriminant function analysis was used to determine the combination of variables that best classified cases based on phase of illness. The model identified two discriminant functions: the first was statistically significant and correlated with intra-individual fluctuation in activity and regularity of activity (sample entropy) in the active morning period; the second correlated with several measures of activity from the evening period (e.g. Fourier analysis, autocorrelation, sample entropy). A classification table generated from both functions correctly classified 79% of all cases based on phase of illness (χ 2  = 36.21; df 4; p = 0.001). However, 42% of bipolar depression cases were misclassified as being in manic phase. The findings should be treated with caution as this was a small-scale pilot study and we did not control for prescribed treatments, medication adherence, etc. However, the insights gained should encourage more widespread adoption of statistical approaches to the classification of cases alongside the application of more sophisticated modelling of activity patterns. The difficulty of accurately classifying cases of bipolar depression requires further research, as it is unclear whether the lower prediction rate reflects weaknesses in a model based only on actigraphy data, or if it reflects clinical reality i.e. the possibility that there may be more than one subtype of bipolar depression.

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

Polycystic ovarian morphology and the diagnosis of polycystic ovary syndrome: redefining threshold levels for follicle count and serum anti-Müllerian hormone using cluster analysis.

PubMed

Lie Fong, S; Laven, J S E; Duhamel, A; Dewailly, D

2017-08-01

Can cluster analysis be used to differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with polycystic ovarian morphology (PCOM) in a non-subjective manner? Cluster analysis can be used to accurately and non-subjectively differentiate between normo-ovulatory women with normal ovaries and normo-ovulatory women with PCOM. Currently, PCOM is diagnosed using a fixed threshold level, i.e. 12 or more follicles per ovary, and is one of the diagnostic criteria of polycystic ovary syndrome (PCOS). However, PCOM is also encountered in normo-ovulatory women, suggesting that it could just represent a normal variant. On the other hand, recent studies have shown subtle endocrine abnormalities in women with isolated PCOM that resemble those found in women with PCOS. Because of the strong correlation between anti-Müllerian hormone (AMH) and follicle number, a high serum AMH level has been proposed as a surrogate marker for PCOM and could, therefore, be integrated in the diagnostic classifications for PCOS. This was a retrospective observational cohort study. Original cohorts had been recruited for previous studies between 1998 and 2010. Two hundred ninety-seven regularly cycling women and 700 women with PCOS were eligible for inclusion. Cluster analysis was performed in 297 regularly cycling women. After exclusion of 'PCOM' clusters, each 'non-PCOM' cluster (young, n = 118 and old, n = 100) was included in the construction of a receiver operating characteristics curve to test the diagnostic performance of follicle number per ovary (FNPO) and serum AMH in discriminating similarly aged full-blown PCOS patients (n = 411 and 237, respectively) from normal regularly cycling non-PCOM women. The optimal number of clusters was four; age was the most important classifying variable, followed by the FNPO and serum AMH. Two distinct clusters of normo-ovulatory women with PCOM were isolated and differed solely by age, i.e. 'young' and 'old'. Both 'PCOM' clusters had their similarly aged counterpart of 'non-PCOM' clusters. Likewise, two clusters comprised women younger than 30 years, with (n = 28, 'PCOM regularly cycling women') or without (n = 118, 'normal regularly cycling women') features of PCOM (increased FNPO and/or serum AMH). The two other clusters in older women could be labelled 'normal regularly cycling women' or 'PCOM regularly cycling women' (n = 100 and 51, respectively). The prevalence of PCOM was significantly greater in old than in young regularly cycling women controls. In the young population, after exclusion of the 'PCOM regularly cycling women', the diagnostic performance of AMH, expressed by area under the curve (AUC) (AUC = 0.903; CI (0.876-0.930)) to differentiate PCOS women from normal regularly cycling women was similar to that using the FNPO (AUC = 0.915, CI (0.891-0.940)) (P = 0.25), confirming results from earlier studies. In the old population, the diagnostic performance of AMH was greater than that of FNPO (AUCs = 0.948 (0.927-0.970) vs 0.874 (0.836-0.912), respectively, P = 0.00035). Cut-off levels of AMH and antral follicle count distinguishing regularly cycling non-PCOM women from PCOS women were higher in young women than in older women. Data of normal women were obtained from earlier studies, aiming to measure normal endocrine values. Apparently, the strong effect of age in cluster analysis revealed a dichotomy in the age distribution among the cohort of regularly cycling women included. This was involuntary since in none of the original studies, eligibility was limited by age and there was considerable overlap in age ranges of the cohorts. Transvaginal ultrasound was performed using a 6.5-8 mHz probe and our data confirm that this threshold level for FNPO is still valid if using such probe frequencies, although the use of devices with a maximum frequency lower than 8 mHz has become obsolete. Obviously, newer ultrasound scanner using higher transducer frequency will facilitate the detection of more follicles. Our data support the use of AMH as a surrogate for ultrasound to define PCOM, which is one of the three items of the Rotterdam classification. They also show that age should be taken into account to define the optimal threshold. The fact that the prevalence of PCOM was increased in the older regularly cycling women, may be due to 'attenuated' PCOS, a phenomenon that has been described in ageing women with PCOS. These women might have had anovulatory cycles in the past and have become ovulatory with increasing age, and were, therefore, eligible for this study. However, since most women included at older age have had spontaneous pregnancies in the past, PCOM at older age may be associated with a subclinical form of PCOS, which may also be present in young regularly cycling women. No funding was received for this study. J.S.E.L. has received grants and support from Ferring, MSD, Organon, Merck-Serono, Schering Plough and Serono during recruitment and analysis of data for this study. S.L.F., A.D. and D.D. do not have any conflict of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Phase stability analysis of chirp evoked auditory brainstem responses by Gabor frame operators.

PubMed

Corona-Strauss, Farah I; Delb, Wolfgang; Schick, Bernhard; Strauss, Daniel J

2009-12-01

We have recently shown that click evoked auditory brainstem responses (ABRs) can be efficiently processed using a novelty detection paradigm. Here, ABRs as a large-scale reflection of a stimulus locked neuronal group synchronization at the brainstem level are detected as novel instance-novel as compared to the spontaneous activity which does not exhibit a regular stimulus locked synchronization. In this paper we propose for the first time Gabor frame operators as an efficient feature extraction technique for ABR single sweep sequences that is in line with this paradigm. In particular, we use this decomposition technique to derive the Gabor frame phase stability (GFPS) of sweep sequences of click and chirp evoked ABRs. We show that the GFPS of chirp evoked ABRs provides a stable discrimination of the spontaneous activity from stimulations above the hearing threshold with a small number of sweeps, even at low stimulation intensities. It is concluded that the GFPS analysis represents a robust feature extraction method for ABR single sweep sequences. Further studies are necessary to evaluate the value of the presented approach for clinical applications.

Differences in game-related statistics of basketball performance by game location for men's winning and losing teams.

PubMed

Gómez, Miguel A; Lorenzo, Alberto; Barakat, Rubén; Ortega, Enrique; Palao, José M

2008-02-01

The aim of the present study was to identify game-related statistics that differentiate winning and losing teams according to game location. The sample included 306 games of the 2004-2005 regular season of the Spanish professional men's league (ACB League). The independent variables were game location (home or away) and game result (win or loss). The game-related statistics registered were free throws (successful and unsuccessful), 2- and 3-point field goals (successful and unsuccessful), offensive and defensive rebounds, blocks, assists, fouls, steals, and turnovers. Descriptive and inferential analyses were done (one-way analysis of variance and discriminate analysis). The multivariate analysis showed that winning teams differ from losing teams in defensive rebounds (SC = .42) and in assists (SC = .38). Similarly, winning teams differ from losing teams when they play at home in defensive rebounds (SC = .40) and in assists (SC = .41). On the other hand, winning teams differ from losing teams when they play away in defensive rebounds (SC = .44), assists (SC = .30), successful 2-point field goals (SC = .31), and unsuccessful 3-point field goals (SC = -.35). Defensive rebounds and assists were the only game-related statistics common to all three analyses.

Application of gas chromatography/flame ionization detector-based metabolite fingerprinting for authentication of Asian palm civet coffee (Kopi Luwak).

PubMed

Jumhawan, Udi; Putri, Sastia Prama; Yusianto; Bamba, Takeshi; Fukusaki, Eiichiro

2015-11-01

Development of authenticity screening for Asian palm civet coffee, the world-renowned priciest coffee, was previously reported using metabolite profiling through gas chromatography/mass spectrometry (GC/MS). However, a major drawback of this approach is the high cost of the instrument and maintenance. Therefore, an alternative method is needed for quality and authenticity evaluation of civet coffee. A rapid, reliable and cost-effective analysis employing a universal detector, GC coupled with flame ionization detector (FID), and metabolite fingerprinting has been established for discrimination analysis of 37 commercial and non-commercial coffee beans extracts. gas chromatography/flame ionization detector (GC/FID) provided higher sensitivity over a similar range of detected compounds than GC/MS. In combination with multivariate analysis, GC/FID could successfully reproduce quality prediction from GC/MS for differentiation of commercial civet coffee, regular coffee and coffee blend with 50 wt % civet coffee content without prior metabolite details. Our study demonstrated that GC/FID-based metabolite fingerprinting can be effectively actualized as an alternative method for coffee authenticity screening in industries. Copyright © 2015. Published by Elsevier B.V.

Auditory Stimulus Processing and Task Learning Are Adequate in Dyslexia, but Benefits From Regularities Are Reduced.

PubMed

Daikhin, Luba; Raviv, Ofri; Ahissar, Merav

2017-02-01

The reading deficit for people with dyslexia is typically associated with linguistic, memory, and perceptual-discrimination difficulties, whose relation to reading impairment is disputed. We proposed that automatic detection and usage of serial sound regularities for individuals with dyslexia is impaired (anchoring deficit hypothesis), leading to the formation of less reliable sound predictions. Agus, Carrión-Castillo, Pressnitzer, and Ramus, (2014) reported seemingly contradictory evidence by showing similar performance by participants with and without dyslexia in a demanding auditory task that contained task-relevant regularities. To carefully assess the sensitivity of participants with dyslexia to regularities of this task, we replicated their study. Thirty participants with and 24 without dyslexia performed the replicated task. On each trial, a 1-s noise stimulus was presented. Participants had to decide whether the stimulus contained repetitions (was constructed from a 0.5-s noise segment repeated twice) or not. It is implicit in this structure that some of the stimuli with repetitions were themselves repeated across trials. We measured the ability to detect within-noise repetitions and the sensitivity to cross-trial repetitions of the same noise stimuli. We replicated the finding of similar mean performance. However, individuals with dyslexia were less sensitive to the cross-trial repetition of noise stimuli and tended to be more sensitive to repetitions in novel noise stimuli. These findings indicate that online auditory processing for individuals with dyslexia is adequate but their implicit retention and usage of sound regularities is indeed impaired.

Clustered Regularly Interspaced Short Palindromic Repeats Are emm Type-Specific in Highly Prevalent Group A Streptococci

PubMed Central

Zheng, Po-Xing; Chan, Yuen-Chi; Chiou, Chien-Shun; Chiang-Ni, Chuan; Wang, Shu-Ying; Tsai, Pei-Jane; Chuang, Woei-Jer; Lin, Yee-Shin; Liu, Ching-Chuan; Wu, Jiunn-Jong

2015-01-01

Clustered regularly interspaced short palindromic repeats (CRISPR) are the bacterial adaptive immune system against foreign nucleic acids. Given the variable nature of CRISPR, it could be a good marker for molecular epidemiology. Group A streptococcus is one of the major human pathogens. It has two CRISPR loci, including CRISPR01 and CRISPR02. The aim of this study was to analyze the distribution of CRISPR-associated gene cassettes (cas) and CRISPR arrays in highly prevalent emm types. The cas cassette and CRISPR array in two CRISPR loci were analyzed in a total of 332 strains, including emm1, emm3, emm4, emm12, and emm28 strains. The CRISPR type was defined by the spacer content of each CRISPR array. All strains had at least one cas cassette or CRISPR array. More than 90% of the spacers were found in one emm type, specifically. Comparing the consistency between emm and CRISPR types by Simpson’s index of diversity and the adjusted Wallace coefficient, CRISPR01 type was concordant to emm type, and CRISPR02 showed unidirectional congruence to emm type, suggesting that at least for the majority of isolates causing infection in high income countries, the emm type can be inferred from CRISPR analysis, which can further discriminate isolates sharing the same emm type. PMID:26710228

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.

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

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.

Robust Statistics and Regularization for Feature Extraction and UXO Discrimination

DTIC Science & Technology

2011-07-01

July 11, 2011 real data we find that this technique has an improved probability of finding all ordnance in a test data set, relative to previously...many sites. Tests on larger data sets should still be carried out. In previous work we considered a bootstrapping approach to selecting the operating...Marginalizing over x we obtain the probability that the ith order statistic in the test data belongs to the T class (55) P (T |x(i)) = ∞∫ −∞ P (T |x)p(x

Plausibility assessment of a 2-state self-paced mental task-based BCI using the no-control performance analysis.

PubMed

Faradji, Farhad; Ward, Rabab K; Birch, Gary E

2009-06-15

The feasibility of having a self-paced brain-computer interface (BCI) based on mental tasks is investigated. The EEG signals of four subjects performing five mental tasks each are used in the design of a 2-state self-paced BCI. The output of the BCI should only be activated when the subject performs a specific mental task and should remain inactive otherwise. For each subject and each task, the feature coefficient and the classifier that yield the best performance are selected, using the autoregressive coefficients as the features. The classifier with a zero false positive rate and the highest true positive rate is selected as the best classifier. The classifiers tested include: linear discriminant analysis, quadratic discriminant analysis, Mahalanobis discriminant analysis, support vector machine, and radial basis function neural network. The results show that: (1) some classifiers obtained the desired zero false positive rate; (2) the linear discriminant analysis classifier does not yield acceptable performance; (3) the quadratic discriminant analysis classifier outperforms the Mahalanobis discriminant analysis classifier and performs almost as well as the radial basis function neural network; and (4) the support vector machine classifier has the highest true positive rates but unfortunately has nonzero false positive rates in most cases.

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.

[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…

Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning.

PubMed

Jing, Xiao-Yuan; Zhu, Xiaoke; Wu, Fei; Hu, Ruimin; You, Xinge; Wang, Yunhong; Feng, Hui; Yang, Jing-Yu

2017-03-01

Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high resolution (HR), while probe images are usually low resolution (LR) in the identification scenarios with large variation of illumination, weather, or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD 2 L) approach for SR person re-identification task. With the HR and LR dictionary pair and mapping matrices learned from the features of HR and LR training images, SLD 2 L can convert the features of the LR probe images into HR features. To ensure that the converted features have favorable discriminative capability and the learned dictionaries can well characterize intrinsic feature spaces of the HR and LR images, we design a discriminant term and a low-rank regularization term for SLD 2 L. Moreover, considering that low resolution results in different degrees of loss for different types of visual appearance features, we propose a multi-view SLD 2 L (MVSLD 2 L) approach, which can learn the type-specific dictionary pair and mappings for each type of feature. Experimental results on multiple publicly available data sets demonstrate the effectiveness of our proposed approaches for the SR person re-identification task.

SPEPlip: the detection of signal peptide and lipoprotein cleavage sites.

PubMed

Fariselli, Piero; Finocchiaro, Giacomo; Casadio, Rita

2003-12-12

SPEPlip is a neural network-based method, trained and tested on a set of experimentally derived signal peptides from eukaryotes and prokaryotes. SPEPlip identifies the presence of sorting signals and predicts their cleavage sites. The accuracy in cross-validation is similar to that of other available programs: the rate of false positives is 4 and 6%, for prokaryotes and eukaryotes respectively and that of false negatives is 3% in both cases. When a set of 409 prokaryotic lipoproteins is predicted, SPEPlip predicts 97% of the chains in the signal peptide class. However, by integrating SPEPlip with a regular expression search utility based on the PROSITE pattern, we can successfully discriminate signal peptide-containing chains from lipoproteins. We propose the method for detecting and discriminating signal peptides containing chains and lipoproteins. It can be accessed through the web page at http://gpcr.biocomp.unibo.it/predictors/

DEVELOPMENT AND PSYCHOMETRIC TESTING OF A MULTIDIMENSIONAL INSTRUMENT OF PERCEIVED DISCRIMINATION AMONG AFRICAN AMERICANS IN THE JACKSON HEART STUDY

PubMed Central

Sims, Mario; Wyatt, Sharon B.; Gutierrez, Mary Lou; Taylor, Herman A.; Williams, David R.

2009-01-01

Objective Assessing the discrimination-health disparities hypothesis requires psychometrically sound, multidimensional measures of discrimination. Among the available discrimination measures, few are multidimensional and none have adequate psychometric testing in a large, African American sample. We report the development and psychometric testing of the multidimensional Jackson Heart Study Discrimination (JHSDIS) Instrument. Methods A multidimensional measure assessing the occurrence, frequency, attribution, and coping responses to perceived everyday and lifetime discrimination; lifetime burden of discrimination; and effect of skin color was developed and tested in the 5302-member cohort of the Jackson Heart Study. Internal consistency was calculated by using Cronbach α. coefficient. Confirmatory factor analysis established the dimensions, and intercorrelation coefficients assessed the discriminant validity of the instrument. Setting Tri-county area of the Jackson, MS metropolitan statistical area. Results The JHSDIS was psychometrically sound (overall α=.78, .84 and .77, respectively, for the everyday and lifetime subscales). Confirmatory factor analysis yielded 11 factors, which confirmed the a priori dimensions represented. Conclusions The JHSDIS combined three scales into a single multidimensional instrument with good psychometric properties in a large sample of African Americans. This analysis lays the foundation for using this instrument in research that will examine the association between perceived discrimination and CVD among African Americans. PMID:19341164

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.

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.

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.

Negative muon chemistry: the quantum muon effect and the finite nuclear mass effect.

PubMed

Posada, Edwin; Moncada, Félix; Reyes, Andrés

2014-10-09

The any-particle molecular orbital method at the full configuration interaction level has been employed to study atoms in which one electron has been replaced by a negative muon. In this approach electrons and muons are described as quantum waves. A scheme has been proposed to discriminate nuclear mass and quantum muon effects on chemical properties of muonic and regular atoms. This study reveals that the differences in the ionization potentials of isoelectronic muonic atoms and regular atoms are of the order of millielectronvolts. For the valence ionizations of muonic helium and muonic lithium the nuclear mass effects are more important. On the other hand, for 1s ionizations of muonic atoms heavier than beryllium, the quantum muon effects are more important. In addition, this study presents an assessment of the nuclear mass and quantum muon effects on the barrier of Heμ + H2 reaction.

Boosting CNN performance for lung texture classification using connected filtering

NASA Astrophysics Data System (ADS)

Tarando, Sebastián. Roberto; Fetita, Catalin; Kim, Young-Wouk; Cho, Hyoun; Brillet, Pierre-Yves

2018-02-01

Infiltrative lung diseases describe a large group of irreversible lung disorders requiring regular follow-up with CT imaging. Quantifying the evolution of the patient status imposes the development of automated classification tools for lung texture. This paper presents an original image pre-processing framework based on locally connected filtering applied in multiresolution, which helps improving the learning process and boost the performance of CNN for lung texture classification. By removing the dense vascular network from images used by the CNN for lung classification, locally connected filters provide a better discrimination between different lung patterns and help regularizing the classification output. The approach was tested in a preliminary evaluation on a 10 patient database of various lung pathologies, showing an increase of 10% in true positive rate (on average for all the cases) with respect to the state of the art cascade of CNNs for this task.

[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...

Advanced algorithms for radiographic material discrimination and inspection system design

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

Gilbert, Andrew J.; McDonald, Benjamin S.; Deinert, Mark R.

X-ray and neutron radiography are powerful tools for non-invasively inspecting the interior of objects. Materials can be discriminated by noting how the radiographic signal changes with variations in the input spectrum or inspection mode. However, current methods are limited in their ability to differentiate when multiple materials are present, especially within large and complex objects. With X-ray radiography, the inability to distinguish materials of a similar atomic number is especially problematic. To overcome these critical limitations, we augmented our existing inverse problem framework with two important expansions: 1) adapting the previous methodology for use with multi-modal radiography and energy-integrating detectors,more » and 2) applying the Cramer-Rao lower bound to select an optimal set of inspection modes for a given application a priori. Adding these expanded capabilities to our algorithmic framework with adaptive regularization, we observed improved discrimination between high-Z materials, specifically plutonium and tungsten. The combined system can estimate plutonium mass within our simulated system to within 1%. Three types of inspection modes were modeled: multi-endpoint X-ray radiography alone; in combination with neutron radiography using deuterium-deuterium (DD); or in combination with neutron radiography using deuterium-tritium (DT) sources.« less

Discriminative Dictionary Learning With Two-Level Low Rank and Group Sparse Decomposition for Image Classification.

PubMed

Wen, Zaidao; Hou, Zaidao; Jiao, Licheng

2017-11-01

Discriminative dictionary learning (DDL) framework has been widely used in image classification which aims to learn some class-specific feature vectors as well as a representative dictionary according to a set of labeled training samples. However, interclass similarities and intraclass variances among input samples and learned features will generally weaken the representability of dictionary and the discrimination of feature vectors so as to degrade the classification performance. Therefore, how to explicitly represent them becomes an important issue. In this paper, we present a novel DDL framework with two-level low rank and group sparse decomposition model. In the first level, we learn a class-shared and several class-specific dictionaries, where a low rank and a group sparse regularization are, respectively, imposed on the corresponding feature matrices. In the second level, the class-specific feature matrix will be further decomposed into a low rank and a sparse matrix so that intraclass variances can be separated to concentrate the corresponding feature vectors. Extensive experimental results demonstrate the effectiveness of our model. Compared with the other state-of-the-arts on several popular image databases, our model can achieve a competitive or better performance in terms of the classification accuracy.

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.

Rapid identification of pearl powder from Hyriopsis cumingii by Tri-step infrared spectroscopy combined with computer vision technology

NASA Astrophysics Data System (ADS)

Liu, Siqi; Wei, Wei; Bai, Zhiyi; Wang, Xichang; Li, Xiaohong; Wang, Chuanxian; Liu, Xia; Liu, Yuan; Xu, Changhua

2018-01-01

Pearl powder, an important raw material in cosmetics and Chinese patent medicines, is commonly uneven in quality and frequently adulterated with low-cost shell powder in the market. The aim of this study is to establish an adequate approach based on Tri-step infrared spectroscopy with enhancing resolution combined with chemometrics for qualitative identification of pearl powder originated from three different quality grades of pearls and quantitative prediction of the proportions of shell powder adulterated in pearl powder. Additionally, computer vision technology (E-eyes) can investigate the color difference among different pearl powders and make it traceable to the pearl quality trait-visual color categories. Though the different grades of pearl powder or adulterated pearl powder have almost identical IR spectra, SD-IR peak intensity at about 861 cm- 1 (v2 band) exhibited regular enhancement with the increasing quality grade of pearls, while the 1082 cm- 1 (v1 band), 712 cm- 1 and 699 cm- 1 (v4 band) were just the reverse. Contrastly, only the peak intensity at 862 cm- 1 was enhanced regularly with the increasing concentration of shell powder. Thus, the bands in the ranges of (1550-1350 cm- 1, 730-680 cm- 1) and (830-880 cm- 1, 690-725 cm- 1) could be exclusive ranges to discriminate three distinct pearl powders and identify adulteration, respectively. For massive sample analysis, a qualitative classification model and a quantitative prediction model based on IR spectra was established successfully by principal component analysis (PCA) and partial least squares (PLS), respectively. The developed method demonstrated great potential for pearl powder quality control and authenticity identification in a direct, holistic manner.

Rapid identification of pearl powder from Hyriopsis cumingii by Tri-step infrared spectroscopy combined with computer vision technology.

PubMed

Liu, Siqi; Wei, Wei; Bai, Zhiyi; Wang, Xichang; Li, Xiaohong; Wang, Chuanxian; Liu, Xia; Liu, Yuan; Xu, Changhua

2018-01-15

Pearl powder, an important raw material in cosmetics and Chinese patent medicines, is commonly uneven in quality and frequently adulterated with low-cost shell powder in the market. The aim of this study is to establish an adequate approach based on Tri-step infrared spectroscopy with enhancing resolution combined with chemometrics for qualitative identification of pearl powder originated from three different quality grades of pearls and quantitative prediction of the proportions of shell powder adulterated in pearl powder. Additionally, computer vision technology (E-eyes) can investigate the color difference among different pearl powders and make it traceable to the pearl quality trait-visual color categories. Though the different grades of pearl powder or adulterated pearl powder have almost identical IR spectra, SD-IR peak intensity at about 861cm -1 (v 2 band) exhibited regular enhancement with the increasing quality grade of pearls, while the 1082cm -1 (v 1 band), 712cm -1 and 699cm -1 (v 4 band) were just the reverse. Contrastly, only the peak intensity at 862cm -1 was enhanced regularly with the increasing concentration of shell powder. Thus, the bands in the ranges of (1550-1350cm -1 , 730-680cm -1 ) and (830-880cm -1 , 690-725cm -1 ) could be exclusive ranges to discriminate three distinct pearl powders and identify adulteration, respectively. For massive sample analysis, a qualitative classification model and a quantitative prediction model based on IR spectra was established successfully by principal component analysis (PCA) and partial least squares (PLS), respectively. The developed method demonstrated great potential for pearl powder quality control and authenticity identification in a direct, holistic manner. Copyright © 2017. Published by Elsevier B.V.

A stimulus-control account of regulated drug intake in rats.

PubMed

Panlilio, Leigh V; Thorndike, Eric B; Schindler, Charles W

2008-02-01

Patterns of drug self-administration are often highly regular, with a consistent pause after each self-injection. This pausing might occur because the animal has learned that additional injections are not reinforcing once the drug effect has reached a certain level, possibly due to the reinforcement system reaching full capacity. Thus, interoceptive effects of the drug might function as a discriminative stimulus, signaling when additional drug will be reinforcing and when it will not. This hypothetical stimulus control aspect of drug self-administration was emulated using a schedule of food reinforcement. Rats' nose-poke responses produced food only when a cue light was present. No drug was administered at any time. However, the state of the light stimulus was determined by calculating what the whole-body drug level would have been if each response in the session had produced a drug injection. The light was only presented while this virtual drug level was below a specific threshold. A range of doses of cocaine and remifentanil were emulated using parameters based on previous self-administration experiments. Response patterns were highly regular, dose-dependent, and remarkably similar to actual drug self-administration. This similarity suggests that the emulation schedule may provide a reasonable model of the contingencies inherent in drug reinforcement. Thus, these results support a stimulus control account of regulated drug intake in which rats learn to discriminate when the level of drug effect has fallen to a point where another self-injection will be reinforcing.

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).

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.

Joint image reconstruction method with correlative multi-channel prior for x-ray spectral computed tomography

NASA Astrophysics Data System (ADS)

Kazantsev, Daniil; Jørgensen, Jakob S.; Andersen, Martin S.; Lionheart, William R. B.; Lee, Peter D.; Withers, Philip J.

2018-06-01

Rapid developments in photon-counting and energy-discriminating detectors have the potential to provide an additional spectral dimension to conventional x-ray grayscale imaging. Reconstructed spectroscopic tomographic data can be used to distinguish individual materials by characteristic absorption peaks. The acquired energy-binned data, however, suffer from low signal-to-noise ratio, acquisition artifacts, and frequently angular undersampled conditions. New regularized iterative reconstruction methods have the potential to produce higher quality images and since energy channels are mutually correlated it can be advantageous to exploit this additional knowledge. In this paper, we propose a novel method which jointly reconstructs all energy channels while imposing a strong structural correlation. The core of the proposed algorithm is to employ a variational framework of parallel level sets to encourage joint smoothing directions. In particular, the method selects reference channels from which to propagate structure in an adaptive and stochastic way while preferring channels with a high data signal-to-noise ratio. The method is compared with current state-of-the-art multi-channel reconstruction techniques including channel-wise total variation and correlative total nuclear variation regularization. Realistic simulation experiments demonstrate the performance improvements achievable by using correlative regularization methods.

Constrained Low-Rank Learning Using Least Squares-Based Regularization.

PubMed

Li, Ping; Yu, Jun; Wang, Meng; Zhang, Luming; Cai, Deng; Li, Xuelong

2017-12-01

Low-rank learning has attracted much attention recently due to its efficacy in a rich variety of real-world tasks, e.g., subspace segmentation and image categorization. Most low-rank methods are incapable of capturing low-dimensional subspace for supervised learning tasks, e.g., classification and regression. This paper aims to learn both the discriminant low-rank representation (LRR) and the robust projecting subspace in a supervised manner. To achieve this goal, we cast the problem into a constrained rank minimization framework by adopting the least squares regularization. Naturally, the data label structure tends to resemble that of the corresponding low-dimensional representation, which is derived from the robust subspace projection of clean data by low-rank learning. Moreover, the low-dimensional representation of original data can be paired with some informative structure by imposing an appropriate constraint, e.g., Laplacian regularizer. Therefore, we propose a novel constrained LRR method. The objective function is formulated as a constrained nuclear norm minimization problem, which can be solved by the inexact augmented Lagrange multiplier algorithm. Extensive experiments on image classification, human pose estimation, and robust face recovery have confirmed the superiority of our method.

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.

Automated processing of the single-lead electrocardiogram for the detection of obstructive sleep apnoea.

PubMed

de Chazal, Philip; Heneghan, Conor; Sheridan, Elaine; Reilly, Richard; Nolan, Philip; O'Malley, Mark

2003-06-01

A method for the automatic processing of the electrocardiogram (ECG) for the detection of obstructive apnoea is presented. The method screens nighttime single-lead ECG recordings for the presence of major sleep apnoea and provides a minute-by-minute analysis of disordered breathing. A large independently validated database of 70 ECG recordings acquired from normal subjects and subjects with obstructive and mixed sleep apnoea, each of approximately eight hours in duration, was used throughout the study. Thirty-five of these recordings were used for training and 35 retained for independent testing. A wide variety of features based on heartbeat intervals and an ECG-derived respiratory signal were considered. Classifiers based on linear and quadratic discriminants were compared. Feature selection and regularization of classifier parameters were used to optimize classifier performance. Results show that the normal recordings could be separated from the apnoea recordings with a 100% success rate and a minute-by-minute classification accuracy of over 90% is achievable.

Influence of red wine fermentation oenological additives on inoculated strain implantation.

PubMed

Duarte, Filomena L; Alves, Ana Claudia; Alemão, Maria Filomena; Baleiras-Couto, M Margarida

2013-06-01

Pure selected cultures of Saccharomyces cerevisiae starters are regularly used in the wine industry. A survey of S. cerevisiae populations during red wine fermentations was performed in order to evaluate the influence of oenological additives on the implantation of the inoculated strain. Pilot scale fermentations (500 L) were conducted with active dry yeast (ADY) and other commercial oenological additives, namely two commercial fermentation activators and two commercial tannins. Six microsatellite markers were used to type S. cerevisiae strains. The methodology proved to be very discriminating as a great diversity of wild strains (48 genotypes) was detected. Statistical analysis confirmed a high detection of the inoculated commercial strain, and for half the samples an effective implantation of ADY (over 80 %) was achieved. At late fermentation time, ADY strain implantation in fermentations conducted with commercial additives was lower than in the control. These results question the efficacy of ADY addition in the presence of other additives, indicating that further studies are needed to improve knowledge on oenological additives' use.

Socio-Structural Barriers, Protective Factors, and HIV Risk Among Central-Asian Female Migrants in Moscow

PubMed Central

Zabrocki, Christopher; Weine, Stevan; Chen, Stephanie; Brajkovic, Ivana; Bahromov, Mahbat; Loue, Sana; Jonbekov, Jonbek; Shoakova, Farzona

2013-01-01

Objective This study aimed to build formative knowledge on socio-structural barriers, protective factors, and HIV sexual risk amongst Central-Asian female migrants in Moscow. Methods Data collection included ethnographic interviews in Moscow with a purposive sample of 30 unmarried female migrants, 15 from Kyrgyzstan and 15 from Tajikistan. Results Study participants reported difficulties with acquiring documents for legal status, financial insecurity, discrimination, sexual harassment, and lack of support. Based on analysis of the cases, one pathway linked lack of legal documentation and instrumental support with elevated sexual risk. Another pathways linked traditional cultural attitudes with both no and moderate sexual risk. Conclusion Future HIV prevention efforts with Central Asian female migrants in Moscow should be multilevel and include: increasing HIV and prevention knowledge and skills, promoting condom use with regular partners, identifying and supporting cultural attitudes that protect against HIV sexual risk behaviors, facilitating legal status, building community support, and increasing economic options. PMID:25360392

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.

Quality of Life of Transgender Women From China and Associated Factors: A Cross-Sectional Study.

PubMed

Yang, Xiaoshi; Zhao, Lina; Wang, Lie; Hao, Chun; Gu, Yuan; Song, Wei; Zhao, Qun; Wang, Xiaoli

2016-06-01

Transgender women are exposed to stressful situations such as gender transition and transition-related discrimination because of their limited acceptance by the general population and inadequate government-supplied resources, which can compromise their quality of life (QOL). However, there is a paucity of research on the QOL of transgender women from China. To assess the QOL of transgender women from China and explore its associated factors. A cross-sectional study was performed by convenience sampling in Shenyang, China from January 2014 to July 2014. This sample consisted of 209 transgender women. The women were interviewed face-to-face to assess their QOL and related factors using the 36-item Short-Form Health Survey, the Adult Dispositional (Trait) Hope Scale, and the EGO Resilience Scale. Response scores were calculated based on a questionnaire design. Hierarchical multiple regression analysis was performed to explore factors associated with QOL. Transgender women who used hormone therapy reported significantly lower levels of the physical component summary (PCS) and the mental component summary (MCS) compared with those who did not (P < .05). Hierarchical multiple regression analysis showed that of the 23 independent variables, 8 were significantly associated with the PCS and 9 were significantly associated with the MCS. The PCS was significantly and negatively associated with age and being chased or insulted by law enforcement officials. The PCS was positively associated with not using hormone therapy, having no casual partners, less discrimination from friends, knowledge of HIV prevention, hope, and resilience. Educational level and being chased or insulted by law enforcement officials were negatively associated with the MCS, whereas not using hormone therapy, having no regular partners or casual partners, less discrimination from friends, less social discrimination, knowledge of HIV prevention, and hope were positively associated with the MCS. Chinese transgender women reported high levels of physical QOL but low levels of mental QOL. Their mental QOL was more pronounced than their physical QOL. Transition status and sexual partnership played the most important roles in physical and mental health. Furthermore, mental QOL was best predicted by assessing positive capabilities, such as levels of hope. Future interventions should focus on recognizing transition status and identifying risky sexual partnerships, especially for the casual partners involved in these partnerships. In addition, positive capabilities are needed to ameliorate the negative impact of transition on QOL in Chinese transgender women. Copyright © 2016 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

Everyday Discrimination and Mood and Substance Use Disorders: A Latent Profile Analysis with African Americans and Caribbean Blacks

PubMed Central

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

2016-01-01

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. PMID:25254321

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.

Can Birds Perceive Rhythmic Patterns? A Review and Experiments on a Songbird and a Parrot Species

PubMed Central

ten Cate, Carel; Spierings, Michelle; Hubert, Jeroen; Honing, Henkjan

2016-01-01

While humans can easily entrain their behavior with the beat in music, this ability is rare among animals. Yet, comparative studies in non-human species are needed if we want to understand how and why this ability evolved. Entrainment requires two abilities: (1) recognizing the regularity in the auditory stimulus and (2) the ability to adjust the own motor output to the perceived pattern. It has been suggested that beat perception and entrainment are linked to the ability for vocal learning. The presence of some bird species showing beat induction, and also the existence of vocal learning as well as vocal non-learning bird taxa, make them relevant models for comparative research on rhythm perception and its link to vocal learning. Also, some bird vocalizations show strong regularity in rhythmic structure, suggesting that birds might perceive rhythmic structures. In this paper we review the available experimental evidence for the perception of regularity and rhythms by birds, like the ability to distinguish regular from irregular stimuli over tempo transformations and report data from new experiments. While some species show a limited ability to detect regularity, most evidence suggests that birds attend primarily to absolute and not relative timing of patterns and to local features of stimuli. We conclude that, apart from some large parrot species, there is limited evidence for beat and regularity perception among birds and that the link to vocal learning is unclear. We next report the new experiments in which zebra finches and budgerigars (both vocal learners) were first trained to distinguish a regular from an irregular pattern of beats and then tested on various tempo transformations of these stimuli. The results showed that both species reduced the discrimination after tempo transformations. This suggests that, as was found in earlier studies, they attended mainly to local temporal features of the stimuli, and not to their overall regularity. However, some individuals of both species showed an additional sensitivity to the more global pattern if some local features were left unchanged. Altogether our study indicates both between and within species variation, in which birds attend to a mixture of local and to global rhythmic features. PMID:27242635

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.

Intellectual disability and bleeding diathesis due to deficient CMP--sialic acid transport.

PubMed

Mohamed, Miski; Ashikov, Angel; Guillard, Mailys; Robben, Joris H; Schmidt, Samuel; van den Heuvel, B; de Brouwer, Arjan P M; Gerardy-Schahn, Rita; Deen, Peter M T; Wevers, Ron A; Lefeber, Dirk J; Morava, Eva

2013-08-13

To identify the underlying genetic defect in a patient with intellectual disability, seizures, ataxia, macrothrombocytopenia, renal and cardiac involvement, and abnormal protein glycosylation. Genetic studies involved homozygosity mapping by 250K single nucleotide polymorphism array and SLC35A1 sequencing. Functional studies included biochemical assays for N-glycosylation and mucin-type O-glycosylation and SLC35A1-encoded cytidine 5'-monophosphosialic acid (CMP-sialic acid) transport after heterologous expression in yeast. We performed biochemical analysis and found combined N- and O-glycosylation abnormalities and specific reduction in sialylation in this patient. Homozygosity mapping revealed homozygosity for the CMP-sialic acid transporter SLC35A1. Mutation analysis identified a homozygous c.303G > C (p.Gln101His) missense mutation that was heterozygous in both parents. Functional analysis of mutant SLC35A1 showed normal Golgi localization but 50% reduction in transport activity of CMP-sialic acid in vitro. We confirm an autosomal recessive, generalized sialylation defect due to mutations in SLC35A1. The primary neurologic presentation consisting of ataxia, intellectual disability, and seizures, in combination with bleeding diathesis and proteinuria, is discriminative from a previous case described with deficient sialic acid transporter. Our study underlines the importance of sialylation for normal CNS development and regular organ function.

Decoding of top-down cognitive processing for SSVEP-controlled BMI

PubMed Central

Min, Byoung-Kyong; Dähne, Sven; Ahn, Min-Hee; Noh, Yung-Kyun; Müller, Klaus-Robert

2016-01-01

We present a fast and accurate non-invasive brain-machine interface (BMI) based on demodulating steady-state visual evoked potentials (SSVEPs) in electroencephalography (EEG). Our study reports an SSVEP-BMI that, for the first time, decodes primarily based on top-down and not bottom-up visual information processing. The experimental setup presents a grid-shaped flickering line array that the participants observe while intentionally attending to a subset of flickering lines representing the shape of a letter. While the flickering pixels stimulate the participant’s visual cortex uniformly with equal probability, the participant’s intention groups the strokes and thus perceives a ‘letter Gestalt’. We observed decoding accuracy of 35.81% (up to 65.83%) with a regularized linear discriminant analysis; on average 2.05-fold, and up to 3.77-fold greater than chance levels in multi-class classification. Compared to the EEG signals, an electrooculogram (EOG) did not significantly contribute to decoding accuracies. Further analysis reveals that the top-down SSVEP paradigm shows the most focalised activation pattern around occipital visual areas; Granger causality analysis consistently revealed prefrontal top-down control over early visual processing. Taken together, the present paradigm provides the first neurophysiological evidence for the top-down SSVEP BMI paradigm, which potentially enables multi-class intentional control of EEG-BMIs without using gaze-shifting. PMID:27808125

Decoding of top-down cognitive processing for SSVEP-controlled BMI

NASA Astrophysics Data System (ADS)

Min, Byoung-Kyong; Dähne, Sven; Ahn, Min-Hee; Noh, Yung-Kyun; Müller, Klaus-Robert

2016-11-01

We present a fast and accurate non-invasive brain-machine interface (BMI) based on demodulating steady-state visual evoked potentials (SSVEPs) in electroencephalography (EEG). Our study reports an SSVEP-BMI that, for the first time, decodes primarily based on top-down and not bottom-up visual information processing. The experimental setup presents a grid-shaped flickering line array that the participants observe while intentionally attending to a subset of flickering lines representing the shape of a letter. While the flickering pixels stimulate the participant’s visual cortex uniformly with equal probability, the participant’s intention groups the strokes and thus perceives a ‘letter Gestalt’. We observed decoding accuracy of 35.81% (up to 65.83%) with a regularized linear discriminant analysis; on average 2.05-fold, and up to 3.77-fold greater than chance levels in multi-class classification. Compared to the EEG signals, an electrooculogram (EOG) did not significantly contribute to decoding accuracies. Further analysis reveals that the top-down SSVEP paradigm shows the most focalised activation pattern around occipital visual areas; Granger causality analysis consistently revealed prefrontal top-down control over early visual processing. Taken together, the present paradigm provides the first neurophysiological evidence for the top-down SSVEP BMI paradigm, which potentially enables multi-class intentional control of EEG-BMIs without using gaze-shifting.

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.

Neighborhood Structural Similarity Mapping for the Classification of Masses in Mammograms.

PubMed

Rabidas, Rinku; Midya, Abhishek; Chakraborty, Jayasree

2018-05-01

In this paper, two novel feature extraction methods, using neighborhood structural similarity (NSS), are proposed for the characterization of mammographic masses as benign or malignant. Since gray-level distribution of pixels is different in benign and malignant masses, more regular and homogeneous patterns are visible in benign masses compared to malignant masses; the proposed method exploits the similarity between neighboring regions of masses by designing two new features, namely, NSS-I and NSS-II, which capture global similarity at different scales. Complementary to these global features, uniform local binary patterns are computed to enhance the classification efficiency by combining with the proposed features. The performance of the features are evaluated using the images from the mini-mammographic image analysis society (mini-MIAS) and digital database for screening mammography (DDSM) databases, where a tenfold cross-validation technique is incorporated with Fisher linear discriminant analysis, after selecting the optimal set of features using stepwise logistic regression method. The best area under the receiver operating characteristic curve of 0.98 with an accuracy of is achieved with the mini-MIAS database, while the same for the DDSM database is 0.93 with accuracy .

Classification and prediction of rice wines with different marked ages by using a voltammetric electronic tongue.

PubMed

Wei, Zhenbo; Wang, Jun; Ye, Linshuang

2011-08-15

A voltammetric electronic tongue (VE-tongue) was developed to discriminate the difference between Chinese rice wines in this research. Three types of Chinese rice wine with different marked ages (1, 3, and 5 years) were classified by the VE-tongue by principal component analysis (PCA) and cluster analysis (CA). The VE-tongue consisted of six working electrodes (gold, silver, platinum, palladium, tungsten, and titanium) in a standard three-electrode configuration. The multi-frequency large amplitude pulse voltammetry (MLAPV), which consisted of four segments of 1 Hz, 10 Hz, 100 Hz, and 1000 Hz, was applied as the potential waveform. The three types of Chinese rice wine could be classified accurately by PCA and CA, and some interesting regularity is shown in the score plots with the help of PCA. Two regression models, partial least squares (PLS) and back-error propagation-artificial neural network (BP-ANN), were used for wine age prediction. The regression results showed that the marked ages of the three types of Chinese rice wine were successfully predicted using PLS and BP-ANN. Copyright © 2011 Elsevier B.V. All rights reserved.

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.

Associated factors of self-reported psychopathology and health related quality of life among men who have sex with men (MSM) with HIV/AIDS in Dalian, China: a pilot study.

PubMed

Hidru, Tesfaldet Habtemariam; Wang, Feng; Lolokote, Sainyugu; Jia, Yong; Chen, Min; Tong, Wei; Li, Xiao-Feng

2016-12-01

Despite the availability of Anti-Retroviral Therapy (ART), the health-related quality of life (HRQoL) among HIV-positive men who have sex with men (HIVMSM) in China remains poor. This study aimed to explore the relationship between self-reported psychopathology and HRQoL among HIVMSM in Dalian, China. A cross-sectional study was conducted in 112 HIVMSM. Symptom check list 90 (SCL 90): a measure of psychopathology and World Health Organization quality of life in HIV infection (WHOQOL-HIV-Bref): a measure of HRQoL were used. Correlation and multiple regression analysis were employed to explore the association between self-reported psychopathology and HRQoL in HIVMSM. Out of the total 112 HIVMSM cases, 9 (8 %) cases were homosexuals and 103 (92 %) ones were bisexuals. The participants who had low family income (P = 0.001), perceived discrimination (P = 0.001) and lack of regular attendance in medical follow-ups (P = 0.014) reported poorer HRQoL than their counterparts. Somatization, obsession, depression, phobia and overall SCL 90 scores in self-reported psycholpathology had a negative impact on the domains of HRQoL among HIVMSM. Total quality of life was predicted by family income, perceived discrimination, and medical follow-up attendance. Self-reported psychopathology was negatively correlated with HRQoL in HIVMSM. The Strategies that target MSM focusing on linking and engaging HIV-positive patients in medical care is the key step to improve their HRQoL. More emphasis is needed on the newly diagnosed HIVMSM in Dalian in order to develop a more targeted intervention to prevent perceived discrimination and lack of proper medical follow-up services. The trial registration number does not require for this manuscript. The study is cross-sectional design that do not involve intervention at all, it is not a clinical trial.

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

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.

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.

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)

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.

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.

The Role of Visual Eccentricity on Preference for Abstract Symmetry

PubMed Central

O’ Sullivan, Noreen; Bertamini, Marco

2016-01-01

This study tested preference for abstract patterns, comparing random patterns to a two-fold bilateral symmetry. Stimuli were presented at random locations in the periphery. Preference for bilateral symmetry has been extensively studied in central vision, but evaluation at different locations had not been systematically investigated. Patterns were presented for 200 ms within a large circular region. On each trial participant changed fixation and were instructed to select any location. Eccentricity values were calculated a posteriori as the distance between ocular coordinates at pattern onset and coordinates for the centre of the pattern. Experiment 1 consisted of two Tasks. In Task 1, participants detected pattern regularity as fast as possible. In Task 2 they evaluated their liking for the pattern on a Likert-scale. Results from Task 1 revealed that with our parameters eccentricity did not affect symmetry detection. However, in Task 2, eccentricity predicted more negative evaluation of symmetry, but not random patterns. In Experiment 2 participants were either presented with symmetry or random patterns. Regularity was task-irrelevant in this task. Participants discriminated the proportion of black/white dots within the pattern and then evaluated their liking for the pattern. Even when only one type of regularity was presented and regularity was task-irrelevant, preference evaluation for symmetry decreased with increasing eccentricity, whereas eccentricity did not affect the evaluation of random patterns. We conclude that symmetry appreciation is higher for foveal presentation in a way not fully accounted for by sensitivity. PMID:27124081

The Role of Visual Eccentricity on Preference for Abstract Symmetry.

PubMed

Rampone, Giulia; O' Sullivan, Noreen; Bertamini, Marco

2016-01-01

This study tested preference for abstract patterns, comparing random patterns to a two-fold bilateral symmetry. Stimuli were presented at random locations in the periphery. Preference for bilateral symmetry has been extensively studied in central vision, but evaluation at different locations had not been systematically investigated. Patterns were presented for 200 ms within a large circular region. On each trial participant changed fixation and were instructed to select any location. Eccentricity values were calculated a posteriori as the distance between ocular coordinates at pattern onset and coordinates for the centre of the pattern. Experiment 1 consisted of two Tasks. In Task 1, participants detected pattern regularity as fast as possible. In Task 2 they evaluated their liking for the pattern on a Likert-scale. Results from Task 1 revealed that with our parameters eccentricity did not affect symmetry detection. However, in Task 2, eccentricity predicted more negative evaluation of symmetry, but not random patterns. In Experiment 2 participants were either presented with symmetry or random patterns. Regularity was task-irrelevant in this task. Participants discriminated the proportion of black/white dots within the pattern and then evaluated their liking for the pattern. Even when only one type of regularity was presented and regularity was task-irrelevant, preference evaluation for symmetry decreased with increasing eccentricity, whereas eccentricity did not affect the evaluation of random patterns. We conclude that symmetry appreciation is higher for foveal presentation in a way not fully accounted for by sensitivity.

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.

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.

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.

Numerical modeling of higher order magnetic moments in UXO discrimination

USGS Publications Warehouse

Sanchez, V.; Yaoguo, L.; Nabighian, M.N.; Wright, D.L.

2008-01-01

The surface magnetic anomaly observed in unexploded ordnance (UXO) clearance is mainly dipolar, and consequently, the dipole is the only magnetic moment regularly recovered in UXO discrimination. The dipole moment contains information about the intensity of magnetization but lacks information about the shape of the target. In contrast, higher order moments, such as quadrupole and octupole, encode asymmetry properties of the magnetization distribution within the buried targets. In order to improve our understanding of magnetization distribution within UXO and non-UXO objects and to show its potential utility in UXO clearance, we present a numerical modeling study of UXO and related metallic objects. The tool for the modeling is a nonlinear integral equation describing magnetization within isolated compact objects of high susceptibility. A solution for magnetization distribution then allows us to compute the magnetic multipole moments of the object, analyze their relationships, and provide a depiction of the anomaly produced by different moments within the object. Our modeling results show the presence of significant higher order moments for more asymmetric objects, and the fields of these higher order moments are well above the noise level of magnetic gradient data. The contribution from higher order moments may provide a practical tool for improved UXO discrimination. ?? 2008 IEEE.

Comparison of level discrimination, increment detection, and comodulation masking release in the audio- and envelope-frequency domains

PubMed Central

Nelson, Paul C.; Ewert, Stephan D.; Carney, Laurel H.; Dau, Torsten

2008-01-01

In general, the temporal structure of stimuli must be considered to account for certain observations made in detection and masking experiments in the audio-frequency domain. Two such phenomena are (1) a heightened sensitivity to amplitude increments with a temporal fringe compared to gated level discrimination performance and (2) lower tone-in-noise detection thresholds using a modulated masker compared to those using an unmodulated masker. In the current study, translations of these two experiments were carried out to test the hypothesis that analogous cues might be used in the envelope-frequency domain. Pure-tone carrier amplitude-modulation (AM) depth-discrimination thresholds were found to be similar using both traditional gated stimuli and using a temporally modulated fringe for a fixed standard depth (ms=0.25) and a range of AM frequencies (4-64 Hz). In a second experiment, masked sinusoidal AM detection thresholds were compared in conditions with and without slow and regular fluctuations imposed on the instantaneous masker AM depth. Release from masking was obtained only for very slow masker fluctuations (less than 2 Hz). A physiologically motivated model that effectively acts as a first-order envelope change detector accounted for several, but not all, of the key aspects of the data. PMID:17471731

Development of a 6LiF/ZnS-based Neutron Multiplicity Counter

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

Stave, Sean C.; Behling, Richard S.; Bernacki, Bruce E.

2016-10-06

Abstract–Neutron multiplicity counters are used in safeguards to provide rapid assay of samples which contain an unknown amount of plutonium in a potentially unknown configuration. A project at PNNL is using regular and nickel-quenched 6LiF/ZnS neutron-scintillator sheets and wavelength shifting plastic for light pipes in place of 3He. A combination of laboratory and modeling work predicts a LiF/ZnS-based system to be able to match or exceed the performance of the best 3He-based systems available. Also, the Ni-quenched material is expected to allow for improved neutron/gamma-ray discrimination at twice the event rate relative to the non-Ni-quenched LiF/ZnS. A new system basedmore » on the LiF/ZnS material is under construction and components are being used to optimize the detection efficiency and neutron/gamma-ray discrimination properties. Components of the new system are partially constructed and undergoing performance testing utilizing high-speed digitizers with field programmable gate arrays to perform the neutron/gamma-ray discrimination. The expected performance of the full-scale system is expected to be nearly the same as for 3He-based systems and is due for completion in 2016.« less

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.

Risk factors for accident death in the U.S. Army, 2004-2009.

PubMed

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B; Ursano, Robert J; Heeringa, Steven G

2014-12-01

Accidents are one of the leading causes of death among U.S. active-duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty from line-of-duty accident deaths. Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004-2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers and increased for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate not-line-of-duty from line-of-duty accident deaths. Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. Copyright © 2014 American Journal of Preventive Medicine. All rights reserved.

Risk Factors for Accident Death in the U.S. Army, 2004–2009

PubMed Central

Lewandowski-Romps, Lisa; Peterson, Christopher; Berglund, Patricia A.; Collins, Stacey; Cox, Kenneth; Hauret, Keith; Jones, Bruce; Kessler, Ronald C.; Mitchell, Colter; Park, Nansook; Schoenbaum, Michael; Stein, Murray B.; Ursano, Robert J.; Heeringa, Steven G.

2014-01-01

Background Accidents are one of the leading causes of death among U.S. active duty Army soldiers. Evidence-based approaches to injury prevention could be strengthened by adding person-level characteristics (e.g., demographics) to risk models tested on diverse soldier samples studied over time. Purpose To identify person-level risk indicators of accident deaths in Regular Army soldiers during a time frame of intense military operations, and to discriminate risk of not-line-of-duty (NLOD) from line-of-duty (LOD) accident deaths. Methods Administrative data acquired from multiple Army/Department of Defense sources for active duty Army soldiers during 2004–2009 were analyzed in 2013. Logistic regression modeling was used to identify person-level sociodemographic, service-related, occupational, and mental health predictors of accident deaths. Results Delayed rank progression or demotion and being male, unmarried, in a combat arms specialty, and of low rank/service length increased odds of accident death for enlisted soldiers. Unique to officers was high risk associated with aviation specialties. Accident death risk decreased over time for currently deployed, enlisted soldiers while increasing for those never deployed. Mental health diagnosis was associated with risk only for previous and never-deployed, enlisted soldiers. Models did not discriminate NLOD from LOD accident deaths. Conclusions Adding more refined person-level and situational risk indicators to current models could enhance understanding of accident death risk specific to soldier rank and deployment status. Stable predictors could help identify high risk of accident deaths in future cohorts of Regular Army soldiers. PMID:25441238

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.

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…

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.

Suit says working at home is a form of job accommodation.

PubMed

D'Agostino, T

1999-10-15

The Equal Employment Opportunity Commission (EEOC) in San Francisco filed a reasonable accommodation complaint on behalf of [name removed] against [name removed] [name removed] Corp. [Name removed] developed complications of diabetes and asked to work at home two days per week to maintain her doctor's recommended eating and exercise schedules. [Name removed] refused. EEOC claims the company permitted a similarly situated male employee to work at home on a regular basis and alleged that the company's action was sex discrimination as well as discrimination on the basis of disability. The agency seeks a permanent injunction to bar [name removed] from denying such reasonable accommodations, as well as compensatory and punitive damages. The case tests the court's receptiveness to working at home as a form of accommodation. EEOC recognizes that some jobs require the worker's presence at the job site and that some workers need supervision, but holds there are situations where working at home is appropriate. Enforcement guidance issued by the EEOC in March on working at home is provided.

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.

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

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.

Homophone dominance at the whole-word and sub-word levels: spelling errors suggest full-form storage of regularly inflected verb forms.

PubMed

Sandra, Dominiek

2010-01-01

Two experiments and two corpus studies focus on homophone dominance in the spelling of regularly inflected verb forms, the phenomenon that the higher-frequency homophone causes more intrusion errors on the lower-frequency one than vice versa. Experiment 1 was a speeded dictation task focusing on the Dutch imperative, a verb form whose formation rule is poorly known. A clear-cut effect of homophone dominance was found. This effect was equally strong when the target imperative was preceded by another imperative in the same sentence whose pronunciation reflected the spelling rule. Experiment 2 indicated that the effect of homophone dominance cannot be reduced to an effect of recency. Language users cannot discriminate a recently seen verb form when shown the two homophones. Instead, they choose the most frequent spelling pattern. In Corpus Study 1 a Google search on the world wide web revealed a sublexical effect of homophone dominance in the spelling errors on regular past tense forms. Corpus Study 2 demonstrated the validity of the search method. The sublexical effect of homophone dominance, involving units that cut across the stem-suffix boundary, lends itself naturally to a representational model of the connectionist or analogical processing tradition but is hard to reconcile with a rule-based account.

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.

Regular and Random Components in Aiming-Point Trajectory During Rifle Aiming and Shooting

PubMed Central

Goodman, Simon; Haufler, Amy; Shim, Jae Kun; Hatfield, Bradley

2009-01-01

The authors examined the kinematic qualities of the aiming trajectory as related to expertise. In all, 2 phases of the trajectory were discriminated. The first phase was regular approximation to the target accompanied by substantial fluctuations obeying the Weber–Fechner law. During the first phase, shooters did not initiate the triggering despite any random closeness of the aiming point (AP) to the target. In the second phase, beginning at 0.6–0.8 s before the trigger pull, shooters applied a different control strategy: They waited until the following random fluctuation brought the AP closer to the target and then initiated triggering. This strategy is tenable when sensitivity of perception is greater than precision of the motor action, and could be considered a case of stochastic resonance. The strategies that novices and experts used distinguished only in the values of parameters. The authors present an analytical model explaining the main properties of shooting. PMID:19508963

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.

Polymorphism of CRISPR shows separated natural groupings of Shigella subtypes and evidence of horizontal transfer of CRISPR

PubMed Central

Yang, Chaojie; Li, Peng; Su, Wenli; Li, Hao; Liu, Hongbo; Yang, Guang; Xie, Jing; Yi, Shengjie; Wang, Jian; Cui, Xianyan; Wu, Zhihao; Wang, Ligui; Hao, Rongzhang; Jia, Leili; Qiu, Shaofu; Song, Hongbin

2015-01-01

Clustered, regularly interspaced, short palindromic repeats (CRISPR) act as an adaptive RNA-mediated immune mechanism in bacteria. They can also be used for identification and evolutionary studies based on polymorphisms within the CRISPR locus. We amplified and analyzed 6 CRISPR loci from 237 Shigella strains belonging to the 4 species groups, as well as 13 Escherichia coli strains. The CRISPR-associated (cas) gene sequence arrays of these strains were screened and compared. The CRISPR sequences from Shigella were conserved among subtypes, suggesting that CRISPR may represent a new identification tool for the detection and discrimination of Shigella species. Secondary structure analysis showed a different stem-loop structure at the terminal repeat, suggesting a distinct recognition mechanism in the formation of crRNA. In addition, the presence of “self-target” spacers and polymorphisms within CRISPR in Shigella indicated a selective pressure for inhibition of this system, which has the potential to damage “self DNA.” Homology analysis of spacers showed that CRISPR might be involved in the regulation of virulence transmission. Phylogenetic analysis based on CRISPR sequences from Shigella and E. coli indicated that although phenotypic properties maintain convergent evolution, the 4 Shigella species do not represent natural groupings. Surprisingly, comparative analysis of Shigella repeats with other species provided new evidence for CRISPR horizontal transfer. Our results suggested that CRISPR analysis is applicable for the detection of Shigella species and for investigation of evolutionary relationships. PMID:26327282

Polymorphism of CRISPR shows separated natural groupings of Shigella subtypes and evidence of horizontal transfer of CRISPR.

PubMed

Yang, Chaojie; Li, Peng; Su, Wenli; Li, Hao; Liu, Hongbo; Yang, Guang; Xie, Jing; Yi, Shengjie; Wang, Jian; Cui, Xianyan; Wu, Zhihao; Wang, Ligui; Hao, Rongzhang; Jia, Leili; Qiu, Shaofu; Song, Hongbin

2015-01-01

Clustered, regularly interspaced, short palindromic repeats (CRISPR) act as an adaptive RNA-mediated immune mechanism in bacteria. They can also be used for identification and evolutionary studies based on polymorphisms within the CRISPR locus. We amplified and analyzed 6 CRISPR loci from 237 Shigella strains belonging to the 4 species groups, as well as 13 Escherichia coli strains. The CRISPR-associated (cas) gene sequence arrays of these strains were screened and compared. The CRISPR sequences from Shigella were conserved among subtypes, suggesting that CRISPR may represent a new identification tool for the detection and discrimination of Shigella species. Secondary structure analysis showed a different stem-loop structure at the terminal repeat, suggesting a distinct recognition mechanism in the formation of crRNA. In addition, the presence of "self-target" spacers and polymorphisms within CRISPR in Shigella indicated a selective pressure for inhibition of this system, which has the potential to damage "self DNA." Homology analysis of spacers showed that CRISPR might be involved in the regulation of virulence transmission. Phylogenetic analysis based on CRISPR sequences from Shigella and E. coli indicated that although phenotypic properties maintain convergent evolution, the 4 Shigella species do not represent natural groupings. Surprisingly, comparative analysis of Shigella repeats with other species provided new evidence for CRISPR horizontal transfer. Our results suggested that CRISPR analysis is applicable for the detection of Shigella species and for investigation of evolutionary relationships.

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®

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

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

PubMed

Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Target discrimination of man-made objects using passive polarimetric signatures acquired in the visible and infrared spectral bands

NASA Astrophysics Data System (ADS)

Lavigne, Daniel A.; Breton, Mélanie; Fournier, Georges; Charette, Jean-François; Pichette, Mario; Rivet, Vincent; Bernier, Anne-Pier

2011-10-01

Surveillance operations and search and rescue missions regularly exploit electro-optic imaging systems to detect targets of interest in both the civilian and military communities. By incorporating the polarization of light as supplementary information to such electro-optic imaging systems, it is possible to increase their target discrimination capabilities, considering that man-made objects are known to depolarized light in different manner than natural backgrounds. As it is known that electro-magnetic radiation emitted and reflected from a smooth surface observed near a grazing angle becomes partially polarized in the visible and infrared wavelength bands, additional information about the shape, roughness, shading, and surface temperatures of difficult targets can be extracted by processing effectively such reflected/emitted polarized signatures. This paper presents a set of polarimetric image processing algorithms devised to extract meaningful information from a broad range of man-made objects. Passive polarimetric signatures are acquired in the visible, shortwave infrared, midwave infrared, and longwave infrared bands using a fully automated imaging system developed at DRDC Valcartier. A fusion algorithm is used to enable the discrimination of some objects lying in shadowed areas. Performance metrics, derived from the computed Stokes parameters, characterize the degree of polarization of man-made objects. Field experiments conducted during winter and summer time demonstrate: 1) the utility of the imaging system to collect polarized signatures of different objects in the visible and infrared spectral bands, and 2) the enhanced performance of target discrimination and fusion algorithms to exploit the polarized signatures of man-made objects against cluttered backgrounds.

Visual cues for woodpeckers: light reflectance of decayed wood varies by decay fungus

USGS Publications Warehouse

O'Daniels, Sean T.; Kesler, Dylan C.; Mihail, Jeanne D.; Webb, Elisabeth B.; Werner, Scott J.

2018-01-01

The appearance of wood substrates is likely relevant to bird species with life histories that require regular interactions with wood for food and shelter. Woodpeckers detect decayed wood for cavity placement or foraging, and some species may be capable of detecting trees decayed by specific fungi; however, a mechanism allowing for such specificity remains unidentified. We hypothesized that decay fungi associated with woodpecker cavity sites alter the substrate reflectance in a species-specific manner that is visually discriminable by woodpeckers. We grew 10 species of wood decay fungi from pure cultures on sterile wood substrates of 3 tree species. We then measured the relative reflectance spectra of decayed and control wood wafers and compared them using the receptor noise-limited (RNL) color discrimination model. The RNL model has been used in studies of feather coloration, egg shells, flowers, and fruit to model how the colors of objects appear to birds. Our analyses indicated 6 of 10 decayed substrate/control comparisons were above the threshold of discrimination (i.e., indicating differences discriminable by avian viewers), and 12 of 13 decayed substrate comparisons were also above threshold for a hypothetical woodpecker. We conclude that woodpeckers should be capable of visually detecting decayed wood on trees where bark is absent, and they should also be able to detect visually species-specific differences in wood substrates decayed by fungi used in this study. Our results provide evidence for a visual mechanism by which woodpeckers could identify and select substrates decayed by specific fungi, which has implications for understanding ecologically important woodpecker–fungus interactions.

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…

Data-driven modeling of sleep EEG and EOG reveals characteristics indicative of pre-Parkinson's and Parkinson's disease.

PubMed

Christensen, Julie A E; Zoetmulder, Marielle; Koch, Henriette; Frandsen, Rune; Arvastson, Lars; Christensen, Søren R; Jennum, Poul; Sorensen, Helge B D

2014-09-30

Manual scoring of sleep relies on identifying certain characteristics in polysomnograph (PSG) signals. However, these characteristics are disrupted in patients with neurodegenerative diseases. This study evaluates sleep using a topic modeling and unsupervised learning approach to identify sleep topics directly from electroencephalography (EEG) and electrooculography (EOG). PSG data from control subjects were used to develop an EOG and an EEG topic model. The models were applied to PSG data from 23 control subjects, 25 patients with periodic leg movements (PLMs), 31 patients with idiopathic REM sleep behavior disorder (iRBD) and 36 patients with Parkinson's disease (PD). The data were divided into training and validation datasets and features reflecting EEG and EOG characteristics based on topics were computed. The most discriminative feature subset for separating iRBD/PD and PLM/controls was estimated using a Lasso-regularized regression model. The features with highest discriminability were the number and stability of EEG topics linked to REM and N3, respectively. Validation of the model indicated a sensitivity of 91.4% and a specificity of 68.8% when classifying iRBD/PD patients. The topics showed visual accordance with the manually scored sleep stages, and the features revealed sleep characteristics containing information indicative of neurodegeneration. This study suggests that the amount of N3 and the ability to maintain NREM and REM sleep have potential as early PD biomarkers. Data-driven analysis of sleep may contribute to the evaluation of neurodegenerative patients. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Federal Pay Equity Act of 1984. Part 2. Hearings before the Subcommittee on Compensation and Employee Benefits of the Committee on Post Office and Civil Service, House of Representatives, Ninety-Eighth Congress, Second Session on H.R. 4599 and H.R. 5092. (May 30, July 17, October 18, 1984).

ERIC Educational Resources Information Center

Congress of the U. S., Washington, DC. House Committee on Post Office and Civil Service.

In these three congressional hearings on pay equity, focuses are on two bills--the Federal Pay Equity Act of 1984, which would examine wage discrimination within the Federal civil service system, and the Pay Equity Act of 1984, which would mandate the Equal Employment Opportunity Commission to report regularly on activities to enforce pay equity…

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.

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.

Improved discrimination between monocotyledonous and dicotyledonous plants for weed control based on the blue-green region of ultraviolet-induced fluorescence spectra.

PubMed

Panneton, Bernard; Guillaume, Serge; Roger, Jean-Michel; Samson, Guy

2010-01-01

Precision weeding by spot spraying in real time requires sensors to discriminate between weeds and crop without contact. Among the optical based solutions, the ultraviolet (UV) induced fluorescence of the plants appears as a promising alternative. In a first paper, the feasibility of discriminating between corn hybrids, monocotyledonous, and dicotyledonous weeds was demonstrated on the basis of the complete spectra. Some considerations about the different sources of fluorescence oriented the focus to the blue-green fluorescence (BGF) part, ignoring the chlorophyll fluorescence that is inherently more variable in time. This paper investigates the potential of performing weed/crop discrimination on the basis of several large spectral bands in the BGF area. A partial least squares discriminant analysis (PLS-DA) was performed on a set of 1908 spectra of corn and weed plants over 3 years and various growing conditions. The discrimination between monocotyledonous and dicotyledonous plants based on the blue-green fluorescence yielded robust models (classification error between 1.3 and 4.6% for between-year validation). On the basis of the analysis of the PLS-DA model, two large bands were chosen in the blue-green fluorescence zone (400-425 nm and 425-490 nm). A linear discriminant analysis based on the signal from these two bands also provided very robust inter-year results (classification error from 1.5% to 5.2%). The same selection process was applied to discriminate between monocotyledonous weeds and maize but yielded no robust models (up to 50% inter-year error). Further work will be required to solve this problem and provide a complete UV fluorescence based sensor for weed-maize discrimination.

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.

Graph Laplacian Regularization for Image Denoising: Analysis in the Continuous Domain.

PubMed

Pang, Jiahao; Cheung, Gene

2017-04-01

Inverse imaging problems are inherently underdetermined, and hence, it is important to employ appropriate image priors for regularization. One recent popular prior-the graph Laplacian regularizer-assumes that the target pixel patch is smooth with respect to an appropriately chosen graph. However, the mechanisms and implications of imposing the graph Laplacian regularizer on the original inverse problem are not well understood. To address this problem, in this paper, we interpret neighborhood graphs of pixel patches as discrete counterparts of Riemannian manifolds and perform analysis in the continuous domain, providing insights into several fundamental aspects of graph Laplacian regularization for image denoising. Specifically, we first show the convergence of the graph Laplacian regularizer to a continuous-domain functional, integrating a norm measured in a locally adaptive metric space. Focusing on image denoising, we derive an optimal metric space assuming non-local self-similarity of pixel patches, leading to an optimal graph Laplacian regularizer for denoising in the discrete domain. We then interpret graph Laplacian regularization as an anisotropic diffusion scheme to explain its behavior during iterations, e.g., its tendency to promote piecewise smooth signals under certain settings. To verify our analysis, an iterative image denoising algorithm is developed. Experimental results show that our algorithm performs competitively with state-of-the-art denoising methods, such as BM3D for natural images, and outperforms them significantly for piecewise smooth images.

On the Relations among Regular, Equal Unique Variances, and Image Factor Analysis Models.

ERIC Educational Resources Information Center

Hayashi, Kentaro; Bentler, Peter M.

2000-01-01

Investigated the conditions under which the matrix of factor loadings from the factor analysis model with equal unique variances will give a good approximation to the matrix of factor loadings from the regular factor analysis model. Extends the results to the image factor analysis model. Discusses implications for practice. (SLD)

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.

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

Linear discriminant analysis of dermoscopic parameters for the differentiation of early melanomas from Clark naevi.

PubMed

Oka, Hiroshi; Tanaka, Masaru; Kobayashi, Seiichiro; Argenziano, Giuseppe; Soyer, H Peter; Nishikawa, Takeji

2004-04-01

As a first step to develop a screening system for pigmented skin lesions, we performed digital discriminant analyses between early melanomas and Clark naevi. A total of 59 cases of melanoma, including 23 melanoma in situ and 36 thin invasive melanomas (Breslow thickness < or =0.75 mm), and 188 clinically equivocal, histopathologically diagnosed Clark naevi were used in our study. After calculating 62 mathematical variables related to the colour, texture, asymmetry and circularity based on the dermoscopic findings of the pigmented skin lesions, we performed multivariate stepwise discriminant analysis using these variables to differentiate melanomas from naevi. The sensitivities and specificities of our model were 94.4 and 98.4%, respectively, for discriminating between melanomas (Breslow thickness < or =0.75 mm) and Clark naevi, and 73.9 and 85.6%, respectively, for discriminating between melanoma in situ and Clark naevi. Our algorithm accurately discriminated invasive melanomas from Clark naevi, but not melanomas in situ from Clark naevi.

Some observations on the use of discriminant analysis in ecology

USGS Publications Warehouse

Williams, B.K.

1983-01-01

The application of discriminant analysis in ecological investigations is discussed. The appropriate statistical assumptions for discriminant analysis are illustrated, and both classification and group separation approaches are outlined. Three assumptions that are crucial in ecological studies are discussed at length, and the consequences of their violation are developed. These assumptions are: equality of dispersions, identifiability of prior probabilities, and precise and accurate estimation of means and dispersions. The use of discriminant functions for purposes of interpreting ecological relationships is also discussed. It is suggested that the common practice of imputing ecological 'meaning' to the signs and magnitudes of coefficients be replaced by an assessment of 'structure coefficients.' Finally, the potential and limitations of representation of data in canonical space are considered, and some cautionary points are made concerning ecological interpretation of patterns in canonical space.

Trial participants' experiences of early enhanced speech and language therapy after stroke compared with employed visitor support: a qualitative study nested within a randomized controlled trial.

PubMed

Young, Alys; Gomersall, Timothy; Bowen, Audrey

2013-02-01

To explore trial participants' experiences of the process and outcomes of early, enhanced speech and language therapy after stroke with support from an employed visitor. Qualitative study nested within a randomized controlled trial. Twney-two people who, after stroke, had a diagnosis of aphasia (12), dysarthria (5) or both (5) and who participated in the ACT NoW study. Eight English NHS usual care settings. Individual interviews. Thematic content analysis assisted by a bespoke data transformation protocol for incorporating non-verbal and semantically ambiguous data. Participants highly regarded regular and sustained contact with someone outside of immediate family/friends who engaged them in deliberate activities/communication in the early months after stroke. Participants identified differences in the process of intervention between speech and language therapists and employed visitors. But no major discriminations were made between the impact or value of this contact according to whether provided by a speech and language therapist or employed visitor. Participant-defined criteria for effectiveness of contact included: impact on mood and confidence, self-recognition of progress and the meeting of individual needs. As in the randomized controlled trial, participants reported no evidence of added benefit of early communication therapy beyond that from attention control. The findings do not imply that regular contact with any non-professional can have beneficial effects for someone with aphasia or dysarthria in the early weeks following a stroke. The study points to specific conditions that would have to be met for contact to have a positive effect.

Feature selection and recognition from nonspecific volatile profiles for discrimination of apple juices according to variety and geographical origin.

PubMed

Guo, Jing; Yue, Tianli; Yuan, Yahong

2012-10-01

Apple juice is a complex mixture of volatile and nonvolatile components. To develop discrimination models on the basis of the volatile composition for an efficient classification of apple juices according to apple variety and geographical origin, chromatography volatile profiles of 50 apple juice samples belonging to 6 varieties and from 5 counties of Shaanxi (China) were obtained by headspace solid-phase microextraction coupled with gas chromatography. The volatile profiles were processed as continuous and nonspecific signals through multivariate analysis techniques. Different preprocessing methods were applied to raw chromatographic data. The blind chemometric analysis of the preprocessed chromatographic profiles was carried out. Stepwise linear discriminant analysis (SLDA) revealed satisfactory discriminations of apple juices according to variety and geographical origin, provided respectively 100% and 89.8% success rate in terms of prediction ability. Finally, the discriminant volatile compounds selected by SLDA were identified by gas chromatography-mass spectrometry. The proposed strategy was able to verify the variety and geographical origin of apple juices involving only a reduced number of discriminate retention times selected by the stepwise procedure. This result encourages the similar procedures to be considered in quality control of apple juices. This work presented a method for an efficient discrimination of apple juices according to apple variety and geographical origin using HS-SPME-GC-MS together with chemometric tools. Discrimination models developed could help to achieve greater control over the quality of the juice and to detect possible adulteration of the product. © 2012 Institute of Food Technologists®

Productivity or discrimination? An economic analysis of excess-weight penalty in the Swedish labor market.

PubMed

Dackehag, Margareta; Gerdtham, Ulf-G; Nordin, Martin

2015-07-01

This article investigates the excess-weight penalty in income for men and women in the Swedish labor market, using longitudinal data. It compares two identification strategies, OLS and individual fixed effects, and distinguishes between two main sources of excess-weight penalties, lower productivity because of bad health and discrimination. For men, the analysis finds a significant obesity penalty related to discrimination when applying individual fixed effects. We do not find any significant excess-weight penalty for women.

The Limits of Outcomes Analysis; A Comment on "Sex Discrimination in Higher Employment: An Empirical Analysis of the Case Law."

ERIC Educational Resources Information Center

Lee, Barbara A.

1990-01-01

Questions assumptions by Schoenfeld and Zirkel in a study reviewing gender discrimination cases against institutions of higher education. Critiques the methodology used in that study, cautions about the overall utility of "outcomes analysis," and reports more promising routes of empirical legal research. (15 references) (MLF)

Vigilance in the discrimination-stress model for Black Americans.

PubMed

Himmelstein, Mary S; Young, Danielle M; Sanchez, Diana T; Jackson, James S

2015-01-01

Daily events of discrimination are important factors in understanding health disparities. Vigilant coping, or protecting against anticipated discrimination by monitoring and modifying behaviour, is an understudied mechanism that may link discrimination and health outcomes. This study investigates how responding to everyday discrimination with anticipatory vigilance relates to the health of Black men and women. Black adults (N = 221) from the Detroit area completed measures of discrimination, adverse life events, vigilance coping, stress, depressive symptoms and self-reported health. Vigilance coping strategies mediated the relationship between discrimination and stress. Multi-group path analysis revealed that stress in turn was associated with increased depression in men and women. Self-reported health consequences of stress differed between men and women. Vigilance coping mediates the link between discrimination and stress, and stress has consequences for health outcomes resulting from discrimination. More research is needed to understand other underlying contributors to discrimination, stress and poor health outcomes as well as to create potential interventions to ameliorate health outcomes in the face of discrimination-related stress.

Proton Nuclear Magnetic Resonance-Spectroscopic Discrimination of Wines Reflects Genetic Homology of Several Different Grape (V. vinifera L.) Cultivars

PubMed Central

Zhu, Yong; Wen, Wen; Zhang, Fengmin; Hardie, Jim W.

2015-01-01

Background and Aims 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. Methods and Results 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. Conclusions 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. Significance of the Study 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. PMID:26658757

Parameters Selection for Bivariate Multiscale Entropy Analysis of Postural Fluctuations in Fallers and Non-Fallers Older Adults.

PubMed

Ramdani, Sofiane; Bonnet, Vincent; Tallon, Guillaume; Lagarde, Julien; Bernard, Pierre Louis; Blain, Hubert

2016-08-01

Entropy measures are often used to quantify the regularity of postural sway time series. Recent methodological developments provided both multivariate and multiscale approaches allowing the extraction of complexity features from physiological signals; see "Dynamical complexity of human responses: A multivariate data-adaptive framework," in Bulletin of Polish Academy of Science and Technology, vol. 60, p. 433, 2012. The resulting entropy measures are good candidates for the analysis of bivariate postural sway signals exhibiting nonstationarity and multiscale properties. These methods are dependant on several input parameters such as embedding parameters. Using two data sets collected from institutionalized frail older adults, we numerically investigate the behavior of a recent multivariate and multiscale entropy estimator; see "Multivariate multiscale entropy: A tool for complexity analysis of multichannel data," Physics Review E, vol. 84, p. 061918, 2011. We propose criteria for the selection of the input parameters. Using these optimal parameters, we statistically compare the multivariate and multiscale entropy values of postural sway data of non-faller subjects to those of fallers. These two groups are discriminated by the resulting measures over multiple time scales. We also demonstrate that the typical parameter settings proposed in the literature lead to entropy measures that do not distinguish the two groups. This last result confirms the importance of the selection of appropriate input parameters.

Assessment of craniometric traits in South Indian dry skulls for sex determination.

PubMed

Ramamoorthy, Balakrishnan; Pai, Mangala M; Prabhu, Latha V; Muralimanju, B V; Rai, Rajalakshmi

2016-01-01

The skeleton plays an important role in sex determination in forensic anthropology. The skull bone is considered as the second best after the pelvic bone in sex determination due to its better retention of morphological features. Different populations have varying skeletal characteristics, making population specific analysis for sex determination essential. Hence the objective of this investigation is to obtain the accuracy of sex determination using cranial parameters of adult skulls to the highest percentage in South Indian population and to provide a baseline data for sex determination in South India. Seventy adult preserved human skulls were taken and based on the morphological traits were classified into 43 male skulls and 27 female skulls. A total of 26 craniometric parameters were studied. The data were analyzed by using the SPSS discriminant function. The analysis of stepwise, multivariate, and univariate discriminant function gave an accuracy of 77.1%, 85.7%, and 72.9% respectively. Multivariate direct discriminant function analysis classified skull bones into male and female with highest levels of accuracy. Using stepwise discriminant function analysis, the most dimorphic variable to determine sex of the skull, was biauricular breadth followed by weight. Subjecting the best dimorphic variables to univariate discriminant analysis, high levels of accuracy of sexual dimorphism was obtained. Percentage classification of high accuracies were obtained in this study indicating high level of sexual dimorphism in the crania, setting specific discriminant equations for the gender determination in South Indian people. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Demographic and clinical features related to perceived discrimination in schizophrenia.

PubMed

Fresán, Ana; Robles-García, Rebeca; Madrigal, Eduardo; Tovilla-Zarate, Carlos-Alfonso; Martínez-López, Nicolás; Arango de Montis, Iván

2018-04-01

Perceived discrimination contributes to the development of internalized stigma among those with schizophrenia. Evidence on demographic and clinical factors related to the perception of discrimination among this population is both contradictory and scarce in low- and middle-income countries. Accordingly, the main purpose of this study is to determine the demographic and clinical factors predicting the perception of discrimination among Mexican patients with schizophrenia. Two hundred and seventeen adults with paranoid schizophrenia completed an interview on their demographic status and clinical characteristics. Symptom severity was assessed using the Positive and Negative Syndrome Scale; and perceived discrimination using 13 items from the King's Internalized Stigma Scale. Bivariate linear associations were determined to identify the variables of interest to be included in a linear regression analysis. Years of education, age of illness onset and length of hospitalization were associated with discrimination. However, only age of illness onset and length of hospitalization emerged as predictors of perceived discrimination in the final regression analysis, with longer length of hospitalization being the independent variable with the greatest contribution. Fortunately, this is a modifiable factor regarding the perception of discrimination and self-stigma. Strategies for achieving this as part of community-based mental health care are also discussed. Copyright © 2017 Elsevier B.V. All rights reserved.

Racial discrimination, binge drinking, and negative drinking consequences among black college students: serial mediation by depressive symptoms and coping motives.

PubMed

Desalu, Jessica M; Kim, Jueun; Zaso, Michelle J; Corriders, Sydnee R; Loury, Jacoby A; Minter, Monique L; Park, Aesoon

2017-09-21

Experiences of racial discrimination have been associated with diverse negative health outcomes among racial minorities. However, extant findings of the association between racial discrimination and alcohol behaviors among Black college students are mixed. The current study examined mediating roles of depressive symptoms and coping drinking motives in the association of perceived racial discrimination with binge drinking and negative drinking consequences. Data were obtained from a cross-sectional study of Black college students attending a predominantly White institution in the northeastern US (N = 251, 66% female, mean age = 20 years). Results from path analysis showed that, when potential mediators were not considered, perceived racial discrimination was positively associated with negative drinking consequences but not frequency of binge drinking. Serial multiple mediation analysis showed that depressive symptoms and in turn coping drinking motives partially mediated the associations of perceived racial discrimination with both binge drinking frequency and negative drinking consequences (after controlling for sex, age, and negative life events). Perceived racial discrimination is directly associated with experiences of alcohol-related problems, but not binge drinking behaviors among Black college students. Affective responses to perceived racial discrimination experiences and drinking to cope may serve as risk mechanisms for alcohol-related problems in this population. Implications for prevention and intervention efforts are discussed.

Ranking procedure for partial discriminant analysis

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

Beckman, R.J.; Johnson, M.E.

1981-09-01

A rank procedure developed by Broffitt, Randles, and Hogg (1976) is modified to control the conditional probability of misclassification given that classification has been attempted. This modification leads to a useful solution to the two-population partial discriminant analysis problem for even moderately sized training sets.

Brain-computer interfacing under distraction: an evaluation study

NASA Astrophysics Data System (ADS)

Brandl, Stephanie; Frølich, Laura; Höhne, Johannes; Müller, Klaus-Robert; Samek, Wojciech

2016-10-01

Objective. While motor-imagery based brain-computer interfaces (BCIs) have been studied over many years by now, most of these studies have taken place in controlled lab settings. Bringing BCI technology into everyday life is still one of the main challenges in this field of research. Approach. This paper systematically investigates BCI performance under 6 types of distractions that mimic out-of-lab environments. Main results. We report results of 16 participants and show that the performance of the standard common spatial patterns (CSP) + regularized linear discriminant analysis classification pipeline drops significantly in this ‘simulated’ out-of-lab setting. We then investigate three methods for improving the performance: (1) artifact removal, (2) ensemble classification, and (3) a 2-step classification approach. While artifact removal does not enhance the BCI performance significantly, both ensemble classification and the 2-step classification combined with CSP significantly improve the performance compared to the standard procedure. Significance. Systematically analyzing out-of-lab scenarios is crucial when bringing BCI into everyday life. Algorithms must be adapted to overcome nonstationary environments in order to tackle real-world challenges.

Action Recognition Using Nonnegative Action Component Representation and Sparse Basis Selection.

PubMed

Wang, Haoran; Yuan, Chunfeng; Hu, Weiming; Ling, Haibin; Yang, Wankou; Sun, Changyin

2014-02-01

In this paper, we propose using high-level action units to represent human actions in videos and, based on such units, a novel sparse model is developed for human action recognition. There are three interconnected components in our approach. First, we propose a new context-aware spatial-temporal descriptor, named locally weighted word context, to improve the discriminability of the traditionally used local spatial-temporal descriptors. Second, from the statistics of the context-aware descriptors, we learn action units using the graph regularized nonnegative matrix factorization, which leads to a part-based representation and encodes the geometrical information. These units effectively bridge the semantic gap in action recognition. Third, we propose a sparse model based on a joint l2,1-norm to preserve the representative items and suppress noise in the action units. Intuitively, when learning the dictionary for action representation, the sparse model captures the fact that actions from the same class share similar units. The proposed approach is evaluated on several publicly available data sets. The experimental results and analysis clearly demonstrate the effectiveness of the proposed approach.

Analysis of the discriminative methods for diagnosis of benign and malignant solitary pulmonary nodules based on serum markers.

PubMed

Wang, Wanping; Liu, Mingyue; Wang, Jing; Tian, Rui; Dong, Junqiang; Liu, Qi; Zhao, Xianping; Wang, Yuanfang

2014-01-01

Screening indexes of tumor serum markers for benign and malignant solitary pulmonary nodules (SPNs) were analyzed to find the optimum method for diagnosis. Enzyme-linked immunosorbent assays, an automatic immune analyzer and radioimmunoassay methods were used to examine the levels of 8 serum markers in 164 SPN patients, and the sensitivity for differential diagnosis of malignant or benign SPN was compared for detection using a single plasma marker or a combination of markers. The results for serological indicators that closely relate to benign and malignant SPNs were screened using the Fisher discriminant analysis and a non-conditional logistic regression analysis method, respectively. The results were then verified by the k-means clustering analysis method. The sensitivity when using a combination of serum markers to detect SPN was higher than that using a single marker. By Fisher discriminant analysis, cytokeratin 19 fragments (CYFRA21-1), carbohydrate antigen 125 (CA125), squamous cell carcinoma antigen (SCC) and breast cancer antigen (CA153), which relate to the benign and malignant SPNs, were screened. Through non-conditional logistic regression analysis, CYFRA21-1, SCC and CA153 were obtained. Using the k-means clustering analysis, the cophenetic correlation coefficient (0.940) obtained by the Fisher discriminant analysis was higher than that obtained with logistic regression analysis (0.875). This study indicated that the Fisher discriminant analysis functioned better in screening out serum markers to recognize the benign and malignant SPN. The combined detection of CYFRA21-1, CA125, SCC and CA153 is an effective way to distinguish benign and malignant SPN, and will find an important clinical application in the early diagnosis of SPN. © 2014 S. Karger GmbH, Freiburg.

A comparison of two follow-up analyses after multiple analysis of variance, analysis of variance, and descriptive discriminant analysis: A case study of the program effects on education-abroad programs

Treesearch

Alvin H. Yu; Garry Chick

2010-01-01

This study compared the utility of two different post-hoc tests after detecting significant differences within factors on multiple dependent variables using multivariate analysis of variance (MANOVA). We compared the univariate F test (the Scheffé method) to descriptive discriminant analysis (DDA) using an educational-tour survey of university study-...

Synthesis and analysis of discriminators under influence of broadband non-Gaussian noise

NASA Astrophysics Data System (ADS)

Artyushenko, V. M.; Volovach, V. I.

2018-01-01

We considered the problems of the synthesis and analysis of discriminators, when the useful signal is exposed to non-Gaussian additive broadband noise. It is shown that in this case, the discriminator of the tracking meter should contain the nonlinear transformation unit, the characteristics of which are determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian broadband noise and mismatch errors. The parameters of the discriminatory and phase characteristics of the discriminators working under the above conditions are obtained. It is shown that the efficiency of non-linear processing depends on the ratio of power of FM noise to the power of Gaussian noise. The analysis of the information loss of signal transformation caused by the linear section of discriminatory characteristics of the unit of nonlinear transformations of the discriminator is carried out. It is shown that the average slope of the nonlinear transformation characteristic is determined by the Fisher information relative to the probability density function of the mixture of non-Gaussian noise and mismatch errors.

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

PubMed

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

2013-12-15

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

[Study on the classification of dominant pathogens related to febrile respiratory syndrome, based on the method of Bayes discriminant analysis].

PubMed

Li, X C; Li, J S; Meng, L; Bai, Y N; Yu, D S; Liu, X N; Liu, X F; Jiang, X J; Ren, X W; Yang, X T; Shen, X P; Zhang, J W

2017-08-10

Objective: To understand the dominant pathogens of febrile respiratory syndrome (FRS) patients in Gansu province and to establish the Bayes discriminant function in order to identify the patients infected with the dominant pathogens. Methods: FRS patients were collected in various sentinel hospitals of Gansu province from 2009 to 2015 and the dominant pathogens were determined by describing the composition of pathogenic profile. Significant clinical variables were selected by stepwise discriminant analysis to establish the Bayes discriminant function. Results: In the detection of pathogens for FRS, both influenza virus and rhinovirus showed higher positive rates than those caused by other viruses (13.79%, 8.63%), that accounting for 54.38%, 13.73% of total viral positive patients. Most frequently detected bacteria would include Streptococcus pneumoniae , and haemophilus influenza (44.41%, 18.07%) that accounting for 66.21% and 24.55% among the bacterial positive patients. The original-validated rate of discriminant function, established by 11 clinical variables, was 73.1%, with the cross-validated rate as 70.6%. Conclusion: Influenza virus, Rhinovirus, Streptococcus pneumoniae and Haemophilus influenzae were the dominant pathogens of FRS in Gansu province. Results from the Bayes discriminant analysis showed both higher accuracy in the classification of dominant pathogens, and applicative value for FRS.

Development of Chinese Version of Polycystic Ovary Syndrome Health-Related Quality of Life Questionnaire (Chi-PCOSQ)

PubMed Central

Ou, Huang-tz; Chen, Pei-Chi

2015-01-01

Objectives To develop the Chinese version of the Polycystic Ovary Syndrome Health-related Quality of Life Questionnaire (Chi-PCOSQ). Research Design and Method This cross-sectional study was conducted in a medical center in Taiwan. Eighty women who met the criteria were enrolled: female, age range of 18–45 years, competent in the Chinese language, had been diagnosed with polycystic ovary syndrome (PCOS), and were regularly followed at outpatient clinics (defined as at least two outpatient visits before enrollment). The PCOSQ was translated and culturally adapted according to standard procedures. A semi-structured interview was applied to assess face validity. Exploratory factor analysis (EFA) was applied to determine scale constructs. Measurements of internal consistency via Cronbach’s α, test-retest reliability via intraclass correlation coefficient (ICC), construct validity, and discriminative validity were performed. Results Five additional items, representing the issues of acne, hair loss, and fear of getting diabetes, were incorporated into the original scale. A six-factor structure emerged as a result of the EFA, explaining 71.9% of the variance observed. The reliability analyses demonstrated satisfactory results for Cronbach’s α ranging from 0.78–0.96, and for ICC ranging from 0.73–0.86. Construct validity was confirmed by significant correlation between the domains of the Chi-PCOSQ and generic health-related quality of life (HRQoL) measures (WHOQOL-BREF, EQ-5D) and clinical parameters (body mass index, waist-hip ratio, blood pressure). The known-group analysis indicated that the Chi-PCOSQ is a discriminative tool that differentiates patients according to their HRQoL. Conclusion The Chi-PCOSQ seems internally consistent, culturally acceptable, and our preliminary evidence suggests that it may be reliable and valid. The Chi-PCOSQ is a promising assessment tool to address the HRQoL of women affected by PCOS in Chinese-speaking countries and to further identify ethnic/cultural differences in the HRQoL of women with PCOS. PMID:26452153

Japanese International Female Students' Experience of Discrimination, Prejudice, and Stereotypes

ERIC Educational Resources Information Center

Bonazzo, Claude; Wong, Y. Joel

2007-01-01

This qualitative study examined four Japanese international female college students' experience of discrimination, prejudice, and stereotypes in a predominately white university. Four themes emerged from the analysis of data: (1) overt forms of prejudice and discrimination; (2) stereotypes common to Asians; (3) stereotypes unique to the Japanese;…

Race, Sex, and Discrimination in School Settings: A Multilevel Analysis of Associations with Delinquency

ERIC Educational Resources Information Center

Chambers, Brittany D.; Erausquin, Jennifer Toller

2018-01-01

Background: Adolescence is a critical phase of development and experimentation with delinquent behaviors. There is a growing body of literature exploring individual and structural impacts of discrimination on health outcomes and delinquent behaviors. However, there is limited research assessing how school diversity and discrimination impact…

Ethiopian Emerging Adult Immigrants in Israel: Coping with Discrimination and Racism

ERIC Educational Resources Information Center

Walsh, Sophie D.; Tuval-Mashiach, Rivka

2012-01-01

Experiences of discrimination and racism and individual coping strategies were examined among 22 emerging adult Ethiopian immigrants in Israel. In-depth interviews explored the way they perceive, understand, respond to, and cope with experiences of discrimination. Qualitative analysis identified an initial contrast between those interviewees who…

Racial Discrimination and Asian Mental Health: A Meta-Analysis

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2011-01-01

Although research on racial discrimination and mental health has proliferated, findings are varied and dispersed. This study explored the critical question of how Asians, in particular, deal with discrimination and how this relates to Asian mental health. With 99 correlations from 23 independent studies, the overall relationship between racial…

The Influence of Racial Identity Profiles on the Relationship between Racial Discrimination and Depressive Symptoms

ERIC Educational Resources Information Center

Banks, Kira Hudson; Kohn-Wood, Laura P.

2007-01-01

This study examined the association between racial identity profiles, discrimination, and mental health outcomes. African American college students (N = 194) completed measures of racial discrimination, racial identity, college hassles, and depressive symptoms. Four meaningful profiles emerged through a cluster analysis of seven dimensions of…

Statistical analysis of Thematic Mapper Simulator data for the geobotanical discrimination of rock types in southwest Oregon

NASA Technical Reports Server (NTRS)

Morrissey, L. A.; Weinstock, K. J.; Mouat, D. A.; Card, D. H.

1984-01-01

An evaluation of Thematic Mapper Simulator (TMS) data for the geobotanical discrimination of rock types based on vegetative cover characteristics is addressed in this research. A methodology for accomplishing this evaluation utilizing univariate and multivariate techniques is presented. TMS data acquired with a Daedalus DEI-1260 multispectral scanner were integrated with vegetation and geologic information for subsequent statistical analyses, which included a chi-square test, an analysis of variance, stepwise discriminant analysis, and Duncan's multiple range test. Results indicate that ultramafic rock types are spectrally separable from nonultramafics based on vegetative cover through the use of statistical analyses.

Soybean varieties discrimination using non-imaging hyperspectral sensor

NASA Astrophysics Data System (ADS)

da Silva Junior, Carlos Antonio; Nanni, Marcos Rafael; Shakir, Muhammad; Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; Cezar, Everson; de Gois, Givanildo; Lima, Mendelson; Wojciechowski, Julio Cesar; Shiratsuchi, Luciano Shozo

2018-03-01

Infrared region of electromagnetic spectrum has remarkable applications in crop studies. Infrared along with Red band has been used to develop certain vegetation indices. These indices like NDVI, EVI provide important information on any crop physiological stages. The main objective of this research was to discriminate 4 different soybean varieties (BMX Potência, NA5909, FT Campo Mourão and Don Mario) using non-imaging hyperspectral sensor. The study was conducted in four agricultural areas in the municipality of Deodápolis (MS), Brazil. For spectral analysis, 2400 field samples were taken from soybean leaves by means of FieldSpec 3 JR spectroradiometer in the range from 350 to 2500 nm. The data were evaluated through multivariate analysis with the whole set of spectral curves isolated by blue, green, red and near infrared wavelengths along with the addition of vegetation indices like (Enhanced Vegetation Index - EVI, Normalized Difference Vegetation Index - NDVI, Green Normalized Difference Vegetation Index - GNDVI, Soil-adjusted Vegetation Index - SAVI, Transformed Vegetation Index - TVI and Optimized Soil-Adjusted Vegetation Index - OSAVI). A number of the analysis performed where, discriminant (60 and 80% of the data), simulated discriminant (40 and 20% of data), principal component (PC) and cluster analysis (CA). Discriminant and simulated discriminant analyze presented satisfactory results, with average global hit rates of 99.28 and 98.77%, respectively. The results obtained by PC and CA revealed considerable associations between the evaluated variables and the varieties, which indicated that each variety has a variable that discriminates it more effectively in relation to the others. There was great variation in the sample size (number of leaves) for estimating the mean of variables. However, it was possible to observe that 200 leaves allow to obtain a maximum error of 2% in relation to the mean.

GRace: a MATLAB-based application for fitting the discrimination-association model.

PubMed

Stefanutti, Luca; Vianello, Michelangelo; Anselmi, Pasquale; Robusto, Egidio

2014-10-28

The Implicit Association Test (IAT) is a computerized two-choice discrimination task in which stimuli have to be categorized as belonging to target categories or attribute categories by pressing, as quickly and accurately as possible, one of two response keys. The discrimination association model has been recently proposed for the analysis of reaction time and accuracy of an individual respondent to the IAT. The model disentangles the influences of three qualitatively different components on the responses to the IAT: stimuli discrimination, automatic association, and termination criterion. The article presents General Race (GRace), a MATLAB-based application for fitting the discrimination association model to IAT data. GRace has been developed for Windows as a standalone application. It is user-friendly and does not require any programming experience. The use of GRace is illustrated on the data of a Coca Cola-Pepsi Cola IAT, and the results of the analysis are interpreted and discussed.

Energy-Discriminative Performance of a Spectral Micro-CT System

PubMed Central

He, Peng; Yu, Hengyong; Bennett, James; Ronaldson, Paul; Zainon, Rafidah; Butler, Anthony; Butler, Phil; Wei, Biao; Wang, Ge

2013-01-01

Experiments were performed to evaluate the energy-discriminative performance of a spectral (multi-energy) micro-CT system. The system, designed by MARS (Medipix All Resolution System) Bio-Imaging Ltd. (Christchurch, New Zealand), employs a photon-counting energy-discriminative detector technology developed by CERN (European Organization for Nuclear Research). We used the K-edge attenuation characteristic of some known materials to calibrate the detector’s photon energy discrimination. For tomographic analysis, we used the compressed sensing (CS) based ordered-subset simultaneous algebraic reconstruction techniques (OS-SART) to reconstruct sample images, which is effective to reduce noise and suppress artifacts. Unlike conventional CT, the principal component analysis (PCA) method can be applied to extract and quantify additional attenuation information from a spectral CT dataset. Our results show that the spectral CT has a good energy-discriminative performance and provides more attenuation information than the conventional CT. PMID:24004864

B-mode ultrasound examination of canine mammary gland neoplastic lesions of small size (diameter < 2 cm).

PubMed

Vannozzi, Iacopo; Tesi, Matteo; Zangheri, Marta; Innocenti, Viola Maria; Rota, Alessandra; Citi, Simonetta; Poli, Alessandro

2018-06-01

Ultrasonography is a valuable tool for the evaluation of neoplastic lesions in the dog and there is a growing interest in the use of this technique for the stadiation of canine mammary tumours. An accurate assessment of small sized nodules facilitates the stadiation of the mammary lesions and helps the clinician in the choice of the most indicated surgical therapy. The aim of this study was to identify those ultrasound criteria that may be useful in discriminating between benign and malignant lesions of small size (diameter smaller than 2 cm). Sixty-two nodules, < 2 cm in larger diameter, belonging to thirty-five bitches presented between January 2012 and February 2014 were evaluated. Tumours were observed by conventional ultrasound and assessed for: shape (regular-irregular), limit (defined-ill-defined), margins (regular-irregular), echogenicity (hypoechoic-isoechoic-hyperecoic), echotexture (homogeneus-heterogeneus), presence of hyperecoic halo, distal acoustic enhancement or shadowing and surrounding tissue alterations. Among the alterations in surrounding tissues, the disruption of the glandular tissue and the increase in echogenicity of the peritumoral tissues were assessed. Thereafter, bitches were subjected to mastectomy and nodules were evaluated histologically. None of the ultasound criteria considered in the current study showed a statistically significant relation with malignancy, except for the presence of alterations in the tissue surrounding the nodules. According to our results, this characteristic may indicate malignancy, however its subjectivity may affect the applicability in clinical practice. In conclusions, conventional ultrasound in bitches had a limited ability in discriminating benign and malignant mammary gland neoplastic lesions of small size (diameter < 2 cm).

The Effects of Discrimination Experience on Life Satisfaction of North Korean Refugees: Mediating Effect of Stress.

PubMed

Noh, Jin-Won; Park, Hyunchun; Kim, Minji; Kwon, Young Dae; Kim, Jin-Seok; Yu, Shieun

2018-01-01

This study investigated the mediation effect of stress between the experience of discrimination and life satisfaction among North Korean refugees who resettled in South Korea. The findings of the current study provide empirical evidence for the need of social interventions to mitigate adverse effects of stress on North Korean refugees who are subject to social discrimination on a daily basis. In this study, we included 500 subjects among 2,138 North Korean refugees who took refuge in South Korea in 2007. The interview started from April 6th 2009 and finished on May 25th 2009. We conducted moderator effect analysis with Path analysis was conducted because we confirm the experience of discrimination was affected by life satisfaction and stress can affected life satisfaction as a moderator. The experience of discrimination significantly affects stress and stress significantly affects life satisfaction. However, the experience of discrimination was not directly related to life satisfaction. The more stress the study respondents experienced, the lower the life satisfaction they reported. The present finding suggests that the effects of discriminating experiences on the life satisfaction of North Korean refugees in South Korea were mediated by their own perceived stress.

Fluorescent polymer sensor array for detection and discrimination of explosives in water.

PubMed

Woodka, Marc D; Schnee, Vincent P; Polcha, Michael P

2010-12-01

A fluorescent polymer sensor array (FPSA) was made from commercially available fluorescent polymers coated onto glass beads and was tested to assess the ability of the array to discriminate between different analytes in aqueous solution. The array was challenged with exposures to 17 different analytes, including the explosives trinitrotoluene (TNT), tetryl, and RDX, various explosive-related compounds (ERCs), and nonexplosive electron-withdrawing compounds (EWCs). The array exhibited a natural selectivity toward EWCs, while the non-electron-withdrawing explosive 1,3,5-trinitroperhydro-1,3,5-triazine (RDX) produced no response. Response signatures were visualized by principal component analysis (PCA), and classified by linear discriminant analysis (LDA). RDX produced the same response signature as the sampled blanks and was classified accordingly. The array exhibited excellent discrimination toward all other compounds, with the exception of the isomers of nitrotoluene and aminodinitrotoluene. Of particular note was the ability of the array to discriminate between the three isomers of dinitrobenzene. The natural selectivity of the FPSA toward EWCs, plus the ability of the FPSA to discriminate between different EWCs, could be used to design a sensor with a low false alarm rate and an excellent ability to discriminate between explosives and explosive-related compounds.

Effect of Sample Preparation on the Discrimination of Bacterial Isolates Cultured in Liquid Nutrient Media Using Laser-Induced Breakdown Spectroscopy (LIBS).

PubMed

Gamble, Gary R; Park, Bosoon; Yoon, Seung-Chul; Lawrence, Kurt C

2016-03-01

Laser-induced breakdown spectroscopy (LIBS) is used as the basis for discrimination between two genera of gram-negative bacteria and two genera of gram-positive bacteria representing pathogenic threats commonly found in poultry processing rinse waters. Because LIBS-based discrimination relies primarily upon the relative proportions of inorganic cell components including Na, K, Mg, and Ca, this study aims to determine the effects of trace mineral content and pH found in the water source used to isolate the bacteria upon the reliability of the resulting discriminant analysis. All four genera were cultured using tryptic soy agar (TSA) as the nutrient medium, and were grown under identical environmental conditions. The only variable introduced is the source water used to isolate the cultured bacteria. Cultures of each bacterium were produced using deionized (DI) water under two atmosphere conditions, reverse osmosis (RO) water, tap water, phosphate buffered saline (PBS) water, and TRIS buffered water. After 3 days of culture growth, the bacteria were centrifuged and washed three times in the same water source. Bacteria were then freeze dried, mixed with microcrystalline cellulose, and a pellet was made for LIBS analysis. Principal component analysis (PCA) was used to extract related variations in LIBS spectral data among the four bacteria genera and six water types used to isolate the bacteria, and Mahalanobis discriminant analysis (MDA) was used for classification. Results indicate not only that the four genera can be discriminated from each other in each water type, but that each genus can be discriminated by water type used for isolation. It is concluded that in order for LIBS to be a reliable and repeatable method for discrimination of bacteria grown in liquid nutrient media, care must be taken to insure that the water source used in purification of the culture be precisely controlled regarding pH, ionic strength, and proportionate amounts of mineral cations present. © The Author(s) 2016.

Resting-state brain activity in the motor cortex reflects task-induced activity: A multi-voxel pattern analysis.

PubMed

Kusano, Toshiki; Kurashige, Hiroki; Nambu, Isao; Moriguchi, Yoshiya; Hanakawa, Takashi; Wada, Yasuhiro; Osu, Rieko

2015-08-01

It has been suggested that resting-state brain activity reflects task-induced brain activity patterns. In this study, we examined whether neural representations of specific movements can be observed in the resting-state brain activity patterns of motor areas. First, we defined two regions of interest (ROIs) to examine brain activity associated with two different behavioral tasks. Using multi-voxel pattern analysis with regularized logistic regression, we designed a decoder to detect voxel-level neural representations corresponding to the tasks in each ROI. Next, we applied the decoder to resting-state brain activity. We found that the decoder discriminated resting-state neural activity with accuracy comparable to that associated with task-induced neural activity. The distribution of learned weighted parameters for each ROI was similar for resting-state and task-induced activities. Large weighted parameters were mainly located on conjunctive areas. Moreover, the accuracy of detection was higher than that for a decoder whose weights were randomly shuffled, indicating that the resting-state brain activity includes multi-voxel patterns similar to the neural representation for the tasks. Therefore, these results suggest that the neural representation of resting-state brain activity is more finely organized and more complex than conventionally considered.

Towards a truly mobile auditory brain-computer interface: exploring the P300 to take away.

PubMed

De Vos, Maarten; Gandras, Katharina; Debener, Stefan

2014-01-01

In a previous study we presented a low-cost, small, and wireless 14-channel EEG system suitable for field recordings (Debener et al., 2012, psychophysiology). In the present follow-up study we investigated whether a single-trial P300 response can be reliably measured with this system, while subjects freely walk outdoors. Twenty healthy participants performed a three-class auditory oddball task, which included rare target and non-target distractor stimuli presented with equal probabilities of 16%. Data were recorded in a seated (control condition) and in a walking condition, both of which were realized outdoors. A significantly larger P300 event-related potential amplitude was evident for targets compared to distractors (p<.001), but no significant interaction with recording condition emerged. P300 single-trial analysis was performed with regularized stepwise linear discriminant analysis and revealed above chance-level classification accuracies for most participants (19 out of 20 for the seated, 16 out of 20 for the walking condition), with mean classification accuracies of 71% (seated) and 64% (walking). Moreover, the resulting information transfer rates for the seated and walking conditions were comparable to a recently published laboratory auditory brain-computer interface (BCI) study. This leads us to conclude that a truly mobile auditory BCI system is feasible. © 2013.

[Test set for the evaluation of hearing and speech development after cochlear implantation in children].

PubMed

Lamprecht-Dinnesen, A; Sick, U; Sandrieser, P; Illg, A; Lesinski-Schiedat, A; Döring, W H; Müller-Deile, J; Kiefer, J; Matthias, K; Wüst, A; Konradi, E; Riebandt, M; Matulat, P; Von Der Haar-Heise, S; Swart, J; Elixmann, K; Neumann, K; Hildmann, A; Coninx, F; Meyer, V; Gross, M; Kruse, E; Lenarz, T

2002-10-01

Since autumn 1998 the multicenter interdisciplinary study group "Test Materials for CI Children" has been compiling a uniform examination tool for evaluation of speech and hearing development after cochlear implantation in childhood. After studying the relevant literature, suitable materials were checked for practical applicability, modified and provided with criteria for execution and break-off. For data acquisition, observation forms for preparation of a PC-version were developed. The evaluation set contains forms for master data with supplements relating to postoperative processes. The hearing tests check supra-threshold hearing with loudness scaling for children, speech comprehension in silence (Mainz and Göttingen Test for Speech Comprehension in Childhood) and phonemic differentiation (Oldenburg Rhyme Test for Children), the central auditory processes of detection, discrimination, identification and recognition (modification of the "Frankfurt Functional Hearing Test for Children") and audiovisual speech perception (Open Paragraph Tracking, Kiel Speech Track Program). The materials for speech and language development comprise phonetics-phonology, lexicon and semantics (LOGO Pronunciation Test), syntax and morphology (analysis of spontaneous speech), language comprehension (Reynell Scales), communication and pragmatics (observation forms). The MAIS and MUSS modified questionnaires are integrated. The evaluation set serves quality assurance and permits factor analysis as well as controls for regularity through the multicenter comparison of long-term developmental trends after cochlear implantation.

The convergent and discriminant validity of burnout measures in sport: a multi-trait/multi-method analysis.

PubMed

Cresswell, Scott L; Eklund, Robert C

2006-02-01

Athlete burnout research has been hampered by the lack of an adequate measurement tool. The Athlete Burnout Questionnaire (ABQ) and the Maslach Burnout Inventory General Survey (MBI-GS) are two recently developed self-report instruments designed to assess burnout. The convergent and discriminant validity of the ABQ and MBI-GS were assessed through multi-trait/multi-method analysis with a sporting population. Overall, the ABQ and the MBI-GS displayed acceptable convergent validity with matching subscales highly correlated, and satisfactory internal discriminant validity with lower correlations between non-matching subscales. Both scales also indicated an adequate discrimination between the concepts of burnout and depression. These findings add support to previous findings in non-sporting populations that depression and burnout are separate constructs. Based on the psychometric results, construct validity analysis and practical considerations, the results support the use of the ABQ to assess athlete burnout.

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

PubMed

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

2017-08-15

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

Discrimination of Bacillus anthracis from closely related microorganisms by analysis of 16S and 23S rRNA with oligonucleotide microchips

DOEpatents

Bavykin, Sergei G.; Mirzabekov, Andrei D.

2007-10-30

The present invention is directed to a novel method of discriminating a highly infectious bacterium Bacillus anthracis from a group of closely related microorganisms. Sequence variations in the 16S and 23S rRNA of the B. cereus subgroup including B. anthracis are utilized to construct an array that can detect these sequence variations through selective hybridizations. The identification and analysis of these sequence variations enables positive discrimination of isolates of the B. cereus group that includes B. anthracis. Discrimination of single base differences in rRNA was achieved with a microchip during analysis of B. cereus group isolates from both single and in mixed probes, as well as identification of polymorphic sites. Successful use of a microchip to determine the appropriate subgroup classification using eight reference microorganisms from the B. cereus group as a study set, was demonstrated.

Taxonomic discrimination of higher plants by pyrolysis mass spectrometry.

PubMed

Kim, S W; Ban, S H; Chung, H J; Choi, D W; Choi, P S; Yoo, O J; Liu, J R

2004-02-01

Pyrolysis mass spectrometry (PyMS) is a rapid, simple, high-resolution analytical method based on thermal degradation of complex material in a vacuum and has been widely applied to the discrimination of closely related microbial strains. Leaf samples of six species and one variety of higher plants (Rosa multiflora, R. multiflora var. platyphylla, Sedum kamtschaticum, S. takesimense, S. sarmentosum, Hepatica insularis, and H. asiatica) were subjected to PyMS for spectral fingerprinting. Principal component analysis of PyMS data was not able to discriminate these plants in discrete clusters. However, canonical variate analysis of PyMS data separated these plants from one another. A hierarchical dendrogram based on canonical variate analysis was in agreement with the known taxonomy of the plants at the variety level. These results indicate that PyMS is able to discriminate higher plants based on taxonomic classification at the family, genus, species, and variety level.

Evaluation of an electronic nose for odorant and process monitoring of alkaline-stabilized biosolids production.

PubMed

Romero-Flores, Adrian; McConnell, Laura L; Hapeman, Cathleen J; Ramirez, Mark; Torrents, Alba

2017-11-01

Electronic noses have been widely used in the food industry to monitor process performance and quality control, but use in wastewater and biosolids treatment has not been fully explored. Therefore, we examined the feasibility of an electronic nose to discriminate between treatment conditions of alkaline stabilized biosolids and compared its performance with quantitative analysis of key odorants. Seven lime treatments (0-30% w/w) were prepared and the resultant off-gas was monitored by GC-MS and by an electronic nose equipped with ten metal oxide sensors. A pattern recognition model was created using linear discriminant analysis (LDA) and principal component analysis (PCA) of the electronic nose data. In general, LDA performed better than PCA. LDA showed clear discrimination when single tests were evaluated, but when the full data set was included, discrimination between treatments was reduced. Frequency of accurate recognition was tested by three algorithms with Euclidan and Mahalanobis performing at 81% accuracy and discriminant function analysis at 70%. Concentrations of target compounds by GC-MS were in agreement with those reported in literature and helped to elucidate the behavior of the pattern recognition via comparison of individual sensor responses to different biosolids treatment conditions. Results indicated that the electronic nose can discriminate between lime percentages, thus providing the opportunity to create classes of under-dosed and over-dosed relative to regulatory requirements. Full scale application will require careful evaluation to maintain accuracy under variable process and environmental conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2009-01-01

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

Detection of Lung Cancer by Sensor Array Analyses of Exhaled Breath

PubMed Central

Machado, Roberto F.; Laskowski, Daniel; Deffenderfer, Olivia; Burch, Timothy; Zheng, Shuo; Mazzone, Peter J.; Mekhail, Tarek; Jennings, Constance; Stoller, James K.; Pyle, Jacqueline; Duncan, Jennifer; Dweik, Raed A.; Erzurum, Serpil C.

2005-01-01

Rationale: Electronic noses are successfully used in commercial applications, including detection and analysis of volatile organic compounds in the food industry. Objectives: We hypothesized that the electronic nose could identify and discriminate between lung diseases, especially bronchogenic carcinoma. Methods: In a discovery and training phase, exhaled breath of 14 individuals with bronchogenic carcinoma and 45 healthy control subjects or control subjects without cancer was analyzed. Principal components and canonic discriminant analysis of the sensor data was used to determine whether exhaled gases could discriminate between cancer and noncancer. Discrimination between classes was performed using Mahalanobis distance. Support vector machine analysis was used to create and apply a cancer prediction model prospectively in a separate group of 76 individuals, 14 with and 62 without cancer. Main Results: Principal components and canonic discriminant analysis demonstrated discrimination between samples from patients with lung cancer and those from other groups. In the validation study, the electronic nose had 71.4% sensitivity and 91.9% specificity for detecting lung cancer; positive and negative predictive values were 66.6 and 93.4%, respectively. In this population with a lung cancer prevalence of 18%, positive and negative predictive values were 66.6 and 94.5%, respectively. Conclusion: The exhaled breath of patients with lung cancer has distinct characteristics that can be identified with an electronic nose. The results provide feasibility to the concept of using the electronic nose for managing and detecting lung cancer. PMID:15750044

The Categorical Perception Deficit in Dyslexia: A Meta-Analysis

ERIC Educational Resources Information Center

Noordenbos, Mark W.; Serniclaes, Willy

2015-01-01

Speech perception in dyslexia is characterized by a categorical perception (CP) deficit, demonstrated by weaker discrimination of acoustic differences between phonemic categories in conjunction with better discrimination of acoustic differences within phonemic categories. We performed a meta-analysis of studies that examined the reliability of the…

Automated pre-processing and multivariate vibrational spectra analysis software for rapid results in clinical settings

NASA Astrophysics Data System (ADS)

Bhattacharjee, T.; Kumar, P.; Fillipe, L.

2018-02-01

Vibrational spectroscopy, especially FTIR and Raman, has shown enormous potential in disease diagnosis, especially in cancers. Their potential for detecting varied pathological conditions are regularly reported. However, to prove their applicability in clinics, large multi-center multi-national studies need to be undertaken; and these will result in enormous amount of data. A parallel effort to develop analytical methods, including user-friendly software that can quickly pre-process data and subject them to required multivariate analysis is warranted in order to obtain results in real time. This study reports a MATLAB based script that can automatically import data, preprocess spectra— interpolation, derivatives, normalization, and then carry out Principal Component Analysis (PCA) followed by Linear Discriminant Analysis (LDA) of the first 10 PCs; all with a single click. The software has been verified on data obtained from cell lines, animal models, and in vivo patient datasets, and gives results comparable to Minitab 16 software. The software can be used to import variety of file extensions, asc, .txt., .xls, and many others. Options to ignore noisy data, plot all possible graphs with PCA factors 1 to 5, and save loading factors, confusion matrices and other parameters are also present. The software can provide results for a dataset of 300 spectra within 0.01 s. We believe that the software will be vital not only in clinical trials using vibrational spectroscopic data, but also to obtain rapid results when these tools get translated into clinics.

Chemometric classification of gunshot residues based on energy dispersive X-ray microanalysis and inductively coupled plasma analysis with mass-spectrometric detection

NASA Astrophysics Data System (ADS)

Steffen, S.; Otto, M.; Niewoehner, L.; Barth, M.; Bro¿żek-Mucha, Z.; Biegstraaten, J.; Horváth, R.

2007-09-01

A gunshot residue sample that was collected from an object or a suspected person is automatically searched for gunshot residue relevant particles. Particle data (such as size, morphology, position on the sample for manual relocation, etc.) as well as the corresponding X-ray spectra and images are stored. According to these data, particles are classified by the analysis-software into different groups: 'gunshot residue characteristic', 'consistent with gunshot residue' and environmental particles, respectively. Potential gunshot residue particles are manually checked and - if necessary - confirmed by the operating forensic scientist. As there are continuing developments on the ammunition market worldwide, it becomes more and more difficult to assign a detected particle to a particular ammunition brand. As well, the differentiation towards environmental particles similar to gunshot residue is getting more complex. To keep external conditions unchanged, gunshot residue particles were collected using a specially designed shooting device for the test shots revealing defined shooting distances between the weapon's muzzle and the target. The data obtained as X-ray spectra of a number of particles (3000 per ammunition brand) were reduced by Fast Fourier Transformation and subjected to a chemometric evaluation by means of regularized discriminant analysis. In addition to the scanning electron microscopy in combination with energy dispersive X-ray microanalysis results, isotope ratio measurements based on inductively coupled plasma analysis with mass-spectrometric detection were carried out to provide a supplementary feature for an even lower risk of misclassification.

Rapid discrimination of different Apiaceae species based on HPTLC fingerprints and targeted flavonoids determination using multivariate image analysis.

PubMed

Shawky, Eman; Abou El Kheir, Rasha M

2018-02-11

Species of Apiaceae are used in folk medicine as spices and in officinal medicinal preparations of drugs. They are an excellent source of phenolics exhibiting antioxidant activity, which are of great benefit to human health. Discrimination among Apiaceae medicinal herbs remains an intricate challenge due to their morphological similarity. In this study, a combined "untargeted" and "targeted" approach to investigate different Apiaceae plants species was proposed by using the merging of high-performance thin layer chromatography (HPTLC)-image analysis and pattern recognition methods which were used for fingerprinting and classification of 42 different Apiaceae samples collected from Egypt. Software for image processing was applied for fingerprinting and data acquisition. HPTLC fingerprint assisted by principal component analysis (PCA) and hierarchical cluster analysis (HCA)-heat maps resulted in a reliable untargeted approach for discrimination and classification of different samples. The "targeted" approach was performed by developing and validating an HPTLC method allowing the quantification of eight flavonoids. The combination of quantitative data with PCA and HCA-heat-maps allowed the different samples to be discriminated from each other. The use of chemometrics tools for evaluation of fingerprints reduced expense and analysis time. The proposed method can be adopted for routine discrimination and evaluation of the phytochemical variability in different Apiaceae species extracts. Copyright © 2018 John Wiley & Sons, Ltd.

[Discriminant Analysis of Lavender Essential Oil by Attenuated Total Reflectance Infrared Spectroscopy].

PubMed

Tang, Jun; Wang, Qing; Tong, Hong; Liao, Xiang; Zhang, Zheng-fang

2016-03-01

This work aimed to use attenuated total reflectance Fourier transform infrared spectroscopy to identify the lavender essential oil by establishing a Lavender variety and quality analysis model. So, 96 samples were tested. For all samples, the raw spectra were pretreated as second derivative, and to determine the 1 750-900 cm(-1) wavelengths for pattern recognition analysis on the basis of the variance calculation. The results showed that principal component analysis (PCA) can basically discriminate lavender oil cultivar and the first three principal components mainly represent the ester, alcohol and terpenoid substances. When the orthogonal partial least-squares discriminant analysis (OPLS-DA) model was established, the 68 samples were used for the calibration set. Determination coefficients of OPLS-DA regression curve were 0.959 2, 0.976 4, and 0.958 8 respectively for three varieties of lavender essential oil. Three varieties of essential oil's the root mean square error of prediction (RMSEP) in validation set were 0.142 9, 0.127 3, and 0.124 9, respectively. The discriminant rate of calibration set and the prediction rate of validation set had reached 100%. The model has the very good recognition capability to detect the variety and quality of lavender essential oil. The result indicated that a model which provides a quick, intuitive and feasible method had been built to discriminate lavender oils.

Characterization of toners and inkjets by laser ablation spectrochemical methods and Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy

NASA Astrophysics Data System (ADS)

Trejos, Tatiana; Corzo, Ruthmara; Subedi, Kiran; Almirall, José

2014-02-01

Detection and sourcing of counterfeit currency, examination of counterfeit security documents and determination of authenticity of medical records are examples of common forensic document investigations. In these cases, the physical and chemical composition of the ink entries can provide important information for the assessment of the authenticity of the document or for making inferences about common source. Previous results reported by our group have demonstrated that elemental analysis, using either Laser Ablation-Inductively Coupled Plasma-Mass Spectrometry (LA-ICP-MS) or Laser Ablation Induced Breakdown Spectroscopy (LIBS), provides an effective, practical and robust technique for the discrimination of document substrates and writing inks with minimal damage to the document. In this study, laser-based methods and Scanning Electron Microscopy-Energy Dispersive X-Ray Spectroscopy (SEM-EDS) methods were developed, optimized and validated for the forensic analysis of more complex inks such as toners and inkjets, to determine if their elemental composition can differentiate documents printed from different sources and to associate documents that originated from the same printing source. Comparison of the performance of each of these methods is presented, including the analytical figures of merit, discrimination capability and error rates. Different calibration strategies resulting in semi-quantitative and qualitative analysis, comparison methods (match criteria) and data analysis and interpretation tools were also developed. A total of 27 black laser toners originating from different manufacturing sources and/or batches were examined to evaluate the discrimination capability of each method. The results suggest that SEM-EDS offers relatively poor discrimination capability for this set (~ 70.7% discrimination of all the possible comparison pairs or a 29.3% type II error rate). Nonetheless, SEM-EDS can still be used as a complementary method of analysis since it has the advantage of being non-destructive to the sample in addition to providing imaging capabilities to further characterize toner samples by their particle morphology. Laser sampling methods resulted in an improvement of the discrimination between different sources with LIBS producing 89% discrimination and LA-ICP-MS resulting in 100% discrimination. In addition, a set of 21 black inkjet samples was examined by each method. The results show that SEM-EDS is not appropriate for inkjet examinations since their elemental composition is typically below the detection capabilities with only sulfur detected in this set, providing only 47.4% discrimination between possible comparison pairs. Laser sampling methods were shown to provide discrimination greater than 94% for this same inkjet set with false exclusion and false inclusion rates lower than 4.1% and 5.7%, for LA-ICP-MS and LIBS respectively. Overall these results confirmed the utility of the examination of printed documents by laser-based micro-spectrochemical methods. SEM-EDS analysis of toners produced a limited utility for discrimination within sources but was not an effective tool for inkjet ink discrimination. Both LA-ICP-MS and LIBS can be used in forensic laboratories to chemically characterize inks on documents and to complement the information obtained by conventional methods and enhance their evidential value.

Application of Turchin's method of statistical regularization

NASA Astrophysics Data System (ADS)

Zelenyi, Mikhail; Poliakova, Mariia; Nozik, Alexander; Khudyakov, Alexey

2018-04-01

During analysis of experimental data, one usually needs to restore a signal after it has been convoluted with some kind of apparatus function. According to Hadamard's definition this problem is ill-posed and requires regularization to provide sensible results. In this article we describe an implementation of the Turchin's method of statistical regularization based on the Bayesian approach to the regularization strategy.

A Multi-modal, Discriminative and Spatially Invariant CNN for RGB-D Object Labeling.

PubMed

Asif, Umar; Bennamoun, Mohammed; Sohel, Ferdous

2017-08-30

While deep convolutional neural networks have shown a remarkable success in image classification, the problems of inter-class similarities, intra-class variances, the effective combination of multimodal data, and the spatial variability in images of objects remain to be major challenges. To address these problems, this paper proposes a novel framework to learn a discriminative and spatially invariant classification model for object and indoor scene recognition using multimodal RGB-D imagery. This is achieved through three postulates: 1) spatial invariance - this is achieved by combining a spatial transformer network with a deep convolutional neural network to learn features which are invariant to spatial translations, rotations, and scale changes, 2) high discriminative capability - this is achieved by introducing Fisher encoding within the CNN architecture to learn features which have small inter-class similarities and large intra-class compactness, and 3) multimodal hierarchical fusion - this is achieved through the regularization of semantic segmentation to a multi-modal CNN architecture, where class probabilities are estimated at different hierarchical levels (i.e., imageand pixel-levels), and fused into a Conditional Random Field (CRF)- based inference hypothesis, the optimization of which produces consistent class labels in RGB-D images. Extensive experimental evaluations on RGB-D object and scene datasets, and live video streams (acquired from Kinect) show that our framework produces superior object and scene classification results compared to the state-of-the-art methods.

A solar cycle dependence of nonlinearity in magnetospheric activity

NASA Astrophysics Data System (ADS)

Johnson, Jay R.; Wing, Simon

2005-04-01

The nonlinear dependencies inherent to the historical Kp data stream (1932-2003) are examined using mutual information and cumulant-based cost as discriminating statistics. The discriminating statistics are compared with surrogate data streams that are constructed using the corrected amplitude adjustment Fourier transform (CAAFT) method and capture the linear properties of the original Kp data. Differences are regularly seen in the discriminating statistics a few years prior to solar minima, while no differences are apparent at the time of solar maxima. These results suggest that the dynamics of the magnetosphere tend to be more linear at solar maximum than at solar minimum. The strong nonlinear dependencies tend to peak on a timescale around 40-50 hours and are statistically significant up to 1 week. Because the solar wind driver variables, VBs, and dynamical pressure exhibit a much shorter decorrelation time for nonlinearities, the results seem to indicate that the nonlinearity is related to internal magnetospheric dynamics. Moreover, the timescales for the nonlinearity seem to be on the same order as that for storm/ring current relaxation. We suggest that the strong solar wind driving that occurs around solar maximum dominates the magnetospheric dynamics, suppressing the internal magnetospheric nonlinearity. On the other hand, in the descending phase of the solar cycle just prior to solar minimum, when magnetospheric activity is weaker, the dynamics exhibit a significant nonlinear internal magnetospheric response that may be related to increased solar wind speed.

Comparison of Three Contemporary Risk Scores for Mortality Following Elective Abdominal Aortic Aneurysm Repair

PubMed Central

Grant, S.W.; Hickey, G.L.; Carlson, E.D.; McCollum, C.N.

2014-01-01

Objective/background A number of contemporary risk prediction models for mortality following elective abdominal aortic aneurysm (AAA) repair have been developed. Before a model is used either in clinical practice or to risk-adjust surgical outcome data it is important that its performance is assessed in external validation studies. Methods The British Aneurysm Repair (BAR) score, Medicare, and Vascular Governance North West (VGNW) models were validated using an independent prospectively collected sample of multicentre clinical audit data. Consecutive, data on 1,124 patients undergoing elective AAA repair at 17 hospitals in the north-west of England and Wales between April 2011 and March 2013 were analysed. The outcome measure was in-hospital mortality. Model calibration (observed to expected ratio with chi-square test, calibration plots, calibration intercept and slope) and discrimination (area under receiver operating characteristic curve [AUC]) were assessed in the overall cohort and procedural subgroups. Results The mean age of the population was 74.4 years (SD 7.7); 193 (17.2%) patients were women and the majority of patients (759, 67.5%) underwent endovascular aneurysm repair. All three models demonstrated good calibration in the overall cohort and procedural subgroups. Overall discrimination was excellent for the BAR score (AUC 0.83, 95% confidence interval [CI] 0.76–0.89), and acceptable for the Medicare and VGNW models, with AUCs of 0.78 (95% CI 0.70–0.86) and 0.75 (95% CI 0.65–0.84) respectively. Only the BAR score demonstrated good discrimination in procedural subgroups. Conclusion All three models demonstrated good calibration and discrimination for the prediction of in-hospital mortality following elective AAA repair and are potentially useful. The BAR score has a number of advantages, which include being developed on the most contemporaneous data, excellent overall discrimination, and good performance in procedural subgroups. Regular model validations and recalibration will be essential. PMID:24837173

Comparison of three contemporary risk scores for mortality following elective abdominal aortic aneurysm repair.

PubMed

Grant, S W; Hickey, G L; Carlson, E D; McCollum, C N

2014-07-01

A number of contemporary risk prediction models for mortality following elective abdominal aortic aneurysm (AAA) repair have been developed. Before a model is used either in clinical practice or to risk-adjust surgical outcome data it is important that its performance is assessed in external validation studies. The British Aneurysm Repair (BAR) score, Medicare, and Vascular Governance North West (VGNW) models were validated using an independent prospectively collected sample of multicentre clinical audit data. Consecutive, data on 1,124 patients undergoing elective AAA repair at 17 hospitals in the north-west of England and Wales between April 2011 and March 2013 were analysed. The outcome measure was in-hospital mortality. Model calibration (observed to expected ratio with chi-square test, calibration plots, calibration intercept and slope) and discrimination (area under receiver operating characteristic curve [AUC]) were assessed in the overall cohort and procedural subgroups. The mean age of the population was 74.4 years (SD 7.7); 193 (17.2%) patients were women and the majority of patients (759, 67.5%) underwent endovascular aneurysm repair. All three models demonstrated good calibration in the overall cohort and procedural subgroups. Overall discrimination was excellent for the BAR score (AUC 0.83, 95% confidence interval [CI] 0.76-0.89), and acceptable for the Medicare and VGNW models, with AUCs of 0.78 (95% CI 0.70-0.86) and 0.75 (95% CI 0.65-0.84) respectively. Only the BAR score demonstrated good discrimination in procedural subgroups. All three models demonstrated good calibration and discrimination for the prediction of in-hospital mortality following elective AAA repair and are potentially useful. The BAR score has a number of advantages, which include being developed on the most contemporaneous data, excellent overall discrimination, and good performance in procedural subgroups. Regular model validations and recalibration will be essential. Copyright © 2014 European Society for Vascular Surgery. Published by Elsevier Ltd. All rights reserved.

Texture-Based Analysis of 100 MR Examinations of Head and Neck Tumors - Is It Possible to Discriminate Between Benign and Malignant Masses in a Multicenter Trial?

PubMed

Fruehwald-Pallamar, J; Hesselink, J R; Mafee, M F; Holzer-Fruehwald, L; Czerny, C; Mayerhoefer, M E

2016-02-01

To evaluate whether texture-based analysis of standard MRI sequences can help in the discrimination between benign and malignant head and neck tumors. The MR images of 100 patients with a histologically clarified head or neck mass, from two different institutions, were analyzed. Texture-based analysis was performed using texture analysis software, with region of interest measurements for 2 D and 3 D evaluation independently for all axial sequences. COC, RUN, GRA, ARM, and WAV features were calculated for all ROIs. 10 texture feature subsets were used for a linear discriminant analysis, in combination with k-nearest-neighbor classification. Benign and malignant tumors were compared with regard to texture-based values. There were differences in the images from different field-strength scanners, as well as from different vendors. For the differentiation of benign and malignant tumors, we found differences on STIR and T2-weighted images for 2 D, and on contrast-enhanced T1-TSE with fat saturation for 3 D evaluation. In a separate analysis of the subgroups 1.5 and 3 Tesla, more discriminating features were found. Texture-based analysis is a useful tool in the discrimination of benign and malignant tumors when performed on one scanner with the same protocol. We cannot recommend this technique for the use of multicenter studies with clinical data. 2 D/3 D texture-based analysis can be performed in head and neck tumors. Texture-based analysis can differentiate between benign and malignant masses. Analyzed MR images should originate from one scanner with an identical protocol. © Georg Thieme Verlag KG Stuttgart · New York.

Workplace discrimination and health among Filipinos in the United States.

PubMed

de Castro, Arnold B; Gee, Gilbert C; Takeuchi, David T

2008-03-01

We examined the association between work discrimination and morbidity among Filipinos in the United States, independent of more-global measures of discrimination. Data were collected from the Filipino American Community Epidemiological Survey. Our analysis focused on 1652 participants who were employed at the time of data collection, and we used negative binomial regression to determine the association between work discrimination and health conditions. The report of workplace discrimination specific to being Filipino was associated with an increased number of health conditions. This association persisted even after we controlled for everyday discrimination, a general assessment of discrimination; job concerns, a general assessment of unpleasant work circumstances; having immigrated for employment reasons; job category; income; education; gender; and other sociodemographic factors. Racial discrimination in the workplace was positively associated with poor health among Filipino Americans after we controlled for reports of everyday discrimination and general concerns about one's job. This finding shows the importance of considering the work setting as a source of discrimination and its effect on morbidity among racial minorities.

The Role of Discrimination in Care Postponement Among Trans-Feminine Individuals in the U.S. National Transgender Discrimination Survey.

PubMed

Glick, Jennifer L; Theall, Katherine P; Andrinopoulos, Katherine M; Kendall, Carl

2018-04-01

This study examines the associations between discrimination experiences (types and locations) and care postponement among trans-feminine individuals in the United States. This secondary, cross-sectional study utilized a subset of the data from the National Transgender Discrimination Survey (n = 2248), specifically for trans-feminine individuals. In this analysis, we examined the relationship between discrimination and primary care postponement. Twenty-six percent (26.25%) of the study sample reported delaying preventive care due to fear of discrimination; 23.98%-46.66% of respondents reported past experiences of discrimination (setting dependent). Discrimination in health and non-health settings and different types of discrimination-being denied services, verbally harassed, or physically assaulted-were all significantly associated with delaying care; respondents reporting discrimination were up to 20 times more likely to postpone care. While discrimination at a health location had the strongest association with care postponement (adjusted odds ratio = 9.65, confidence interval = 7.60-12.24), discrimination in all non-health-related locations was also important. Individuals reporting discrimination in greater numbers of locations and multiple types of discrimination were more likely to postpone care. To promote preventive care-seeking, these results affirm the importance of interventions that promote discrimination-free environments for gender minorities.

Analysis of the Tikhonov regularization to retrieve thermal conductivity depth-profiles from infrared thermography data

NASA Astrophysics Data System (ADS)

Apiñaniz, Estibaliz; Mendioroz, Arantza; Salazar, Agustín; Celorrio, Ricardo

2010-09-01

We analyze the ability of the Tikhonov regularization to retrieve different shapes of in-depth thermal conductivity profiles, usually encountered in hardened materials, from surface temperature data. Exponential, oscillating, and sigmoidal profiles are studied. By performing theoretical experiments with added white noises, the influence of the order of the Tikhonov functional and of the parameters that need to be tuned to carry out the inversion are investigated. The analysis shows that the Tikhonov regularization is very well suited to reconstruct smooth profiles but fails when the conductivity exhibits steep slopes. We check a natural alternative regularization, the total variation functional, which gives much better results for sigmoidal profiles. Accordingly, a strategy to deal with real data is proposed in which we introduce this total variation regularization. This regularization is applied to the inversion of real data corresponding to a case hardened AISI1018 steel plate, giving much better anticorrelation of the retrieved conductivity with microindentation test data than the Tikhonov regularization. The results suggest that this is a promising way to improve the reliability of local inversion methods.

Sequential Ideal-Observer Analysis of Visual Discriminations.

ERIC Educational Resources Information Center

Geisler, Wilson S.

1989-01-01

A new analysis, based on the concept of the ideal observer in signal detection theory, is described. It allows: tracing of the flow of discrimination information through the initial physiological stages of visual processing for arbitrary spatio-chromatic stimuli, and measurement of the information content of said visual stimuli. (TJH)

Prediction of Recidivism in Juvenile Offenders Based on Discriminant Analysis.

ERIC Educational Resources Information Center

Proefrock, David W.

The recent development of strong statistical techniques has made accurate predictions of recidivism possible. To investigate the utility of discriminant analysis methodology in making predictions of recidivism in juvenile offenders, the court records of 271 male and female juvenile offenders, aged 12-16, were reviewed. A cross validation group…

Fourier transform infrared spectroscopy and chemometrics for the characterization and discrimination of writing/photocopier paper types: Application in forensic document examinations

NASA Astrophysics Data System (ADS)

Kumar, Raj; Kumar, Vinay; Sharma, Vishal

2017-01-01

The aim of the present work is to explore the non-destructive application of ATR-FTIR technique for characterization and discrimination of paper samples which could be helpful to give forensic aid in resolving legal cases. Twenty-four types of paper brands were purchased from local market in and around Chandigarh, India. All the paper samples were subjected to ATR-FTIR analysis from 400 to 4000 cm- 1 wavenumber range. The qualitative feature and Chemometrics of the obtained spectral data are used for characterization and discrimination. Characterization is achieved by matching the peaks with standards of cellulose and inorganic fillers, a usual constituents of paper. Three different regions of IR, i.e. 400-2000 cm- 1, 2000-4000 cm- 1 and 400-4000 cm- 1 were selected for differentiation by Chemometrics analysis. The discrimination is achieved on the basis of three principal components, i.e. PC 1, PC 2 and PC 3. It is observed that maximum discrimination was procured in the wave number range of i.e. 2000-4000 cm- 1. Discriminating power was calculated on the basis of qualitative features as well, and it is found that the discrimination of paper samples was better achieved by Chemometrics analysis rather than qualitative features. The discriminating power by Chemometrics is 99.64% and which is larger as ever achieved by any group for present number of samples. The present result confirms that this study will be highly useful in forensic document examination work in the legal cases, where the authenticity of the document is challenged. The results are completely analytical and, therefore, overcome the problem encounter in traditional routine light/radiation scanning methods which are still in practice by various questioned document laboratories.

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.

Perceived Discrimination Experiences and Mental Health of Latina/o American Persons

ERIC Educational Resources Information Center

Moradi, Bonnie; Risco, Cristina

2006-01-01

With a sample of 128 Latina/o persons, the present study examined a model that tested direct, indirect, and mediated relations among perceived discrimination, psychological distress, self-esteem, sense of personal control, and acculturation to Latina/o and U.S. cultures. Path analysis of the model indicated that (a) perceived discrimination was…

Their Personal Side of Street-Level Bureaucracy: Discrimination or Neutral Competence?

ERIC Educational Resources Information Center

Thomas, John Clayton

1986-01-01

Analysis of data on citizen contacts with the Cincinnati municipal bureaucracy reveals some possible racial and social discrimination in treatment of citizens, but no discrimination by income. However, municipal administrators appear mostly to be exercising neutral competence in their dealings with citizens, and not always to the disadvantage of…

An Analysis of Discrimination by Real Estate Brokers.

ERIC Educational Resources Information Center

Yinger, John

This paper focuses on designing policies to eliminate discrimination in the sale of single-family houses by analyzing the behavior of the agents who actually do most of the discriminating, namely real estate agents. Discriminatory practices are said to be supported by policies of house builders, lending institutions, and government, and by the…

Kernel PLS-SVC for Linear and Nonlinear Discrimination

NASA Technical Reports Server (NTRS)

Rosipal, Roman; Trejo, Leonard J.; Matthews, Bryan

2003-01-01

A new methodology for discrimination is proposed. This is based on kernel orthonormalized partial least squares (PLS) dimensionality reduction of the original data space followed by support vector machines for classification. Close connection of orthonormalized PLS and Fisher's approach to linear discrimination or equivalently with canonical correlation analysis is described. This gives preference to use orthonormalized PLS over principal component analysis. Good behavior of the proposed method is demonstrated on 13 different benchmark data sets and on the real world problem of the classification finger movement periods versus non-movement periods based on electroencephalogram.

Digital pulse-shape analysis with a TRACE early silicon prototype

NASA Astrophysics Data System (ADS)

Mengoni, D.; Dueñas, J. A.; Assié, M.; Boiano, C.; John, P. R.; Aliaga, R. J.; Beaumel, D.; Capra, S.; Gadea, A.; Gonzáles, V.; Gottardo, A.; Grassi, L.; Herrero-Bosch, V.; Houdy, T.; Martel, I.; Parkar, V. V.; Perez-Vidal, R.; Pullia, A.; Sanchis, E.; Triossi, A.; Valiente Dobón, J. J.

2014-11-01

A highly segmented silicon-pad detector prototype has been tested to explore the performance of the digital pulse shape analysis in the discrimination of the particles reaching the silicon detector. For the first time a 200 μm thin silicon detector, grown using an ordinary floating zone technique, has been shown to exhibit a level discrimination thanks to the fine segmentation. Light-charged particles down to few MeV have been separated, including their punch-through. A coaxial HPGe detector in time coincidence has further confirmed the quality of the particle discrimination.

[Discrimination of varieties of brake fluid using visual-near infrared spectra].

PubMed

Jiang, Lu-lu; Tan, Li-hong; Qiu, Zheng-jun; Lu, Jiang-feng; He, Yong

2008-06-01

A new method was developed to fast discriminate brands of brake fluid by means of visual-near infrared spectroscopy. Five different brands of brake fluid were analyzed using a handheld near infrared spectrograph, manufactured by ASD Company, and 60 samples were gotten from each brand of brake fluid. The samples data were pretreated using average smoothing and standard normal variable method, and then analyzed using principal component analysis (PCA). A 2-dimensional plot was drawn based on the first and the second principal components, and the plot indicated that the clustering characteristic of different brake fluid is distinct. The foregoing 6 principal components were taken as input variable, and the band of brake fluid as output variable to build the discriminate model by stepwise discriminant analysis method. Two hundred twenty five samples selected randomly were used to create the model, and the rest 75 samples to verify the model. The result showed that the distinguishing rate was 94.67%, indicating that the method proposed in this paper has good performance in classification and discrimination. It provides a new way to fast discriminate different brands of brake fluid.

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

PubMed

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

2018-01-16

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

[Phoneme analysis and phoneme discrimination of juvenile speech therapy school students].

PubMed

Franz, S; Rosanowski, F; Eysholdt, U; Hoppe, U

2011-05-01

Phoneme analysis and phoneme discrimination, important factors in acquiring spoken and written language, have been evaluated in juvenile speech therapy school students. The results have been correlated with the results of a school achievement test. The following questions were of interest: Do students in the lower verbal skill segment show pathological phoneme analysis and phoneme discrimination skills? Do the results of the school achievement test differ from the results by students visiting German "Hauptschule"? How does phoneme analysis and phoneme discrimination performance correlate to other tested parameters? 74 students of a speech therapy school ranging from 7 (th) to 9 (th) grade were examined (ages 12;10-17;04) with the Heidelberg Phoneme Discrimination Test H-LAD and the school achievement test "Prüfsystem für Schul- und Bildungsberatung PSB-R 6-13". Compared to 4 (th) graders the juvenile speech therapy school students showed worse results in the H-LAD test with good differentiation in the lower measuring range. In the PSB-R 6-13 test the examined students did worse compared to students visiting German "Hauptschule" for all grades except 9 (th) grade. Comparing H-LAD and PSB-R 6-13 shows a significant correlation for the sub-tests covering language competence and intelligence but not for the concentration tests. Pathological phoneme analysis and phoneme discrimination skills suggest elevated need for counseling, but this needs to corroborated through additional linguistic parameters and measuring non-verbal intelligence. Further trails are needed in order to clarify whether the results can lead to sophisticated therapy algorithms for educational purposes. © Georg Thieme Verlag KG Stuttgart · New York.

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

PubMed

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

2016-06-01

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

[Men who have sex with men and human immunodeficiency virus testing in dental practice].

PubMed

Elizondo, Jesús Eduardo; Treviño, Ana Cecilia; Violant, Deborah; Rivas-Estilla, Ana María; Álvarez, Mario Moisés

To explore the attitudes of men who have sex with men (MSM) towards the implementation of rapid HIV-1/2 testing in the dental practice, and to evaluate MSM's perceptions of stigma and discrimination related to sexual orientation by dental care professionals. Cross-sectional study using a self-administered, anonymous, structured analytical questionnaire answered by 185 MSM in Mexico. The survey included sociodemographic variables, MSM's perceptions towards public and private dental providers, and dental services, as well as their perception towards rapid HIV-1/2 testing in the dental practice. In addition, the perception of stigma and discrimination associated with their sexual orientation was explored by designing a psychometric Likert-type scale. The statistical analysis included factor analysis and non-hierarchical cluster analysis. 86.5% of the respondents expressed their willingness to take a rapid HIV-1/2 screening test during their dental visit. Nevertheless, 91.9% of them considered it important that dental professionals must be well-trained before administering any rapid HIV-1/2 tests. Factor analysis revealed two factors: experiences of sexual orientation stigma and discrimination in dental settings, and feelings of concern about the attitude of the dentist and dental staff towards their sexual orientation. Based on these factors and cluster analysis, three user profiles were identified: users who have not experienced stigma and discrimination (90.3%); users who have not experienced stigma and discrimination, but feel a slight concern (8.1%), and users who have experienced some form of discrimination and feel concern (1.6%). The dental practice may represent a potential location for rapid HIV-1/2 testing contributing to early HIV infection diagnosis. Copyright © 2017 SESPAS. Publicado por Elsevier España, S.L.U. All rights reserved.

Meta-analysis of studies assessing the efficacy of projective techniques in discriminating child sexual abuse.

PubMed

West, M M

1998-11-01

This meta-analysis of 12 studies assesses the efficacy of projective techniques to discriminate between sexually abused children and nonsexually abused children. A literature search was conducted to identify published studies that used projective instruments with sexually abused children. Those studies that reported statistics that allowed for an effect size to be calculated, were then included in the meta-analysis. There were 12 studies that fit the criteria. The projectives reviewed include The Rorschach, The Hand Test, The Thematic Apperception Test (TAT), the Kinetic Family Drawings, Human Figure Drawings, Draw Your Favorite Kind of Day, The Rosebush: A Visualization Strategy, and The House-Tree-Person. The results of this analysis gave an over-all effect size of d = .81, which is a large effect. Six studies included only a norm group of nondistressed, nonabused children with the sexual abuse group. The average effect size was d = .87, which is impressive. Six studies did include a clinical group of distressed nonsexually abused subjects and the effect size lowered to d = .76, which is a medium to large effect. This indicates that projective instruments can discriminate distressed children from nondistressed subjects, quite well. In the studies that included a clinical group of distressed children who were not sexually abused, the lower effect size indicates that the instruments were less able to discriminate the type of distress. This meta-analysis gives evidence that projective techniques have the ability to discriminate between children who have been sexually abused and those who were not abused sexually. However, further research that is designed to include clinical groups of distressed children is needed in order to determine how well the projectives can discriminate the type of distress.

Vigilance in the discrimination-stress model for Black Americans

PubMed Central

Himmelstein, Mary S.; Young, Danielle M.; Sanchez, Diana T.; Jackson, James S.

2015-01-01

Objective Daily events of discrimination are important factors in understanding health disparities. Vigilant coping, or protecting against anticipated discrimination by monitoring and modifying behaviour, is an understudied mechanism that may link discrimination and health outcomes. This study investigates how responding to everyday discrimination with anticipatory vigilance relates to the health of Black men and women. Methods Black adults (N = 221) from the Detroit area completed measures of discrimination, adverse life events, vigilance coping, stress, depressive symptoms and self-reported health. Results Vigilance coping strategies mediated the relationship between discrimination and stress. Multi-group path analysis revealed that stress in turn was associated with increased depression in men and women. Self-reported health consequences of stress differed between men and women. Conclusions Vigilance coping mediates the link between discrimination and stress, and stress has consequences for health outcomes resulting from discrimination. More research is needed to understand other underlying contributors to discrimination, stress and poor health outcomes as well as to create potential interventions to ameliorate health outcomes in the face of discrimination-related stress. PMID:25247925

Automated Texture Classification of the Mawrth Vallis Landing Site Region

NASA Astrophysics Data System (ADS)

Parente, M.; Bayley, L.; Hunkins, L.; McKeown, N. K.; Bishop, J. L.

2009-12-01

Supervised classification techniques have been developed to discriminate geomorphologic units in HiRISE images of Mawrth Vallis on Mars, one of the MSL candidate landing sites. A variety of clay minerals that indicate water was once present have been identified in the ancient bedrock at Mawrth Vallis [1-7]. These clay-rich rocks exhibit distinct surface textures in HiRISE images, where the nontronite-bearing unit consists of two primary textures: 2-5 m irregular inverted polygons and irregular parallel fracture sets ([8,13], Fig. b-c). In contrast, the montmorillonite-bearing unit consists of 0.5-1.5 m regular polygons ([8,13], Fig. e). We also characterized dunes (Fig. d), and the spectrally unremarkable caprock unit (Fig. a). Classification of these textures was performed by extracting discriminatory features from gray-level run length matrices (GLRLMs) [9], gray-level co-occurrence matrices (GLCMs) [10], and semivariograms [11] calculated for small blocks of data in HiRISE images. Preliminary results using an algorithm containing eight of these classification features produced a texture classification technique that is 85 percent accurate. The discriminant analysis (e.g. [12]) classifier we used modeled a linear discriminant function for each class based on the training feature vectors for that class. The test vector with the largest value for its discriminant function was then assigned to each class. We assumed linear functions were acceptable for small training sets and we performed automated selection in order to identify the most discriminative features for the textures in Mawrth Vallis. Continued efforts are underway to test and refine this procedure in order to optimize texture recognition on a broader collection of textures, representing additional surface components from Mawrth Vallis and other landing sites on Mars. [1] Bibring, J.-P., et al. (2005) Science, 307, 1576-1581. [2] Poulet, F., et al. (2005) Nature, 438, 632-627. [3] Bishop, J. L., et al. (2008) Science, 321, 830-833. [4] Wray, J. J., et al. (2008) GRL, 35, L12202. [5] Loizeau, D., et al. (2009) Icarus, (in press). [6] McKeown, N. K., et al. (2009) JGR- Planets, (in press). [7] Noe Dobrea, E. Z., et al. (2009) JGR- Planets, (in revision). [8] McKeown, N. K. et al. (2009) LPSC abs. #2433. [9] Galloway, M. M., (1975),Computer Graphics and Image Processing 4, 172-179. [10] Haralick, R. M., (1973) IEEE Trans. on Systems, Man and Cybernetics 3, 610-621. [11] Curran, P. J., Remote Sensing of Environment 24, 493-507, 1988. [12] Hastie T., et al. (2005), The elements of statistical learning. Springer. [13] McKeown, N. K., et al. (2009) AGU

Motives for adult participation in physical activity: type of activity, age, and gender.

PubMed

Molanorouzi, Keyvan; Khoo, Selina; Morris, Tony

2015-01-31

In recent years, there has been a decline in physical activity among adults. Motivation has been shown to be a crucial factor in maintaining physical activity. The purpose of this study was to examine whether motives for participation could accurately discriminate gender, age, and type of physical activity. A quantitative, cross-sectional descriptive research design was employed. The Physical Activity and Leisure Motivation Scale (PALMS) was used to assess motives for physical activity in 1,360 adults (703 males, 657 females) who had been exercising regularly for at least six months. The PALMS consists of 40 items that constitute eight sub-scales (mastery, enjoyment, psychological condition, physical condition, appearance, others' expectations, affiliation, competition/ego). Respondents were divided into two age groups (young adults aged 20 to 40 years and middle-aged adults 41 to 64 years) and five types of activity (individual racing sports plus bowls, team sports, racquet sports, martial arts, and exercise). The group discriminant function analyses revealed significant canonical functions correctly classifying the cases into gender (82%), age group (83%), team sport players 76%, individual racing sport plus bowls players 91%, racquet sport players 90%, exercisers 84%, and martial art players 91%. The competition/ego, appearance, physical condition, and mastery sub-scales contributed most to gender differences. Five sub-scales (mastery, psychological condition, others' expectations, affiliation, and enjoyment) contributed most to the discriminant function for age. For type of activity, different sub-scales were the strongest contributors to the discriminant function for each type of PA. The findings in this study suggest that strong and important motives for participation in physical activity are different across type of activity, age, and gender in adults. Understanding the motives that influence physical activity participation is critical for developing interventions to promote higher levels of involvement.

Numeral size, spacing between targets, and exposure time in discrimination by elderly people using an lcd monitor.

PubMed

Huang, Kuo-Chen; Yeh, Po-Chan

2007-04-01

The present study investigated the effects of numeral size, spacing between targets, and exposure time on the discrimination performance by elderly and younger people using a liquid crystal display screen. Analysis showed size of numerals significantly affected discrimination, which increased with increasing numeral size. Spacing between targets also had a significant effect on discrimination, i.e., the larger the space between numerals, the better their discrimination. When the spacing between numerals increased to 4 or 5 points, however, discrimination did not increase beyond that for 3-point spacing. Although performance increased with increasing exposure time, the difference in discrimination at an exposure time of 0.8 vs 1.0 sec. was not significant. The accuracy by the elderly group was less than that by younger subjects.

Racial discrimination and cortisol output: A meta-analysis.

PubMed

Korous, Kevin M; Causadias, José M; Casper, Deborah M

2017-11-01

Although the relation between stress and physiology is well documented, attempts at understanding the link between racial discrimination and cortisol output, specifically, have produced mixed results, likely due to study characteristics such as racial/ethnic composition of the samples (e.g., African American, Latino), measures of discrimination, and research design (e.g., cross-sectional, experimental). To estimate the overall association between racial discrimination and cortisol output among racial/ethnic minority individuals and to determine if the association between racial discrimination and cortisol output is moderated by age, race/ethnicity, type of discrimination measure, sex, and research design. Using a random effects model, the overall effect size based on k = 16 studies (19% unpublished) and N = 1506 participants was r¯ = 0.040, 95% CI = -0.038 to 0.117. Studies were conducted predominantly in the U.S. (81%). Notably, experimental studies (r¯ = 0.267) exhibited larger effect sizes compared to non-experimental studies (r¯ = -0.007). Age, race/ethnicity, type of discrimination measure, and sex did not moderate the effect sizes. This meta-analysis provides evidence that the measurement of the association between racial discrimination and cortisol is complex, and it offers valuable insight regarding methods and designs that can inform future research on this topic. Limitations and future directions are discussed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fine-Scale Skeletal Banding Can Distinguish Symbiotic from Asymbiotic Species among Modern and Fossil Scleractinian Corals.

PubMed

Frankowiak, Katarzyna; Kret, Sławomir; Mazur, Maciej; Meibom, Anders; Kitahara, Marcelo V; Stolarski, Jarosław

2016-01-01

Understanding the evolution of scleractinian corals on geological timescales is key to predict how modern reef ecosystems will react to changing environmental conditions in the future. Important to such efforts has been the development of several skeleton-based criteria to distinguish between the two major ecological groups of scleractinians: zooxanthellates, which live in symbiosis with dinoflagellate algae, and azooxanthellates, which lack endosymbiotic dinoflagellates. Existing criteria are based on overall skeletal morphology and bio/geo-chemical indicators-none of them being particularly robust. Here we explore another skeletal feature, namely fine-scale growth banding, which differs between these two groups of corals. Using various ultra-structural imaging techniques (e.g., TEM, SEM, and NanoSIMS) we have characterized skeletal growth increments, composed of doublets of optically light and dark bands, in a broad selection of extant symbiotic and asymbiotic corals. Skeletons of zooxanthellate corals are characterized by regular growth banding, whereas in skeletons of azooxanthellate corals the growth banding is irregular. Importantly, the regularity of growth bands can be easily quantified with a coefficient of variation obtained by measuring bandwidths on SEM images of polished and etched skeletal surfaces of septa and/or walls. We find that this coefficient of variation (lower values indicate higher regularity) ranges from ~40 to ~90% in azooxanthellate corals and from ~5 to ~15% in symbiotic species. With more than 90% (28 out of 31) of the studied corals conforming to this microstructural criterion, it represents an easy and robust method to discriminate between zooxanthellate and azooxanthellate corals. This microstructural criterion has been applied to the exceptionally preserved skeleton of the Triassic (Norian, ca. 215 Ma) scleractinian Volzeia sp., which contains the first example of regular, fine-scale banding of thickening deposits in a fossil coral of this age. The regularity of its growth banding strongly suggests that the coral was symbiotic with zooxanthellates.

Fine-Scale Skeletal Banding Can Distinguish Symbiotic from Asymbiotic Species among Modern and Fossil Scleractinian Corals

PubMed Central

Frankowiak, Katarzyna; Kret, Sławomir; Mazur, Maciej; Meibom, Anders; Kitahara, Marcelo V.; Stolarski, Jarosław

2016-01-01

Understanding the evolution of scleractinian corals on geological timescales is key to predict how modern reef ecosystems will react to changing environmental conditions in the future. Important to such efforts has been the development of several skeleton-based criteria to distinguish between the two major ecological groups of scleractinians: zooxanthellates, which live in symbiosis with dinoflagellate algae, and azooxanthellates, which lack endosymbiotic dinoflagellates. Existing criteria are based on overall skeletal morphology and bio/geo-chemical indicators—none of them being particularly robust. Here we explore another skeletal feature, namely fine-scale growth banding, which differs between these two groups of corals. Using various ultra-structural imaging techniques (e.g., TEM, SEM, and NanoSIMS) we have characterized skeletal growth increments, composed of doublets of optically light and dark bands, in a broad selection of extant symbiotic and asymbiotic corals. Skeletons of zooxanthellate corals are characterized by regular growth banding, whereas in skeletons of azooxanthellate corals the growth banding is irregular. Importantly, the regularity of growth bands can be easily quantified with a coefficient of variation obtained by measuring bandwidths on SEM images of polished and etched skeletal surfaces of septa and/or walls. We find that this coefficient of variation (lower values indicate higher regularity) ranges from ~40 to ~90% in azooxanthellate corals and from ~5 to ~15% in symbiotic species. With more than 90% (28 out of 31) of the studied corals conforming to this microstructural criterion, it represents an easy and robust method to discriminate between zooxanthellate and azooxanthellate corals. This microstructural criterion has been applied to the exceptionally preserved skeleton of the Triassic (Norian, ca. 215 Ma) scleractinian Volzeia sp., which contains the first example of regular, fine-scale banding of thickening deposits in a fossil coral of this age. The regularity of its growth banding strongly suggests that the coral was symbiotic with zooxanthellates. PMID:26751803

Workplace Discrimination Is Associated With Alcohol Abuse Among Ethnically Diverse Hospital Staff.

PubMed

Thrasher, Angela D; Wells, Anita M; Spencer, S Melinda; Cofie, Leslie; Yen, Irene H

2016-05-01

Research suggests that workplace discrimination plays a role in absenteeism, productivity, and turnover. A link among workplace discrimination, mental health, and health disparities may also exist. The purpose of this study was to determine whether self-reported workplace discrimination is associated with alcohol abuse among hospital workers. Cross-sectional analysis of baseline data collected from a prospective cohort study of workers in two healthcare institutions (n = 664) was conducted. Workplace discrimination in the previous 12 months was reported by 14% (n = 91) of participants who were four times more likely to score higher on likely alcohol abuse than their peers. White participants who reported any discrimination were more likely to score higher on likely alcohol abuse than racial/ethnic minority participants who reported any discrimination. Given a diversifying workforce, further research is needed on how workplace discrimination contributes to stress and maladaptive coping, and ultimately health disparities. © 2016 The Author(s).

On convergence and convergence rates for Ivanov and Morozov regularization and application to some parameter identification problems in elliptic PDEs

NASA Astrophysics Data System (ADS)

Kaltenbacher, Barbara; Klassen, Andrej

2018-05-01

In this paper we provide a convergence analysis of some variational methods alternative to the classical Tikhonov regularization, namely Ivanov regularization (also called the method of quasi solutions) with some versions of the discrepancy principle for choosing the regularization parameter, and Morozov regularization (also called the method of the residuals). After motivating nonequivalence with Tikhonov regularization by means of an example, we prove well-definedness of the Ivanov and the Morozov method, convergence in the sense of regularization, as well as convergence rates under variational source conditions. Finally, we apply these results to some linear and nonlinear parameter identification problems in elliptic boundary value problems.

Perceived discrimination and sexual precursor behaviors in Mexican American preadolescent girls: The role of psychological distress, sexual attitudes, and marianismo beliefs.

PubMed

Sanchez, Delida; Whittaker, Tiffany A; Hamilton, Emma; Zayas, Luis H

2016-07-01

This study explored the relation between perceived discrimination and sexual precursor behaviors among 205 Mexican American preadolescent middle school girls. In addition, this study examined whether psychological distress and sexual attitudes mediated and whether marianismo beliefs moderated this relation. A categorical confirmatory factor analysis (CCFA) of the Marianismo Beliefs Scale (MBS) was conducted to test the factor structure with a preadolescent Mexican American population (ages 11-14). A path analysis of analytic models was then performed to examine the hypothesized relations between perceived discrimination, psychological distress, sexual attitudes, marianismo beliefs, and sexual precursor behaviors. Results of the CCFA did not support the original 5-factor structure of the MBS for preadolescent Latina girls. However, a revised version of the MBS indicated an acceptable model fit, and findings from the path analysis indicated that perceived discrimination was both directly and indirectly linked to sexual precursor behaviors via psychological distress. Marianismo was not found to moderate the relation between perceived discrimination and sexual risk behaviors, however certain marianismo pillars were significantly negatively linked with sexual attitudes and precursor behaviors. This study underscores the importance of psychological distress in the perceived discrimination and sexual precursor link as well as the compensatory aspects of marianismo against sexual precursor behaviors in Mexican American preadolescent girls. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

[Identification of Dendrobium varieties by infrared spectroscopy].

PubMed

Liu, Fei; Wang, Yuan-Zhong; Yang, Chun-Yan; Jin, Hang

2014-11-01

The difference of Dendrobium varieties were analyzed by Fourier transform infrared (FTIR) spectroscopy. The infrared spectra of 206 stems from 30 Dendrobium varieties were obtained, and showed that polysaccharides, especially fiber, were the main components in Dendrobium plants. FTIR combined with Wilks' Lambda stepwise discriminative analysis was used to identify Dendrobium varieties. The effects of spectral range and number of training samples on the discrimination results were also analysed. Two hundred eighty seven variables in the spectral range of 1 800-1 250 cm(-1) were studied, and showed that the return discrimination is 100% correct when the training samples number of each species was 2, 3, 4, 5, and 6, respectively, whereas for the remaining samples the correct rates of identification were equal to 79.4%, 91.3%, 93.0%, 98.2%, and 100%, respectively. The same discriminative analyses on five different training samples in the spectral range of 1 800-1 500, 1 500-1 250, 1 250-600, 1 250-950 and 950-650 cm(-1) were compared, which showed that the variables in the range of 1 800-1 250, 1 800-1 500 and 950-600 cm(-1) were more suitable for variety identification, and one can obtain the satisfactory result for discriminative analysis when the training sample is more than 3. Our results indicate that FTIR combined with stepwise discriminative analysis is an effective way to distinguish different Dendrobium varieties.

A novel typing method for Listeria monocytogenes using high-resolution melting analysis (HRMA) of tandem repeat regions.

PubMed

Ohshima, Chihiro; Takahashi, Hajime; Iwakawa, Ai; Kuda, Takashi; Kimura, Bon

2017-07-17

Listeria monocytogenes, which is responsible for causing food poisoning known as listeriosis, infects humans and animals. Widely distributed in the environment, this bacterium is known to contaminate food products after being transmitted to factories via raw materials. To minimize the contamination of products by food pathogens, it is critical to identify and eliminate factory entry routes and pathways for the causative bacteria. High resolution melting analysis (HRMA) is a method that takes advantage of differences in DNA sequences and PCR product lengths that are reflected by the disassociation temperature. Through our research, we have developed a multiple locus variable-number tandem repeat analysis (MLVA) using HRMA as a simple and rapid method to differentiate L. monocytogenes isolates. While evaluating our developed method, the ability of MLVA-HRMA, MLVA using capillary electrophoresis, and multilocus sequence typing (MLST) was compared for their ability to discriminate between strains. The MLVA-HRMA method displayed greater discriminatory ability than MLST and MLVA using capillary electrophoresis, suggesting that the variation in the number of repeat units, along with mutations within the DNA sequence, was accurately reflected by the melting curve of HRMA. Rather than relying on DNA sequence analysis or high-resolution electrophoresis, the MLVA-HRMA method employs the same process as PCR until the analysis step, suggesting a combination of speed and simplicity. The result of MLVA-HRMA method is able to be shared between different laboratories. There are high expectations that this method will be adopted for regular inspections at food processing facilities in the near future. Copyright © 2017. Published by Elsevier B.V.

Teleradiology from the provider's perspective-cost analysis for a mid-size university hospital.

PubMed

Rosenberg, Christian; Kroos, Kristin; Rosenberg, Britta; Hosten, Norbert; Flessa, Steffen

2013-08-01

Real costs of teleradiology services have not been systematically calculated. Pricing policies are not evidence-based. This study aims to prove the feasibility of performing an original cost analysis for teleradiology services and show break-even points to perform cost-effective practice. Based on the teleradiology services provided by the Greifswald University Hospital in northeastern Germany, a detailed process analysis and an activity-based costing model revealed costs per service unit according to eight examination categories. The Monte Carlo method was used to simulate the cost amplitude and identify pricing thresholds. Twenty-two sub-processes and four staff categories were identified. The average working time for one unit was 55 (x-ray) to 72 min (whole-body CT). Personnel costs were dominant (up to 68 %), representing lower limit costs. The Monte Carlo method showed the cost distribution per category according to the deficiency risk. Avoiding deficient pricing by a likelihood of 90 % increased the cost of a cranial CT almost twofold as compared with the lower limit cost. Original cost analysis is possible when providing teleradiology services with complex statutory requirements in place. Methodology and results provide useful data to help enhance efficiency in hospital management as well as implement realistic reimbursement fees. • Analysis of original costs of teleradiology is possible for a providing hospital • Results discriminate pricing thresholds and lower limit costs to perform cost-effective practice • The study methods represent a managing tool to enhance efficiency in providing facilities • The data are useful to help represent telemedicine services in regular medical fee schedules.

Differentiating sex and species of Western Grebes (Aechmophorus occidentalis) and Clark's Grebes (Aechmophorus clarkii) and their eggs using external morphometrics and discriminant function analysis

USGS Publications Warehouse

Hartman, C. Alex; Ackerman, Joshua T.; Eagles-Smith, Collin A.; Herzog, Mark

2016-01-01

In birds where males and females are similar in size and plumage, sex determination by alternative means is necessary. Discriminant function analysis based on external morphometrics was used to distinguish males from females in two closely related species: Western Grebe (Aechmophorus occidentalis) and Clark's Grebe (A. clarkii). Additionally, discriminant function analysis was used to evaluate morphometric divergence between Western and Clark's grebe adults and eggs. Aechmophorus grebe adults (n = 576) and eggs (n = 130) were sampled across 29 lakes and reservoirs throughout California, USA, and adult sex was determined using molecular analysis. Both Western and Clark's grebes exhibited considerable sexual size dimorphism. Males averaged 6–26% larger than females among seven morphological measurements, with the greatest sexual size dimorphism occurring for bill morphometrics. Discriminant functions based on bill length, bill depth, and short tarsus length correctly assigned sex to 98% of Western Grebes, and a function based on bill length and bill depth correctly assigned sex to 99% of Clark's Grebes. Further, a simplified discriminant function based only on bill depth correctly assigned sex to 96% of Western Grebes and 98% of Clark's Grebes. In contrast, external morphometrics were not suitable for differentiating between Western and Clark's grebe adults or their eggs, with correct classification rates of discriminant functions of only 60%, 63%, and 61% for adult males, adult females, and eggs, respectively. Our results indicate little divergence in external morphology between species of Aechmophorus grebes, and instead separation is much greater between males and females.

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.

Development and Validation of Discriminant Analysis Models for Student Loan Defaultees and Non-Defaultees.

ERIC Educational Resources Information Center

Myers, Greeley; Siera, Steven

1980-01-01

Default on guaranteed student loans has been increasing. The use of discriminant analysis as a technique to identify "good" v "bad" student loans based on information available from the loan application is discussed. Research to test the ability of models to such predictions is reported. (Author/MLW)

A new method for fingerprinting sediments source contributions using distances from discriminant function analysis

USDA-ARS?s Scientific Manuscript database

Mixing models have been used to predict sediment source contributions. The inherent problem of the mixing models limited the number of sediment sources. The objective of this study is to develop and evaluate a new method using Discriminant Function Analysis (DFA) to fingerprint sediment source contr...

Signal Detection Methods and Discriminant Analysis Applied to Categorization of Newspaper and Government Documents: A Preliminary Study.

ERIC Educational Resources Information Center

Ng, Kwong Bor; Rieh, Soo Young; Kantor, Paul

2000-01-01

Discussion of natural language processing focuses on experiments using linear discriminant analysis to distinguish "Wall Street Journal" texts from "Federal Register" tests using information about the frequency of occurrence of word boundaries, sentence boundaries, and punctuation marks. Displays and interprets results in terms…

The Economic Status of Migrant Wives: An Application of Discriminant Analysis.

ERIC Educational Resources Information Center

Rytina, Nancy F.

1981-01-01

Lower work rate of migrant wives after moving is a function of moving for husbands' job opportunities and being in the childrearing stage of life. Discriminant analysis reveals that socioeconomic characteristics are lower for nonworking than migrant wives. Working migrant wives have more education and higher status jobs than nonmigrants.…

Practitioner Representations of Environmental Uncertainty: An Application of Discriminant Analysis.

ERIC Educational Resources Information Center

Acharya, Lalit

Multiple discriminant analysis was used to analyze the structure of a perceived environmental uncertainty variable employed previously in research on public relations roles. Data came from a subset (N=229) of a national sample of public relations practitioners belonging to the Public Relations Society of America, who completed a set of scaled…

Metabolomic Approach for Discrimination of Four- and Six-Year-Old Red Ginseng (Panax ginseng) Using UPLC-QToF-MS.

PubMed

Shin, Jung-Sub; Park, Hee-Won; In, Gyo; Seo, Hyun Kyu; Won, Tae Hyung; Jang, Kyoung Hwa; Cho, Byung-Goo; Han, Chang Kyun; Shin, Jongheon

2016-09-01

Panax ginseng C.A. MEYER is one of the most popular medicinal herbs in Asia and the chemical constituents are changed by processing methods such as steaming or sun drying. Metabolomic analysis was performed to distinguish age discrimination of four- and six-year-old red ginseng using ultra-performance liquid chromatography quadruple time of flight mass spectrometry (UPLC-QToF-MS) with multivariate statistical analysis. Principal component analysis (PCA) showed clear discrimination between extracts of red ginseng of different ages and suggest totally six discrimination markers (two for four-year-old and four for six-year-old red ginseng). Among these, one marker was isolated and the structure determined by NMR spectroscopic analysis was 13-cis-docosenamide (marker 6-1) from six-year-old red ginseng. This is the first report of a metabolomic study regarding the age differentiation of red ginseng using UPLC-QToF-MS and determination of the structure of the marker. These results will contribute to the quality control and standardization as well as provide a scientific basis for pharmacological research on red ginseng.

The specter of discrimination: Fear of interpersonal racial discrimination among adolescents in Chicago.

PubMed

Herda, Daniel

2016-01-01

This analysis examines fear of interpersonal racial discrimination among Black, Hispanic, and White adolescents. The extent and correlates of these concerns are examined using survey data from the Project for Human Development in Chicago Neighborhoods. Borrowing from the fear-of-crime literature, the contact hypothesis, and group threat theory, several hypotheses are developed linking discrimination fear to direct personal experience with discrimination, indirect or vicarious experience, and environmental signals of discrimination. Results show that about half of Blacks and Hispanics have feared discrimination in the past year. Multivariate results indicate that fear is most likely if one has experienced victimization first-hand and when one's parent is affected by discrimination. Further, a larger presence neighborhood outgroups produces greater fear. Overall, discrimination fear constitutes an additional obstacle for minority adolescents as they transition to adulthood. The phenomenon warrants increased scholarly attention and represents a fruitful avenue for future research. Copyright © 2015 Elsevier Inc. All rights reserved.

Discrimination of acoustically similar conspecific and heterospecific vocalizations by black-capped chickadees (Poecile atricapillus).

PubMed

Hahn, Allison H; Campbell, Kimberley A; Congdon, Jenna V; Hoang, John; McMillan, Neil; Scully, Erin N; Yong, Joshua J H; Elie, Julie E; Sturdy, Christopher B

2017-07-01

Chickadees produce a multi-note chick-a-dee call in multiple socially relevant contexts. One component of this call is the D note, which is a low-frequency and acoustically complex note with a harmonic-like structure. In the current study, we tested black-capped chickadees on a between-category operant discrimination task using vocalizations with acoustic structures similar to black-capped chickadee D notes, but produced by various songbird species, in order to examine the role that phylogenetic distance plays in acoustic perception of vocal signals. We assessed the extent to which discrimination performance was influenced by the phylogenetic relatedness among the species producing the vocalizations and by the phylogenetic relatedness between the subjects' species (black-capped chickadees) and the vocalizers' species. We also conducted a bioacoustic analysis and discriminant function analysis in order to examine the acoustic similarities among the discrimination stimuli. A previous study has shown that neural activation in black-capped chickadee auditory and perceptual brain regions is similar following the presentation of these vocalization categories. However, we found that chickadees had difficulty discriminating between forward and reversed black-capped chickadee D notes, a result that directly corresponded to the bioacoustic analysis indicating that these stimulus categories were acoustically similar. In addition, our results suggest that the discrimination between vocalizations produced by two parid species (chestnut-backed chickadees and tufted titmice) is perceptually difficult for black-capped chickadees, a finding that is likely in part because these vocalizations contain acoustic similarities. Overall, our results provide evidence that black-capped chickadees' perceptual abilities are influenced by both phylogenetic relatedness and acoustic structure.

Moche CAPE Formula: Cost Analysis of Public Education.

ERIC Educational Resources Information Center

Moche, Joanne Spiers

The Moche Cost Analysis of Public Education (CAPE) formula was developed to identify total and per pupil costs of regular elementary education, regular secondary education, elementary special education, and secondary special education. Costs are analyzed across five components: (1) comprehensive costs (including transportation and supplemental…

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

The Effects of Discrimination Experience on Life Satisfaction of North Korean Refugees: Mediating Effect of Stress

PubMed Central

Noh, Jin-Won; Park, Hyunchun; Kim, Minji; Kwon, Young Dae; Kim, Jin-Seok

2018-01-01

Objective This study investigated the mediation effect of stress between the experience of discrimination and life satisfaction among North Korean refugees who resettled in South Korea. The findings of the current study provide empirical evidence for the need of social interventions to mitigate adverse effects of stress on North Korean refugees who are subject to social discrimination on a daily basis. Methods In this study, we included 500 subjects among 2,138 North Korean refugees who took refuge in South Korea in 2007. The interview started from April 6th 2009 and finished on May 25th 2009. We conducted moderator effect analysis with Path analysis was conducted because we confirm the experience of discrimination was affected by life satisfaction and stress can affected life satisfaction as a moderator. Results The experience of discrimination significantly affects stress and stress significantly affects life satisfaction. However, the experience of discrimination was not directly related to life satisfaction. The more stress the study respondents experienced, the lower the life satisfaction they reported. Conclusion The present finding suggests that the effects of discriminating experiences on the life satisfaction of North Korean refugees in South Korea were mediated by their own perceived stress. PMID:29422925

Gender discrimination in the elderly and its impact on the elderly health.

PubMed

Keskinoglu, Pembe; Ucuncu, Tugba; Yildirim, Idris; Gurbuz, Turgut; Ur, Ismail; Ergor, Gul

2007-01-01

The aim of this study was to determine gender discrimination and risk factors in the elderly population and to assess the impact of that discrimination on elderly health. One hundred and sixty-eight elderly individuals who were selected from the records by simple randomized sampling were enrolled in the study. Data were obtained by face-to-face interviews at the residence of the elderly individuals. Chi(2)-Analysis, t-test, Mann-Whitney U-test, and logistic regression were used for data analysis. 81.1% of the elderly were married and 40.5% were middle or high school graduates, and 93.9% of the subjects had at least one living child. It was determined that 51.7% of the females, and 21.3% of the males were exposed to negative gender discrimination. This discrimination was higher among women in all sub-groups. In fact, older women and elderly individuals with only primary school education or less were significantly more exposed to gender discrimination (p=0.008 and p=0.043, respectively). It was found that only economical variables were related to poor health status, without gender discrimination. Despite the fact that the freedom has been obtained in some areas such as participation in household decision-making and dressing, the patriarchal family structure and sexual inequality continue in older age.

The Chronometry of Mental Ability: An Event-Related Potential Analysis of an Auditory Oddball Discrimination Task

ERIC Educational Resources Information Center

Beauchamp, Chris M.; Stelmack, Robert M.

2006-01-01

The relation between intelligence and speed of auditory discrimination was investigated during an auditory oddball task with backward masking. In target discrimination conditions that varied in the interval between the target and the masking stimuli and in the tonal frequency of the target and masking stimuli, higher ability participants (HA)…

Sex Discrimination--Court Narrows Gilbert--Some Pregnancy Discrimination Is Sex Related.

ERIC Educational Resources Information Center

Allen, Claudia G.; Powers, Jean C.

1978-01-01

Issues concerning sex discrimination based on pregnancy, presented in Nashville Gas Co. vs. Satty, and the Supreme Court's treatment of the issues are examined. The way in which the Satty opinion limits the scope of the General Electric Co. vs. Gilbert decision, and an analysis of the implications of the Satty decision are included. (JMD)

Does Attending Worship Mitigate Racial/Ethnic Discrimination in Influencing Health Behaviors? Results from an Analysis of the California Health Interview Survey

ERIC Educational Resources Information Center

Caldwell, Julia T.; Takahashi, Lois M.

2014-01-01

Existing research suggests that religious institutions play a significant role in improving the health of communities, particularly those coping with racial and ethnic discrimination. Using the California Health Interview Survey, this article examines the relationship of self-reported experiences of racial/ethnic discrimination, worship…

Infants with Williams syndrome detect statistical regularities in continuous speech.

PubMed

Cashon, Cara H; Ha, Oh-Ryeong; Graf Estes, Katharine; Saffran, Jenny R; Mervis, Carolyn B

2016-09-01

Williams syndrome (WS) is a rare genetic disorder associated with delays in language and cognitive development. The reasons for the language delay are unknown. Statistical learning is a domain-general mechanism recruited for early language acquisition. In the present study, we investigated whether infants with WS were able to detect the statistical structure in continuous speech. Eighteen 8- to 20-month-olds with WS were familiarized with 2min of a continuous stream of synthesized nonsense words; the statistical structure of the speech was the only cue to word boundaries. They were tested on their ability to discriminate statistically-defined "words" and "part-words" (which crossed word boundaries) in the artificial language. Despite significant cognitive and language delays, infants with WS were able to detect the statistical regularities in the speech stream. These findings suggest that an inability to track the statistical properties of speech is unlikely to be the primary basis for the delays in the onset of language observed in infants with WS. These results provide the first evidence of statistical learning by infants with developmental delays. Copyright © 2016 Elsevier B.V. All rights reserved.

Development and practical implications of the Exercise Resourcefulness Inventory.

PubMed

Fast, Hilary V; Kennett, Deborah J

2015-05-01

To determine the validity and reliability of the Exercise Resourcefulness Inventory (ERI) designed to assess the self-regulatory strategies used to promote regular exercise. In Study 1, the inventory's relationship with other established scales in the exercise behavior change field was examined. In Study 2, the test-retest reliability and predictive validity of the ERI was established by having participants from Study 1 complete the inventory a second time. Internal consistency, and convergent, discriminant, and concurrent validity were supported in both studies. The test-retest correlation of the ERI was .80. As well, participants scoring higher on the ERI in Study 1 were more likely to be at a higher stage of change in Study 2, and greater increases in exercise resourcefulness over time were predictive of advancement to higher stages of change. ERI is a reliable and valid measure to assess the self-regulatory strategies used to promote regular exercise. Facilitators may want to tailor exercise programs for individuals scoring lower in resourcefulness to prevent them from relapsing. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Changes in the aromatic profile of espresso coffee as a function of the grinding grade and extraction time: a study by the electronic nose system.

PubMed

Severini, C; Ricci, I; Marone, M; Derossi, A; De Pilli, T

2015-03-04

The changes in chemical attributes and aromatic profile of espresso coffee (EC) were studied taking into account the extraction time and grinding level as independent variables. Particularly, using an electronic nose system, the changes of the global aromatic profile of EC were highlighted. The results shown as the major amounts of organic acids, solids, and caffeine were extracted in the first 8 s of percolation. The grinding grade significantly affected the quality of EC probably as an effect of the particle size distribution and the percolation pathways of water through the coffee cake. The use of an electronic nose system allowed us to discriminate the fractions of the brew as a function of the percolation time and also the regular coffee obtained from different grinding grades. Particularly, the aromatic profile of a regular coffee (25 mL) was significantly affected by the grinding level of the coffee grounds and percolation time, which are two variables under the control of the bar operator.

Access to and use of health services among undocumented Mexican immigrants in a US urban area.

PubMed

Nandi, Arijit; Galea, Sandro; Lopez, Gerald; Nandi, Vijay; Strongarone, Stacey; Ompad, Danielle C

2008-11-01

We assessed access to and use of health services among Mexican-born undocumented immigrants living in New York City in 2004. We used venue-based sampling to recruit participants from locations where undocumented immigrants were likely to congregate. Participants were 18 years or older, born in Mexico, and current residents of New York City. The main outcome measures were health insurance coverage, access to a regular health care provider, and emergency department care. In multivariable models, living in a residence with fewer other adults, linguistic acculturation, higher levels of formal income, higher levels of social support, and poor health were associated with health insurance coverage. Female gender, fewer children, arrival before 1997, higher levels of formal income, health insurance coverage, greater social support, and not reporting discrimination were associated with access to a regular health care provider. Higher levels of education, higher levels of formal income, and poor health were associated with emergency department care. Absent large-scale political solutions to the challenges of undocumented immigrants, policies that address factors shown to limit access to care may improve health among this growing population.

Prediction of Happy-Sad Mood from Daily Behaviors and Previous Sleep History

PubMed Central

Sano, Akane; Yu, Amy; McHill, Andrew W.; Phillips, Andrew J. K.; Taylor, Sara; Jaques, Natasha; Klerman, Elizabeth B.; Picard, Rosalind W.

2016-01-01

We collected and analyzed subjective and objective data using surveys and wearable sensors worn day and night from 68 participants, for 30 days each, to address questions related to the relationships among sleep duration, sleep irregularity, self-reported Happy-Sad mood and other factors in college students. We analyzed daily and monthly behavior and physiology and identified factors that affect mood, including how accurately sleep duration and sleep regularity for the past 1-5 days classified the participants into high/low mood using support vector machines. We found statistically significant associations among sad mood and poor health-related factors. Behavioral factors such as the percentage of neutral social interactions and the total academic activity hours showed the best performance in separating the Happy-Sad mood groups. Sleep regularity was a more important discriminator of mood than sleep duration for most participants, although both variables predicted happy/sad mood with from 70-82% accuracy. The number of nights giving the best prediction of happy/sad mood varied for different groups of individuals. PMID:26737854

Second-language learning effects on automaticity of speech processing of Japanese phonetic contrasts: An MEG study.

PubMed

Hisagi, Miwako; Shafer, Valerie L; Miyagawa, Shigeru; Kotek, Hadas; Sugawara, Ayaka; Pantazis, Dimitrios

2016-12-01

We examined discrimination of a second-language (L2) vowel duration contrast in English learners of Japanese (JP) with different amounts of experience using the magnetoencephalography mismatch field (MMF) component. Twelve L2 learners were tested before and after a second semester of college-level JP; half attended a regular rate course and half an accelerated course with more hours per week. Results showed no significant change in MMF for either the regular or accelerated learning group from beginning to end of the course. We also compared these groups against nine L2 learners who had completed four semesters of college-level JP. These 4-semester learners did not significantly differ from 2-semester learners, in that only a difference in hemisphere activation (interacting with time) between the two groups approached significance. These findings suggest that targeted training of L2 phonology may be necessary to allow for changes in processing of L2 speech contrasts at an early, automatic level. Copyright © 2016 Elsevier B.V. All rights reserved.

A regularized approach for geodesic-based semisupervised multimanifold learning.

PubMed

Fan, Mingyu; Zhang, Xiaoqin; Lin, Zhouchen; Zhang, Zhongfei; Bao, Hujun

2014-05-01

Geodesic distance, as an essential measurement for data dissimilarity, has been successfully used in manifold learning. However, most geodesic distance-based manifold learning algorithms have two limitations when applied to classification: 1) class information is rarely used in computing the geodesic distances between data points on manifolds and 2) little attention has been paid to building an explicit dimension reduction mapping for extracting the discriminative information hidden in the geodesic distances. In this paper, we regard geodesic distance as a kind of kernel, which maps data from linearly inseparable space to linear separable distance space. In doing this, a new semisupervised manifold learning algorithm, namely regularized geodesic feature learning algorithm, is proposed. The method consists of three techniques: a semisupervised graph construction method, replacement of original data points with feature vectors which are built by geodesic distances, and a new semisupervised dimension reduction method for feature vectors. Experiments on the MNIST, USPS handwritten digit data sets, MIT CBCL face versus nonface data set, and an intelligent traffic data set show the effectiveness of the proposed algorithm.

The consequences of perceived discrimination for psychological well-being: a meta-analytic review.

PubMed

Schmitt, Michael T; Branscombe, Nyla R; Postmes, Tom; Garcia, Amber

2014-07-01

In 2 meta-analyses, we examined the relationship between perceived discrimination and psychological well-being and tested a number of moderators of that relationship. In Meta-Analysis 1 (328 independent effect sizes, N = 144,246), we examined correlational data measuring both perceived discrimination and psychological well-being (e.g., self-esteem, depression, anxiety, psychological distress, life satisfaction). Using a random-effects model, the mean weighted effect size was significantly negative, indicating harm (r = -.23). Effect sizes were larger for disadvantaged groups (r = -.24) compared to advantaged groups (r = -.10), larger for children compared to adults, larger for perceptions of personal discrimination compared to group discrimination, and weaker for racism and sexism compared to other stigmas. The negative relationship was significant across different operationalizations of well-being but was somewhat weaker for positive outcomes (e.g., self-esteem, positive affect) than for negative outcomes (e.g., depression, anxiety, negative affect). Importantly, the effect size was significantly negative even in longitudinal studies that controlled for prior levels of well-being (r = -.15). In Meta-Analysis 2 (54 independent effect sizes, N = 2,640), we examined experimental data from studies manipulating perceptions of discrimination and measuring well-being. We found that the effect of discrimination on well-being was significantly negative for studies that manipulated general perceptions of discrimination (d = -.25), but effects did not differ from 0 when attributions to discrimination for a specific negative event were compared to personal attributions (d = .06). Overall, results support the idea that the pervasiveness of perceived discrimination is fundamental to its harmful effects on psychological well-being. PsycINFO Database Record (c) 2014 APA, all rights reserved.

Quantitative and Discriminative Evaluation of Contents of Phenolic and Flavonoid and Antioxidant Competence for Chinese Honeys from Different Botanical Origins.

PubMed

Shen, Shi; Wang, Jingbo; Zhuo, Qin; Chen, Xi; Liu, Tingting; Zhang, Shuang-Qing

2018-05-08

Phenolics and flavonoids in honey are considered as the main phytonutrients which not only act as natural antioxidants, but can also be used as floral markers for honey identification. In this study, the chemical profiles of phenolics and flavonoids, antioxidant competences including total phenolic content, DPPH and ABTS assays and discrimination using chemometric analysis of various Chinese monofloral honeys from six botanical origins (acacia, Vitex , linden, rapeseed, Astragalus and Codonopsis ) were examined. A reproducible and sensitive ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) method was optimized and validated for the simultaneous determination of 38 phenolics, flavonoids and abscisic acid in honey. Formononetin, ononin, calycosin and calycosin-7- O -β-d-glucoside were identified and quantified in honeys for the first time. Principal component analysis (PCA) showed obvious differences among the honey samples in three-dimensional space accounting for 72.63% of the total variance. Hierarchical cluster analysis (HCA) also revealed that the botanical origins of honey samples correlated with their phenolic and flavonoid contents. Partial least squares-discriminant analysis (PLS-DA) classification was performed to derive a model with high prediction ability. Orthogonal partial least squares-discriminant analysis (OPLS-DA) model was employed to identify markers specific to a particular honey type. The results indicated that Chinese honeys contained various and discriminative phenolics and flavonoids, as well as antioxidant competence from different botanical origins, which was an alternative approach to honey identification and nutritional evaluation.

Prediction of hospital failure: a post-PPS analysis.

PubMed

Gardiner, L R; Oswald, S L; Jahera, J S

1996-01-01

This study investigates the ability of discriminant analysis to provide accurate predictions of hospital failure. Using data from the period following the introduction of the Prospective Payment System, we developed discriminant functions for each of two hospital ownership categories: not-for-profit and proprietary. The resulting discriminant models contain six and seven variables, respectively. For each ownership category, the variables represent four major aspects of financial health (liquidity, leverage, profitability, and efficiency) plus county marketshare and length of stay. The proportion of closed hospitals misclassified as open one year before closure does not exceed 0.05 for either ownership type. Our results show that discriminant functions based on a small set of financial and nonfinancial variables provide the capability to predict hospital failure reliably for both not-for-profit and proprietary hospitals.

The relation of racial identity, ethnic identity, and racial socialization to discrimination-distress: a meta-analysis of Black Americans.

PubMed

Lee, Debbiesiu L; Ahn, Soyeon

2013-01-01

This meta-analysis synthesized the results of 27 studies examining the relations of racial identity, ethnic identity, and racial socialization to discrimination-distress for Black Americans. The purpose was to uncover which constructs connected to racial identity, ethnic identity, and racial socialization most strongly correlate with racial discrimination and psychological distress. Discrimination significantly related to aspects of racial identity, including immersion-emersion, public regard, encounter, Afrocentricity/racial centrality/private regard, and internalization. Distress significantly correlated with preencounter/assimilation, encounter, public regard, immersion-emersion, and Afrocentricity/racial centrality/private regard. Several of these relationships were significantly moderated by the measure of racial identity or demographic variables (gender or age). Implications of these findings are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Linear discriminant analysis with misallocation in training samples

NASA Technical Reports Server (NTRS)

Chhikara, R. (Principal Investigator); Mckeon, J.

1982-01-01

Linear discriminant analysis for a two-class case is studied in the presence of misallocation in training samples. A general appraoch to modeling of mislocation is formulated, and the mean vectors and covariance matrices of the mixture distributions are derived. The asymptotic distribution of the discriminant boundary is obtained and the asymptotic first two moments of the two types of error rate given. Certain numerical results for the error rates are presented by considering the random and two non-random misallocation models. It is shown that when the allocation procedure for training samples is objectively formulated, the effect of misallocation on the error rates of the Bayes linear discriminant rule can almost be eliminated. If, however, this is not possible, the use of Fisher rule may be preferred over the Bayes rule.

Assay based on electrical impedance spectroscopy to discriminate between normal and cancerous mammalian cells

NASA Astrophysics Data System (ADS)

Giana, Fabián Eduardo; Bonetto, Fabián José; Bellotti, Mariela Inés

2018-03-01

In this work we present an assay to discriminate between normal and cancerous cells. The method is based on the measurement of electrical impedance spectra of in vitro cell cultures. We developed a protocol consisting on four consecutive measurement phases, each of them designed to obtain different information about the cell cultures. Through the analysis of the measured data, 26 characteristic features were obtained for both cell types. From the complete set of features, we selected the most relevant in terms of their discriminant capacity by means of conventional statistical tests. A linear discriminant analysis was then carried out on the selected features, allowing the classification of the samples in normal or cancerous with 4.5% of false positives and no false negatives.

Assay based on electrical impedance spectroscopy to discriminate between normal and cancerous mammalian cells.

PubMed

Giana, Fabián Eduardo; Bonetto, Fabián José; Bellotti, Mariela Inés

2018-03-01

In this work we present an assay to discriminate between normal and cancerous cells. The method is based on the measurement of electrical impedance spectra of in vitro cell cultures. We developed a protocol consisting on four consecutive measurement phases, each of them designed to obtain different information about the cell cultures. Through the analysis of the measured data, 26 characteristic features were obtained for both cell types. From the complete set of features, we selected the most relevant in terms of their discriminant capacity by means of conventional statistical tests. A linear discriminant analysis was then carried out on the selected features, allowing the classification of the samples in normal or cancerous with 4.5% of false positives and no false negatives.

The discrimination of man-made explosions from earthquakes using seismo-acoustic analysis in the Korean Peninsula

NASA Astrophysics Data System (ADS)

Che, Il-Young; Jeon, Jeong-Soo

2010-05-01

Korea Institute of Geoscience and Mineral Resources (KIGAM) operates an infrasound network consisting of seven seismo-acoustic arrays in South Korea. Development of the arrays began in 1999, partially in collaboration with Southern Methodist University, with the goal of detecting distant infrasound signals from natural and anthropogenic phenomena in and around the Korean Peninsula. The main operational purpose of this network is to discriminate man-made seismic events from seismicity including thousands of seismic events per year in the region. The man-made seismic events are major cause of error in estimating the natural seismicity, especially where the seismic activity is weak or moderate such as in the Korean Peninsula. In order to discriminate the man-made explosions from earthquakes, we have applied the seismo-acoustic analysis associating seismic and infrasonic signals generated from surface explosion. The observations of infrasound at multiple arrays made it possible to discriminate surface explosion, because small or moderate size earthquake is not sufficient to generate infrasound. Till now we have annually discriminated hundreds of seismic events in seismological catalog as surface explosions by the seismo-acoustic analysis. Besides of the surface explosions, the network also detected infrasound signals from other sources, such as bolide, typhoons, rocket launches, and underground nuclear test occurred in and around the Korean Peninsula. In this study, ten years of seismo-acoustic data are reviewed with recent infrasonic detection algorithm and association method that finally linked to the seismic monitoring system of the KIGAM to increase the detection rate of surface explosions. We present the long-term results of seismo-acoustic analysis, the detection capability of the multiple arrays, and implications for seismic source location. Since the seismo-acoustic analysis is proved as a definite method to discriminate surface explosion, the analysis will be continuously used for estimating natural seismicity and understanding infrasonic sources.

Simple non-laboratory- and laboratory-based risk assessment algorithms and nomogram for detecting undiagnosed diabetes mellitus.

PubMed

Wong, Carlos K H; Siu, Shing-Chung; Wan, Eric Y F; Jiao, Fang-Fang; Yu, Esther Y T; Fung, Colman S C; Wong, Ka-Wai; Leung, Angela Y M; Lam, Cindy L K

2016-05-01

The aim of the present study was to develop a simple nomogram that can be used to predict the risk of diabetes mellitus (DM) in the asymptomatic non-diabetic subjects based on non-laboratory- and laboratory-based risk algorithms. Anthropometric data, plasma fasting glucose, full lipid profile, exercise habits, and family history of DM were collected from Chinese non-diabetic subjects aged 18-70 years. Logistic regression analysis was performed on a random sample of 2518 subjects to construct non-laboratory- and laboratory-based risk assessment algorithms for detection of undiagnosed DM; both algorithms were validated on data of the remaining sample (n = 839). The Hosmer-Lemeshow test and area under the receiver operating characteristic (ROC) curve (AUC) were used to assess the calibration and discrimination of the DM risk algorithms. Of 3357 subjects recruited, 271 (8.1%) had undiagnosed DM defined by fasting glucose ≥7.0 mmol/L or 2-h post-load plasma glucose ≥11.1 mmol/L after an oral glucose tolerance test. The non-laboratory-based risk algorithm, with scores ranging from 0 to 33, included age, body mass index, family history of DM, regular exercise, and uncontrolled blood pressure; the laboratory-based risk algorithm, with scores ranging from 0 to 37, added triglyceride level to the risk factors. Both algorithms demonstrated acceptable calibration (Hosmer-Lemeshow test: P = 0.229 and P = 0.483) and discrimination (AUC 0.709 and 0.711) for detection of undiagnosed DM. A simple-to-use nomogram for detecting undiagnosed DM has been developed using validated non-laboratory-based and laboratory-based risk algorithms. © 2015 Ruijin Hospital, Shanghai Jiaotong University School of Medicine and Wiley Publishing Asia Pty Ltd.

Rapid differential diagnosis of diabetes insipidus in a 7-month-old infant: The copeptin approach.

PubMed

Vergier, J; Fromonot, J; Alvares De Azevedo Macedo, A; Godefroy, A; Marquant, E; Guieu, R; Tsimaratos, M; Reynaud, R

2018-01-01

Diabetes insipidus is characterized by hypoosmotic polyuria related to deficiency of arginine-vasopressin (AVP) secretion (central diabetes insipidus, CDI) or renal insensitivity to AVP (nephrogenic diabetes insipidus, NDI). The water deprivation test with assessment of AVP activity is currently the gold standard for differential diagnosis in patients presenting polyuria-polydipsia syndrome. Nevertheless, it can be dangerous without proper surveillance and its interpretation may be challenging. Other markers have been suggested. Direct quantification of circulating AVP is not sufficient for diagnosis: vasopressin is unstable, analysis is complex. AVP comes from prohormone preprovasopressin with concomitant release of copeptin (C-terminal moiety) in the equimolar ratio. Copeptin is stable in vitro, with easy and rapid measurement (<4h). Past studies have shown greater sensitivity and specificity of copeptin versus AVP to discriminate etiologies of polyuria in adults, but its value has not been demonstrated in infants yet. A 7-month-old infant presented polyuria-polydipsia syndrome with poor weight gain. Laboratory tests pointed out hypernatremia (170mmol/L) and blood hyperosmolarity (330mOsm/L) with inappropriate urinary hypoosmolarity (168mOsm/L). Plasmatic copeptin measurement was found at a very high level, 303pmol/L (1-14pmol/L). DdAVP administration did not improve the polyuria, confirming the final diagnosis of NDI. Hyperhydration with a hypoosmolar diet normalized the hydration status and circulating levels of copeptin within 1 week. Copeptin, a stable peptide reflecting AVP secretion, could be a safer and faster biomarker for etiological diagnosis of polyuria-polydipsia syndrome in children. Before regularization of hydration status, a single baseline measurement may be enough to discriminate NDI from other etiologies without the water deprivation test. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Predictive value of early near-infrared spectroscopy monitoring of patients with traumatic brain injury.

PubMed

Vilkė, Alina; Bilskienė, Diana; Šaferis, Viktoras; Gedminas, Martynas; Bieliauskaitė, Dalia; Tamašauskas, Arimantas; Macas, Andrius

2014-01-01

Traumatic brain injury (TBI) is the leading cause of death and disability in young adults. Study aimed to define the predictive value of early near-infrared spectroscopy (NIRS) monitoring of TBI patients in a Lithuanian clinical setting. Data of 61 patients was analyzed. Predictive value of early NIRS monitoring, computed tomography data and regular intensive care unit (ICU) parameters was investigated. Twenty-six patients expressed clinically severe TBI; 14 patients deceased. Patients who survived expressed higher NIRS values at the periods of admission to operative room (75.4%±9.8% vs. 71.0%±20.5%; P=0.013) and 1h after admission to ICU (74.7%±1.5% vs. 61.9%±19.4%; P=0.029). The NIRS values discriminated hospital mortality groups more accurately than admission GCS score, blood sugar or hemoglobin levels. Admission INR value and NIRS value at 1h after admission to ICU were selected by discriminant analysis into the optimal set of features when classifying hospital mortality groups. Average efficiency of classification using this method was 88.9%. When rsO2 values at 1h after admission to ICU did not exceed 68.0% in the left hemisphere and 68.3% in the right hemisphere, the hazard ratio for death increased by 17.7 times (P<0.01) and 5.1 times (P<0.05), respectively. NIRS plays an important role in the clinical care of TBI patients. Regional brain saturation monitoring provides accurate predictive data, which can improve the allocation of scarce medical resources, set the treatment goals and alleviate the early communication with patients' relatives. Copyright © 2014 Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

IgG Glycome in Colorectal Cancer.

PubMed

Vučković, Frano; Theodoratou, Evropi; Thaçi, Kujtim; Timofeeva, Maria; Vojta, Aleksandar; Štambuk, Jerko; Pučić-Baković, Maja; Rudd, Pauline M; Đerek, Lovorka; Servis, Dražen; Wennerström, Annika; Farrington, Susan M; Perola, Markus; Aulchenko, Yurii; Dunlop, Malcolm G; Campbell, Harry; Lauc, Gordan

2016-06-15

Alternative glycosylation has significant structural and functional consequences on IgG and consequently also on cancer immunosurveillance. Because of technological limitations, the effects of highly heritable individual variations and the differences in the dynamics of changes in IgG glycosylation on colorectal cancer were never investigated before. Using recently developed high-throughput UPLC technology for IgG glycosylation analysis, we analyzed IgG glycome composition in 760 patients with colorectal cancer and 538 matching controls. Effects of surgery were evaluated in 28 patients sampled before and three times after surgery. A predictive model was built using regularized logistic regression and evaluated using a 10-cross validation procedure. Furthermore, IgG glycome composition was analyzed in 39 plasma samples collected before initial diagnosis of colorectal cancer. We have found that colorectal cancer associates with decrease in IgG galactosylation, IgG sialylation and increase in core-fucosylation of neutral glycans with concurrent decrease of core-fucosylation of sialylated glycans. Although a model based on age and sex did not show discriminative power (AUC = 0.499), the addition of glycan variables into the model considerably increased the discriminative power of the model (AUC = 0.755). However, none of these differences were significant in the small set of samples collected before the initial diagnosis. Considering the functional relevance of IgG glycosylation for both tumor immunosurveillance and clinical efficacy of therapy with mAbs, individual variation in IgG glycosylation may turn out to be important for prediction of disease course or the choice of therapy, thus warranting further, more detailed studies of IgG glycosylation in colorectal cancer. Clin Cancer Res; 22(12); 3078-86. ©2016 AACR. ©2016 American Association for Cancer Research.

Workplace Discrimination and Health Among Filipinos in the United States

PubMed Central

de Castro, Arnold B.; Gee, Gilbert C.; Takeuchi, David T.

2008-01-01

Objectives. We examined the association between work discrimination and morbidity among Filipinos in the United States, independent of more-global measures of discrimination. Methods. Data were collected from the Filipino American Community Epidemiological Survey. Our analysis focused on 1652 participants who were employed at the time of data collection, and we used negative binomial regression to determine the association between work discrimination and health conditions. Results. The report of workplace discrimination specific to being Filipino was associated with an increased number of health conditions. This association persisted even after we controlled for everyday discrimination, a general assessment of discrimination; job concerns, a general assessment of unpleasant work circumstances; having immigrated for employment reasons; job category; income; education; gender; and other sociodemographic factors. Conclusions. Racial discrimination in the workplace was positively associated with poor health among Filipino Americans after we controlled for reports of everyday discrimination and general concerns about one’s job. This finding shows the importance of considering the work setting as a source of discrimination and its effect on morbidity among racial minorities. PMID:18235069

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.

A Statistical Discrimination Experiment for Eurasian Events Using a Twenty-Seven-Station Network

DTIC Science & Technology

1980-07-08

to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...to test the effectiveness of a multivariate method of analysis for distinguishing earthquakes from explosions. The data base for the experiment...the weight assigned to each variable whenever a new one is added. Jennrich, R. I. (1977). Stepwise discriminant analysis , in Statistical Methods for

Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options.

PubMed

Quanbao, Jiang; Shuzhuo, Li; Marcus W, Feldman

2011-08-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination.

Demographic Consequences of Gender Discrimination in China: Simulation Analysis of Policy Options

PubMed Central

Quanbao, Jiang; Marcus W., Feldman

2013-01-01

The large number of missing females in China, a consequence of gender discrimination, is having and will continue to have a profound effect on the country's population development. In this paper, we analyze the causes of this gender discrimination in terms of institutions, culture and, economy, and suggest public policies that might help eliminate gender discrimination. Using a population simulation model, we study the effect of public policies on the sex ratio at birth and excess female child mortality, and the effect of gender discrimination on China's population development. We find that gender discrimination will decrease China's population size, number of births, and working age population, accelerate population aging and exacerbate the male marriage squeeze. These results provide theoretical support for suggesting that the government enact and implement public policies aimed at eliminating gender discrimination. PMID:24363477

Determination of Ignitable Liquids in Fire Debris: Direct Analysis by Electronic Nose

PubMed Central

Ferreiro-González, Marta; Barbero, Gerardo F.; Palma, Miguel; Ayuso, Jesús; Álvarez, José A.; Barroso, Carmelo G.

2016-01-01

Arsonists usually use an accelerant in order to start or accelerate a fire. The most widely used analytical method to determine the presence of such accelerants consists of a pre-concentration step of the ignitable liquid residues followed by chromatographic analysis. A rapid analytical method based on headspace-mass spectrometry electronic nose (E-Nose) has been developed for the analysis of Ignitable Liquid Residues (ILRs). The working conditions for the E-Nose analytical procedure were optimized by studying different fire debris samples. The optimized experimental variables were related to headspace generation, specifically, incubation temperature and incubation time. The optimal conditions were 115 °C and 10 min for these two parameters. Chemometric tools such as hierarchical cluster analysis (HCA) and linear discriminant analysis (LDA) were applied to the MS data (45–200 m/z) to establish the most suitable spectroscopic signals for the discrimination of several ignitable liquids. The optimized method was applied to a set of fire debris samples. In order to simulate post-burn samples several ignitable liquids (gasoline, diesel, citronella, kerosene, paraffin) were used to ignite different substrates (wood, cotton, cork, paper and paperboard). A full discrimination was obtained on using discriminant analysis. This method reported here can be considered as a green technique for fire debris analyses. PMID:27187407

A study on fast digital discrimination of neutron and gamma-ray for improvement neutron emission profile measurementa)

PubMed Central

Uchida, Y.; Takada, E.; Fujisaki, A.; Isobe, M.; Shinohara, K.; Tomita, H.; Kawarabayashi, J.; Iguchi, T.

2014-01-01

Neutron and γ-ray (n-γ) discrimination with a digital signal processing system has been used to measure the neutron emission profile in magnetic confinement fusion devices. However, a sampling rate must be set low to extend the measurement time because the memory storage is limited. Time jitter decreases a discrimination quality due to a low sampling rate. As described in this paper, a new charge comparison method was developed. Furthermore, automatic n-γ discrimination method was examined using a probabilistic approach. Analysis results were investigated using the figure of merit. Results show that the discrimination quality was improved. Automatic discrimination was applied using the EM algorithm and k-means algorithm. PMID:25430297

An exploratory examination of the associations among racial and ethnic discrimination, racial climate, and trauma-related symptoms in a college student population.

PubMed

Pieterse, Alex L; Carter, Robert T; Evans, Sarah A; Walter, Rebecca A

2010-07-01

In this study, we examined the association among perceptions of racial and/or ethnic discrimination, racial climate, and trauma-related symptoms among 289 racially diverse college undergraduates. Study measures included the Perceived Stress Scale, the Perceived Ethnic Discrimination Questionnaire, the Posttraumatic Stress Disorder Checklist-Civilian Version, and the Racial Climate Scale. Results of a multivariate analysis of variance (MANOVA) indicated that Asian and Black students reported more frequent experiences of discrimination than did White students. Additionally, the MANOVA indicated that Black students perceived the campus racial climate as being more negative than did White and Asian students. A hierarchical regression analysis showed that when controlling for generic life stress, perceptions of discrimination contributed an additional 10% of variance in trauma-related symptoms for Black students, and racial climate contributed an additional 7% of variance in trauma symptoms for Asian students. (c) 2010 APA, all rights reserved.

Women cannot discriminate between different paracervical block techniques applied to opposite sides of the cervix.

PubMed

Grossman, R A

1995-09-01

The purpose of this study was to determine whether women can discriminate better from less effective paracervical block techniques applied to opposite sides of the cervix. If this discrimination could be made, it would be possible to compare different techniques and thus improve the quality of paracervical anesthesia. Two milliliters of local anesthetic was applied to one side and 6 ml to the other side of volunteers' cervices before cervical dilation. Statistical examination was by sequential analysis. The study was stopped after 47 subjects had entered, when sequential analysis found that there was no significant difference in women's perception of pain. Nine women reported more pain on the side with more anesthesia and eight reported more pain on the side with less anesthesia. Because the amount of anesthesia did not make a difference, the null hypothesis (that women cannot discriminate between different anesthetic techniques) was accepted. Women are not able to discriminate different doses of local anesthetic when applied to opposite sides of the cervix.

Unsupervised spike sorting based on discriminative subspace learning.

PubMed

Keshtkaran, Mohammad Reza; Yang, Zhi

2014-01-01

Spike sorting is a fundamental preprocessing step for many neuroscience studies which rely on the analysis of spike trains. In this paper, we present two unsupervised spike sorting algorithms based on discriminative subspace learning. The first algorithm simultaneously learns the discriminative feature subspace and performs clustering. It uses histogram of features in the most discriminative projection to detect the number of neurons. The second algorithm performs hierarchical divisive clustering that learns a discriminative 1-dimensional subspace for clustering in each level of the hierarchy until achieving almost unimodal distribution in the subspace. The algorithms are tested on synthetic and in-vivo data, and are compared against two widely used spike sorting methods. The comparative results demonstrate that our spike sorting methods can achieve substantially higher accuracy in lower dimensional feature space, and they are highly robust to noise. Moreover, they provide significantly better cluster separability in the learned subspace than in the subspace obtained by principal component analysis or wavelet transform.

Evaluation of FTIR spectroscopy as diagnostic tool for colorectal cancer using spectral analysis

NASA Astrophysics Data System (ADS)

Dong, Liu; Sun, Xuejun; Chao, Zhang; Zhang, Shiyun; Zheng, Jianbao; Gurung, Rajendra; Du, Junkai; Shi, Jingsen; Xu, Yizhuang; Zhang, Yuanfu; Wu, Jinguang

2014-03-01

The aim of this study is to confirm FTIR spectroscopy as a diagnostic tool for colorectal cancer. 180 freshly removed colorectal samples were collected from 90 patients for spectrum analysis. The ratios of spectral intensity and relative intensity (/I1460) were calculated. Principal component analysis (PCA) and Fisher's discriminant analysis (FDA) were applied to distinguish the malignant from normal. The FTIR parameters of colorectal cancer and normal tissues were distinguished due to the contents or configurations of nucleic acids, proteins, lipids and carbohydrates. Related to nitrogen containing, water, protein and nucleic acid were increased significantly in the malignant group. Six parameters were selected as independent factors to perform discriminant functions. The sensitivity for FTIR in diagnosing colorectal cancer was 96.6% by discriminant analysis. Our study demonstrates that FTIR can be a useful technique for detection of colorectal cancer and may be applied in clinical colorectal cancer diagnosis.

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

PubMed

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

2009-01-01

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

Discrimination of honeys using colorimetric sensor arrays, sensory analysis and gas chromatography techniques.

PubMed

Tahir, Haroon Elrasheid; Xiaobo, Zou; Xiaowei, Huang; Jiyong, Shi; Mariod, Abdalbasit Adam

2016-09-01

Aroma profiles of six honey varieties of different botanical origins were investigated using colorimetric sensor array, gas chromatography-mass spectrometry (GC-MS) and descriptive sensory analysis. Fifty-eight aroma compounds were identified, including 2 norisoprenoids, 5 hydrocarbons, 4 terpenes, 6 phenols, 7 ketones, 9 acids, 12 aldehydes and 13 alcohols. Twenty abundant or active compounds were chosen as key compounds to characterize honey aroma. Discrimination of the honeys was subsequently implemented using multivariate analysis, including hierarchical clustering analysis (HCA) and principal component analysis (PCA). Honeys of the same botanical origin were grouped together in the PCA score plot and HCA dendrogram. SPME-GC/MS and colorimetric sensor array were able to discriminate the honeys effectively with the advantages of being rapid, simple and low-cost. Moreover, partial least squares regression (PLSR) was applied to indicate the relationship between sensory descriptors and aroma compounds. Copyright © 2016 Elsevier Ltd. All rights reserved.

Otolith shape analysis for stock discrimination of two Collichthys genus croaker (Pieces: Sciaenidae,) from the northern Chinese coast

NASA Astrophysics Data System (ADS)

Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

2017-08-01

The otolith morphology of two croaker species (Collichthys lucidus and Collichthys niveatus) from three areas (Liaodong Bay, LD; Huanghe (Yellow) River estuary, HRE; Jiaozhou Bay, JZ) along the northern Chinese coast were investigated for species identification and stock discrimination. The otolith contour shape described by elliptic Fourier coefficients (EFC) were analysed using principal components analysis (PCA) and stepwise canonical discriminant analysis (CDA) to identify species and stocks. The two species were well differentiated, with an overall classification success rate of 97.8%. And variations in the otolith shapes were significant enough to discriminate among the three geographical samples of C. lucidus (67.7%) or C. niveatus (65.2%). Relatively high mis-assignment occurred between the geographically adjacent LD and HRE samples, which implied that individual mixing may exist between the two samples. This study yielded information complementary to that derived from genetic studies and provided information for assessing the stock structure of C. lucidus and C. niveatus in the Bohai Sea and the Yellow Sea.

Discrimination of high-Z materials in concrete-filled containers using muon scattering tomography

NASA Astrophysics Data System (ADS)

Frazão, L.; Velthuis, J.; Thomay, C.; Steer, C.

2016-07-01

An analysis method of identifying materials using muon scattering tomography is presented, which uses previous knowledge of the position of high-Z objects inside a container and distinguishes them from similar materials. In particular, simulations were performed in order to distinguish a block of Uranium from blocks of Lead and Tungsten of the same size, inside a concrete-filled drum. The results show that, knowing the shape and position from previous analysis, it is possible to distinguish 5 × 5 × 5 cm3 blocks of these materials with about 4h of muon exposure, down to 2 × 2 × 2 cm3 blocks with 70h of data using multivariate analysis (MVA). MVA uses several variables, but it does not benefit the discrimination over a simpler method using only the scatter angles. This indicates that the majority of discrimination is provided by the angular information. Momentum information is shown to provide no benefits in material discrimination.

The use of wavelength dispersive X-ray fluorescence in the identification of the elemental composition of vanilla samples and the determination of the geographic origin by discriminant function analysis.

PubMed

Hondrogiannis, Ellen; Rotta, Kathryn; Zapf, Charles M

2013-03-01

Sixteen elements found in 37 vanilla samples from Madagascar, Uganda, India, Indonesia (all Vanilla planifolia species), and Papa New Guinea (Vanilla tahitensis species) were measured by wavelength dispersive X-ray fluorescence (WDXRF) spectroscopy for the purpose of determining the elemental concentrations to discriminate among the origins. Pellets were prepared of the samples and elemental concentrations were calculated based on calibration curves created using 4 Natl. Inst. of Standards and Technology (NIST) standards. Discriminant analysis was used to successfully classify the vanilla samples by their species and their geographical region. Our method allows for higher throughput in the rapid screening of vanilla samples in less time than analytical methods currently available. Wavelength dispersive X-ray fluorescence spectroscopy and discriminant function analysis were used to classify vanilla from different origins resulting in a model that could potentially serve to rapidly validate these samples before purchasing from a producer. © 2013 Institute of Food Technologists®

Workplace discrimination: experiences of practicing physicians.

PubMed

Coombs, Alice A Tolbert; King, Roderick K

2005-04-01

In response to a growing concern regarding physician discrimination in the workplace, this study was developed to: (1) describe the types of discrimination that exist for the practicing physician and (2) determine which groups of physicians are more likely to experience the various forms of discrimination. Surveys were mailed to 1930 practicing physicians in Massachusetts. Participants were asked if they had encountered discrimination, how significant the discrimination was against a specific group, the frequency of personal discrimination, and the type of discrimination. Factor analysis identified four types of discrimination: career advancement, punitive behaviors, practice barriers and hiring barriers. A total of 445 responses were received (a 24% response rate). Sixty-three percent of responding physicians had experienced some form of discrimination. Respondents were women (46%), racial/ethnic minorities (42%) and international medical graduates (IMGs) (40%). In addition, 26% of those classified as white were also IMGs. Over 60% of respondents believed discrimination against IMGs was very or somewhat significant. Almost 27% of males acknowledged that gender bias against females was very or somewhat significant. IMGs were more likely to indicate that discrimination against IMGs was significant in their current organization. Of U.S. medical graduates (USMGs) 44% reported that discrimination against IMGs in their current organization was significant. Nonwhites were more likely to report that discrimination based on race/ethnicity was significant. Nearly 29% of white respondents also believed that such discrimination was very or somewhat significant. Physicians practicing in academic, research, and private practice sectors experience discrimination based on gender, ethnic/racial, and IMG status.

Persistence and withdrawal by students in a preservice science and mathematics teacher education course

NASA Astrophysics Data System (ADS)

Tulip, David F.; Lucas, Keith B.

1991-12-01

At a time when recruitment into preservice teacher education courses in mathematics and science is difficult, one strategy to increase the number of graduates is to minimise the number of students who fail to complete their university courses. This study sought to determine factors which distinguish withdrawers from persisters in the first semester of a B.Ed course. Discriminant analysis was employed; a discriminant function employing seven factors resulted in correct classification in 81% of cases. Further analysis distinguishing between dropouts and transferees resulted in two discriminant functions with some common variables.

Perceived age discrimination in older adults.

PubMed

Rippon, Isla; Kneale, Dylan; de Oliveira, Cesar; Demakakos, Panayotes; Steptoe, Andrew

2014-05-01

to examine perceived age discrimination in a large representative sample of older adults in England. this cross-sectional study of over 7,500 individuals used data from the fifth wave of the English Longitudinal Study of Ageing (ELSA), a longitudinal cohort study of men and women aged 52 years and older in England. Wave 5 asked respondents about the frequency of five everyday discriminatory situations. Participants who attributed any experiences of discrimination to their age were treated as cases of perceived age discrimination. Multivariable logistic regression analysis was used to estimate the odds ratios of experiencing perceived age discrimination in relation to selected sociodemographic factors. approximately a third (33.3%) of all respondents experienced age discrimination, rising to 36.8% in those aged 65 and over. Perceived age discrimination was associated with older age, higher education, lower levels of household wealth and being retired or not in employment. The correlates of age discrimination across the five discriminatory situations were similar. understanding age discrimination is vital if we are to develop appropriate policies and to target future interventions effectively. These findings highlight the scale of the challenge of age discrimination for older adults in England and illustrate that those groups are particularly vulnerable to this form of discrimination.

Imaging ultrasonic dispersive guided wave energy in long bones using linear radon transform.

PubMed

Tran, Tho N H T; Nguyen, Kim-Cuong T; Sacchi, Mauricio D; Le, Lawrence H

2014-11-01

Multichannel analysis of dispersive ultrasonic energy requires a reliable mapping of the data from the time-distance (t-x) domain to the frequency-wavenumber (f-k) or frequency-phase velocity (f-c) domain. The mapping is usually performed with the classic 2-D Fourier transform (FT) with a subsequent substitution and interpolation via c = 2πf/k. The extracted dispersion trajectories of the guided modes lack the resolution in the transformed plane to discriminate wave modes. The resolving power associated with the FT is closely linked to the aperture of the recorded data. Here, we present a linear Radon transform (RT) to image the dispersive energies of the recorded ultrasound wave fields. The RT is posed as an inverse problem, which allows implementation of the regularization strategy to enhance the focusing power. We choose a Cauchy regularization for the high-resolution RT. Three forms of Radon transform: adjoint, damped least-squares, and high-resolution are described, and are compared with respect to robustness using simulated and cervine bone data. The RT also depends on the data aperture, but not as severely as does the FT. With the RT, the resolution of the dispersion panel could be improved up to around 300% over that of the FT. Among the Radon solutions, the high-resolution RT delineated the guided wave energy with much better imaging resolution (at least 110%) than the other two forms. The Radon operator can also accommodate unevenly spaced records. The results of the study suggest that the high-resolution RT is a valuable imaging tool to extract dispersive guided wave energies under limited aperture. Copyright © 2014 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Physical exercise induces specific adaptations resulting in reduced organ injury and mortality during severe polymicrobial sepsis.

PubMed

Sossdorf, Maik; Fischer, Jacqueline; Meyer, Stefan; Dahlke, Katja; Wissuwa, Bianka; Seidel, Carolin; Schrepper, Andrea; Bockmeyer, Clemens L; Lupp, Amelie; Neugebauer, Sophie; Schmerler, Diana; Rödel, Jürgen; Claus, Ralf A; Otto, Gordon P

2013-10-01

High physical activity levels are associated with wide-ranging health benefits, disease prevention, and longevity. In the present study, we examined the impact of regular physical exercise on the severity of organ injury and survival probability, as well as characteristics of the systemic immune and metabolic response during severe polymicrobial sepsis. Animal study. University laboratory. Male C57BL/6N mice. Mice were trained for 6 weeks by treadmill and voluntary wheel running or housed normally. Polymicrobial sepsis in mice was induced by injection of fecal slurry. Subsequently, mice were randomized into the following groups: healthy controls, 6 hours postsepsis, and 24 hours postsepsis. Blood and organ samples were collected and investigated by measuring clinical chemistry variables, cytokines, plasma metabolites, and bacterial clearance. Organ morphology and damage were characterized by histological staining. Physical exercise improved survival and the ability of bacterial clearance in blood and organs. The release of pro- and anti-inflammatory cytokines, including interleukin-6 and interleukin-10, was diminished in trained compared to untrained mice during sepsis. The sepsis-associated acute kidney tubular damage was less pronounced in pretrained animals. By metabolic profiling and regression analysis, we detected lysophosphatidylcholine 14:0, tryptophan, as well as pimelylcarnitine linked with levels of neutrophil gelatinase-associated lipocalin representing acute tubular injury (corrected R=0.910; p<0.001). We identified plasma lysophosphatidylcholine 16:0, lysophosphatidylcholine 17:0, and lysophosphatidylcholine 18:0 as significant metabolites discriminating between trained and untrained mice during sepsis. Regular physical exercise reduces sepsis-associated acute kidney injury and death. As a specific mechanism of exercise-induced adaptation, we identified various lysophosphatidylcholines that might function as surrogate for improved outcome in sepsis.

The Regularity of Sustained Firing Reveals Two Populations of Slowly Adapting Touch Receptors in Mouse Hairy Skin

PubMed Central

Wellnitz, Scott A.; Lesniak, Daine R.; Gerling, Gregory J.

2010-01-01

Touch is initiated by diverse somatosensory afferents that innervate the skin. The ability to manipulate and classify receptor subtypes is prerequisite for elucidating sensory mechanisms. Merkel cell–neurite complexes, which distinguish shapes and textures, are experimentally tractable mammalian touch receptors that mediate slowly adapting type I (SAI) responses. The assessment of SAI function in mutant mice has been hindered because previous studies did not distinguish SAI responses from slowly adapting type II (SAII) responses, which are thought to arise from different end organs, such as Ruffini endings. Thus we sought methods to discriminate these afferent types. We developed an epidermis-up ex vivo skin–nerve chamber to record action potentials from afferents while imaging Merkel cells in intact receptive fields. Using model-based cluster analysis, we found that two types of slowly adapting receptors were readily distinguished based on the regularity of touch-evoked firing patterns. We identified these clusters as SAI (coefficient of variation = 0.78 ± 0.09) and SAII responses (0.21 ± 0.09). The identity of SAI afferents was confirmed by recording from transgenic mice with green fluorescent protein–expressing Merkel cells. SAI receptive fields always contained fluorescent Merkel cells (n = 10), whereas SAII receptive fields lacked these cells (n = 5). Consistent with reports from other vertebrates, mouse SAI and SAII responses arise from afferents exhibiting similar conduction velocities, receptive field sizes, mechanical thresholds, and firing rates. These results demonstrate that mice, like other vertebrates, have two classes of slowly adapting light-touch receptors, identify a simple method to distinguish these populations, and extend the utility of skin–nerve recordings for genetic dissection of touch receptor mechanisms. PMID:20393068

[Primary Study on Noninvasive Detection of Vascular Function Based on Finger Temperature Change].

PubMed

Dong, Qing; Li, Xia; Wan, Yungao; Lu, Gaoquan; Wang, Xinxin; Zhang, Kuan

2016-02-01

By studying the relationship between fingertip temperature changes and arterial function during vascular reactivity test, we established a new non-invasive method for detecting vascular function, in order to provide an assistance for early diagnosis and prevention of cardiovascular diseases. We customized three modules respectively for blood occlusion, measurement of finger temperature and blood oxygen acquisition, and then we established the hardware of data acquisition system. And the software was programmed with Labview. Healthy subjects [group A, n = 24, (44.6 ± 9.0) years] and subjects with cardiovascular diseases [group B, n = 33, (57.2 ± 9.9) years)] were chosen for the study. Subject's finger temperature, blood oxygen and occlusion pressure of block side during and after unilateral arm brachial artery occlusion were recorded, as well as some other regular physiological indexes. By time-domain analysis, we extracted 12 parameters from fingertip temperature signal, including the initial temperature (Ti), temperature rebound (TR), the time of the temperature recovering to initial status (RIt) and other parameters from the finger temperature signal. We in the experiment also measured other regular physiological body mass index (BMI), systolic blood pressure (SBP), diastiolic blood pressure (DBP) and so on. Results showed that 8 parameters difference between the two group of data were significant. based on the statistical results. A discriminant function of vascular function status was established afterwards. We found in the study that the changes of finger temperature during unilateral arms brachial artery occlusion and open were closely related to vascular function. We hope that the method presented in this article could lay a foundation of early detection of vascular function.

Special event discrimination analysis: The TEXAR blind test and identification of the August 16, 1997 Kara Sea event. Final report, 13 September 1995--31 January 1998

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

Baumgardt, D.

1998-03-31

The International Monitoring System (IMS) for the Comprehensive Test Ban Treaty (CTBT) faces the serious challenge of being able to accurately and reliably identify seismic events in any region of the world. Extensive research has been performed in recent years on developing discrimination techniques which appear to classify seismic events into broad categories of source types, such as nuclear explosion, earthquake, and mine blast. This report examines in detail the problem of effectiveness of regional discrimination procedures in the application of waveform discriminants to Special Event identification and the issue of discriminant transportability.

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

Uchida, Y., E-mail: h1312101@mailg.nc-toyama.ac.jp; Takada, E.; Fujisaki, A.

Neutron and γ-ray (n-γ) discrimination with a digital signal processing system has been used to measure the neutron emission profile in magnetic confinement fusion devices. However, a sampling rate must be set low to extend the measurement time because the memory storage is limited. Time jitter decreases a discrimination quality due to a low sampling rate. As described in this paper, a new charge comparison method was developed. Furthermore, automatic n-γ discrimination method was examined using a probabilistic approach. Analysis results were investigated using the figure of merit. Results show that the discrimination quality was improved. Automatic discrimination was appliedmore » using the EM algorithm and k-means algorithm.« less

Sex Discrimination in Higher Education Employment: An Empirical Analysis of the Case Law.

ERIC Educational Resources Information Center

Schoenfeld, Sage L.; Zirkel, Perry A.

1989-01-01

Analysis of 132 court decisions for the period of 1976-86 concerning sex discrimination of faculty and nonfaculty employees in higher education indicates that the overall odds favor the defendant-institutions over the plaintiff-employees by a four-to-one ratio. The most frequently litigated institutional action was salary, followed by hiring and…

The Relation of Racial Identity, Ethnic Identity, and Racial Socialization to Discrimination-Distress: A Meta-Analysis of Black Americans

ERIC Educational Resources Information Center

Lee, Debbiesiu L.; Ahn, Soyeon

2013-01-01

This meta-analysis synthesized the results of 27 studies examining the relations of racial identity, ethnic identity, and racial socialization to discrimination-distress for Black Americans. The purpose was to uncover which constructs connected to racial identity, ethnic identity, and racial socialization most strongly correlate with racial…

Early discrimination of nasopharyngeal carcinoma based on tissue deoxyribose nucleic acid surface-enhanced Raman spectroscopy analysis

NASA Astrophysics Data System (ADS)

Qiu, Sufang; Li, Chao; Lin, Jinyong; Xu, Yuanji; Lu, Jun; Huang, Qingting; Zou, Changyan; Chen, Chao; Xiao, Nanyang; Lin, Duo; Chen, Rong; Pan, Jianji; Feng, Shangyuan

2016-12-01

Surface-enhanced Raman spectroscopy (SERS) was employed to detect deoxyribose nucleic acid (DNA) variations associated with the development of nasopharyngeal carcinoma (NPC). Significant SERS spectral differences between the DNA extracted from early NPC, advanced NPC, and normal nasopharyngeal tissue specimens were observed at 678, 729, 788, 1337, 1421, 1506, and 1573 cm-1, which reflects the genetic variations in NPC. Principal component analysis combined with discriminant function analysis for early NPC discrimination yielded a diagnostic accuracy of 86.8%, 92.3%, and 87.9% for early NPC, advanced NPC, and normal nasopharyngeal tissue DNA, respectively. In this exploratory study, we demonstrated the potential of SERS for early detection of NPC based on the DNA molecular study of biopsy tissues.

Discriminant analysis of some east Tennessee forest herb niches. Environmental Sciences Division Publication No. 752

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

Mann, L.K.; Shugart, H.H.; Kitchings, J.T.

1978-03-01

The purpose of this study was to evaluate the effectiveness of using discriminant analysis in assessing plant niches. As a component of research by the Environmental Research Park Project at Oak Ridge, Tennessee, five sites were inventoried for herbaceous species. From this inventory, four sympatric species of Galium and seventeen co-occurring herbaceous species were selected for discriminant analysis. The four species of Galium were treated as two data sets: one was composed of information collected at one site (a mesic hardwood area) and the other contained data from two cedar sites of shallow soil over limestone bedrock. The seventeen herbaceousmore » species all occurred in the mesic hardwood area.« less

Principal Component Analysis for pulse-shape discrimination of scintillation radiation detectors

NASA Astrophysics Data System (ADS)

Alharbi, T.

2016-01-01

In this paper, we report on the application of Principal Component analysis (PCA) for pulse-shape discrimination (PSD) of scintillation radiation detectors. The details of the method are described and the performance of the method is experimentally examined by discriminating between neutrons and gamma-rays with a liquid scintillation detector in a mixed radiation field. The performance of the method is also compared against that of the conventional charge-comparison method, demonstrating the superior performance of the method particularly at low light output range. PCA analysis has the important advantage of automatic extraction of the pulse-shape characteristics which makes the PSD method directly applicable to various scintillation detectors without the need for the adjustment of a PSD parameter.

Terahertz time-domain attenuated total reflection spectroscopy applied to the rapid discrimination of the botanical origin of honeys

NASA Astrophysics Data System (ADS)

Liu, Wen; Zhang, Yuying; Yang, Si; Han, Donghai

2018-05-01

A new technique to identify the floral resources of honeys is demanded. Terahertz time-domain attenuated total reflection spectroscopy combined with chemometrics methods was applied to discriminate different categorizes (Medlar honey, Vitex honey, and Acacia honey). Principal component analysis (PCA), cluster analysis (CA) and partial least squares-discriminant analysis (PLS-DA) have been used to find information of the botanical origins of honeys. Spectral range also was discussed to increase the precision of PLS-DA model. The accuracy of 88.46% for validation set was obtained, using PLS-DA model in 0.5-1.5 THz. This work indicated terahertz time-domain attenuated total reflection spectroscopy was an available approach to evaluate the quality of honey rapidly.

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2013-01-01

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

Does Anger Regulation Mediate the Discrimination-Mental Health Link among Mexican-Origin Adolescents? A Longitudinal Mediation Analysis Using Multilevel Modeling

ERIC Educational Resources Information Center

Park, Irene J. K.; Wang, Lijuan; Williams, David R.; Alegría, Margarita

2017-01-01

Although prior research has consistently documented the association between racial/ethnic discrimination and poor mental health outcomes, the mechanisms that underlie this link are still unclear. The present 3-wave longitudinal study tested the mediating role of anger regulation in the discrimination-mental health link among 269 Mexican-origin…

Perceived Discrimination among African American Adolescents and Allostatic Load: A Longitudinal Analysis with Buffering Effects

ERIC Educational Resources Information Center

Brody, Gene H.; Lei, Man-Kit; Chae, David H.; Yu, Tianyi; Kogan, Steven M.; Beach, Steven R. H.

2014-01-01

This study was designed to examine the prospective relations of perceived racial discrimination with allostatic load (AL), along with a possible buffer of the association. A sample of 331 African Americans in the rural South provided assessments of perceived discrimination from ages 16 to 18 years. When youth were 18 years, caregivers reported…

Citrus species and hybrids depicted by near- and mid-infrared spectroscopy.

PubMed

Páscoa, Ricardo Nmj; Moreira, Silvana; Lopes, João A; Sousa, Clara

2018-01-31

Citrus trees are among the most cultivated plants in the world, with a high economic impact. The wide sexual compatibility among relatives gave rise to a large number of hybrids that are difficult to discriminate. This work sought to explore the ability of infrared spectroscopy to discriminate among Citrus species and/or hybrids and to contribute to the elucidation of its relatedness. Adult leaves of 18 distinct Citrus plants were included in this work. Near- and mid-infrared (NIR and FTIR) spectra were acquired from leaves after harvesting and a drying period of 1 month. Spectra were modelled by principal component analysis and partial least squares discriminant analysis. Both techniques revealed a high discrimination potential (78.5-95.9%), being the best results achieved with NIR spectroscopy and air-dried leaves (95.9%). Infrared spectroscopy was able to successfully discriminate several Citrus species and/or hybrids. Our results contributed also to enhance insights regarding the studied Citrus species and/or hybrids. Despite the benefit of including additional samples, the results herein obtained clearly pointed infrared spectroscopy as a reliable technique for Citrus species and/or hybrid discrimination. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Discrimination Between Patients With Alzheimer Disease and Healthy Subjects Using Layer Analysis of Cerebral Blood Flow and Xenon Solubility Coefficient in Xenon-Enhanced Computed Tomography.

PubMed

Sase, Shigeru; Yamamoto, Homaro; Kawashima, Ena; Tan, Xin; Sawa, Yutaka

The aim of this study was to develop a method for discriminating between patients with Alzheimer disease (AD) and healthy subjects using layer analysis of cerebral blood flow (CBF) and xenon solubility coefficient (λ) in xenon-enhanced computed tomography (CT). Xenon-enhanced CT was performed on 27 patients with AD (81.7 [3.3] years old) and 15 healthy volunteers (78.6 [4.0] years old) using a wide volume CT. For each subject, we created the first- (surface) to sixth-layer images of CBF and λ for the 6 viewing directions (layer thickness, 5 mm). For the discriminant views, receiver operating characteristic curves for the ratio of CBF to λ were created to identify patients with AD. For the third- and fourth-layer left lateral views, which were designated as the discriminant views, areas under the receiver operating characteristic curve were 96.8% and 97.4%, respectively. With the use of the discriminant views obtained by xenon-enhanced CT, we could effectively discriminate between patients with AD and healthy subjects using both CBF and λ.

Syndrome Analysis: Chronic Alcoholism in Adults.

ERIC Educational Resources Information Center

Pendorf, James E.

1990-01-01

Provides outline narrative of most possible outcomes of regular heavy alcohol use, regular alcohol abuse, or chronic alcoholism. A systems analysis approach is used to expose conditions that may result when a human organism is subjected to excessive and chronic alcohol consumption. Such an approach illustrates the detrimental effects which alcohol…

Regularized Generalized Structured Component Analysis

ERIC Educational Resources Information Center

Hwang, Heungsun

2009-01-01

Generalized structured component analysis (GSCA) has been proposed as a component-based approach to structural equation modeling. In practice, GSCA may suffer from multi-collinearity, i.e., high correlations among exogenous variables. GSCA has yet no remedy for this problem. Thus, a regularized extension of GSCA is proposed that integrates a ridge…

Comparative decision models for anticipating shortage of food grain production in India

NASA Astrophysics Data System (ADS)

Chattopadhyay, Manojit; Mitra, Subrata Kumar

2018-01-01

This paper attempts to predict food shortages in advance from the analysis of rainfall during the monsoon months along with other inputs used for crop production, such as land used for cereal production, percentage of area covered under irrigation and fertiliser use. We used six binary classification data mining models viz., logistic regression, Multilayer Perceptron, kernel lab-Support Vector Machines, linear discriminant analysis, quadratic discriminant analysis and k-Nearest Neighbors Network, and found that linear discriminant analysis and kernel lab-Support Vector Machines are equally suitable for predicting per capita food shortage with 89.69 % accuracy in overall prediction and 92.06 % accuracy in predicting food shortage ( true negative rate). Advance information of food shortage can help policy makers to take remedial measures in order to prevent devastating consequences arising out of food non-availability.

A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction

NASA Astrophysics Data System (ADS)

Wels, Michael; Zheng, Yefeng; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2011-06-01

We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average Dice coefficients of 0.93 ± 0.03 (WM) and 0.90 ± 0.05 (GM) on simulated mono-spectral and 0.94 ± 0.02 (WM) and 0.92 ± 0.04 (GM) on simulated multi-spectral data from the BrainWeb repository. The scores are 0.81 ± 0.09 (WM) and 0.82 ± 0.06 (GM) and 0.87 ± 0.05 (WM) and 0.83 ± 0.12 (GM) for the two collections of real-world data sets—consisting of 20 and 18 volumes, respectively—provided by the Internet Brain Segmentation Repository.

A discriminative model-constrained EM approach to 3D MRI brain tissue classification and intensity non-uniformity correction.

PubMed

Wels, Michael; Zheng, Yefeng; Huber, Martin; Hornegger, Joachim; Comaniciu, Dorin

2011-06-07

We describe a fully automated method for tissue classification, which is the segmentation into cerebral gray matter (GM), cerebral white matter (WM), and cerebral spinal fluid (CSF), and intensity non-uniformity (INU) correction in brain magnetic resonance imaging (MRI) volumes. It combines supervised MRI modality-specific discriminative modeling and unsupervised statistical expectation maximization (EM) segmentation into an integrated Bayesian framework. While both the parametric observation models and the non-parametrically modeled INUs are estimated via EM during segmentation itself, a Markov random field (MRF) prior model regularizes segmentation and parameter estimation. Firstly, the regularization takes into account knowledge about spatial and appearance-related homogeneity of segments in terms of pairwise clique potentials of adjacent voxels. Secondly and more importantly, patient-specific knowledge about the global spatial distribution of brain tissue is incorporated into the segmentation process via unary clique potentials. They are based on a strong discriminative model provided by a probabilistic boosting tree (PBT) for classifying image voxels. It relies on the surrounding context and alignment-based features derived from a probabilistic anatomical atlas. The context considered is encoded by 3D Haar-like features of reduced INU sensitivity. Alignment is carried out fully automatically by means of an affine registration algorithm minimizing cross-correlation. Both types of features do not immediately use the observed intensities provided by the MRI modality but instead rely on specifically transformed features, which are less sensitive to MRI artifacts. Detailed quantitative evaluations on standard phantom scans and standard real-world data show the accuracy and robustness of the proposed method. They also demonstrate relative superiority in comparison to other state-of-the-art approaches to this kind of computational task: our method achieves average Dice coefficients of 0.93 ± 0.03 (WM) and 0.90 ± 0.05 (GM) on simulated mono-spectral and 0.94 ± 0.02 (WM) and 0.92 ± 0.04 (GM) on simulated multi-spectral data from the BrainWeb repository. The scores are 0.81 ± 0.09 (WM) and 0.82 ± 0.06 (GM) and 0.87 ± 0.05 (WM) and 0.83 ± 0.12 (GM) for the two collections of real-world data sets-consisting of 20 and 18 volumes, respectively-provided by the Internet Brain Segmentation Repository.

Evaluation of removal of the size effect using data scaling and elliptic Fourier descriptors in otolith shape analysis, exemplified by the discrimination of two yellow croaker stocks along the Chinese coast

NASA Astrophysics Data System (ADS)

Zhao, Bo; Liu, Jinhu; Song, Junjie; Cao, Liang; Dou, Shuozeng

2017-11-01

Removal of the length effect in otolith shape analysis for stock identification using length scaling is an important issue; however, few studies have attempted to investigate the effectiveness or weakness of this methodology in application. The aim of this study was to evaluate whether commonly used size scaling methods and normalized elliptic Fourier descriptors (NEFDs) could effectively remove the size effect of fish in stock discrimination. To achieve this goal, length groups from two known geographical stocks of yellow croaker, Larimichthys polyactis, along the Chinese coast (five groups from the Changjiang River estuary of the East China Sea and three groups from the Bohai Sea) were subjected to otolith shape analysis. The results indicated that the variation of otolith shape caused by intra-stock fish length might exceed that due to inter-stock geographical separation, even when otolith shape variables are standardized with length scaling methods. This variation could easily result in misleading stock discrimination through otolith shape analysis. Therefore, conclusions about fish stock structure should be carefully drawn from otolith shape analysis because the observed discrimination may primarily be due to length effects, rather than differences among stocks. The application of multiple methods, such as otoliths shape analysis combined with elemental fingering, tagging or genetic analysis, is recommended for sock identification.

Perceived Interpersonal Discrimination and Older Women’s Mental Health: Accumulation Across Domains, Attributions, and Time

PubMed Central

Bécares, Laia; Zhang, Nan

2018-01-01

Abstract Experiencing discrimination is associated with poor mental health, but how cumulative experiences of perceived interpersonal discrimination across attributes, domains, and time are associated with mental disorders is still unknown. Using data from the Study of Women’s Health Across the Nation (1996–2008), we applied latent class analysis and generalized linear models to estimate the association between cumulative exposure to perceived interpersonal discrimination and older women’s mental health. We found 4 classes of perceived interpersonal discrimination, ranging from cumulative exposure to discrimination over attributes, domains, and time to none or minimal reports of discrimination. Women who experienced cumulative perceived interpersonal discrimination over time and across attributes and domains had the highest risk of depression (Center for Epidemiologic Studies Depression Scale score ≥16) compared with women in all other classes. This was true for all women regardless of race/ethnicity, although the type and severity of perceived discrimination differed across racial/ethnic groups. Cumulative exposure to perceived interpersonal discrimination across attributes, domains, and time has an incremental negative long-term association with mental health. Studies that examine exposure to perceived discrimination due to a single attribute in 1 domain or at 1 point in time underestimate the magnitude and complexity of discrimination and its association with health. PMID:29036550

A Three-Dimensional Finite Element Analysis of the Stress Distribution Generated by Splinted and Nonsplinted Prostheses in the Rehabilitation of Various Bony Ridges with Regular or Short Morse Taper Implants.

PubMed

Toniollo, Marcelo Bighetti; Macedo, Ana Paula; Rodrigues, Renata Cristina; Ribeiro, Ricardo Faria; de Mattos, Maria G

The aim of this study was to compare the biomechanical performance of splinted or nonsplinted prostheses over short- or regular-length Morse taper implants (5 mm and 11 mm, respectively) in the posterior area of the mandible using finite element analysis. Three-dimensional geometric models of regular implants (Ø 4 × 11 mm) and short implants (Ø 4 × 5 mm) were placed into a simulated model of the left posterior mandible that included the first premolar tooth; all teeth posterior to this tooth had been removed. The four experimental groups were as follows: regular group SP (three regular implants were rehabilitated with splinted prostheses), regular group NSP (three regular implants were rehabilitated with nonsplinted prostheses), short group SP (three short implants were rehabilitated with splinted prostheses), and short group NSP (three short implants were rehabilitated with nonsplinted prostheses). Oblique forces were simulated in molars (365 N) and premolars (200 N). Qualitative and quantitative analyses of the minimum principal stress in bone were performed using ANSYS Workbench software, version 10.0. The use of splinting in the short group reduced the stress to the bone surrounding the implants and tooth. The use of NSP or SP in the regular group resulted in similar stresses. The best indication when there are short implants is to use SP. Use of NSP is feasible only when regular implants are present.

Application of artificial neural network model combined with four biomarkers in auxiliary diagnosis of lung cancer.

PubMed

Duan, Xiaoran; Yang, Yongli; Tan, Shanjuan; Wang, Sihua; Feng, Xiaolei; Cui, Liuxin; Feng, Feifei; Yu, Songcheng; Wang, Wei; Wu, Yongjun

2017-08-01

The purpose of the study was to explore the application of artificial neural network model in the auxiliary diagnosis of lung cancer and compare the effects of back-propagation (BP) neural network with Fisher discrimination model for lung cancer screening by the combined detections of four biomarkers of p16, RASSF1A and FHIT gene promoter methylation levels and the relative telomere length. Real-time quantitative methylation-specific PCR was used to detect the levels of three-gene promoter methylation, and real-time PCR method was applied to determine the relative telomere length. BP neural network and Fisher discrimination analysis were used to establish the discrimination diagnosis model. The levels of three-gene promoter methylation in patients with lung cancer were significantly higher than those of the normal controls. The values of Z(P) in two groups were 2.641 (0.008), 2.075 (0.038) and 3.044 (0.002), respectively. The relative telomere lengths of patients with lung cancer (0.93 ± 0.32) were significantly lower than those of the normal controls (1.16 ± 0.57), t = 4.072, P < 0.001. The areas under the ROC curve (AUC) and 95 % CI of prediction set from Fisher discrimination analysis and BP neural network were 0.670 (0.569-0.761) and 0.760 (0.664-0.840). The AUC of BP neural network was higher than that of Fisher discrimination analysis, and Z(P) was 0.76. Four biomarkers are associated with lung cancer. BP neural network model for the prediction of lung cancer is better than Fisher discrimination analysis, and it can provide an excellent and intelligent diagnosis tool for lung cancer.

Detection of cervical lesions by multivariate analysis of diffuse reflectance spectra: a clinical study.

PubMed

Prabitha, Vasumathi Gopala; Suchetha, Sambasivan; Jayanthi, Jayaraj Lalitha; Baiju, Kamalasanan Vijayakumary; Rema, Prabhakaran; Anuraj, Koyippurath; Mathews, Anita; Sebastian, Paul; Subhash, Narayanan

2016-01-01

Diffuse reflectance (DR) spectroscopy is a non-invasive, real-time, and cost-effective tool for early detection of malignant changes in squamous epithelial tissues. The present study aims to evaluate the diagnostic power of diffuse reflectance spectroscopy for non-invasive discrimination of cervical lesions in vivo. A clinical trial was carried out on 48 sites in 34 patients by recording DR spectra using a point-monitoring device with white light illumination. The acquired data were analyzed and classified using multivariate statistical analysis based on principal component analysis (PCA) and linear discriminant analysis (LDA). Diagnostic accuracies were validated using random number generators. The receiver operating characteristic (ROC) curves were plotted for evaluating the discriminating power of the proposed statistical technique. An algorithm was developed and used to classify non-diseased (normal) from diseased sites (abnormal) with a sensitivity of 72 % and specificity of 87 %. While low-grade squamous intraepithelial lesion (LSIL) could be discriminated from normal with a sensitivity of 56 % and specificity of 80 %, and high-grade squamous intraepithelial lesion (HSIL) from normal with a sensitivity of 89 % and specificity of 97 %, LSIL could be discriminated from HSIL with 100 % sensitivity and specificity. The areas under the ROC curves were 0.993 (95 % confidence interval (CI) 0.0 to 1) and 1 (95 % CI 1) for the discrimination of HSIL from normal and HSIL from LSIL, respectively. The results of the study show that DR spectroscopy could be used along with multivariate analytical techniques as a non-invasive technique to monitor cervical disease status in real time.

Bias of phencyclidine discrimination by the schedule of reinforcement.

PubMed Central

McMillan, D E; Wenger, G R

1984-01-01

Pigeons, trained to discriminate phencyclidine from saline under a procedure requiring the bird to track the location of a color, received cumulative doses of phencyclidine, pentobarbital, or d-amphetamine with a variety of schedules of reinforcement in effect (across phases). When the same second-order schedules were used to reinforce responding after either saline or phencyclidine administration, stimulus control by phencyclidine did not depend on the schedule parameter. When different second-order schedules were used that biased responding toward the phencyclidine-correlated key color, pigeons responded on the phencyclidine-correlated key at lower doses of phencyclidine and pentobarbital than when the second-order schedule biased responding toward the saline key color. A similar but less marked effect was obtained with d-amphetamine. Attempts to produce bias by changing reinforcement magnitude (duration of food availability) were less successful. A signal-detection analysis of dose-effect curves for phencyclidine under two of the second-order schedules employed suggested that at low doses of phencyclidine, response bias is a major determinant of responding. As doses were increased, position preferences occurred and response bias decreased; at higher doses both response bias and position preference decreased and discriminability increased. With low doses of pentobarbital, responding again was biased but increasing doses produced position preference with only small increases in discriminability. At low doses of d-amphetamine responding also was biased, but bias did not decrease consistently with dose nor did discriminability increase. These experiments suggest that the schedule of reinforcement can be used to bias responding toward or away from making the drug-correlated response in drug discrimination experiments, and that signal-detection analysis and analysis of responding at a position can be used to separate the discriminability of the drug state from other effects of the drug on responding. PMID:6481300

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

USGS Publications Warehouse

Hoff, Michael H.

2004-01-01

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

Diagnosing basal cell carcinoma in vivo by near-infrared Raman spectroscopy: a Principal Components Analysis discrimination algorithm

NASA Astrophysics Data System (ADS)

Silveira, Landulfo, Jr.; Silveira, Fabrício L.; Bodanese, Benito; Pacheco, Marcos Tadeu T.; Zângaro, Renato A.

2012-02-01

This work demonstrated the discrimination among basal cell carcinoma (BCC) and normal human skin in vivo using near-infrared Raman spectroscopy. Spectra were obtained in the suspected lesion prior resectional surgery. After tissue withdrawn, biopsy fragments were submitted to histopathology. Spectra were also obtained in the adjacent, clinically normal skin. Raman spectra were measured using a Raman spectrometer (830 nm) with a fiber Raman probe. By comparing the mean spectra of BCC with the normal skin, it has been found important differences in the 800-1000 cm-1 and 1250-1350 cm-1 (vibrations of C-C and amide III, respectively, from lipids and proteins). A discrimination algorithm based on Principal Components Analysis and Mahalanobis distance (PCA/MD) could discriminate the spectra of both tissues with high sensitivity and specificity.