Race-based job discrimination, disparities in job control, and their joint effects on health.

PubMed

Meyer, John D

2014-05-01

To examine disparities between job control scores in Black and White subjects and attempt to discern whether self-rated low job control in Blacks may arise from structural segregation into different jobs, or represents individual responses to race-based discrimination in hiring or promotion. Data from the National Survey of Midlife in the United States (MIDUS) were analyzed by mixed-effects linear regression and variance regression to determine the effects of grouping by occupation, and racial discrimination in hiring or promotion, on control scores from the Job Content Questionnaire in Black and White subjects. Path analyses were constructed to determine the mediating effect of discrimination on pathways from education and job control to self-rated health. Black subjects exhibited lower mean job control scores compared to Whites (mean score difference 2.26, P < 0.001) adjusted for age, sex, education, and income. This difference narrowed to 1.86 when adjusted for clustering by occupation, and was greatly reduced by conditioning on race-based discrimination (score difference 1.03, P = 0.12). Path analyses showed greater reported discrimination in Blacks with increasing education, and a stronger effect of job control on health in Black subjects. Individual racially-based discrimination appears a stronger determinant than structural segregation in reduced job control in Black workers, and may contribute to health disparities consequent on work. © 2013 Wiley Periodicals, Inc.

The Association Between Racial and Gender Discrimination and Body Mass Index Among Residents Living in Lower-income Housing

PubMed Central

Shelton, Rachel C.; Puleo, Elaine; Bennett, Gary G.; McNeill, Lorna H.; Sorensen, Glorian; Emmons, Karen M.

2010-01-01

Background Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. Objectives The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Methods Baseline survey data were collected among 1,307 (weighted N=1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Results Our sample was predominately Black (weighted n=956) and Hispanic (weighted n=857), and female (weighted n=1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m−2 (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. Conclusions While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities. PMID:19769005

The association between racial and gender discrimination and body mass index among residents living in lower-income housing.

PubMed

Shelton, Rachel C; Puleo, Elaine; Bennett, Gary G; McNeill, Lorna H; Sorensen, Glorian; Emmons, Karen M

2009-01-01

Research on the association between self-reported racial or gender discrimination and body mass index (BMI) has been limited and inconclusive to date, particularly among lower-income populations. The aim of the current study was to examine the association between self-reported racial and gender discrimination and BMI among a sample of adult residents living in 12 urban lower-income housing sites in Boston, Masschusetts (USA). Baseline survey data were collected among 1,307 (weighted N = 1907) study participants. For analyses, linear regression models with a cluster design were conducted using SUDAAN and SAS statistical software. Our sample was predominately Black (weighted n = 956) and Hispanic (weighted n = 857), and female (weighted n = 1420), with a mean age of 49.3 (SE: .40) and mean BMI of 30.2 kg m(-2) (SE: .19). Nearly 47% of participants reported ever experiencing racial discrimination, and 24.8% reported ever experiencing gender discrimination. In bivariate and multivariable linear regression models, no main effect association was found between either racial or gender discrimination and BMI. While our findings suggest that self-reported discrimination is not a key determinant of BMI among lower-income housing residents, these results should be considered in light of study limitations. Future researchers may want to investigate this association among other relevant samples, and other social contextual and cultural factors should be explored to understand how they contribute to disparities.

Intergenerational Consequences: Women's Experiences of Discrimination in Pregnancy Predict Infant Social-Emotional Development at 6 Months and 1 Year.

PubMed

Rosenthal, Lisa; Earnshaw, Valerie A; Moore, Joan M; Ferguson, Darrah N; Lewis, Tené T; Reid, Allecia E; Lewis, Jessica B; Stasko, Emily C; Tobin, Jonathan N; Ickovics, Jeannette R

2018-04-01

Racial/ethnic and socioeconomic disparities in infant development in the United States have lifelong consequences. Discrimination predicts poorer health and academic outcomes. This study explored for the first time intergenerational consequences of women's experiences of discrimination reported during pregnancy for their infants' social-emotional development in the first year of life. Data come from a longitudinal study with predominantly Black and Latina, socioeconomically disadvantaged, urban young women (N = 704, Mage = 18.53) across pregnancy through 1 year postpartum. Women were recruited from community hospitals and health centers in a Northeastern US city. Linear regression analyses examined whether women's experiences of everyday discrimination reported during pregnancy predicted social-emotional development outcomes among their infants at 6 months and 1 year of age, controlling for potentially confounding medical and sociodemographic factors. Path analyses tested if pregnancy distress, anxiety, or depressive symptoms mediated significant associations. Everyday discrimination reported during pregnancy prospectively predicted greater inhibition/separation problems and greater negative emotionality, but did not predict attention skills or positive emotionality, at 6 months and 1 year. Depressive symptoms mediated the association of discrimination with negative emotionality at 6 months, and pregnancy distress, anxiety, and depressive symptoms mediated the association of discrimination with negative emotionality at 1 year. Findings support that there are intergenerational consequences of discrimination, extending past findings to infant social-emotional development outcomes in the first year of life. It may be important to address discrimination before and during pregnancy and enhance support to mothers and infants exposed to discrimination to promote health equity across the life span.

Using Discrete Loss Functions and Weighted Kappa for Classification: An Illustration Based on Bayesian Network Analysis

ERIC Educational Resources Information Center

Zwick, Rebecca; Lenaburg, Lubella

2009-01-01

In certain data analyses (e.g., multiple discriminant analysis and multinomial log-linear modeling), classification decisions are made based on the estimated posterior probabilities that individuals belong to each of several distinct categories. In the Bayesian network literature, this type of classification is often accomplished by assigning…

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.

Environmental discrimination of wines using the content of lithium, potassium and rubidium.

PubMed

Del Signore, Antonella

2003-01-01

56 wine samples were analysed to determine their content of Li, K and Rb. These samples came from 28 species of vine grown on two plots of land, each of which had different pedo-climatic characteristics. The data collected were elaborated using Linear Discriminant Analysis (LDA); this statistical approach showed that it was possible to net differentiate both the soil where the different species of vines were grown and the colour of wines. The variable "species of vine nationality", instead, has not been discriminated by LDA. These results point out that it is possible to identify the place of origin of wines and that the "environment" variable prevails over the others, using the content of Li, K and Rb.

Race-based rejection sensitivity partially accounts for the relationship between racial discrimination and distressing attenuated positive psychotic symptoms.

PubMed

Anglin, Deidre M; Greenspoon, Michelle; Lighty, Quenesha; Ellman, Lauren M

2016-10-01

Self-reported experiences of racial discrimination have been associated with a continuum of psychotic experiences in racial and ethnic minority populations; however, the underlying mechanisms of this relationship are not yet clear. Race-based rejection sensitivity (RS-race) has been associated with thought intrusions about being the target of racial discrimination; therefore, the present study aimed to determine whether RS-race accounts for the relationship between racial discrimination and psychotic-like experiences in racial and ethnic minority populations. A sample of 644 young adults from a US urban, predominantly immigrant, and racial and ethnic minority population was administered a self-report inventory of psychosis risk (i.e. Prodromal Questionnaire (PQ) ), providing a dimensional assessment of the total number of attenuated positive psychotic symptoms experienced as distressing (APPS-distress). Participants also completed the Experiences of Discrimination Questionnaire and the Rejection Sensitivity Questionnaire-Race. Hierarchical linear regression analyses revealed that RS-race and racial discrimination were both significantly related to higher levels of APPS-distress. Bootstrapping analyses of indirect effects indicated that RS-race partially accounted for the relationship between racial discrimination and APPS-distress. Although the cross-sectional nature of the data limits conclusions about causal inference, our findings do suggest that racial discrimination and RS-race may both be important for understanding risk for distress in the psychotic spectrum among racial and ethnic minority young adults. Some individuals who report racial discrimination may be more vulnerable to APPS-distress in part because they are anxiously anticipating being racially slighted, and this should be explored further in prospective clinical high-risk studies. © 2014 Wiley Publishing Asia Pty Ltd.

determination of sex in south african blacks by discriminant function analysis of mandibular linear dimensions : A preliminary investigation using the zulu local population.

PubMed

Franklin, Daniel; O'Higgins, Paul; Oxnard, Charles E; Dadour, Ian

2006-12-01

The determination of sex is a critical component in forensic anthropological investigation. The literature attests to numerous metrical standards, each utilizing diffetent skeletal elements, for sex determination in South A frican Blacks. Metrical standards are popular because they provide a high degree of expected accuracy and are less error-prone than subjective nonmetric visual techniques. We note, however, that there appears to be no established metric mandible discriminant function standards for sex determination in this population.We report here on a preliminary investigation designed to evaluate whether the mandible is a practical element for sex determination in South African Blacks. The sample analyzed comprises 40 nonpathological Zulu individuals drawn from the R.A. Dart Collection. Ten linear measurements, obtained from mathematically trans-formed three-dimensional landmark data, are analyzed using basic univariate statistics and discriminant function analyses. Seven of the 10 measurements examined are found to be sexually dimorphic; the dimensions of the ramus are most dimorphic. The sex classification accuracy of the discriminant functions ranged from 72.5 to 87.5% for the univariate method, 92.5% for the stepwise method, and 57.5 to 95% for the direct method. We conclude that the mandible is an extremely useful element for sex determination in this population.

Self-Reported Experiences of Discrimination and Depression in Native Hawaiians.

PubMed

Antonio, Mapuana Ck; Ahn, Hyeong Jun; Ing, Claire Townsend; Dillard, Adrienne; Cassel, Kevin; Kekauoha, B Puni; Kaholokula, Joseph Keawe'aimoku

2016-09-01

Discrimination is an acute and chronic stressor that negatively impacts the health of many ethnic groups in the United States. Individuals who perceive increased levels of discrimination are at risk of experiencing psychological distress and symptoms of depression. No study to date has examined the relationship between perceived discrimination and mental health in Native Hawaiians. The purpose of this study is to explore the relationship between perceived discrimination and depression based on the Homestead Health Survey mailed to Native Hawaiian residents of Hawaiian Home Lands. This study also explores the role of cultural identity and how it may impact experiences of discrimination and symptoms of depression. Based on cross-sectional data obtained from 104 Native Hawaiian residents, a significant positive correlation was found between perceived discrimination and symptoms of depression (r= 0.32, P<.001). Cultural identity did not significantly correlate with discrimination or depression. Multiple linear regression analyses indicate that the relationship between depression and discrimination remained statistically significant (coefficient estimate of 0.18; P<.01), after accounting for differences in socio-demographics and degree of identification with the Native Hawaiian and American cultures. These findings are consistent with other studies that have focused on the effects of discrimination on psychological wellbeing for other ethnic minority populations.

Self-Reported Experiences of Discrimination and Depression in Native Hawaiians

PubMed Central

Ahn, Hyeong Jun; Ing, Claire Townsend; Dillard, Adrienne; Cassel, Kevin; Kekauoha, B Puni; Kaholokula, Joseph Keawe‘aimoku

2016-01-01

Discrimination is an acute and chronic stressor that negatively impacts the health of many ethnic groups in the United States. Individuals who perceive increased levels of discrimination are at risk of experiencing psychological distress and symptoms of depression. No study to date has examined the relationship between perceived discrimination and mental health in Native Hawaiians. The purpose of this study is to explore the relationship between perceived discrimination and depression based on the Homestead Health Survey mailed to Native Hawaiian residents of Hawaiian Home Lands. This study also explores the role of cultural identity and how it may impact experiences of discrimination and symptoms of depression. Based on cross-sectional data obtained from 104 Native Hawaiian residents, a significant positive correlation was found between perceived discrimination and symptoms of depression (r= 0.32, P<.001). Cultural identity did not significantly correlate with discrimination or depression. Multiple linear regression analyses indicate that the relationship between depression and discrimination remained statistically significant (coefficient estimate of 0.18; P<.01), after accounting for differences in socio-demographics and degree of identification with the Native Hawaiian and American cultures. These findings are consistent with other studies that have focused on the effects of discrimination on psychological wellbeing for other ethnic minority populations. PMID:27688952

Discrimination, perceived social inequity, and mental health among rural-to-urban migrants in China.

PubMed

Lin, Danhua; Li, Xiaoming; Wang, Bo; Hong, Yan; Fang, Xiaoyi; Qin, Xiong; Stanton, Bonita

2011-04-01

Status-based discrimination and inequity have been associated with the process of migration, especially with economics-driven internal migration. However, their association with mental health among economy-driven internal migrants in developing countries is rarely assessed. This study examines discriminatory experiences and perceived social inequity in relation to mental health status among rural-to-urban migrants in China. Cross-sectional data were collected from 1,006 rural-to-urban migrants in 2004-2005 in Beijing, China. Participants reported their perceptions and experiences of being discriminated in daily life in urban destination and perceived social inequity. Mental health was measured using the symptom checklist-90 (SCL-90). Multivariate analyses using general linear model were performed to test the effect of discriminatory experience and perceived social inequity on mental health. Experience of discrimination was positively associated with male gender, being married at least once, poorer health status, shorter duration of migration, and middle range of personal income. Likewise, perceived social inequity was associated with poorer health status, higher education attainment, and lower personal income. Multivariate analyses indicate that both experience of discrimination and perceived social inequity were strongly associated with mental health problems of rural-to-urban migrants. Experience of discrimination in daily life and perceived social inequity have a significant influence on mental health among rural-to-urban migrants. The findings underscore the needs to reduce public or societal discrimination against rural-to-urban migrants, to eliminate structural barriers (i.e., dual household registrations) for migrants to fully benefit from the urban economic development, and to create a positive atmosphere to improve migrant's psychological well-being.

Relationship between item difficulty and discrimination indices in true/false-type multiple choice questions of a para-clinical multidisciplinary paper.

PubMed

Sim, Si-Mui; Rasiah, Raja Isaiah

2006-02-01

This paper reports the relationship between the difficulty level and the discrimination power of true/false-type multiple-choice questions (MCQs) in a multidisciplinary paper for the para-clinical year of an undergraduate medical programme. MCQ items in papers taken from Year II Parts A, B and C examinations for Sessions 2001/02, and Part B examinations for 2002/03 and 2003/04, were analysed to obtain their difficulty indices and discrimination indices. Each paper consisted of 250 true/false items (50 questions of 5 items each) on topics drawn from different disciplines. The questions were first constructed and vetted by the individual departments before being submitted to a central committee, where the final selection of the MCQs was made, based purely on the academic judgement of the committee. There was a wide distribution of item difficulty indices in all the MCQ papers analysed. Furthermore, the relationship between the difficulty index (P) and discrimination index (D) of the MCQ items in a paper was not linear, but more dome-shaped. Maximal discrimination (D = 51% to 71%) occurred with moderately easy/difficult items (P = 40% to 74%). On average, about 38% of the MCQ items in each paper were "very easy" (P > or =75%), while about 9% were "very difficult" (P <25%). About two-thirds of these very easy/difficult items had "very poor" or even negative discrimination (D < or =20%). MCQ items that demonstrate good discriminating potential tend to be moderately difficult items, and the moderately-to-very difficult items are more likely to show negative discrimination. There is a need to evaluate the effectiveness of our MCQ items.

Socioeconomic status discrimination and C-reactive protein in African-American and White adults.

PubMed

Van Dyke, Miriam E; Vaccarino, Viola; Dunbar, Sandra B; Pemu, Priscilla; Gibbons, Gary H; Quyyumi, Arshed A; Lewis, Tené T

2017-08-01

We examined the association between socioeconomic status (SES) discrimination and C-reactive protein (CRP) in a biracial cohort of middle-aged adults using an intersectionality framework. Participants were 401 African-American and White adults from a population-based cohort in the Southeastern United States. SES discrimination was self-reported with a modified Experiences of Discrimination Scale, and CRP levels were assayed from blood samples. Linear regression analyses were used to examine the associations among SES discrimination, race, education, and CRP after controlling for age, gender, racial and gender discrimination, financial and general stress, body mass index, smoking, sleep quality, and depressive symptoms. Intersectional effects were tested using race×SES discrimination, education×SES discrimination and race×education×SES discrimination interactions. Adjusting for sociodemographics, racial discrimination, gender discrimination, and all relevant two-way interaction terms, we observed a significant race×education×SES discrimination interaction (p=0.019). In adjusted models stratified by race and education, SES discrimination was associated with elevated CRP among higher educated African-Americans (β=0.29, p=0.018), but not lower educated African-Americans (β=-0.13, p=0.32); or lower educated (β=-0.02, p=0.92) or higher educated (β=-0.01, p=0.90) Whites. Findings support the relevance of SES discrimination as an important discriminatory stressor for CRP specifically among higher educated African-Americans. Copyright © 2017 Elsevier Ltd. All rights reserved.

Racial discrimination associated with higher diastolic blood pressure in a sample of American Indian adults

PubMed Central

Thayer, Zaneta M.; Blair, Irene V.; Buchwald, Dedra S.; Manson, Spero M.

2017-01-01

Objectives Hypertension prevalence is high among American Indians (AIs). AIs experience a substantial burden of interpersonal racial discrimination, which in other populations has been associated with higher blood pressure. The purpose of this study is to understand whether racial discrimination experiences are associated with higher blood pressure in AIs. Materials and Methods We used the Everyday Discrimination Scale to evaluate the relationship between discrimination and measured blood pressure among 77 AIs from two reservation communities in the Northern Plains. We used multivariate linear regression to evaluate the association of racial discrimination with systolic and diastolic blood pressure, respectively. Racial discrimination, systolic blood pressure, and diastolic blood pressure were analyzed as continuous variables. All analyses adjusted for sex, waist circumference, age, posttraumatic stress disorder status, and education. Results We found that 61% of participants experienced discrimination that they attributed to their race or ancestry. Racial discrimination was associated with significantly higher diastolic blood pressure (β = 0.22, SE = 0.09, P = 0.02), and with a similar non-significant trend toward higher systolic blood pressure (β = 0.25, SE = 0.15, P = 0.09). Conclusion The results of this analysis suggest that racial discrimination may contribute to higher diastolic blood pressure within Native communities. These findings highlight one pathway through which the social environment can shape patterns of biology and health in AI and other socially and politically marginalized groups. PMID:28198537

Fully optimized discrimination of physiological responses to auditory stimuli

PubMed Central

Kruglikov, Stepan Y; Chari, Sharmila; Rapp, Paul E; Weinstein, Steven L; Given, Barbara K; Schiff, Steven J

2008-01-01

The use of multivariate measurements to characterize brain activity (electrical, magnetic, optical) is widespread. The most common approaches to reduce the complexity of such observations include principal and independent component analyses (PCA and ICA), which are not well suited for discrimination tasks. We addressed two questions: first, how do the neurophysiological responses to elongated phonemes relate to tone and phoneme responses in normal children, and, second, how discriminable are these responses. We employed fully optimized linear discrimination analysis to maximally separate the multi-electrode responses to tones and phonemes, and classified the response to elongated phonemes. We find that discrimination between tones and phonemes is dependent upon responses from associative regions of the brain apparently distinct from the primary sensory cortices typically emphasized by PCA or ICA, and that the neuronal correlates corresponding to elongated phonemes are highly variable in normal children (about half respond with neural correlates of tones and half as phonemes). Our approach is made feasible by the increase in computational power of ordinary personal computers and has significant advantages for a wide range of neuronal imaging modalities. PMID:18430975

Discrimination, Perceived Social Inequity, and Mental Health Among Rural-to-Urban Migrants in China

PubMed Central

Lin, Danhua; Wang, Bo; Hong, Yan; Qin, Xiong; Stanton, Bonita

2010-01-01

Status-based discrimination and inequity have been associated with the process of migration, especially with economics-driven internal migration. However, their association with mental health among economy-driven internal migrants in developing countries is rarely assessed. This study examines discriminatory experiences and perceived social inequity in relation to mental health status among rural-to-urban migrants in China. Cross-sectional data were collected from 1,006 rural-to-urban migrants in 2004–2005 in Beijing, China. Participants reported their perceptions and experiences of being discriminated in daily life in urban destination and perceived social inequity. Mental health was measured using the symptom checklist-90 (SCL-90). Multivariate analyses using general linear model were performed to test the effect of discriminatory experience and perceived social inequity on mental health. Experience of discrimination was positively associated with male gender, being married at least once, poorer health status, shorter duration of migration, and middle range of personal income. Likewise, perceived social inequity was associated with poorer health status, higher education attainment, and lower personal income. Multivariate analyses indicate that both experience of discrimination and perceived social inequity were strongly associated with mental health problems of rural-to-urban migrants. Experience of discrimination in daily life and perceived social inequity have a significant influence on mental health among rural-to-urban migrants. The findings underscore the needs to reduce public or societal discrimination against rural-to-urban migrants, to eliminate structural barriers (i.e., dual household registrations) for migrants to fully benefit from the urban economic development, and to create a positive atmosphere to improve migrant's psychological well-being. PMID:20033772

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.

The association of cumulative discrimination on quality of care, patient-centered care, and dissatisfaction with care in adults with type 2 diabetes.

PubMed

Cykert, David M; Williams, Joni S; Walker, Rebekah J; Davis, Kimberly S; Egede, Leonard E

2017-01-01

Discrimination is linked to negative health outcomes, but little research has investigated how the cumulative effect of discrimination impacts perceptions of care. This study investigated the influence of cumulative perceived discrimination on quality of care, patient-centeredness, and dissatisfaction with care in adults with type 2 diabetes. Six hundred two patients from two primary care clinics in Charleston, SC. Linear regression models assessed associations between perceived discrimination and quality of care, patient-centered care, and dissatisfaction with care. The models control for race, site, age, gender, marital status, duration of diabetes, education, hours worked weekly, income, and health status. The mean age was 61.5years, with 66.3% non-Hispanic blacks, and 41.9% earning less than $20,000 annually. In final adjusted analyses, lower patient-centered care was associated with a higher discrimination score (β=-0.28; p=0.006), reporting at least 1 category of discrimination (β=-1.47; p=0.002), and reporting at least 2 categories of discrimination (β=-1.34; p=0.004). Dissatisfaction with care was associated with at least 2 categories of discrimination (β=0.45; p=0.002). No significant associations were seen with quality of care indicators. Increased cumulative discrimination was associated with decreased feeling of patient-centeredness and increased dissatisfaction with care. However, these perceptions of discrimination were not significantly associated with quality indicators. Copyright © 2017 Elsevier Inc. All rights reserved.

Ethnic identity, racial discrimination and attenuated psychotic symptoms in an urban population of emerging adults.

PubMed

Anglin, Deidre M; Lui, Florence; Espinosa, Adriana; Tikhonov, Aleksandr; Ellman, Lauren

2018-06-01

Studies suggest strong ethnic identity generally protects against negative mental health outcomes associated with racial discrimination. In light of evidence suggesting racial discrimination may enhance psychosis risk in racial and ethnic minority (REM) populations, the present study explored the relationship between ethnic identity and attenuated positive psychotic symptoms (APPS) and whether ethnic identity moderates the association between racial discrimination and these symptoms. A sample of 644 non-help-seeking REM emerging adults was administered self-report inventories for psychosis risk, experiences of discrimination and ethnic identity. Latent class analysis was applied to determine the nature and number of ethnic identity types in this population. The direct association between ethnic identity and APPS and the interaction between ethnic identity and racial discrimination on APPS were determined in linear regression analyses. Results indicated three ethnic identity classes (very low, moderate to high and very high). Ethnic identity was not directly related to APPS; however, it was related to APPS under racially discriminating conditions. Specifically, participants who experienced discrimination in the moderate to high or very high ethnic identity classes reported fewer symptoms than participants who experienced discrimination in the very low ethnic identity class. Strong ethnic group affiliation and connection may serve a protective function for psychosis risk in racially discriminating environments and contexts among REM young adults. The possible social benefits of strong ethnic identification among REM youth who face racial discrimination should be explored further in clinical high-risk studies. © 2016 John Wiley & Sons Australia, Ltd.

Multivariate analysis of volatile compounds detected by headspace solid-phase microextraction/gas chromatography: A tool for sensory classification of cork stoppers.

PubMed

Prat, Chantal; Besalú, Emili; Bañeras, Lluís; Anticó, Enriqueta

2011-06-15

The volatile fraction of aqueous cork macerates of tainted and non-tainted agglomerate cork stoppers was analysed by headspace solid-phase microextraction (HS-SPME)/gas chromatography. Twenty compounds containing terpenoids, aliphatic alcohols, lignin-related compounds and others were selected and analysed in individual corks. Cork stoppers were previously classified in six different classes according to sensory descriptions including, 2,4,6-trichloroanisole taint and other frequent, non-characteristic odours found in cork. A multivariate analysis of the chromatographic data of 20 selected chemical compounds using linear discriminant analysis models helped in the differentiation of the a priori made groups. The discriminant model selected five compounds as the best combination. Selected compounds appear in the model in the following order; 2,4,6 TCA, fenchyl alcohol, 1-octen-3-ol, benzyl alcohol and benzothiazole. Unfortunately, not all six a priori differentiated sensory classes were clearly discriminated in the model, probably indicating that no measurable differences exist in the chromatographic data for some categories. The predictive analyses of a refined model in which two sensory classes were fused together resulted in a good classification. Prediction rates of control (non-tainted), TCA, musty-earthy-vegetative, vegetative and chemical descriptions were 100%, 100%, 85%, 67.3% and 100%, respectively, when the modified model was used. The multivariate analysis of chromatographic data will help in the classification of stoppers and provide a perfect complement to sensory analyses. Copyright © 2010 Elsevier Ltd. All rights reserved.

Predictive models reduce talent development costs in female gymnastics.

PubMed

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

2017-04-01

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

Botanical discrimination of Greek unifloral honeys with physico-chemical and chemometric analyses.

PubMed

Karabagias, Ioannis K; Badeka, Anastasia V; Kontakos, Stavros; Karabournioti, Sofia; Kontominas, Michael G

2014-12-15

The aim of the present study was to investigate the possibility of characterisation and classification of Greek unifloral honeys (pine, thyme, fir and orange blossom) according to botanical origin using volatile compounds, conventional physico-chemical parameters and chemometric analyses (MANOVA and Linear Discriminant Analysis). For this purpose, 119 honey samples were collected during the harvesting period 2011 from 14 different regions in Greece known to produce unifloral honey of good quality. Physico-chemical analysis included the identification and semi quantification of fifty five volatile compounds performed by Headspace Solid Phase Microextraction coupled to gas chromatography/mass spectroscopy and the determination of conventional quality parameters such as pH, free, lactonic, total acidity, electrical conductivity, moisture, ash, lactonic/free acidity ratio and colour parameters L, a, b. Results showed that using 40 diverse variables (30 volatile compounds of different classes and 10 physico-chemical parameters) the honey samples were satisfactorily classified according to botanical origin using volatile compounds (84.0% correct prediction), physicochemical parameters (97.5% correct prediction), and the combination of both (95.8% correct prediction) indicating that multi element analysis comprises a powerful tool for honey discrimination purposes. Copyright © 2014 Elsevier Ltd. All rights reserved.

Self-reported discrimination and mental health among Asian Indians: Cultural beliefs and coping style as moderators

PubMed Central

Nadimpalli, Sarah B.; Kanaya, Alka M.; McDade, Thomas W.; Kandula, Namratha R.

2016-01-01

The South Asian (SA) population has been underrepresented in research linking discrimination with health indicators; studies that focus on the unique cultural and psychosocial experiences of different SA subgroups are needed. The purpose of this study was to examine associations between self-reported discrimination and mental health among Asian Indians (AIs), and whether traditional cultural beliefs (believing that South Asian cultural traditions should be practiced in the US), coping style, and social support moderated these relationships. Asian Indians (N = 733) had been recruited from community-based sampling frames for the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study were included in this analysis. Multiple linear regression analyses were employed to evaluate relationships between discrimination and depressive symptoms, anger, and anxiety. Participants (men = 54%) were on average 55 years of age and had high levels of English proficiency, education, and income. Higher reports of discrimination were significantly associated with higher depressive symptoms, B = .27 (.05) p < .001, anger, B = .08 (.01), p < .001, and anxiety, B = .10 (.01), p < .001. Associations between discrimination and anger, B = −.005 (.002), p = .02, were weakest among those with stronger cultural beliefs. The link between discrimination and anxiety was attenuated by an active coping style, B = −.05 (.03), p = .04. In sum, self-reported discrimination appeared to adversely impact the mental health of AIs. Discrimination may be better coped with by having strong traditional cultural beliefs and actively managing experiences of discrimination. PMID:27668066

Chronic exposure to everyday discrimination and sleep in a multiethnic sample of middle-aged women.

PubMed

Lewis, Tené T; Troxel, Wendy M; Kravitz, Howard M; Bromberger, Joyce T; Matthews, Karen A; Hall, Martica H

2013-07-01

Researchers have suggested that poor sleep may play a role in the association between discrimination and health, but studies linking experiences of discrimination to sleep are limited. The authors examined associations between reports of everyday discrimination over 4 years (chronic everyday discrimination) and subjective and objective indicators of poor sleep. Participants were 368 African American, Caucasian, and Chinese women from the Study of Women's Health Across the Nation Sleep Study. Everyday discrimination was assessed each year from baseline through the third follow-up exam via questionnaire with the Everyday Discrimination Scale (intraclass correlation coefficient over 4 years = .90). Subjective sleep complaints were measured beginning in Year 5 with the Pittsburgh Sleep Quality Index. Objective indices of sleep continuity, duration, and architecture were assessed via in-home polysomnography, beginning in Year 5. In linear regression analyses adjusted for age, race/ethnicity, and financial strain, chronic everyday discrimination was associated with more subjective sleep complaints (Estimate = 1.52, p < .001) and polysomnography-assessed wakefulness after sleep onset (Estimate = .19, p < .02), a marker of sleep continuity. Findings did not differ by race/ethnicity and remained significant after adjusting for menopausal status, body mass index, medication use, and depressive symptoms. Experiences of chronic everyday discrimination are independently associated with both subjective and objective indices of poor sleep. Findings add to the growing literature linking discrimination to key markers of biobehavioral health. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Racial discrimination associated with higher diastolic blood pressure in a sample of American Indian adults.

PubMed

Thayer, Zaneta M; Blair, Irene V; Buchwald, Dedra S; Manson, Spero M

2017-05-01

Hypertension prevalence is high among American Indians (AIs). AIs experience a substantial burden of interpersonal racial discrimination, which in other populations has been associated with higher blood pressure. The purpose of this study is to understand whether racial discrimination experiences are associated with higher blood pressure in AIs. We used the Everyday Discrimination Scale to evaluate the relationship between discrimination and measured blood pressure among 77 AIs from two reservation communities in the Northern Plains. We used multivariate linear regression to evaluate the association of racial discrimination with systolic and diastolic blood pressure, respectively. Racial discrimination, systolic blood pressure, and diastolic blood pressure were analyzed as continuous variables. All analyses adjusted for sex, waist circumference, age, posttraumatic stress disorder status, and education. We found that 61% of participants experienced discrimination that they attributed to their race or ancestry. Racial discrimination was associated with significantly higher diastolic blood pressure (β = 0.22, SE = 0.09, p = .02), and with a similar non-significant trend toward higher systolic blood pressure (β = 0.25, SE = 0.15, p = .09). The results of this analysis suggest that racial discrimination may contribute to higher diastolic blood pressure within Native communities. These findings highlight one pathway through which the social environment can shape patterns of biology and health in AI and other socially and politically marginalized groups. © 2017 Wiley Periodicals, Inc.

A Predictive Model to Identify Patients With Fecal Incontinence Based on High-Definition Anorectal Manometry.

PubMed

Zifan, Ali; Ledgerwood-Lee, Melissa; Mittal, Ravinder K

2016-12-01

Three-dimensional high-definition anorectal manometry (3D-HDAM) is used to assess anal sphincter function; it determines profiles of regional pressure distribution along the length and circumference of the anal canal. There is no consensus, however, on the best way to analyze data from 3D-HDAM to distinguish healthy individuals from persons with sphincter dysfunction. We developed a computer analysis system to analyze 3D-HDAM data and to aid in the diagnosis and assessment of patients with fecal incontinence (FI). In a prospective study, we performed 3D-HDAM analysis of 24 asymptomatic healthy subjects (control subjects; all women; mean age, 39 ± 10 years) and 24 patients with symptoms of FI (all women; mean age, 58 ± 13 years). Patients completed a standardized questionnaire (FI severity index) to score the severity of FI symptoms. We developed and evaluated a robust prediction model to distinguish patients with FI from control subjects using linear discriminant, quadratic discriminant, and logistic regression analyses. In addition to collecting pressure information from the HDAM data, we assessed regional features based on shape characteristics and the anal sphincter pressure symmetry index. The combination of pressure values, anal sphincter area, and reflective symmetry values was identified in patients with FI versus control subjects with an area under the curve value of 1.0. In logistic regression analyses using different predictors, the model identified patients with FI with an area under the curve value of 0.96 (interquartile range, 0.22). In discriminant analysis, results were classified with a minimum error of 0.02, calculated using 10-fold cross-validation; different combinations of predictors produced median classification errors of 0.16 in linear discriminant analysis (interquartile range, 0.25) and 0.08 in quadratic discriminant analysis (interquartile range, 0.25). We developed and validated a novel prediction model to analyze 3D-HDAM data. This system can accurately distinguish patients with FI from control subjects. Copyright © 2016 AGA Institute. Published by Elsevier Inc. All rights reserved.

Perceived discrimination and social networks among older African Americans and Caribbean blacks.

PubMed

Marshall, Gillian L; Rue, Tessa C

2012-01-01

The relationship between perceived discrimination and depressive symptoms among older black American populations is poorly understood. Although a small number of studies have examined the relationship between stress and social support, few have examined the association between perceived discrimination, social networks, and depressive symptoms among a representative sample of older racial and ethnic groups. This study examines (a) the relationship between sociodemographic factors, perceived discrimination and depressive symptoms and (b) social networks as a potential moderator in the perceived discrimination and depressive symptom relationship between 2 groups of older black Americans. This was a cross-sectional study using data from the National Survey of American Life with a sample of older African Americans (N = 837) and Caribbean blacks (N = 271). Depressive symptoms were assessed using the 12-item Center for Epidemiological Studies Depression scale. Linear regression analyses were used to predict depressive symptoms. The relationship between perceived discrimination and depressive symptoms was significant in both groups. Social networks contributed as a protective factor for depressive symptoms for both groups. However, there was no significant moderation effect. Results suggest that regardless of ethnic affiliation, the experience of perceived discrimination is similar in both groups and is a risk factor for depressive symptoms. Future research is needed in this area to better understand the associations between sociodemographic factors, perceived discrimination, social networks, and their impact on depressive symptoms.

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

PubMed

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

2017-03-01

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

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.

Virtual Assessment of Sex: Linear and Angular Traits of the Mandibular Ramus Using Three-Dimensional Computed Tomography.

PubMed

Inci, Ercan; Ekizoglu, Oguzhan; Turkay, Rustu; Aksoy, Sema; Can, Ismail Ozgur; Solmaz, Dilek; Sayin, Ibrahim

2016-10-01

Morphometric analysis of the mandibular ramus (MR) provides highly accurate data to discriminate sex. The objective of this study was to demonstrate the utility and accuracy of MR morphometric analysis for sex identification in a Turkish population.Four hundred fifteen Turkish patients (18-60 y; 201 male and 214 female) who had previously had multidetector computed tomography scans of the cranium were included in the study. Multidetector computed tomography images were obtained using three-dimensional reconstructions and a volume-rendering technique, and 8 linear and 3 angular values were measured. Univariate, bivariate, and multivariate discriminant analyses were performed, and the accuracy rates for determining sex were calculated.Mandibular ramus values produced high accuracy rates of 51% to 95.6%. Upper ramus vertical height had the highest rate at 95.6%, and bivariate analysis showed 89.7% to 98.6% accuracy rates with the highest ratios of mandibular flexure upper border and maximum ramus breadth. Stepwise discrimination analysis gave a 99% accuracy rate for all MR variables.Our study showed that the MR, in particular morphometric measures of the upper part of the ramus, can provide valuable data to determine sex in a Turkish population. The method combines both anthropological and radiologic studies.

Analysis of Optimal Sequential State Discrimination for Linearly Independent Pure Quantum States.

PubMed

Namkung, Min; Kwon, Younghun

2018-04-25

Recently, J. A. Bergou et al. proposed sequential state discrimination as a new quantum state discrimination scheme. In the scheme, by the successful sequential discrimination of a qubit state, receivers Bob and Charlie can share the information of the qubit prepared by a sender Alice. A merit of the scheme is that a quantum channel is established between Bob and Charlie, but a classical communication is not allowed. In this report, we present a method for extending the original sequential state discrimination of two qubit states to a scheme of N linearly independent pure quantum states. Specifically, we obtain the conditions for the sequential state discrimination of N = 3 pure quantum states. We can analytically provide conditions when there is a special symmetry among N = 3 linearly independent pure quantum states. Additionally, we show that the scenario proposed in this study can be applied to quantum key distribution. Furthermore, we show that the sequential state discrimination of three qutrit states performs better than the strategy of probabilistic quantum cloning.

Differential effect of race, education, gender, and language discrimination on glycemic control in adults with type 2 diabetes.

PubMed

Reynolds, D Brice; Walker, Rebekah J; Campbell, Jennifer A; Egede, Leonard E

2015-04-01

Discrimination has been linked to negative health outcomes, but little research has investigated different types of discrimination to determine if some have a greater impact on outcomes. We examined the differential effect of discrimination based on race, level of education, gender, and language on glycemic control in adults with type 2 diabetes. Six hundred two patients with type 2 diabetes from two adult primary care clinics in the southeastern United States completed validated questionnaires. Questions included perceived discrimination because of race/ethnicity, level of education, sex/gender, or language. A multiple linear regression model assessed the differential effect of each type of perceived discrimination on glycemic control while adjusting for relevant covariates, including race, site, gender, marital status, duration of diabetes, number of years in school, number of hours worked per week, income, and health status. The mean age was 61.5 years, and the mean duration of diabetes was 12.3 years. Of the sample, 61.6% were men, and 64.9% were non-Hispanic black. In adjusted models, education discrimination remained significantly associated with glycemic control (β=0.47; 95% confidence interval, 0.03, 0.92). Race, gender and language discrimination were not significantly associated with poor glycemic control in either unadjusted or adjusted analyses. Discrimination based on education was found to be significantly associated with poor glycemic control. The findings suggest that education discrimination may be an important social determinant to consider when providing care to patients with type 2 diabetes and should be assessed separate from other types of discrimination, such as that based on race.

A face and palmprint recognition approach based on discriminant DCT feature extraction.

PubMed

Jing, Xiao-Yuan; Zhang, David

2004-12-01

In the field of image processing and recognition, discrete cosine transform (DCT) and linear discrimination are two widely used techniques. Based on them, we present a new face and palmprint recognition approach in this paper. It first uses a two-dimensional separability judgment to select the DCT frequency bands with favorable linear separability. Then from the selected bands, it extracts the linear discriminative features by an improved Fisherface method and performs the classification by the nearest neighbor classifier. We detailedly analyze theoretical advantages of our approach in feature extraction. The experiments on face databases and palmprint database demonstrate that compared to the state-of-the-art linear discrimination methods, our approach obtains better classification performance. It can significantly improve the recognition rates for face and palmprint data and effectively reduce the dimension of feature space.

Forest Species Identification with High Spectral Resolution Data

NASA Technical Reports Server (NTRS)

Olson, C. E., Jr.; Zhu, Z.

1985-01-01

Data collected over the Sleeping Bear Sand Dunes Test Site and the Saginaw Forest Test Site (Michigan) with the JPL Airborne Imaging Spectrometer and the Collins' Airborne Spectroradiometer are being used for forest species identification. The linear discriminant function has provided higher identification accuracies than have principal components analyses. Highest identification accuracies are obtained in the 450 to 520 nm spectral region. Spectral bands near 1,300, 1,685 and 2,220 nm appear to be important, also.

Angular velocity discrimination

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.

1990-01-01

Three experiments designed to investigate the ability of naive observers to discriminate rotational velocities of two simultaneously viewed objects are described. Rotations are constrained to occur about the x and y axes, resulting in linear two-dimensional image trajectories. The results indicate that observers can discriminate angular velocities with a competence near that for linear velocities. However, perceived angular rate is influenced by structural aspects of the stimuli.

A new comprehensive index for discriminating adulteration in bovine raw milk.

PubMed

Liu, Jing; Ren, Jing; Liu, Zhen-Min; Guo, Ben-Heng

2015-04-01

This paper proposes a new comprehensive index, called Q, which can effectively discriminate artificial adulterated milk from unadulterated milk. Both normal and adulterated samples of bovine raw milk were analysed by Fourier transform infrared spectroscopic instrument to measure the traditional indices of quality, including fat (FAT), protein (PRO), lactose (LAC), total solids (TS), non-fat solid (NFS), freezing point (FP) and somatic cell counts (SCC). From these traditional indices, this paper elaborates a method to build the index Q. First, correlated analysis and principle component analysis were used to select parameter pairs TS-FAT and FP-LAC as predominant variables. Second, linear-regression analysis and residual analysis are applied to determine the index Q and its discriminating ranges. The verification and two-blind trial results suggested that index Q could accurately detect milk adulteration with maltodextrin and water (as low as 1.0% of adulteration proportions), and with other nine kinds of synthetic adulterants (as low as 0.5% of adulteration proportions). Copyright © 2014 Elsevier Ltd. All rights reserved.

Social integration of Latin-American immigrants in Spain: the influence of the community context.

PubMed

Fuente, Asur; Herrero, Juan

2012-11-01

The main goal of this study is to analyze the degree to which several community elements such as insecurity, discrimination and informal community support might have an influence on the social integration of Latin-American immigrants, a group at risk of social exclusion in Spain. Multivariate linear regression analyses results showed that informal community support is positively related to social integration whereas insecurity is negatively related. The statistical relationship between discrimination and social integration disappears once levels of informal community support are taken into account. A better understanding of the factors that either promote or inhibit the social integration progress of immigrant population is important to orientate public policies and intervention programs that contribute to the adaptation of this population to the host society.

Determination of authenticity of brand perfume using electronic nose prototypes

NASA Astrophysics Data System (ADS)

Gebicki, Jacek; Szulczynski, Bartosz; Kaminski, Marian

2015-12-01

The paper presents the practical application of an electronic nose technique for fast and efficient discrimination between authentic and fake perfume samples. Two self-built electronic nose prototypes equipped with a set of semiconductor sensors were employed for that purpose. Additionally 10 volunteers took part in the sensory analysis. The following perfumes and their fake counterparts were analysed: Dior—Fahrenheit, Eisenberg—J’ose, YSL—La nuit de L’homme, 7 Loewe and Spice Bomb. The investigations were carried out using the headspace of the aqueous solutions. Data analysis utilized multidimensional techniques: principle component analysis (PCA), linear discrimination analysis (LDA), k-nearest neighbour (k-NN). The results obtained confirmed the legitimacy of the electronic nose technique as an alternative to the sensory analysis as far as the determination of authenticity of perfume is concerned.

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.

Linear Discriminant Analysis on a Spreadsheet.

ERIC Educational Resources Information Center

Busbey, Arthur Bresnahan III

1989-01-01

Described is a software package, "Trapeze," within which a routine called LinDis can be used. Discussed are teaching methods, the linear discriminant model and equations, the LinDis worksheet, and an example. The set up for this routine is included. (CW)

Statistical classification techniques for engineering and climatic data samples

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Linear and non-linear analyses of Conner's Continuous Performance Test-II discriminate adult patients with attention deficit hyperactivity disorder from patients with mood and anxiety disorders.

PubMed

Fasmer, Ole Bernt; Mjeldheim, Kristin; Førland, Wenche; Hansen, Anita L; Syrstad, Vigdis Elin Giæver; Oedegaard, Ketil J; Berle, Jan Øystein

2016-08-11

Attention Deficit Hyperactivity Disorder (ADHD) is a heterogeneous disorder. Therefore it is important to look for factors that can contribute to better diagnosis and classification of these patients. The aims of the study were to characterize adult psychiatric out-patients with a mixture of mood, anxiety and attentional problems using an objective neuropsychological test of attention combined with an assessment of mood instability. Newly referred patients (n = 99; aged 18-65 years) requiring diagnostic evaluation of ADHD, mood or anxiety disorders were recruited, and were given a comprehensive diagnostic evaluation including the self-report form of the cyclothymic temperament scale and Conner's Continuous Performance Test II (CPT-II). In addition to the traditional measures from this test we have extracted raw data and analysed time series using linear and non-linear mathematical methods. Fifty patients fulfilled criteria for ADHD, while 49 did not, and were given other psychiatric diagnoses (clinical controls). When compared to the clinical controls the ADHD patients had more omission and commission errors, and higher reaction time variability. Analyses of response times showed higher values for skewness in the ADHD patients, and lower values for sample entropy and symbolic dynamics. Among the ADHD patients 59 % fulfilled criteria for a cyclothymic temperament, and this group had higher reaction time variability and lower scores on complexity than the group without this temperament. The CPT-II is a useful instrument in the assessment of ADHD in adult patients. Additional information from this test was obtained by analyzing response times using linear and non-linear methods, and this showed that ADHD patients with a cyclothymic temperament were different from those without this temperament.

Exploring intentions to discriminate against patients living with HIV/AIDS among future healthcare providers in Malaysia

PubMed Central

Earnshaw, Valerie A.; Jin, Harry; Wickersham, Jeffrey; Kamarulzaman, Adeeba; John, Jacob; Altice, Frederick L.

2015-01-01

OBJECTIVES Stigma towards people living with HIV/AIDS (PLWHA) is strong in Malaysia. Although stigma has been understudied, it may be a barrier to treating the approximately 81 000 Malaysian PLWHA. The current study explores correlates of intentions to discriminate against PLWHA among medical and dental students, the future healthcare providers of Malaysia. METHODS An online, cross-sectional survey of 1296 medical and dental students was conducted in 2012 at seven Malaysian universities; 1165 (89.9%) completed the survey and were analysed. Sociodemographic characteristics, stigma-related constructs and intentions to discriminate against PLWHA were measured. Linear mixed models were conducted, controlling for clustering by university. RESULTS The final multivariate model demonstrated that students who intended to discriminate more against PLWHA were female, less advanced in their training, and studying dentistry. They further endorsed more negative attitudes towards PLWHA, internalised greater HIV-related shame, reported more HIV-related fear and disagreed more strongly that PLWHA deserve good care. The final model accounted for 38% of the variance in discrimination intent, with 10% accounted for by sociodemographic characteristics and 28% accounted for by stigma-related constructs. CONCLUSIONS It is critical to reduce stigma among medical and dental students to eliminate intentions to discriminate and achieve equitable care for Malaysian PLWHA. Stigma-reduction interventions should be multipronged, addressing attitudes, internalised shame, fear and perceptions of deservingness of care. PMID:24666546

Exploring intentions to discriminate against patients living with HIV/AIDS among future healthcare providers in Malaysia.

PubMed

Earnshaw, Valerie A; Jin, Harry; Wickersham, Jeffrey; Kamarulzaman, Adeeba; John, Jacob; Altice, Frederick L

2014-06-01

Stigma towards people living with HIV/AIDS (PLWHA) is strong in Malaysia. Although stigma has been understudied, it may be a barrier to treating the approximately 81 000 Malaysian PLWHA. The current study explores correlates of intentions to discriminate against PLWHA among medical and dental students, the future healthcare providers of Malaysia. An online, cross-sectional survey of 1296 medical and dental students was conducted in 2012 at seven Malaysian universities; 1165 (89.9%) completed the survey and were analysed. Socio-demographic characteristics, stigma-related constructs and intentions to discriminate against PLWHA were measured. Linear mixed models were conducted, controlling for clustering by university. The final multivariate model demonstrated that students who intended to discriminate more against PLWHA were female, less advanced in their training, and studying dentistry. They further endorsed more negative attitudes towards PLWHA, internalised greater HIV-related shame, reported more HIV-related fear and disagreed more strongly that PLWHA deserve good care. The final model accounted for 38% of the variance in discrimination intent, with 10% accounted for by socio-demographic characteristics and 28% accounted for by stigma-related constructs. It is critical to reduce stigma among medical and dental students to eliminate intentions to discriminate and achieve equitable care for Malaysian PLWHA. Stigma-reduction interventions should be multipronged, addressing attitudes, internalised shame, fear and perceptions of deservingness of care. © 2014 John Wiley & Sons Ltd.

Implications of discrimination based on sexuality, gender, and race/ethnicity for psychological distress among working-class sexual minorities: the United for Health Study, 2003-2004.

PubMed

Chae, David H; Krieger, Nancy; Bennett, Gary G; Lindsey, Jane C; Stoddard, Anne M; Barbeau, Elizabeth M

2010-01-01

This study investigated the distribution of demographic characteristics, the prevalence of discrimination based on sexuality, gender, and race, and relationships with psychological distress among 178 working-class sexual minorities (i.e., who identified as lesbian, gay, or bisexual (LGB) or had ever engaged in same-sex sexual behaviors) recruited to the United for Health Study (2003-2004). The results indicated considerable heterogeneity in responses to items assessing sexual orientation and sexual behavior, with a majority of sexual minority participants not identifying as LGB (74.2%). The authors found significant demographic differences in LGB identification by gender, race/ethnicity, nativity, and socioeconomic factors. In addition, LGB participants had higher levels of psychological distress than non-LGB-identified sexual minorities. Linear regression analyses revealed that reports of racial/ethnic discrimination and sexuality discrimination were associated with higher levels of psychological distress among sexual minority participants. The results underscore the need to collect multiple measures of sexuality in conducting research on racially diverse working-class communities; to consider demographic factors in collecting sexuality data; and to disaggregate information on sexuality by LGB identification. Findings also highlight the importance of addressing discrimination in ameliorating problematic mental health outcomes among working-class sexual minorities.

Discrimination in the workplace, reported by people with major depressive disorder: a cross-sectional study in 35 countries

PubMed Central

Brouwers, E P M; Mathijssen, J; Van Bortel, T; Knifton, L; Wahlbeck, K; Van Audenhove, C; Kadri, N; Chang, Ch; Goud, B R; Ballester, D; Tófoli, LF; Bello, R; Jorge-Monteiro, M F; Zäske, H; Milaćić, I; Uçok, A; Bonetto, C; Lasalvia, A; Thornicroft, G; Van Weeghel, J

2016-01-01

Objective Whereas employment has been shown to be beneficial for people with Major Depressive Disorder (MDD) across different cultures, employers’ attitudes have been shown to be negative towards workers with MDD. This may form an important barrier to work participation. Today, little is known about how stigma and discrimination affect work participation of workers with MDD, especially from their own perspective. We aimed to assess, in a working age population including respondents with MDD from 35 countries: (1) if people with MDD anticipate and experience discrimination when trying to find or keep paid employment; (2) if participants in high, middle and lower developed countries differ in these respects; and (3) if discrimination experiences are related to actual employment status (ie, having a paid job or not). Method Participants in this cross-sectional study (N=834) had a diagnosis of MDD in the previous 12 months. They were interviewed using the Discrimination and Stigma Scale (DISC-12). Analysis of variance and generalised linear mixed models were used to analyse the data. Results Overall, 62.5% had anticipated and/or experienced discrimination in the work setting. In very high developed countries, almost 60% of respondents had stopped themselves from applying for work, education or training because of anticipated discrimination. Having experienced workplace discrimination was independently related to unemployment. Conclusions Across different countries and cultures, people with MDD very frequently reported discrimination in the work setting. Effective interventions are needed to enhance work participation in people with MDD, focusing simultaneously on decreasing stigma in the work environment and on decreasing self-discrimination by empowering workers with MDD. PMID:26908523

Discrimination in the workplace, reported by people with major depressive disorder: a cross-sectional study in 35 countries.

PubMed

Brouwers, E P M; Mathijssen, J; Van Bortel, T; Knifton, L; Wahlbeck, K; Van Audenhove, C; Kadri, N; Chang, Ch; Goud, B R; Ballester, D; Tófoli, L F; Bello, R; Jorge-Monteiro, M F; Zäske, H; Milaćić, I; Uçok, A; Bonetto, C; Lasalvia, A; Thornicroft, G; Van Weeghel, J

2016-02-23

Whereas employment has been shown to be beneficial for people with Major Depressive Disorder (MDD) across different cultures, employers' attitudes have been shown to be negative towards workers with MDD. This may form an important barrier to work participation. Today, little is known about how stigma and discrimination affect work participation of workers with MDD, especially from their own perspective. We aimed to assess, in a working age population including respondents with MDD from 35 countries: (1) if people with MDD anticipate and experience discrimination when trying to find or keep paid employment; (2) if participants in high, middle and lower developed countries differ in these respects; and (3) if discrimination experiences are related to actual employment status (ie, having a paid job or not). Participants in this cross-sectional study (N=834) had a diagnosis of MDD in the previous 12 months. They were interviewed using the Discrimination and Stigma Scale (DISC-12). Analysis of variance and generalised linear mixed models were used to analyse the data. Overall, 62.5% had anticipated and/or experienced discrimination in the work setting. In very high developed countries, almost 60% of respondents had stopped themselves from applying for work, education or training because of anticipated discrimination. Having experienced workplace discrimination was independently related to unemployment. Across different countries and cultures, people with MDD very frequently reported discrimination in the work setting. Effective interventions are needed to enhance work participation in people with MDD, focusing simultaneously on decreasing stigma in the work environment and on decreasing self-discrimination by empowering workers with MDD. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Chronic discrimination and bodily pain in a multiethnic cohort of midlife women in the Study of Women's Health Across the Nation.

PubMed

Dugan, Sheila A; Lewis, Tené T; Everson-Rose, Susan A; Jacobs, Elizabeth A; Harlow, Siobán D; Janssen, Imke

2017-09-01

A growing literature links discrimination to key markers of biobehavioral health. While racial or ethnic differences in pain are seen in experimental and clinical studies, the authors were interested in how chronic discrimination contributes to pain within multiple racial or ethnic groups over time. Participants were 3056 African American, Caucasian, Chinese, Hispanic, and Japanese women from the Study of Women's Health Across the Nation. The Everyday Discrimination Scale was assessed from baseline through 13 follow-up examinations. The bodily pain subscale of the MOS 36-Item Short-Form Health Survey (SF-36) was assessed annually. There were large racial or ethnic differences in reports of discrimination and pain. Discrimination attributions also varied by race or ethnicity. In linear mixed model analyses, initially adjusted for age, education, and pain medications, chronic everyday discrimination was associated with more bodily pain in all ethnic groups (beta = -5.84; P < 0.002 for Japanese; beta = -6.17; P < 0.001 for African American; beta = -8.74; P < 0.001 for Chinese; beta = -10.54; P < 0.001 for Caucasians; beta = -12.82; P < 0.001 for Hispanic). Associations remained significant in all ethnic groups after adjusting for additional covariates in subsequent models until adding depressive symptoms as covariate; in the final fully-adjusted models, discrimination remained a significant predictor of pain for African American (beta = -4.50; P < 0.001), Chinese (beta = -6.62; P < 0.001), and Caucasian (beta = -7.86; P < 0.001) women. In this longitudinal study, experiences of everyday discrimination were strongly linked to reports of bodily pain for the majority of women. Further research is needed to determine if addressing psychosocial stressors, such as discrimination, with patients can enhance clinical management of pain symptoms.

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.

An automatic flow system for NIR screening analysis of liquefied petroleum gas with respect to propane content.

PubMed

Dantas, Hebertty V; Barbosa, Mayara F; Nascimento, Elaine C L; Moreira, Pablo N T; Galvão, Roberto K H; Araújo, Mário C U

2013-03-15

This paper proposes a NIR spectrometric method for screening analysis of liquefied petroleum gas (LPG) samples. The proposed method is aimed at discriminating samples with low and high propane content, which can be useful for the adjustment of burn settings in industrial applications. A gas flow system was developed to introduce the LPG sample into a NIR flow cell at constant pressure. In addition, a gas chromatographer was employed to determine the propane content of the sample for reference purposes. The results of a principal component analysis, as well as a classification study using SIMCA (soft independent modeling of class analogies), revealed that the samples can be successfully discriminated with respect to propane content by using the NIR spectrum in the range 8100-8800 cm(-1). In addition, by using SPA-LDA (linear discriminant analysis with variables selected by the successive projections algorithm), it was found that perfect discrimination can also be achieved by using only two wavenumbers (8215 and 8324 cm(-1)). This finding may be of value for the design of a dedicated, low-cost instrument for routine analyses. Copyright © 2012 Elsevier B.V. All rights reserved.

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

PubMed

Macaluso, P J

2011-02-01

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

Scintillation decay time and pulse shape discrimination in oxygenated and deoxygenated solutions of linear alkylbenzene for the SNO+ experiment

NASA Astrophysics Data System (ADS)

O'Keeffe, H. M.; O'Sullivan, E.; Chen, M. C.

2011-06-01

The SNO+ liquid scintillator experiment is under construction in the SNOLAB facility in Canada. The success of this experiment relies upon accurate characterization of the liquid scintillator, linear alkylbenzene (LAB). In this paper, scintillation decay times for alpha and electron excitations in LAB with 2 g/L PPO are presented for both oxygenated and deoxygenated solutions. While deoxygenation is expected to improve pulse shape discrimination in liquid scintillators, it is not commonly demonstrated in the literature. This paper shows that for linear alkylbenzene, deoxygenation improves discrimination between electron and alpha excitations in the scintillator.

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.

Differences in postural tremor dynamics with age and neurological disease.

PubMed

Morrison, Steven; Newell, Karl M; Kavanagh, Justin J

2017-06-01

The overlap of dominant tremor frequencies and similarly amplified tremor observed for Parkinson's disease (PD) and essential tremor (ET) means differentiating between these pathologies is often difficult. As tremor exhibits non-linear properties, employing both linear and non-linear analyses may help distinguish between the tremor dynamics of aging, PD and ET. This study was designed to examine postural tremor in healthy older adults, PD and ET using standard linear and non-linear metrics. Hand and finger postural tremor was recorded in 15 healthy older adults (64 ± 6 years), 15 older individuals with PD (63 ± 6 years), and 10 persons with ET (68 ± 7 years). Linear measures of amplitude, frequency, and between-limb coupling (coherence) were performed. Non-linear measures of regularity (ApEn) and coupling (Cross-ApEn) were also used. Additionally, receiver operating characteristic analyses were performed for those measures that were significantly different between all groups. The results revealed that the linear measures only showed significant differences between the healthy adults and ET/PD persons, but no differences between the two neurological groups. Coherence showed higher bilateral coupling for ET but no differences in inter-limb coupling between PD and healthy subjects. However, ApEn values for finger tremor revealed significant differences between all groups, with tremor for ET persons being more regular (lower ApEn) overall. Similarly, Cross-ApEn results also showed differences between all groups, with ET persons showing strongest inter-limb coupling followed by PD and elderly. Overall, our findings point to the diagnostic potential for non-linear measures of coupling and tremor structure as biomarkers for discriminating between ET, PD and healthy persons.

Discrimination and Telomere Length Among Older Adults in the United States.

PubMed

Liu, Sze Yan; Kawachi, Ichiro

Chronic stress from experiencing discrimination can lead to long-term changes in psychological and physiologic responses, including shorter leukocyte telomere length. We examined the association between leukocyte telomere length and variations in the association by race or type of discrimination. Our study consisted of 3868 US-born non-Hispanic black (hereinafter, black) and non-Hispanic white (hereinafter, white) adult participants from the 2008 Health and Retirement Study biomarker sample with complete sociodemographic and discrimination information. We examined major lifetime unfair treatment and everyday discrimination. Coarsened exact matching matched exposed and unexposed participants on several sociodemographic factors. Coarsened exact matching creates analytic weights for the matched data sets. We applied weighted linear regression to the matched data sets. We conducted 2 subanalyses in which we matched on potential mediators-physical activity, smoking status, and obesity-and examined if racism was associated with shorter telomere length compared with other attributes. All analyses were stratified by race. We found no difference in telomere length for black and white participants reporting major lifetime unfair treatment (β = 0.09; 95% CI, -0.33 to 0.15) or everyday discrimination (β = 0.04; 95% CI, -0.12 to 0.40). Everyday discrimination was associated with shorter leukocyte telomere length among black people (β = -0.23; 95% CI, -0.44 to -0.01) but not among white people (β = 0.05; 95% CI, -0.01 to 0.10). Matching on potential mediators generally decreased the effect estimate among black people. Experiencing everyday discrimination was associated with shortened telomere length among older black adults. Further research is needed to understand the adverse physiologic effects of discrimination to create effective interventions.

Discrimination and Telomere Length Among Older Adults in the United States

PubMed Central

Kawachi, Ichiro

2017-01-01

Objectives: Chronic stress from experiencing discrimination can lead to long-term changes in psychological and physiologic responses, including shorter leukocyte telomere length. We examined the association between leukocyte telomere length and variations in the association by race or type of discrimination. Methods: Our study consisted of 3868 US-born non-Hispanic black (hereinafter, black) and non-Hispanic white (hereinafter, white) adult participants from the 2008 Health and Retirement Study biomarker sample with complete sociodemographic and discrimination information. We examined major lifetime unfair treatment and everyday discrimination. Coarsened exact matching matched exposed and unexposed participants on several sociodemographic factors. Coarsened exact matching creates analytic weights for the matched data sets. We applied weighted linear regression to the matched data sets. We conducted 2 subanalyses in which we matched on potential mediators—physical activity, smoking status, and obesity—and examined if racism was associated with shorter telomere length compared with other attributes. All analyses were stratified by race. Results: We found no difference in telomere length for black and white participants reporting major lifetime unfair treatment (β = 0.09; 95% CI, –0.33 to 0.15) or everyday discrimination (β = 0.04; 95% CI, –0.12 to 0.40). Everyday discrimination was associated with shorter leukocyte telomere length among black people (β = –0.23; 95% CI, –0.44 to –0.01) but not among white people (β = 0.05; 95% CI, –0.01 to 0.10). Matching on potential mediators generally decreased the effect estimate among black people. Conclusions: Experiencing everyday discrimination was associated with shortened telomere length among older black adults. Further research is needed to understand the adverse physiologic effects of discrimination to create effective interventions. PMID:28147207

The mean-square error optimal linear discriminant function and its application to incomplete data vectors

NASA Technical Reports Server (NTRS)

Walker, H. F.

1979-01-01

In many pattern recognition problems, data vectors are classified although one or more of the data vector elements are missing. This problem occurs in remote sensing when the ground is obscured by clouds. Optimal linear discrimination procedures for classifying imcomplete data vectors are discussed.

Study on discrimination of oral cancer from normal using blood plasma based on fluorescence steady and excited state at excitation wavelength 280 nm

NASA Astrophysics Data System (ADS)

Rekha, Pachaiappan; Aruna, Prakasa Rao; Ganesan, Singaravelu

2016-03-01

Many research works based on fluorescence spectroscopy have proven its potential in the diagnosis of various diseases using the spectral signatures of the native key fluorophores such as tryptophan, tyrosine, collagen, NADH, FAD and porphyrin. These fluorophores distribution, concentration and their conformation may be changed depending upon the pathological and metabolic conditions of cells and tissues. In this study, we have made an attempt to characterize the blood plasma of normal subject and oral cancer patients by native fluorescence spectroscopy at 280 nm excitation. Further, the fluorescence data were analyzed by employing the multivariate statistical method - linear discriminant analyses (LDA) using leaves one out cross validation method. The results illustrate the potential of fluorescence spectroscopy technique in the diagnosis of oral cancer using blood plasma.

Third-Degree Price Discrimination Revisited

ERIC Educational Resources Information Center

Kwon, Youngsun

2006-01-01

The author derives the probability that price discrimination improves social welfare, using a simple model of third-degree price discrimination assuming two independent linear demands. The probability that price discrimination raises social welfare increases as the preferences or incomes of consumer groups become more heterogeneous. He derives the…

Feasibility of use of fatty acid and triacylglycerol profiles for the authentication of commercial labelling in Iberian dry-cured sausages.

PubMed

Horcada, Alberto; Fernández-Cabanás, Víctor M; Polvillo, Oliva; Botella, Baltasar; Cubiles, M Dolores; Pino, Rafael; Narváez-Rivas, Mónica; León-Camacho, Manuel; Acuña, Rafael Rodríguez

2013-12-15

In the present study, fatty acid and triacylglycerol profiles were used to evaluate the possibility of authenticating Iberian dry-cured sausages according to their label specifications. 42 Commercial brand 'chorizo' and 39 commercial brand 'salchichón' sausages from Iberian pigs were purchased. 36 Samples were labelled Bellota and 45 bore the generic Ibérico label. In the market, Bellota is considered to be a better class than the generic Ibérico since products with the Bellota label are manufactured with high quality fat obtained from extensively reared pigs fed on acorns and pasture. Analyses of fatty acids and triacylglycerols were carried out by gas chromatography and a flame ion detector. A CP-SIL 88 column (highly substituted cyanopropyl phase; 50 m × 0.25 mm i.d., 0.2 µm film thickness) (Varian, Palo Alto, USA) was used for fatty acid analysis and a fused silica capillary DB-17HT column (50% phenyl-50% methylpolysiloxane; 30 m × 0.25 mm i.d., 0.15 µm film thickness) was used for triacylglycerols. Twelve fatty acids and 16 triacylglycerols were identified. Various discriminant models (linear quadratic discriminant analyses, logistic regression and support vector machines) were trained to predict the sample class (Bellota or Ibérico). These models included fatty acids and triacylglycerols separately and combined fatty acid and triacylglycerol profiles. The number of correctly classified samples according to discriminant analyses can be considered low (lower than 65%). The greatest discriminant rate was obtained when triacylglycerol profiles were included in the model, whilst using a combination of fatty acid and triacylglycerol profiles did not improve the rate of correct assignation. The values that represent the reliability of prediction of the samples according to the label specification were higher for the Ibérico class than for the Bellota class. In fact, quadratic and Support Vector Machine discriminate analyses were not able to assign the Bellota class (0%) when combined fatty acids and triacylglycerols were included in the model. The use of fatty acid and triacylglycerol profiles to discriminate Iberian dry-cured sausages in the market according to their labelling information is unclear. In order to ensure the genuineness of Iberian dry-cured sausages in the market, identification of fatty acid and triacylglycerol profiles should be combined with the application of quality standard traceability techniques. © 2013 Published by Elsevier B.V.

Two-dimensional statistical linear discriminant analysis for real-time robust vehicle-type recognition

NASA Astrophysics Data System (ADS)

Zafar, I.; Edirisinghe, E. A.; Acar, S.; Bez, H. E.

2007-02-01

Automatic vehicle Make and Model Recognition (MMR) systems provide useful performance enhancements to vehicle recognitions systems that are solely based on Automatic License Plate Recognition (ALPR) systems. Several car MMR systems have been proposed in literature. However these approaches are based on feature detection algorithms that can perform sub-optimally under adverse lighting and/or occlusion conditions. In this paper we propose a real time, appearance based, car MMR approach using Two Dimensional Linear Discriminant Analysis that is capable of addressing this limitation. We provide experimental results to analyse the proposed algorithm's robustness under varying illumination and occlusions conditions. We have shown that the best performance with the proposed 2D-LDA based car MMR approach is obtained when the eigenvectors of lower significance are ignored. For the given database of 200 car images of 25 different make-model classifications, a best accuracy of 91% was obtained with the 2D-LDA approach. We use a direct Principle Component Analysis (PCA) based approach as a benchmark to compare and contrast the performance of the proposed 2D-LDA approach to car MMR. We conclude that in general the 2D-LDA based algorithm supersedes the performance of the PCA based approach.

Comparing success levels of different neural network structures in extracting discriminative information from the response patterns of a temperature-modulated resistive gas sensor

NASA Astrophysics Data System (ADS)

Hosseini-Golgoo, S. M.; Bozorgi, H.; Saberkari, A.

2015-06-01

Performances of three neural networks, consisting of a multi-layer perceptron, a radial basis function, and a neuro-fuzzy network with local linear model tree training algorithm, in modeling and extracting discriminative features from the response patterns of a temperature-modulated resistive gas sensor are quantitatively compared. For response pattern recording, a voltage staircase containing five steps each with a 20 s plateau is applied to the micro-heater of the sensor, when 12 different target gases, each at 11 concentration levels, are present. In each test, the hidden layer neuron weights are taken as the discriminatory feature vector of the target gas. These vectors are then mapped to a 3D feature space using linear discriminant analysis. The discriminative information content of the feature vectors are determined by the calculation of the Fisher’s discriminant ratio, affording quantitative comparison among the success rates achieved by the different neural network structures. The results demonstrate a superior discrimination ratio for features extracted from local linear neuro-fuzzy and radial-basis-function networks with recognition rates of 96.27% and 90.74%, respectively.

Structured Kernel Dictionary Learning with Correlation Constraint for Object Recognition.

PubMed

Wang, Zhengjue; Wang, Yinghua; Liu, Hongwei; Zhang, Hao

2017-06-21

In this paper, we propose a new discriminative non-linear dictionary learning approach, called correlation constrained structured kernel KSVD, for object recognition. The objective function for dictionary learning contains a reconstructive term and a discriminative term. In the reconstructive term, signals are implicitly non-linearly mapped into a space, where a structured kernel dictionary, each sub-dictionary of which lies in the span of the mapped signals from the corresponding class, is established. In the discriminative term, by analyzing the classification mechanism, the correlation constraint is proposed in kernel form, constraining the correlations between different discriminative codes, and restricting the coefficient vectors to be transformed into a feature space, where the features are highly correlated inner-class and nearly independent between-classes. The objective function is optimized by the proposed structured kernel KSVD. During the classification stage, the specific form of the discriminative feature is needless to be known, while the inner product of the discriminative feature with kernel matrix embedded is available, and is suitable for a linear SVM classifier. Experimental results demonstrate that the proposed approach outperforms many state-of-the-art dictionary learning approaches for face, scene and synthetic aperture radar (SAR) vehicle target recognition.

Beam tracking phase tomography with laboratory sources

NASA Astrophysics Data System (ADS)

Vittoria, F. A.; Endrizzi, M.; Kallon, G. K. N.; Hagen, C. K.; Diemoz, P. C.; Zamir, A.; Olivo, A.

2018-04-01

An X-ray phase-contrast laboratory system is presented, based on the beam-tracking method. Beam-tracking relies on creating micro-beamlets of radiation by placing a structured mask before the sample, and analysing them by using a detector with sufficient resolution. The system is used in tomographic configuration to measure the three dimensional distribution of the linear attenuation coefficient, difference from unity of the real part of the refractive index, and of the local scattering power of specimens. The complementarity of the three signals is investigated, together with their potential use for material discrimination.

Identification of wheat varieties with a parallel-plate capacitance sensor using fisher linear discriminant analysis

USDA-ARS?s Scientific Manuscript database

Fisher’s linear discriminant (FLD) models for wheat variety classification were developed and validated. The inputs to the FLD models were the capacitance (C), impedance (Z), and phase angle ('), measured at two frequencies. Classification of wheat varieties was obtained as output of the FLD mod...

Robust linear discriminant analysis with distance based estimators

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

Improved pulse shape discriminator for fast neutron-gamma ray detection system

NASA Technical Reports Server (NTRS)

Lockwood, J. A.; St. Onge, R.

1969-01-01

Discriminator in nuclear particle detection system distinguishes nuclear particle type and energy among many different nuclear particles. Discriminator incorporates passive, linear circuit elements so that it will operate over a wide dynamic range.

Abdominal girth and vertebral column length can adjust spinal anesthesia for lower limb surgery, a prospective, observational study.

PubMed

Zhou, Qing-he; Zhu, Bo; Wei, Chang-na; Yan, Min

2016-03-24

Studies have shown that abdominal girth and vertebral column length have high predictive value for spinal spread after administering a dose of plain bupivacaine. we designed a study to identify the specific correlations between abdominal girth, vertebral column length and a 0.5% dosage of plain bupivacaine, which should provide a minimum upper block level (T12) and a suitable upper block level (T10) for lower limb surgeries. A suitable dose of 0.5% plain bupivacaine was administered intrathecally between the L3 and L4 vertebrae for lower limb surgeries. If the upper cephalad spread of the patient by loss of pinprick discrimination was T12 or T10, the patient was enrolled in this study. Five patient variables and intrathecal plain bupivacaine dose were recorded. Linear regression and multiple regression analyses were performed. Totals of 111 patients and 121 patients who lost pinprick discrimination at T12 and T10, respectively, were analyzed in this study. Linear regression analysis showed that only abdominal girth and plain bupivacaine dose were strongly correlated (r =-0.827 for T12, r = -0.806 for T10; both p < 0.0001). Multiple linear regression analysis showed that both abdominal girth and vertebral column length were the key determinants of plain bupivacaine dose (both p < 0.0001). R(2) was 0.874 and 0.860 for the loss of pinprick discrimination at T12 and T10, respectively. Our data indicated that vertebral column length and abdominal girth were strongly correlated with the dosage of intrathecal plain bupivacaine for the loss of pinprick discrimination at T12 and T10. The two regression equations were YT12 = 3.547 + 0.045X1-0.044X2 and YT10 = 3.848 + 0.047X1- 0.046X2 (Y, 0.5% plain bupivacaine volume; X1, vertebral column length;and X 2, abdominal girth), which can accurately predict the minimum and suitable intrathecal bupivacaine dose for lower limb surgery to a great extent, separately.

Discrimination of nuclear explosions and earthquakes from teleseismic distances with a local network of short period seismic stations using artificial neural networks

NASA Astrophysics Data System (ADS)

Tiira, Timo

1996-10-01

Seismic discrimination capability of artificial neural networks (ANNs) was studied using earthquakes and nuclear explosions from teleseismic distances. The events were selected from two areas, which were analyzed separately. First, 23 nuclear explosions from Semipalatinsk and Lop Nor test sites were compared with 46 earthquakes from adjacent areas. Second, 39 explosions from Nevada test site were compared with 27 earthquakes from close-by areas. The basic discriminants were complexity, spectral ratio and third moment of frequency. The spectral discriminants were computed in five different ways to obtain all the information embedded in the signals, some of which were relatively weak. The discriminants were computed using data from six short period stations in Central and southern Finland. The spectral contents of the signals of both classes varied considerably between the stations. The 66 discriminants were formed into 65 optimum subsets of different sizes by using stepwise linear regression. A type of ANN called multilayer perceptron (MLP) was applied to each of the subsets. As a comparison the classification was repeated using linear discrimination analysis (LDA). Since the number of events was small the testing was made with the leave-one-out method. The ANN gave significantly better results than LDA. As a final tool for discrimination a combination of the ten neural nets with the best performance were used. All events from Central Asia were clearly discriminated and over 90% of the events from Nevada region were confidently discriminated. The better performance of ANNs was attributed to its ability to form complex decision regions between the groups and to its highly non-linear nature.

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.

Getting mad but ending up sad: the mental health consequences for African Americans using anger to cope with racism.

PubMed

Pittman, Chavella T

2011-01-01

Anger is a common reaction to stressful life events. However, little is known about anger’s use and efficacy as a coping strategy for racism. Is anger a coping strategy for racism that improves mental health? Or does anger operate in an opposing way, deteriorating mental health? The analyses for this research focused on a probability sample of African Americans who reported experiences of acute (n = 246) or chronic (n = 120) racial discrimination in a survey interview. General linear model results revealed that using anger to cope with racial discrimination negatively affected the general well-being and psychological distress of African Americans. These findings raise concerns about the effectiveness (or lack therefore of) of anger as a common coping mechanism for racism, given the deleterious effects it may have on African Americans’ mental health.

Evaluating the Discriminant Accuracy of a Grammatical Measure With Spanish-Speaking Children

PubMed Central

Gutiérrez-Clellen, Vera F.; Restrepo, M. Adelaida; Simón-Cereijido, Gabriela

2012-01-01

Purpose The purpose of this study was to evaluate the discriminant accuracy of a grammatical measure for the identification of language impairment in Latino Spanish-speaking children. The authors hypothesized that if exposure to and use of English as a second language have an effect on the first language, bilingual children might exhibit lower rates of grammatical accuracy than their peers and be more likely to be misclassified. Method Eighty children with typical language development and 80 with language impairment were sampled from 4 different geographical regions and compared using linear discriminant function analysis. Results Results indicated fair-to-good sensitivity from 4;0 to 5;1 years, good sensitivity from 5;2 to 5;11 years, and poor sensitivity above age 6 years. The discriminant functions derived from the exploratory studies were able to predict group membership in confirmatory analyses with fair-to-excellent sensitivity up to age 6 years. Children who were bilingual did not show lower scores and were not more likely to be misclassified compared with their Spanish-only peers. Conclusions The measure seems to be appropriate for identifying language impairment in either Spanish-dominant or Spanish-only speakers between 4 and 6 years of age. However, for older children, supplemental testing is necessary. PMID:17197491

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

Discrimination of magnoliae officinalis cortex based on the quantitative profiles of magnolosides by two-channel liquid chromatography with electrochemical detection.

PubMed

Xue, Zhenzhen; Kotani, Akira; Yang, Bin; Hakamata, Hideki

2018-05-31

A two-channel liquid chromatography with electrochemical detection system (2LC-ECD) was newly designed for the simultaneous determination of magnolosides A, B, F, H, and L in the first channel and other magnolosides D and M in the second channel, respectively. Peak heights had linear relationships to the magnoloside concentrations in a range of 0.02-16 μmol/L for H, 0.01-12 μmol/L for A, 0.02-12 μmol/L for F and L, 0.01-8 μmol/L for B, 0.002-6 μmol/L for D, and 0.002-4 μmol/L for M, respectively. Seven magnolosides in magnoliae officinalis cortex (MOC) were determined by the 2LC-ECD, and the obtained quantitative profiles of magnolosides were applied to the discrimination between the MOC samples harvested from Hubei and Sichuan (called Chuan po) and from Zhejiang and Fujian (called Wen po). By principal component analysis (PCA) and supervised partial least squares discriminant analysis (PLS-DA) based on the quantitative profiles of the magnolosides, Chuan po were clearly discriminated from Wen po on the plots obtained from our multivariable analyses. Copyright © 2018 Elsevier B.V. All rights reserved.

Taking it like a man: masculine role norms as moderators of the racial discrimination-depressive symptoms association among African American men.

PubMed

Hammond, Wizdom Powell

2012-05-01

I examined the association between everyday racial discrimination and depressive symptoms and explored the moderating role of 2 dimensions of masculine role norms, restrictive emotionality and self-reliance. Cross-sectional survey data from 674 African American men aged 18 years and older recruited primarily from barbershops in 4 US regions (2003-2010) were used. Direct and moderated associations were assessed with multivariate linear regression analyses for the overall sample and different age groups. Models were adjusted for recruitment site, sociodemographics, masculine role norms salience, and general social stress. Everyday racial discrimination was associated with more depressive symptoms across all age groups. Higher restrictive emotionality was associated with more depressive symptoms among men aged 18 to 29 and 30 to 39 years. Self-reliance was associated with fewer depressive symptoms among men aged 18 to 29 years and 40 years and older. The positive association between everyday racial discrimination and depressive symptoms was stronger among men with high restrictive emotionality, but this moderated effect was limited to men older than 30 years. Interventions designed to reduce African American men's depression instigated by racism should be life-course specific and address masculine role norms that encourage emotion restriction.

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study

PubMed Central

Taylor, Jacquelyn Y.; Sun, Yan V.; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R.; Musani, Solomon K.; Sims, Mario; Jackson, James S.

2017-01-01

Abstract Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination. The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status. Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015). This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population. PMID:29069027

The combined effects of genetic risk and perceived discrimination on blood pressure among African Americans in the Jackson Heart Study.

PubMed

Taylor, Jacquelyn Y; Sun, Yan V; Barcelona de Mendoza, Veronica; Ifatunji, Mosi; Rafferty, Jane; Fox, Ervin R; Musani, Solomon K; Sims, Mario; Jackson, James S

2017-10-01

Both genomics and environmental stressors play a significant role in increases in blood pressure (BP). In an attempt to further explain the hypertension (HTN) disparity among African Americans (AA), both genetic underpinnings (selected candidate genes) and stress due to perceived racial discrimination (as reported in the literature) have independently been linked to increased BP among AAs. Although Gene x Environment interactions on BP have been examined, the environmental component of these investigations has focused more on lifestyle behaviors such as smoking, diet, and physical activity, and less on psychosocial stressors such as perceived discrimination.The present study uses candidate gene analyses to identify the relationship between Everyday Discrimination (ED) and Major Life Discrimination (MLD) with increases in systolic BP (SBP) and diastolic BP (DBP) among AA in the Jackson Heart Study. Multiple linear regression models reveal no association between discrimination and BP after adjusting for age, sex, body mass index (BMI), antihypertensive medication use, and current smoking status.Subsequent candidate gene analysis identified 5 SNPs (rs7602215, rs3771724, rs1006502, rs1791926, and rs2258119) that interacted with perceived discrimination and SBP, and 3 SNPs (rs2034454, rs7602215, and rs3771724) that interacted with perceived discrimination and DBP. Most notably, there was a significant SNP × discrimination interaction for 2 SNPs on the SLC4A5 gene: rs3771724 (MLD: SBP P = .034, DBP P = .031; ED: DBP: P = .016) and rs1006502 (MLD: SBP P = .034, DBP P = .030; ED: DBP P = .015).This study supports the idea that SNP × discrimination interactions combine to influence clinically relevant traits such as BP. Replication with similar epidemiological samples is required to ascertain the role of genes and psychosocial stressors in the development and expression of high BP in this understudied population.

Classification of commercial wines from the Canary Islands (Spain) by chemometric techniques using metallic contents.

PubMed

Frías, Sergio; Conde, José E; Rodríguez-Bencomo, Juan J; García-Montelongo, Francisco; Pérez-Trujillo, Juan P

2003-02-06

Eleven elements, K, Na, Ca, Mg, Fe, Cu, Zn, Mn, Sr, Li and Rb, were determined in dry and sweet wines bearing the denominations of origin of El Hierro, La Palma and Lanzarote islands (Canary Islands, Spain). Analyses were performed by flame atomic absorption spectrophotometry, with the exceptions of lithium and rubidium for which flame atomic emission spectrophotometry was used. Sweet wines from La Palma were elaborated as naturally sweet with over-ripe grapes and significant differences were found in all the analysed elements with the exceptions of sodium, iron and rubidium with regard to dry wines from the same island. Contrarily, sweet wines from Lanzarote elaborated with grapes in a similar ripening state to dry wines did not present significant differences between them with the exception of strontium, the content of which was greater in dry wines. Among the three islands, significant differences in mean content were found with the exceptions of iron and copper. Cluster analysis and principal component analysis show differences in wines according to the island of origin and the ripening state of the grapes. Linear discriminant analysis using rubidium, sodium, manganese and strontium, the four most discriminant elements, gave 100% recognition ability and 95.6% prediction ability. The sensitivity and specificity obtained using soft independent modelling of class analogy (SIMCA) as a modelling multivariate technique were both 100% for El Hierro and Lanzarote, and 100 and 95%, respectively, for La Palma. The modelling and discriminant capacities of the different metals were also studied.

Joint Entropy for Space and Spatial Frequency Domains Estimated from Psychometric Functions of Achromatic Discrimination

PubMed Central

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised. PMID:24466158

Joint entropy for space and spatial frequency domains estimated from psychometric functions of achromatic discrimination.

PubMed

Silveira, Vladímir de Aquino; Souza, Givago da Silva; Gomes, Bruno Duarte; Rodrigues, Anderson Raiol; Silveira, Luiz Carlos de Lima

2014-01-01

We used psychometric functions to estimate the joint entropy for space discrimination and spatial frequency discrimination. Space discrimination was taken as discrimination of spatial extent. Seven subjects were tested. Gábor functions comprising unidimensionalsinusoidal gratings (0.4, 2, and 10 cpd) and bidimensionalGaussian envelopes (1°) were used as reference stimuli. The experiment comprised the comparison between reference and test stimulithat differed in grating's spatial frequency or envelope's standard deviation. We tested 21 different envelope's standard deviations around the reference standard deviation to study spatial extent discrimination and 19 different grating's spatial frequencies around the reference spatial frequency to study spatial frequency discrimination. Two series of psychometric functions were obtained for 2%, 5%, 10%, and 100% stimulus contrast. The psychometric function data points for spatial extent discrimination or spatial frequency discrimination were fitted with Gaussian functions using the least square method, and the spatial extent and spatial frequency entropies were estimated from the standard deviation of these Gaussian functions. Then, joint entropy was obtained by multiplying the square root of space extent entropy times the spatial frequency entropy. We compared our results to the theoretical minimum for unidimensional Gábor functions, 1/4π or 0.0796. At low and intermediate spatial frequencies and high contrasts, joint entropy reached levels below the theoretical minimum, suggesting non-linear interactions between two or more visual mechanisms. We concluded that non-linear interactions of visual pathways, such as the M and P pathways, could explain joint entropy values below the theoretical minimum at low and intermediate spatial frequencies and high contrasts. These non-linear interactions might be at work at intermediate and high contrasts at all spatial frequencies once there was a substantial decrease in joint entropy for these stimulus conditions when contrast was raised.

Robust L1-norm two-dimensional linear discriminant analysis.

PubMed

Li, Chun-Na; Shao, Yuan-Hai; Deng, Nai-Yang

2015-05-01

In this paper, we propose an L1-norm two-dimensional linear discriminant analysis (L1-2DLDA) with robust performance. Different from the conventional two-dimensional linear discriminant analysis with L2-norm (L2-2DLDA), where the optimization problem is transferred to a generalized eigenvalue problem, the optimization problem in our L1-2DLDA is solved by a simple justifiable iterative technique, and its convergence is guaranteed. Compared with L2-2DLDA, our L1-2DLDA is more robust to outliers and noises since the L1-norm is used. This is supported by our preliminary experiments on toy example and face datasets, which show the improvement of our L1-2DLDA over L2-2DLDA. Copyright © 2015 Elsevier Ltd. All rights reserved.

A chemiluminescence sensor array for discriminating natural sugars and artificial sweeteners.

PubMed

Niu, Weifen; Kong, Hao; Wang, He; Zhang, Yantu; Zhang, Sichun; Zhang, Xinrong

2012-01-01

In this paper, we report a chemiluminescence (CL) sensor array based on catalytic nanomaterials for the discrimination of ten sweeteners, including five natural sugars and five artificial sweeteners. The CL response patterns ("fingerprints") can be obtained for a given compound on the nanomaterial array and then identified through linear discriminant analysis (LDA). Moreover, each pure sweetener was quantified based on the emission intensities of selected sensor elements. The linear ranges for these sweeteners lie within 0.05-100 mM, but vary with the type of sweetener. The applicability of this array to real-life samples was demonstrated by applying it to various beverages, and the results showed that the sensor array possesses excellent discrimination power and reversibility.

Relative sensitivity of depth discrimination for ankle inversion and plantar flexion movements.

PubMed

Black, Georgia; Waddington, Gordon; Adams, Roger

2014-02-01

25 participants (20 women, 5 men) were tested for sensitivity in discrimination between sets of six movements centered on 8 degrees, 11 degrees, and 14 degrees, and separated by 0.3 degrees. Both inversion and plantar flexion movements were tested. Discrimination of the extent of inversion movement was observed to decline linearly with increasing depth; however, for plantar flexion, the discrimination function for movement extent was found to be non-linear. The relatively better discrimination of plantar flexion movements than inversion movements at around 11 degrees from horizontal is interpreted as an effect arising from differential amounts of practice through use, because this position is associated with the plantar flexion movement made in normal walking. The fact that plantar flexion movements are discriminated better than inversion at one region but not others argues against accounts of superior proprioceptive sensitivity for plantar flexion compared to inversion that are based on general properties of plantar flexion such as the number of muscle fibres on stretch.

Hormonally active agents in the environment and children's behavior: assessing effects on children's gender-dimorphic outcomes.

PubMed

Sandberg, David E; Vena, John E; Weiner, John; Beehler, Gregory P; Swanson, Mya; Meyer-Bahlburg, Heino F L

2003-03-01

Early sex hormone exposure contributes to gender-dimorphic behavioral development in mammals, including humans. Environmental toxicants concentrated in contaminated sport fish can interfere with the actions of sex steroids. This study developed an outcome variable by combining gender-dimorphic behaviors that differentiates boys and girls. Offspring of participants in the New York State Angler Cohort Study (NYSACS) were targeted in a parent-report postal survey. Instruments were selected based on findings of gender differences in the general population. A linear discriminant function model incorporating three gender behavior scales correctly classified the sex of 97.7% of children (252 boys and 234 girls) from a random NYSACS sample. The discriminant function was cross-validated by correctly classifying the sex of 98.4% of children (457 boys and 425 girls) from the remaining NYSACS cases and 97.6% of children (154 boys and 142 girls) from an independent school sample. Within-sex stepwise multiple regression analyses revealed that masculine behavior increased among boys with age and with the number of years of maternal sport fish consumption. In girls, older age and previous live-born siblings were associated with more masculine behavior, whereas feminine behavior increased with the duration of breast feeding. These associations were replicated in an independent sample. A linear discriminant function effectively transformed the binary classification of sex (male-female) to a bipolar continuum of gender (masculinity-femininity). Findings from this study are consistent with the hypothesis that environmental contaminants contribute to shifts in gender-role behavior. Future investigations will need to account for competing explanations of this effect.

Development of PCR primers specific for the amplification and direct sequencing of gyrB genes from microbacteria, order Actinomycetales.

PubMed

Richert, Kathrin; Brambilla, Evelyne; Stackebrandt, Erko

2005-01-01

PCR primer sets were developed for the specific amplification and sequence analyses encoding the gyrase subunit B (gyrB) of members of the family Microbacteriaceae, class Actinobacteria. The family contains species highly related by 16S rRNA gene sequence analyses. In order to test if the gene sequence analysis of gyrB is appropriate to discriminate between closely related species, we evaluate the 16S rRNA gene phylogeny of its members. As the published universal primer set for gyrB failed to amplify the responding gene of the majority of the 80 type strains of the family, three new primer sets were identified that generated fragments with a composite sequence length of about 900 nt. However, the amplification of all three fragments was successful only in 25% of the 80 type strains. In this study, the substitution frequencies in genes encoding gyrase and 16S rDNA were compared for 10 strains of nine genera. The frequency of gyrB nucleotide substitution is significantly higher than that of the 16S rDNA, and no linear correlation exists between the similarities of both molecules among members of the Microbacteriaceae. The phylogenetic analyses using the gyrB sequences provide higher resolution than using 16S rDNA sequences and seem able to discriminate between closely related species.

A comparison of different chemometrics approaches for the robust classification of electronic nose data.

PubMed

Gromski, Piotr S; Correa, Elon; Vaughan, Andrew A; Wedge, David C; Turner, Michael L; Goodacre, Royston

2014-11-01

Accurate detection of certain chemical vapours is important, as these may be diagnostic for the presence of weapons, drugs of misuse or disease. In order to achieve this, chemical sensors could be deployed remotely. However, the readout from such sensors is a multivariate pattern, and this needs to be interpreted robustly using powerful supervised learning methods. Therefore, in this study, we compared the classification accuracy of four pattern recognition algorithms which include linear discriminant analysis (LDA), partial least squares-discriminant analysis (PLS-DA), random forests (RF) and support vector machines (SVM) which employed four different kernels. For this purpose, we have used electronic nose (e-nose) sensor data (Wedge et al., Sensors Actuators B Chem 143:365-372, 2009). In order to allow direct comparison between our four different algorithms, we employed two model validation procedures based on either 10-fold cross-validation or bootstrapping. The results show that LDA (91.56% accuracy) and SVM with a polynomial kernel (91.66% accuracy) were very effective at analysing these e-nose data. These two models gave superior prediction accuracy, sensitivity and specificity in comparison to the other techniques employed. With respect to the e-nose sensor data studied here, our findings recommend that SVM with a polynomial kernel should be favoured as a classification method over the other statistical models that we assessed. SVM with non-linear kernels have the advantage that they can be used for classifying non-linear as well as linear mapping from analytical data space to multi-group classifications and would thus be a suitable algorithm for the analysis of most e-nose sensor data.

Prediction of health levels by remote sensing

NASA Technical Reports Server (NTRS)

Rush, M.; Vernon, S.

1975-01-01

Measures of the environment derived from remote sensing were compared to census population/housing measures in their ability to discriminate among health status areas in two urban communities. Three hypotheses were developed to explore the relationships between environmental and health data. Univariate and multiple step-wise linear regression analyses were performed on data from two sample areas in Houston and Galveston, Texas. Environmental data gathered by remote sensing were found to equal or surpass census data in predicting rates of health outcomes. Remote sensing offers the advantages of data collection for any chosen area or time interval, flexibilities not allowed by the decennial census.

Differential Lipid Profiles of Normal Human Brain Matter and Gliomas by Positive and Negative Mode Desorption Electrospray Ionization – Mass Spectrometry Imaging

PubMed Central

Pirro, Valentina; Hattab, Eyas M.; Cohen-Gadol, Aaron A.; Cooks, R. Graham

2016-01-01

Desorption electrospray ionization—mass spectrometry (DESI-MS) imaging was used to analyze unmodified human brain tissue sections from 39 subjects sequentially in the positive and negative ionization modes. Acquisition of both MS polarities allowed more complete analysis of the human brain tumor lipidome as some phospholipids ionize preferentially in the positive and others in the negative ion mode. Normal brain parenchyma, comprised of grey matter and white matter, was differentiated from glioma using positive and negative ion mode DESI-MS lipid profiles with the aid of principal component analysis along with linear discriminant analysis. Principal component–linear discriminant analyses of the positive mode lipid profiles was able to distinguish grey matter, white matter, and glioma with an average sensitivity of 93.2% and specificity of 96.6%, while the negative mode lipid profiles had an average sensitivity of 94.1% and specificity of 97.4%. The positive and negative mode lipid profiles provided complementary information. Principal component–linear discriminant analysis of the combined positive and negative mode lipid profiles, via data fusion, resulted in approximately the same average sensitivity (94.7%) and specificity (97.6%) of the positive and negative modes when used individually. However, they complemented each other by improving the sensitivity and specificity of all classes (grey matter, white matter, and glioma) beyond 90% when used in combination. Further principal component analysis using the fused data resulted in the subgrouping of glioma into two groups associated with grey and white matter, respectively, a separation not apparent in the principal component analysis scores plots of the separate positive and negative mode data. The interrelationship of tumor cell percentage and the lipid profiles is discussed, and how such a measure could be used to measure residual tumor at surgical margins. PMID:27658243

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.

Latent log-linear models for handwritten digit classification.

PubMed

Deselaers, Thomas; Gass, Tobias; Heigold, Georg; Ney, Hermann

2012-06-01

We present latent log-linear models, an extension of log-linear models incorporating latent variables, and we propose two applications thereof: log-linear mixture models and image deformation-aware log-linear models. The resulting models are fully discriminative, can be trained efficiently, and the model complexity can be controlled. Log-linear mixture models offer additional flexibility within the log-linear modeling framework. Unlike previous approaches, the image deformation-aware model directly considers image deformations and allows for a discriminative training of the deformation parameters. Both are trained using alternating optimization. For certain variants, convergence to a stationary point is guaranteed and, in practice, even variants without this guarantee converge and find models that perform well. We tune the methods on the USPS data set and evaluate on the MNIST data set, demonstrating the generalization capabilities of our proposed models. Our models, although using significantly fewer parameters, are able to obtain competitive results with models proposed in the literature.

Assessment of computer techniques for processing digital LANDSAT MSS data for lithological discrimination of Serra do Ramalho, State of Bahia

NASA Technical Reports Server (NTRS)

Paradella, W. R. (Principal Investigator); Vitorello, I.; Monteiro, M. D.

1984-01-01

Enhancement techniques and thematic classifications were applied to the metasediments of Bambui Super Group (Upper Proterozoic) in the Region of Serra do Ramalho, SW of the state of Bahia. Linear contrast stretch, band-ratios with contrast stretch, and color-composites allow lithological discriminations. The effects of human activities and of vegetation cover mask and limit, in several ways, the lithological discrimination with digital MSS data. Principal component images and color composite of linear contrast stretch of these products, show lithological discrimination through tonal gradations. This set of products allows the delineations of several metasedimentary sequences to a level superior to reconnaissance mapping. Supervised (maximum likelihood classifier) and nonsupervised (K-Means classifier) classification of the limestone sequence, host to fluorite mineralization show satisfactory results.

Experimental optimal maximum-confidence discrimination and optimal unambiguous discrimination of two mixed single-photon states

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

Steudle, Gesine A.; Knauer, Sebastian; Herzog, Ulrike

2011-05-15

We present an experimental implementation of optimum measurements for quantum state discrimination. Optimum maximum-confidence discrimination and optimum unambiguous discrimination of two mixed single-photon polarization states were performed. For the latter the states of rank 2 in a four-dimensional Hilbert space are prepared using both path and polarization encoding. Linear optics and single photons from a true single-photon source based on a semiconductor quantum dot are utilized.

Racial/ethnic and gender differences in the association between self-reported experiences of racial/ethnic discrimination and inflammation in the CARDIA cohort of 4 US communities.

PubMed

Cunningham, Timothy J; Seeman, Teresa E; Kawachi, Ichiro; Gortmaker, Steven L; Jacobs, David R; Kiefe, Catarina I; Berkman, Lisa F

2012-09-01

Inflammation is etiologically implicated in cardiometabolic diseases for which there are known racial/ethnic disparities. Prior studies suggest there may be an association between self-reported experiences of racial/ethnic discrimination and inflammation, particularly C-reactive protein (CRP). It is not known whether that association is influenced by race/ethnicity and gender. In separate hierarchical linear models with time-varying covariates, we examined that association among 901 Black women, 614 Black men, 958 White women, and 863 White men in the Coronary Artery Risk Development in Young Adults (CARDIA) study in four US communities. Self-reported experiences of racial/ethnic discrimination were ascertained in 1992-93 and 2000-01. Inflammation was measured as log-transformed CRP in those years and 2005-06. All analyses were adjusted for blood pressure, plasma total cholesterol, triglycerides, homeostatic model assessment for insulin resistance (HOMA-IR), age, education, and community. Our findings extend prior research by suggesting that, broadly speaking, self-reported experiences of racial/ethnic discrimination are associated with inflammation; however, this association is complex and varies for Black and White women and men. Black women reporting 1 or 2 experiences of discrimination had higher levels of CRP compared to Black women reporting no experiences of discrimination (β = 0.141, SE = 0.062, P < 0.05). This association was not statistically significant among Black women reporting 3 or more experiences of discrimination and not independent of modifiable risks (smoking and obesity) in the final model. White women reporting 3 or more experiences of discrimination had significantly higher levels of CRP compared to White women reporting no experiences of discrimination independent of modifiable risks in the final model (β = 0.300, SE = 0.113, P < 0.01). The association between self-reported experiences of racial/ethnic discrimination and CRP was not statistically significant among Black and White men reporting 1 or 2 experiences of discrimination. Further research in other populations is needed. Published by Elsevier Ltd.

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

PubMed

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

2017-04-12

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

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

PubMed

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

2009-05-01

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

The use of δ(2)H and δ(18)O isotopic analyses combined with chemometrics as a traceability tool for the geographical origin of bell peppers.

PubMed

de Rijke, E; Schoorl, J C; Cerli, C; Vonhof, H B; Verdegaal, S J A; Vivó-Truyols, G; Lopatka, M; Dekter, R; Bakker, D; Sjerps, M J; Ebskamp, M; de Koster, C G

2016-08-01

Two approaches were investigated to discriminate between bell peppers of different geographic origins. Firstly, δ(18)O fruit water and corresponding source water were analyzed and correlated to the regional GNIP (Global Network of Isotopes in Precipitation) values. The water and GNIP data showed good correlation with the pepper data, with constant isotope fractionation of about -4. Secondly, compound-specific stable hydrogen isotope data was used for classification. Using n-alkane fingerprinting data, both linear discriminant analysis (LDA) and a likelihood-based classification, using the kernel-density smoothed data, were developed to discriminate between peppers from different origins. Both methods were evaluated using the δ(2)H values and n-alkanes relative composition as variables. Misclassification rates were calculated using a Monte-Carlo 5-fold cross-validation procedure. Comparable overall classification performance was achieved, however, the two methods showed sensitivity to different samples. The combined values of δ(2)H IRMS, and complimentary information regarding the relative abundance of four main alkanes in bell pepper fruit water, has proven effective for geographic origin discrimination. Evaluation of the rarity of observing particular ranges for these characteristics could be used to make quantitative assertions regarding geographic origin of bell peppers and, therefore, have a role in verifying compliance with labeling of geographical origin. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Prognostic estimation in critical patients. Validation of a new and very simple system of prognostic estimation of survival in an intensive care unit].

PubMed

Abizanda, R; Padron, A; Vidal, B; Mas, S; Belenguer, A; Madero, J; Heras, A

2006-04-01

To make the validation of a new system of prognostic estimation of survival in critical patients (EPEC) seen in a multidisciplinar Intensive care unit (ICU). Prospective analysis of a patient cohort seen in the ICU of a multidisciplinar Intensive Medicine Service of a reference teaching hospital with 19 beds. Four hundred eighty four patients admitted consecutively over 6 months in 2003. Data collection of a basic minimum data set that includes patient identification data (gender, age), reason for admission and their origin, prognostic estimation of survival by EPEC, MPM II 0 and SAPS II (the latter two considered as gold standard). Mortality was evaluated on hospital discharge. EPEC validation was done with analysis of its discriminating capacity (ROC curve), calibration of its prognostic capacity (Hosmer Lemeshow C test), resolution of the 2 x 2 Contingency tables around different probability values (20, 50, 70 and mean value of prognostic estimation). The standardized mortality rate (SMR) for each one of the methods was calculated. Linear regression of the EPEC regarding the MPM II 0 and SAPS II was established and concordance analyses were done (Bland-Altman test) of the prediction of mortality by the three systems. In spite of an apparently good linear correlation, similar accuracy of prediction and discrimination capacity, EPEC is not well-calibrated (no likelihood of death greater than 50%) and the concordance analyses show that more than 10% of the pairs were outside the 95% confidence interval. In spite of its ease of application and calculation and of incorporating delay of admission in ICU as a variable, EPEC does not offer any predictive advantage on MPM II 0 or SAPS II, and its predictions adapt to reality worse.

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields

PubMed Central

Zhao, Henan; Bryant, Garnett W.; Griffin, Wesley; Terrill, Judith E.; Chen, Jian

2017-01-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks. PMID:28113469

Validation of SplitVectors Encoding for Quantitative Visualization of Large-Magnitude-Range Vector Fields.

PubMed

Henan Zhao; Bryant, Garnett W; Griffin, Wesley; Terrill, Judith E; Jian Chen

2017-06-01

We designed and evaluated SplitVectors, a new vector field display approach to help scientists perform new discrimination tasks on large-magnitude-range scientific data shown in three-dimensional (3D) visualization environments. SplitVectors uses scientific notation to display vector magnitude, thus improving legibility. We present an empirical study comparing the SplitVectors approach with three other approaches - direct linear representation, logarithmic, and text display commonly used in scientific visualizations. Twenty participants performed three domain analysis tasks: reading numerical values (a discrimination task), finding the ratio between values (a discrimination task), and finding the larger of two vectors (a pattern detection task). Participants used both mono and stereo conditions. Our results suggest the following: (1) SplitVectors improve accuracy by about 10 times compared to linear mapping and by four times to logarithmic in discrimination tasks; (2) SplitVectors have no significant differences from the textual display approach, but reduce cluttering in the scene; (3) SplitVectors and textual display are less sensitive to data scale than linear and logarithmic approaches; (4) using logarithmic can be problematic as participants' confidence was as high as directly reading from the textual display, but their accuracy was poor; and (5) Stereoscopy improved performance, especially in more challenging discrimination tasks.

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.

Ultrahigh-Dimensional Multiclass Linear Discriminant Analysis by Pairwise Sure Independence Screening

PubMed Central

Pan, Rui; Wang, Hansheng; Li, Runze

2016-01-01

This paper is concerned with the problem of feature screening for multi-class linear discriminant analysis under ultrahigh dimensional setting. We allow the number of classes to be relatively large. As a result, the total number of relevant features is larger than usual. This makes the related classification problem much more challenging than the conventional one, where the number of classes is small (very often two). To solve the problem, we propose a novel pairwise sure independence screening method for linear discriminant analysis with an ultrahigh dimensional predictor. The proposed procedure is directly applicable to the situation with many classes. We further prove that the proposed method is screening consistent. Simulation studies are conducted to assess the finite sample performance of the new procedure. We also demonstrate the proposed methodology via an empirical analysis of a real life example on handwritten Chinese character recognition. PMID:28127109

Discriminating the Mineralogical Composition in Drill Cuttings Based on Absorption Spectra in the Terahertz Range.

PubMed

Miao, Xinyang; Li, Hao; Bao, Rima; Feng, Chengjing; Wu, Hang; Zhan, Honglei; Li, Yizhang; Zhao, Kun

2017-02-01

Understanding the geological units of a reservoir is essential to the development and management of the resource. In this paper, drill cuttings from several depths from an oilfield were studied using terahertz time domain spectroscopy (THz-TDS). Cluster analysis (CA) and principal component analysis (PCA) were employed to classify and analyze the cuttings. The cuttings were clearly classified based on CA and PCA methods, and the results were in agreement with the lithology. Moreover, calcite and dolomite have stronger absorption of a THz pulse than any other minerals, based on an analysis of the PC1 scores. Quantitative analyses of minor minerals were also realized by building a series of linear and non-linear models between contents and PC2 scores. The results prove THz technology to be a promising means for determining reservoir lithology as well as other properties, which will be a significant supplementary method in oil fields.

Determination of authenticity, regional origin, and vintage of Slovenian wines using a combination of IRMS and SNIF-NMR analyses.

PubMed

Ogrinc, N; Kosir, I J; Kocjancic, M; Kidric, J

2001-03-01

The authenticity and geographical origin of wines produced in Slovenia were investigated by a combination of IRMS and SNIF-NMR methods. A total of 102 grape samples of selected wines were carefully collected in three different wine-growing regions of Slovenia in 1996, 1997, and 1998. The stable isotope data were evaluated using principal component analysis (PCA) and linear discriminant analysis (LDA). The isotopic ratios to discriminate between coastal and continental regions are the deuterium/hydrogen isotopic ratio of the methylene site in the ethanol molecule (D/H)(II) and delta(13)C values; including also delta(18)O values in the PCA and LDA made possible separation between the two continental regions Drava and Sava. It was found that delta(18)O values are modified by the meteorological events during grape ripening and harvest. The usefulness of isotopic parameters for detecting adulteration or watering and to assess the geographical origin of wines is improved only when they are used concurrently.

Differentiation of wines according to grape variety and geographical origin based on volatiles profiling using SPME-MS and SPME-GC/MS methods.

PubMed

Ziółkowska, Angelika; Wąsowicz, Erwin; Jeleń, Henryk H

2016-12-15

Among methods to detect wine adulteration, profiling volatiles is one with a great potential regarding robustness, analysis time and abundance of information for subsequent data treatment. Volatile fraction fingerprinting by solid-phase microextraction with direct analysis by mass spectrometry without compounds separation (SPME-MS) was used for differentiation of white as well as red wines. The aim was to differentiate between varieties used for wine production and to also differentiate wines by country of origin. The results obtained were compared to SPME-GC/MS analysis in which compounds were resolved by gas chromatography. For both approaches the same type of statistical procedure was used to compare samples: principal component analysis (PCA) followed by linear discriminant analysis (LDA). White wines (38) and red wines (41) representing different grape varieties and various regions of origin were analysed. SPME-MS proved to be advantageous in use due to better discrimination and higher sample throughput. Copyright © 2016 Elsevier Ltd. All rights reserved.

Prediction of the space adaptation syndrome

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Computational models of location-invariant orthographic processing

NASA Astrophysics Data System (ADS)

Dandurand, Frédéric; Hannagan, Thomas; Grainger, Jonathan

2013-03-01

We trained three topologies of backpropagation neural networks to discriminate 2000 words (lexical representations) presented at different positions of a horizontal letter array. The first topology (zero-deck) contains no hidden layer, the second (one-deck) has a single hidden layer, and for the last topology (two-deck), the task is divided in two subtasks implemented as two stacked neural networks, with explicit word-centred letters as intermediate representations. All topologies successfully simulated two key benchmark phenomena observed in skilled human reading: transposed-letter priming and relative-position priming. However, the two-deck topology most accurately simulated the ability to discriminate words from nonwords, while containing the fewest connection weights. We analysed the internal representations after training. Zero-deck networks implement a letter-based scheme with a position bias to differentiate anagrams. One-deck networks implement a holographic overlap coding in which representations are essentially letter-based and words are linear combinations of letters. Two-deck networks also implement holographic-coding.

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.

Discriminating the reaction types of plant type III polyketide synthases

PubMed Central

Shimizu, Yugo; Ogata, Hiroyuki; Goto, Susumu

2017-01-01

Abstract Motivation: Functional prediction of paralogs is challenging in bioinformatics because of rapid functional diversification after gene duplication events combined with parallel acquisitions of similar functions by different paralogs. Plant type III polyketide synthases (PKSs), producing various secondary metabolites, represent a paralogous family that has undergone gene duplication and functional alteration. Currently, there is no computational method available for the functional prediction of type III PKSs. Results: We developed a plant type III PKS reaction predictor, pPAP, based on the recently proposed classification of type III PKSs. pPAP combines two kinds of similarity measures: one calculated by profile hidden Markov models (pHMMs) built from functionally and structurally important partial sequence regions, and the other based on mutual information between residue positions. pPAP targets PKSs acting on ring-type starter substrates, and classifies their functions into four reaction types. The pHMM approach discriminated two reaction types with high accuracy (97.5%, 39/40), but its accuracy decreased when discriminating three reaction types (87.8%, 43/49). When combined with a correlation-based approach, all 49 PKSs were correctly discriminated, and pPAP was still highly accurate (91.4%, 64/70) even after adding other reaction types. These results suggest pPAP, which is based on linear discriminant analyses of similarity measures, is effective for plant type III PKS function prediction. Availability and Implementation: pPAP is freely available at ftp://ftp.genome.jp/pub/tools/ppap/ Contact: goto@kuicr.kyoto-u.ac.jp Supplementary information: Supplementary data are available at Bioinformatics online. PMID:28334262

Linear Quantitative Profiling Method Fast Monitors Alkaloids of Sophora Flavescens That Was Verified by Tri-Marker Analyses.

PubMed

Hou, Zhifei; Sun, Guoxiang; Guo, Yong

2016-01-01

The present study demonstrated the use of the Linear Quantitative Profiling Method (LQPM) to evaluate the quality of Alkaloids of Sophora flavescens (ASF) based on chromatographic fingerprints in an accurate, economical and fast way. Both linear qualitative and quantitative similarities were calculated in order to monitor the consistency of the samples. The results indicate that the linear qualitative similarity (LQLS) is not sufficiently discriminating due to the predominant presence of three alkaloid compounds (matrine, sophoridine and oxymatrine) in the test samples; however, the linear quantitative similarity (LQTS) was shown to be able to obviously identify the samples based on the difference in the quantitative content of all the chemical components. In addition, the fingerprint analysis was also supported by the quantitative analysis of three marker compounds. The LQTS was found to be highly correlated to the contents of the marker compounds, indicating that quantitative analysis of the marker compounds may be substituted with the LQPM based on the chromatographic fingerprints for the purpose of quantifying all chemicals of a complex sample system. Furthermore, once reference fingerprint (RFP) developed from a standard preparation in an immediate detection way and the composition similarities calculated out, LQPM could employ the classical mathematical model to effectively quantify the multiple components of ASF samples without any chemical standard.

Stable orthogonal local discriminant embedding for linear dimensionality reduction.

PubMed

Gao, Quanxue; Ma, Jingjie; Zhang, Hailin; Gao, Xinbo; Liu, Yamin

2013-07-01

Manifold learning is widely used in machine learning and pattern recognition. However, manifold learning only considers the similarity of samples belonging to the same class and ignores the within-class variation of data, which will impair the generalization and stableness of the algorithms. For this purpose, we construct an adjacency graph to model the intraclass variation that characterizes the most important properties, such as diversity of patterns, and then incorporate the diversity into the discriminant objective function for linear dimensionality reduction. Finally, we introduce the orthogonal constraint for the basis vectors and propose an orthogonal algorithm called stable orthogonal local discriminate embedding. Experimental results on several standard image databases demonstrate the effectiveness of the proposed dimensionality reduction approach.

Testing of a simplified LED based vis/NIR system for rapid ripeness evaluation of white grape (Vitis vinifera L.) for Franciacorta wine.

PubMed

Giovenzana, Valentina; Civelli, Raffaele; Beghi, Roberto; Oberti, Roberto; Guidetti, Riccardo

2015-11-01

The aim of this work was to test a simplified optical prototype for a rapid estimation of the ripening parameters of white grape for Franciacorta wine directly in field. Spectral acquisition based on reflectance at four wavelengths (630, 690, 750 and 850 nm) was proposed. The integration of a simple processing algorithm in the microcontroller software would allow to visualize real time values of spectral reflectance. Non-destructive analyses were carried out on 95 grape bunches for a total of 475 berries. Samplings were performed weekly during the last ripening stages. Optical measurements were carried out both using the simplified system and a portable commercial vis/NIR spectrophotometer, as reference instrument for performance comparison. Chemometric analyses were performed in order to extract the maximum useful information from optical data. Principal component analysis (PCA) was performed for a preliminary evaluation of the data. Correlations between the optical data matrix and ripening parameters (total soluble solids content, SSC; titratable acidity, TA) were carried out using partial least square (PLS) regression for spectra and using multiple linear regression (MLR) for data from the simplified device. Classification analysis were also performed with the aim of discriminate ripe and unripe samples. PCA, MLR and classification analyses show the effectiveness of the simplified system in separating samples among different sampling dates and in discriminating ripe from unripe samples. Finally, simple equations for SSC and TA prediction were calculated. Copyright © 2015 Elsevier B.V. All rights reserved.

Deformation-Aware Log-Linear Models

NASA Astrophysics Data System (ADS)

Gass, Tobias; Deselaers, Thomas; Ney, Hermann

In this paper, we present a novel deformation-aware discriminative model for handwritten digit recognition. Unlike previous approaches our model directly considers image deformations and allows discriminative training of all parameters, including those accounting for non-linear transformations of the image. This is achieved by extending a log-linear framework to incorporate a latent deformation variable. The resulting model has an order of magnitude less parameters than competing approaches to handling image deformations. We tune and evaluate our approach on the USPS task and show its generalization capabilities by applying the tuned model to the MNIST task. We gain interesting insights and achieve highly competitive results on both tasks.

School-Based Racial and Gender Discrimination among African American Adolescents: Exploring Gender Variation in Frequency and Implications for Adjustment

PubMed Central

Chavous, Tabbye M.; Griffin, Tiffany M.

2012-01-01

The present study examined school-based racial and gender discrimination experiences among African American adolescents in Grade 8 (n = 204 girls; n = 209 boys). A primary goal was exploring gender variation in frequency of both types of discrimination and associations of discrimination with academic and psychological functioning among girls and boys. Girls and boys did not vary in reported racial discrimination frequency, but boys reported more gender discrimination experiences. Multiple regression analyses within gender groups indicated that among girls and boys, racial discrimination and gender discrimination predicted higher depressive symptoms and school importance and racial discrimination predicted self-esteem. Racial and gender discrimination were also negatively associated with grade point average among boys but were not significantly associated in girls’ analyses. Significant gender discrimination X racial discrimination interactions resulted in the girls’ models predicting psychological outcomes and in boys’ models predicting academic achievement. Taken together, findings suggest the importance of considering gender- and race-related experiences in understanding academic and psychological adjustment among African American adolescents. PMID:22837794

School-Based Racial and Gender Discrimination among African American Adolescents: Exploring Gender Variation in Frequency and Implications for Adjustment.

PubMed

Cogburn, Courtney D; Chavous, Tabbye M; Griffin, Tiffany M

2011-01-03

The present study examined school-based racial and gender discrimination experiences among African American adolescents in Grade 8 (n = 204 girls; n = 209 boys). A primary goal was exploring gender variation in frequency of both types of discrimination and associations of discrimination with academic and psychological functioning among girls and boys. Girls and boys did not vary in reported racial discrimination frequency, but boys reported more gender discrimination experiences. Multiple regression analyses within gender groups indicated that among girls and boys, racial discrimination and gender discrimination predicted higher depressive symptoms and school importance and racial discrimination predicted self-esteem. Racial and gender discrimination were also negatively associated with grade point average among boys but were not significantly associated in girls' analyses. Significant gender discrimination X racial discrimination interactions resulted in the girls' models predicting psychological outcomes and in boys' models predicting academic achievement. Taken together, findings suggest the importance of considering gender- and race-related experiences in understanding academic and psychological adjustment among African American adolescents.

The relationship between socially-assigned ethnicity, health and experience of racial discrimination for Māori: analysis of the 2006/07 New Zealand Health Survey

PubMed Central

2013-01-01

Background In New Zealand, there are significant and long-standing inequalities in a range of health outcomes, risk factors and healthcare measures between Māori (indigenous peoples) and Pākehā (European). This study expands our understanding of racism as a determinant of such inequalities to examine the concept of socially-assigned ethnicity (how an individual is classified by others ethnically/racially) and its relationship to health and racism for Māori. There is some evidence internationally that being socially-assigned as the dominant ethnic group (in this case European) offers health advantage. Methods We analysed data from the 2006/07 New Zealand Health Survey for adult participants who self-identified their ethnicity as Māori (n = 3160). The association between socially-assigned ethnicity and individual experience of racial discrimination, and socially-assigned ethnicity and health (self-rated health, psychological distress [Kessler 10-item scale]) was assessed using logistic and linear regression analyses, respectively. Results Māori who were socially-assigned as European-only had significantly lower experience of racial discrimination (adjusted odds ratio [OR] = 0.58, 95% confidence interval [CI] = 0.44, 0.78) than Māori who were socially-assigned as non-European. Being socially-assigned as European-only was also associated with health advantage compared to being socially-assigned non-European: more likely to respond with self-rated very good/excellent health (age, sex adjusted OR = 1.39, 95% CI = 1.10, 1.74), and lower Kessler 10 scores (age, sex adjusted mean difference = -0.66, 95% C I = -1.22, -0.10). These results were attenuated following adjustment for socioeconomic measures and experience of racial discrimination. Conclusions Results suggest that, in a race conscious society, the way people’s ethnicities are viewed by others is associated with tangible health risk or advantage, and this is consistent with an understanding of racism as a health determinant. PMID:24028091

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.

Does perceived racial discrimination predict changes in psychological distress and substance use over time? An examination among Black emerging adults.

PubMed

Hurd, Noelle M; Varner, Fatima A; Caldwell, Cleopatra H; Zimmerman, Marc A

2014-07-01

We assessed whether perceived discrimination predicted changes in psychological distress and substance use over time and whether psychological distress and substance use predicted change in perceived discrimination over time. We also assessed whether associations between these constructs varied by gender. Our sample included 607 Black emerging adults (53% female) followed for 4 years. Participants reported the frequency with which they had experienced racial hassles during the past year, symptoms of anxiety and depression during the past week, and cigarette and alcohol use during the past 30 days. We estimated a series of latent growth models to test our study hypotheses. We found that the intercept of perceived discrimination predicted the linear slopes of anxiety symptoms, depressive symptoms, and alcohol use. We did not find any associations between the intercept factors of our mental health or substance use variables and the perceived discrimination linear slope factor. We found limited differences across paths by gender. Our findings suggest a temporal ordering in the associations among perceived racial discrimination, psychological distress, and alcohol use over time among emerging adults. Further, our findings suggest that perceived racial discrimination may be similarly harmful among men and women. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

Research of Face Recognition with Fisher Linear Discriminant

NASA Astrophysics Data System (ADS)

Rahim, R.; Afriliansyah, T.; Winata, H.; Nofriansyah, D.; Ratnadewi; Aryza, S.

2018-01-01

Face identification systems are developing rapidly, and these developments drive the advancement of biometric-based identification systems that have high accuracy. However, to develop a good face recognition system and to have high accuracy is something that’s hard to find. Human faces have diverse expressions and attribute changes such as eyeglasses, mustache, beard and others. Fisher Linear Discriminant (FLD) is a class-specific method that distinguishes facial image images into classes and also creates distance between classes and intra classes so as to produce better classification.

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.

Using Mathematical Analyses Activities to Improve Manipulative Discrimination in Early Childhood Teacher Education

ERIC Educational Resources Information Center

Ertle, Barbrina B.

2017-01-01

This article reports on the findings of manipulative analyses performed by preservice and in-service teachers in an early childhood teacher education program mathematics methods course. The activities are intended to model and promote mathematical analyses for better discrimination between mathematics manipulatives by early childhood teachers.…

RAMAN spectroscopy imaging improves the diagnosis of papillary thyroid carcinoma

NASA Astrophysics Data System (ADS)

Rau, Julietta V.; Graziani, Valerio; Fosca, Marco; Taffon, Chiara; Rocchia, Massimiliano; Crucitti, Pierfilippo; Pozzilli, Paolo; Onetti Muda, Andrea; Caricato, Marco; Crescenzi, Anna

2016-10-01

Recent investigations strongly suggest that Raman spectroscopy (RS) can be used as a clinical tool in cancer diagnosis to improve diagnostic accuracy. In this study, we evaluated the efficiency of Raman imaging microscopy to discriminate between healthy and neoplastic thyroid tissue, by analyzing main variants of Papillary Thyroid Carcinoma (PTC), the most common type of thyroid cancer. We performed Raman imaging of large tissue areas (from 100 × 100 μm2 up to 1 × 1 mm2), collecting 38 maps containing about 9000 Raman spectra. Multivariate statistical methods, including Linear Discriminant Analysis (LDA), were applied to translate Raman spectra differences between healthy and PTC tissues into diagnostically useful information for a reliable tissue classification. Our study is the first demonstration of specific biochemical features of the PTC profile, characterized by significant presence of carotenoids with respect to the healthy tissue. Moreover, this is the first evidence of Raman spectra differentiation between classical and follicular variant of PTC, discriminated by LDA with high efficiency. The combined histological and Raman microscopy analyses allow clear-cut integration of morphological and biochemical observations, with dramatic improvement of efficiency and reliability in the differential diagnosis of neoplastic thyroid nodules, paving the way to integrative findings for tumorigenesis and novel therapeutic strategies.

Taking It Like a Man: Masculine Role Norms as Moderators of the Racial Discrimination–Depressive Symptoms Association Among African American Men

PubMed Central

2012-01-01

Objectives. I examined the association between everyday racial discrimination and depressive symptoms and explored the moderating role of 2 dimensions of masculine role norms, restrictive emotionality and self-reliance. Methods. Cross-sectional survey data from 674 African American men aged 18 years and older recruited primarily from barbershops in 4 US regions (2003–2010) were used. Direct and moderated associations were assessed with multivariate linear regression analyses for the overall sample and different age groups. Models were adjusted for recruitment site, sociodemographics, masculine role norms salience, and general social stress. Results. Everyday racial discrimination was associated with more depressive symptoms across all age groups. Higher restrictive emotionality was associated with more depressive symptoms among men aged 18 to 29 and 30 to 39 years. Self-reliance was associated with fewer depressive symptoms among men aged 18 to 29 years and 40 years and older. The positive association between everyday racial discrimination and depressive symptoms was stronger among men with high restrictive emotionality, but this moderated effect was limited to men older than 30 years. Conclusions. Interventions designed to reduce African American men’s depression instigated by racism should be life-course specific and address masculine role norms that encourage emotion restriction. PMID:22401515

Discriminability of Personality Profiles in Isolated and Co-Morbid Marijuana and Nicotine Users

PubMed Central

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L.; Filbey, Francesca M

2016-01-01

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co-morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana + nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. PMID:27086256

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.

Chestnut flowers as functionalizing agents to enhance the antioxidant properties of highly appreciated traditional pastry.

PubMed

Carocho, Márcio; Barreira, João C M; Bento, Albino; Morales, Patricia; Ferreira, Isabel C F R

2014-11-01

Some studies have proven the antioxidant and antimicrobial potency of chestnut flowers both in the raw matrix and after extraction, and the consumption of their decoctions has been related to beneficial effects towards health. In recent years, due to controversy and ambiguous legislation of chemical conservatives, plant extracts have been successfully used as functionalizing agents in different matrixes by displaying their various beneficial effects towards the foodstuff and/or the consumer. In this paper, decoctions of chestnut flowers as well as the dried flower were added to Portuguese traditional cakes that were then stored for 15 and 30 days, after which they were analysed for their antioxidant potential. The results were analysed by means of a 2 way ANOVA and a linear discriminant analysis, concluding that storage time had a slightly higher influence on alteration of the antioxidant activity. DPPH and TBARS were the most improved parameters, regardless of the concentration added.

Relationship between acculturation, discrimination, and suicidal ideation and attempts among US Hispanics in the National Epidemiologic Survey of Alcohol and Related Conditions.

PubMed

Perez-Rodriguez, M Mercedes; Baca-Garcia, Enrique; Oquendo, Maria A; Wang, Shuai; Wall, Melanie M; Liu, Shang-Min; Blanco, Carlos

2014-04-01

Acculturation is the process by which immigrants acquire the culture of the dominant society. Little is known about the relationship between acculturation and suicidal ideation and attempts among US Hispanics. Our aim was to examine the impact of 5 acculturation measures (age at migration, time in the United States, social network composition, language, race/ethnic orientation) on suicidal ideation and attempts in the largest available nationally representative sample of US Hispanics. Study participants were US Hispanics (N = 6,359) from Wave 2 of the 2004-2005 National Epidemiologic Survey of Alcohol and Related Conditions (N = 34,653). We used linear χ(2) tests and logistic regression models to analyze the association between acculturation and risk of suicidal ideation and attempts. Factors associated with a linear increase in lifetime risk for suicidal ideation and attempts were (1) younger age at migration (linear χ(2)(1) = 57.15; P < .0001), (2) longer time in the United States (linear χ(2)(1)= 36.09; P < .0001), (3) higher degree of English-language orientation (linear χ(2)(1) = 74.08; P <.0001), (4) lower Hispanic composition of social network (linear χ(2)(1) = 36.34; P < .0001), and (5) lower Hispanic racial/ethnic identification (linear χ(2)(1) = 47.77; P <.0001). Higher levels of perceived discrimination were associated with higher lifetime risk for suicidal ideation (β = 0.051; P < .001) and attempts (β = 0.020; P = .003). There was a linear association between multiple dimensions of acculturation and lifetime suicidal ideation and attempts. Discrimination was also associated with lifetime risk for suicidal ideation and attempts. Our results highlight protective aspects of the traditional Hispanic culture, such as high social support, coping strategies, and moral objections to suicide, which are modifiable factors and potential targets for public health interventions aimed at decreasing suicide risk. Culturally sensitive mental health resources need to be made more available to decrease discrimination and stigma. © Copyright 2014 Physicians Postgraduate Press, Inc.

Vegetation characteristics important to common songbirds in east Texas

USGS Publications Warehouse

Conner, Richard N.; Dickson, James G.; Locke, Brian A.; Segelquist, Charles A.

1983-01-01

Multivariate studies of breeding bird communities have used principal component analysis (PCA) or several-group (three or more groups) discriminant function analysis (DFA) to ordinate bird species on vegetational continua (Cody 1968, James 1971, Whitmore 1975). In community studies, high resolution of habitat requirements for individual species is not always possible with either PCA or several-group DFA. When habitat characteristics of several species are examined with a DFA the resultant axes optimally discriminate among all species simultaneously. Hence, the characteristics assigned to a particular species reflect in part the presence of other species in the analyses. A better resolution of each species' habitat requirements may be obtained from a two-group DFA, wherein habitats selected by a species are discriminated from all other available habitats. Analyses using two-group DFAs to compare habitat used by a species with habitat unused by the same species have the potential to provide an optimal frame of reference from which to examine habitat variables (Martinka 1972, Conner and Adkisson 1976, Whitmore 1981). Mathematically (DFA) it is possible to maximally separate two groups of multivariate observations with a single axis (Harner and whitmore 1977). A line drawn in three or n-dimensional space can easily be positioned to intersect two multivariate means (centroids). If three or more centroids for species are analyzed simultaneously, a single line can no longer intersect all centroids unless a perfectly linear relationship exists for the species being examined. The probability of such an occurrence is extremely low. Thus, a high degree of resolution can be realized when a two-group DFA is used to determine habitat parameters important to individual species. We have used two-group DFA to identify vegetation variable important to 12 common species of songbirds in East Texas.

Relating age and hearing loss to monaural, bilateral, and binaural temporal sensitivity1

PubMed Central

Gallun, Frederick J.; McMillan, Garnett P.; Molis, Michelle R.; Kampel, Sean D.; Dann, Serena M.; Konrad-Martin, Dawn L.

2014-01-01

Older listeners are more likely than younger listeners to have difficulties in making temporal discriminations among auditory stimuli presented to one or both ears. In addition, the performance of older listeners is often observed to be more variable than that of younger listeners. The aim of this work was to relate age and hearing loss to temporal processing ability in a group of younger and older listeners with a range of hearing thresholds. Seventy-eight listeners were tested on a set of three temporal discrimination tasks (monaural gap discrimination, bilateral gap discrimination, and binaural discrimination of interaural differences in time). To examine the role of temporal fine structure in these tasks, four types of brief stimuli were used: tone bursts, broad-frequency chirps with rising or falling frequency contours, and random-phase noise bursts. Between-subject group analyses conducted separately for each task revealed substantial increases in temporal thresholds for the older listeners across all three tasks, regardless of stimulus type, as well as significant correlations among the performance of individual listeners across most combinations of tasks and stimuli. Differences in performance were associated with the stimuli in the monaural and binaural tasks, but not the bilateral task. Temporal fine structure differences among the stimuli had the greatest impact on monaural thresholds. Threshold estimate values across all tasks and stimuli did not show any greater variability for the older listeners as compared to the younger listeners. A linear mixed model applied to the data suggested that age and hearing loss are independent factors responsible for temporal processing ability, thus supporting the increasingly accepted hypothesis that temporal processing can be impaired for older compared to younger listeners with similar hearing and/or amounts of hearing loss. PMID:25009458

Foods contributing to vitamin B6, folate, and vitamin B12 intakes and biomarkers status in European adolescents: The HELENA study.

PubMed

Iglesia, Iris; Mouratidou, Theodora; González-Gross, Marcela; Huybrechts, Inge; Breidenassel, Christina; Santabárbara, Javier; Díaz, Ligia-Esperanza; Hällström, Lena; De Henauw, Stefaan; Gottrand, Frédéric; Kafatos, Anthony; Widhalm, Kurt; Manios, Yannis; Molnar, Denes; Stehle, Peter; Moreno, Luis A

2017-06-01

To examine the association between food groups consumption and vitamin B 6 , folate and B 12 intakes and biomarkers in adolescents. In total 2189 individuals participating in the cross-sectional Healthy Lifestyle in Europe by Nutrition in Adolescence study met the eligibility criteria for analysis of dietary intakes (46 % males) and 632 for biomarker analysis (47 % males). Food intakes were assessed by two non-consecutive 24-h recalls. Biomarkers were measured by chromatography and immunoassay. Food groups which best discriminated participants in the extreme tertiles of the distribution of vitamins were identified by discriminant analyses. Food groups with standardised canonical coefficients higher or equal to 0.3 were selected as valid discriminators of vitamins intake and biomarkers extreme tertiles. Linear mixed model elucidated the association between food groups and vitamins intakes and biomarkers. Vitamin B 6 intakes and biomarkers were best discriminated by meat (males and females), margarine and mixed origin lipids only in males and breakfast cereals (females). Breakfast cereals (males), and fruits, margarine and mixed origin lipids, vegetables excluding potatoes, breakfast cereals, and soups/bouillon (females) determined the most folate intakes and biomarkers. Considering vitamin B 12 intakes and biomarkers, meat, and white and butter milk (males and females), snacks (males), and dairy products (females) best discriminated individual in the extremes of the distribution. Fewer associations were obtained with mixed model for biomarkers than for vitamins intakes with food groups. Whereas B-vitamin intakes were associated with their food sources, biomarkers did with overall food consumption. Low-nutrient-density foods may compromise adolescents' vitamin status.

Supervised linear dimensionality reduction with robust margins for object recognition

NASA Astrophysics Data System (ADS)

Dornaika, F.; Assoum, A.

2013-01-01

Linear Dimensionality Reduction (LDR) techniques have been increasingly important in computer vision and pattern recognition since they permit a relatively simple mapping of data onto a lower dimensional subspace, leading to simple and computationally efficient classification strategies. Recently, many linear discriminant methods have been developed in order to reduce the dimensionality of visual data and to enhance the discrimination between different groups or classes. Many existing linear embedding techniques relied on the use of local margins in order to get a good discrimination performance. However, dealing with outliers and within-class diversity has not been addressed by margin-based embedding method. In this paper, we explored the use of different margin-based linear embedding methods. More precisely, we propose to use the concepts of Median miss and Median hit for building robust margin-based criteria. Based on such margins, we seek the projection directions (linear embedding) such that the sum of local margins is maximized. Our proposed approach has been applied to the problem of appearance-based face recognition. Experiments performed on four public face databases show that the proposed approach can give better generalization performance than the classic Average Neighborhood Margin Maximization (ANMM). Moreover, thanks to the use of robust margins, the proposed method down-grades gracefully when label outliers contaminate the training data set. In particular, we show that the concept of Median hit was crucial in order to get robust performance in the presence of outliers.

Rapid differentiation of Ghana cocoa beans by FT-NIR spectroscopy coupled with multivariate classification

NASA Astrophysics Data System (ADS)

Teye, Ernest; Huang, Xingyi; Dai, Huang; Chen, Quansheng

2013-10-01

Quick, accurate and reliable technique for discrimination of cocoa beans according to geographical origin is essential for quality control and traceability management. This current study presents the application of Near Infrared Spectroscopy technique and multivariate classification for the differentiation of Ghana cocoa beans. A total of 194 cocoa bean samples from seven cocoa growing regions were used. Principal component analysis (PCA) was used to extract relevant information from the spectral data and this gave visible cluster trends. The performance of four multivariate classification methods: Linear discriminant analysis (LDA), K-nearest neighbors (KNN), Back propagation artificial neural network (BPANN) and Support vector machine (SVM) were compared. The performances of the models were optimized by cross validation. The results revealed that; SVM model was superior to all the mathematical methods with a discrimination rate of 100% in both the training and prediction set after preprocessing with Mean centering (MC). BPANN had a discrimination rate of 99.23% for the training set and 96.88% for prediction set. While LDA model had 96.15% and 90.63% for the training and prediction sets respectively. KNN model had 75.01% for the training set and 72.31% for prediction set. The non-linear classification methods used were superior to the linear ones. Generally, the results revealed that NIR Spectroscopy coupled with SVM model could be used successfully to discriminate cocoa beans according to their geographical origins for effective quality assurance.

From discrimination to internalized mental illness stigma: The mediating roles of anticipated discrimination and anticipated stigma.

PubMed

Quinn, Diane M; Williams, Michelle K; Weisz, Bradley M

2015-06-01

Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future and how anticipation of stigma in turn predicts greater stigma internalization. Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Correlational analyses indicated that more experiences of discrimination due to one's mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Experiences of discrimination over one's lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. (c) 2015 APA, all rights reserved).

Optimal design of stimulus experiments for robust discrimination of biochemical reaction networks.

PubMed

Flassig, R J; Sundmacher, K

2012-12-01

Biochemical reaction networks in the form of coupled ordinary differential equations (ODEs) provide a powerful modeling tool for understanding the dynamics of biochemical processes. During the early phase of modeling, scientists have to deal with a large pool of competing nonlinear models. At this point, discrimination experiments can be designed and conducted to obtain optimal data for selecting the most plausible model. Since biological ODE models have widely distributed parameters due to, e.g. biologic variability or experimental variations, model responses become distributed. Therefore, a robust optimal experimental design (OED) for model discrimination can be used to discriminate models based on their response probability distribution functions (PDFs). In this work, we present an optimal control-based methodology for designing optimal stimulus experiments aimed at robust model discrimination. For estimating the time-varying model response PDF, which results from the nonlinear propagation of the parameter PDF under the ODE dynamics, we suggest using the sigma-point approach. Using the model overlap (expected likelihood) as a robust discrimination criterion to measure dissimilarities between expected model response PDFs, we benchmark the proposed nonlinear design approach against linearization with respect to prediction accuracy and design quality for two nonlinear biological reaction networks. As shown, the sigma-point outperforms the linearization approach in the case of widely distributed parameter sets and/or existing multiple steady states. Since the sigma-point approach scales linearly with the number of model parameter, it can be applied to large systems for robust experimental planning. An implementation of the method in MATLAB/AMPL is available at http://www.uni-magdeburg.de/ivt/svt/person/rf/roed.html. flassig@mpi-magdeburg.mpg.de Supplementary data are are available at Bioinformatics online.

Novel methods of time-resolved fluorescence data analysis for in-vivo tissue characterization: application to atherosclerosis.

PubMed

Jo, J A; Fang, Q; Papaioannou, T; Qiao, J H; Fishbein, M C; Dorafshar, A; Reil, T; Baker, D; Freischlag, J; Marcu, L

2004-01-01

This study investigates the ability of new analytical methods of time-resolved laser-induced fluorescence spectroscopy (TR-LIFS) data to characterize tissue in-vivo, such as the composition of atherosclerotic vulnerable plaques. A total of 73 TR-LIFS measurements were taken in-vivo from the aorta of 8 rabbits, and subsequently analyzed using the Laguerre deconvolution technique. The investigated spots were classified as normal aorta, thin or thick lesions, and lesions rich in either collagen or macrophages/foam-cells. Different linear and nonlinear classification algorithms (linear discriminant analysis, stepwise linear discriminant analysis, principal component analysis, and feedforward neural networks) were developed using spectral and TR features (ratios of intensity values and Laguerre expansion coefficients, respectively). Normal intima and thin lesions were discriminated from thick lesions (sensitivity >90%, specificity 100%) using only spectral features. However, both spectral and time-resolved features were necessary to discriminate thick lesions rich in collagen from thick lesions rich in foam cells (sensitivity >85%, specificity >93%), and thin lesions rich in foam cells from normal aorta and thin lesions rich in collagen (sensitivity >85%, specificity >94%). Based on these findings, we believe that TR-LIFS information derived from the Laguerre expansion coefficients can provide a valuable additional dimension for in-vivo tissue characterization.

Detection and recognition of simple spatial forms

NASA Technical Reports Server (NTRS)

Watson, A. B.

1983-01-01

A model of human visual sensitivity to spatial patterns is constructed. The model predicts the visibility and discriminability of arbitrary two-dimensional monochrome images. The image is analyzed by a large array of linear feature sensors, which differ in spatial frequency, phase, orientation, and position in the visual field. All sensors have one octave frequency bandwidths, and increase in size linearly with eccentricity. Sensor responses are processed by an ideal Bayesian classifier, subject to uncertainty. The performance of the model is compared to that of the human observer in detecting and discriminating some simple images.

Morphometric study of third-instar larvae from five morphotypes of the Anastrepha fraterculus cryptic species complex (Diptera, Tephritidae)

PubMed Central

Canal, Nelson A.; Hernández-Ortiz, Vicente; Salas, Juan O. Tigrero; Selivon, Denise

2015-01-01

Abstract The occurrence of cryptic species among economically important fruit flies strongly affects the development of management tactics for these pests. Tools for studying cryptic species not only facilitate evolutionary and systematic studies, but they also provide support for fruit fly management and quarantine activities. Previous studies have shown that the South American fruit fly, Anastrepha fraterculus, is a complex of cryptic species, but few studies have been performed on the morphology of its immature stages. An analysis of mandible shape and linear morphometric variability was applied to third-instar larvae of five morphotypes of the Anastrepha fraterculus complex: Mexican, Andean, Ecuadorian, Peruvian and Brazilian-1. Outline geometric morphometry was used to study the mouth hook shape and linear morphometry analysis was performed using 24 linear measurements of the body, cephalopharyngeal skeleton, mouth hook and hypopharyngeal sclerite. Different morphotypes were grouped accurately using canonical discriminant analyses of both the geometric and linear morphometry. The shape of the mandible differed among the morphotypes, and the anterior spiracle length, number of tubules of the anterior spiracle, length and height of the mouth hook and length of the cephalopharyngeal skeleton were the most significant variables in the linear morphometric analysis. Third-instar larvae provide useful characters for studies of cryptic species in the Anastrepha fraterculus complex. PMID:26798253

Linear Quantitative Profiling Method Fast Monitors Alkaloids of Sophora Flavescens That Was Verified by Tri-Marker Analyses

PubMed Central

Hou, Zhifei; Sun, Guoxiang; Guo, Yong

2016-01-01

The present study demonstrated the use of the Linear Quantitative Profiling Method (LQPM) to evaluate the quality of Alkaloids of Sophora flavescens (ASF) based on chromatographic fingerprints in an accurate, economical and fast way. Both linear qualitative and quantitative similarities were calculated in order to monitor the consistency of the samples. The results indicate that the linear qualitative similarity (LQLS) is not sufficiently discriminating due to the predominant presence of three alkaloid compounds (matrine, sophoridine and oxymatrine) in the test samples; however, the linear quantitative similarity (LQTS) was shown to be able to obviously identify the samples based on the difference in the quantitative content of all the chemical components. In addition, the fingerprint analysis was also supported by the quantitative analysis of three marker compounds. The LQTS was found to be highly correlated to the contents of the marker compounds, indicating that quantitative analysis of the marker compounds may be substituted with the LQPM based on the chromatographic fingerprints for the purpose of quantifying all chemicals of a complex sample system. Furthermore, once reference fingerprint (RFP) developed from a standard preparation in an immediate detection way and the composition similarities calculated out, LQPM could employ the classical mathematical model to effectively quantify the multiple components of ASF samples without any chemical standard. PMID:27529425

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.

Discrimination and Acculturative Stress among First-Generation Dominicans

ERIC Educational Resources Information Center

Dawson, Beverly Araujo; Panchanadeswaran, Subadra

2010-01-01

The present study examined the relationship between discriminatory experiences and acculturative stress levels among a sample of 283 Dominican immigrants. Findings from a linear regression analysis revealed that experiences of daily racial discrimination and major racist events were significant predictors of acculturative stress after controlling…

Toward a Model-Based Predictive Controller Design in Brain–Computer Interfaces

PubMed Central

Kamrunnahar, M.; Dias, N. S.; Schiff, S. J.

2013-01-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain–computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8–23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications. PMID:21267657

Toward a model-based predictive controller design in brain-computer interfaces.

PubMed

Kamrunnahar, M; Dias, N S; Schiff, S J

2011-05-01

A first step in designing a robust and optimal model-based predictive controller (MPC) for brain-computer interface (BCI) applications is presented in this article. An MPC has the potential to achieve improved BCI performance compared to the performance achieved by current ad hoc, nonmodel-based filter applications. The parameters in designing the controller were extracted as model-based features from motor imagery task-related human scalp electroencephalography. Although the parameters can be generated from any model-linear or non-linear, we here adopted a simple autoregressive model that has well-established applications in BCI task discriminations. It was shown that the parameters generated for the controller design can as well be used for motor imagery task discriminations with performance (with 8-23% task discrimination errors) comparable to the discrimination performance of the commonly used features such as frequency specific band powers and the AR model parameters directly used. An optimal MPC has significant implications for high performance BCI applications.

Racial discrimination, gender discrimination, and substance abuse among Latina/os nationwide.

PubMed

Otiniano Verissimo, Angie Denisse; Gee, Gilbert C; Ford, Chandra L; Iguchi, Martin Y

2014-01-01

This study investigates the relationship between discrimination and substance abuse among Latina/os, and further examines whether this relationship differs by gender and type of discrimination. Analyses focus on the Latina/o respondents (n = 1,039 men; n = 1,273 women) from the National Latino and Asian American Study carried out from 2002-2003. Outcomes were alcohol abuse and drug abuse measured using DSM-IV definitions and criteria. Additional covariates included immigrant characteristics and demographics. Analyses were completed using gender-stratified multinomial logistic regression. Men reported more discrimination (39.6% vs. 30.3%) and had higher prevalence of alcohol abuse (16.5% vs. 4.5%) and drug abuse (9.5% vs. 2.3%) than women. Discrimination was significantly associated with increased risk of alcohol abuse for women and increased risk of drug abuse for men. Men and women also varied in the types of discrimination (e.g., racial vs. gender) reported, and in the associations between these types of discrimination and substance abuse. These data indicate that discrimination is associated with different substance abuse outcomes between genders. Future research should consider the mechanisms that explain these differences.

Age Discrimination, Social Closure and Employment

ERIC Educational Resources Information Center

Roscigno, Vincent J.; Mong, Sherry; Byron, Reginald; Tester, Griff

2007-01-01

Age discrimination in employment has received mounting attention over the past two decades, and from various cross-cutting social science disciplines. Findings from survey and experimental analyses have revealed the pervasiveness of ageist stereotypes, while aggregate and life course analyses suggest trends toward downward occupational mobility…

Spectral-Spatial Shared Linear Regression for Hyperspectral Image Classification.

PubMed

Haoliang Yuan; Yuan Yan Tang

2017-04-01

Classification of the pixels in hyperspectral image (HSI) is an important task and has been popularly applied in many practical applications. Its major challenge is the high-dimensional small-sized problem. To deal with this problem, lots of subspace learning (SL) methods are developed to reduce the dimension of the pixels while preserving the important discriminant information. Motivated by ridge linear regression (RLR) framework for SL, we propose a spectral-spatial shared linear regression method (SSSLR) for extracting the feature representation. Comparing with RLR, our proposed SSSLR has the following two advantages. First, we utilize a convex set to explore the spatial structure for computing the linear projection matrix. Second, we utilize a shared structure learning model, which is formed by original data space and a hidden feature space, to learn a more discriminant linear projection matrix for classification. To optimize our proposed method, an efficient iterative algorithm is proposed. Experimental results on two popular HSI data sets, i.e., Indian Pines and Salinas demonstrate that our proposed methods outperform many SL methods.

Healthy Aging Delays Scalp EEG Sensitivity to Noise in a Face Discrimination Task

PubMed Central

Rousselet, Guillaume A.; Gaspar, Carl M.; Pernet, Cyril R.; Husk, Jesse S.; Bennett, Patrick J.; Sekuler, Allison B.

2010-01-01

We used a single-trial ERP approach to quantify age-related changes in the time-course of noise sensitivity. A total of 62 healthy adults, aged between 19 and 98, performed a non-speeded discrimination task between two faces. Stimulus information was controlled by parametrically manipulating the phase spectrum of these faces. Behavioral 75% correct thresholds increased with age. This result may be explained by lower signal-to-noise ratios in older brains. ERP from each subject were entered into a single-trial general linear regression model to identify variations in neural activity statistically associated with changes in image structure. The fit of the model, indexed by R2, was computed at multiple post-stimulus time points. The time-course of the R2 function showed significantly delayed noise sensitivity in older observers. This age effect is reliable, as demonstrated by test–retest in 24 subjects, and started about 120 ms after stimulus onset. Our analyses suggest also a qualitative change from a young to an older pattern of brain activity at around 47 ± 4 years old. PMID:21833194

Assessment of resuspended matter and redistribution of macronutrient elements produced by boat disturbance in a eutrophic lagoon.

PubMed

Lenzi, Mauro; Finoia, Maria Grazia; Gennaro, Paola; Mercatali, Isabel; Persia, Emma; Solari, Jacopo; Porrello, Salvatore

2013-07-15

Harvesting of macroalgae by specially equipped boats in a shallow eutrophic lagoon produces evident sediment resuspension. To outline the environmental effects of this disturbance, we examined the quantity of fall-out and the distances travelled by sediment and macronutrients from the source of boat disturbance. Resuspended sediment fall-out (RSFO) was trapped at different distances from the boat path to determine total dry weight, total nitrogen (TN), total carbon (TC), total organic carbon (TOC), total sulphur (TS) and total phosphorus (TP). The data was analysed by principal components analysis (PCA) and linear discriminant analysis (LDA) on PCA factors. Fall-out of C, N, S and P from the plume of resuspended sediment indicated significant re-arrangement of these nutrients: RSFO dry weight and S content decreased with distance from the boat path, whereas TP increased and was the variable responsible for most discrimination at 100 m. The mass of resuspended matter was relatively large, indicating that the boats considerably reshuffle lagoon sediment. Copyright © 2013 Elsevier Ltd. All rights reserved.

Chemical markers of shiikuwasha juice adulterated with calamondin juice.

PubMed

Yamamoto, Kenta; Yahada, Ayumi; Sasaki, Kumi; Ogawa, Kazunori; Koga, Nobuyuki; Ohta, Hideaki

2012-11-07

Detection of shiikuwasha (Citrus depressa Hayata) juice adulterated with calamondin (Citrus madurensis Lour.) juice was investigated by the analyses of (1) phloretin dihydrochalcone glucoside, 3',5'-di-C-β-glucopyranosylphloretin (PD) detected by thin-layer chromatography and high-performance liquid chromatography (HPLC), (2) polymethoxylated flavones (PMFs), included nobiletin, tangeretin, and sinensetin, detected by HPLC, and (3) γ-terpinene peak percentage obtained by headspace solid-phase microextraction gas chromatography with cryofocusing. PD was detected in calamondin juice (25.5 mg/100 mL) but not in shiikuwasha juice. Shiikuwasha juice contained higher levels of nobiletin (48.8 mg/100 mL) than calamondin juice (2.4 mg/100 mL). Shiikuwasha juice was characterized by containing a higher percentage of γ-terpinene (12.3%) than calamondin juice (0.7%). A discrimination function obtained by a linear discriminant analysis with PMFs and a peak ratio of [nobiletin/tangeretin] and γ-terpinene detected the adulteration with accuracies of 91.7%. These three chemical markers were useful to detect shiikuwasha juice that is suspected of being adulterated with calamondin juice.

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

PubMed

Bevilacqua, Marta; Marini, Federico

2014-08-01

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

From Discrimination to Internalized Mental Illness Stigma: The Mediating Roles of Anticipated Discrimination and Anticipated Stigma

PubMed Central

Quinn, Diane M.; Williams, Michelle K.; Weisz, Bradley M.

2015-01-01

Objective Internalizing mental illness stigma is related to poorer well-being, but less is known about the factors that predict levels of internalized stigma. This study explored how experiences of discrimination relate to greater anticipation of discrimination and devaluation in the future, and how anticipation of stigma, in turn predicts greater stigma internalization. Method Participants were 105 adults with mental illness who self-reported their experiences of discrimination based on their mental illness, their anticipation of discrimination and social devaluation from others in the future, and their level of internalized stigma. Participants were approached in several locations and completed surveys on laptop computers. Results Correlational analyses indicated that more experiences of discrimination due to one’s mental illness were related to increased anticipated discrimination in the future, increased anticipated social stigma from others, and greater internalized stigma. Multiple serial mediator analyses showed that the effect of experiences of discrimination on internalized stigma was fully mediated by increased anticipated discrimination and anticipated stigma. Conclusion and Implications for Practice Experiences of discrimination over the lifetime may influence not only how much future discrimination people with mental illness are concerned with but also how much they internalize negative feelings about the self. Mental health professionals may need to address concerns with future discrimination and devaluation in order to decrease internalized stigma. PMID:25844910

Complexity-reduced implementations of complete and null-space-based linear discriminant analysis.

PubMed

Lu, Gui-Fu; Zheng, Wenming

2013-10-01

Dimensionality reduction has become an important data preprocessing step in a lot of applications. Linear discriminant analysis (LDA) is one of the most well-known dimensionality reduction methods. However, the classical LDA cannot be used directly in the small sample size (SSS) problem where the within-class scatter matrix is singular. In the past, many generalized LDA methods has been reported to address the SSS problem. Among these methods, complete linear discriminant analysis (CLDA) and null-space-based LDA (NLDA) provide good performances. The existing implementations of CLDA are computationally expensive. In this paper, we propose a new and fast implementation of CLDA. Our proposed implementation of CLDA, which is the most efficient one, is equivalent to the existing implementations of CLDA in theory. Since CLDA is an extension of null-space-based LDA (NLDA), our implementation of CLDA also provides a fast implementation of NLDA. Experiments on some real-world data sets demonstrate the effectiveness of our proposed new CLDA and NLDA algorithms. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discrimination and mental health problems among homeless minority young people.

PubMed

Milburn, Norweeta G; Batterham, Philip; Ayala, George; Rice, Eric; Solorio, Rosa; Desmond, Kate; Lord, Lynwood; Iribarren, Javier; Rotheram-Borus, Mary Jane

2010-01-01

We examined the associations among perceived discrimination, racial/ethnic identification, and emotional distress in newly homeless adolescents. We assessed a sample of newly homeless adolescents (n=254) in Los Angeles, California, with measures of perceived discrimination and racial/ethnic identification. We assessed emotional distress using the Brief Symptom Inventory and used multivariate linear regression modeling to gauge the impact of discrimination and racial identity on emotional distress. Controlling for race and immigration status, gender, and age, young people with a greater sense of ethnic identification experienced less emotional distress. Young people with a history of racial/ethnic discrimination experienced more emotional distress. Intervention programs that contextualize discrimination and enhance racial/ethnic identification and pride among homeless young people are needed.

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.

Discriminability of personality profiles in isolated and Co-morbid marijuana and nicotine users.

PubMed

Ketcherside, Ariel; Jeon-Slaughter, Haekyung; Baine, Jessica L; Filbey, Francesca M

2016-04-30

Specific personality traits have been linked with substance use disorders (SUDs), genetic mechanisms, and brain systems. Thus, determining the specificity of personality traits to types of SUD can advance the field towards defining SUD endophenotypes as well as understanding the brain systems involved for the development of novel treatments. Disentangling these factors is particularly important in highly co morbid SUDs, such as marijuana and nicotine use, so treatment can occur effectively for both. This study evaluated personality traits that distinguish isolated and co-morbid use of marijuana and nicotine. To that end, we collected the NEO Five Factor Inventory in participants who used marijuana-only (n=59), nicotine-only (n=27), both marijuana and nicotine (n=28), and in non-using controls (n=28). We used factor analyses to identify personality profiles, which are linear combinations of the five NEO Factors. We then conducted Receiver Operating Characteristics (ROC) curve analysis to test accuracy of the personality factors in discriminating isolated and co-morbid marijuana and nicotine users from each other. ROC curve analysis distinguished the four groups based on their NEO personality patterns. Results showed that NEO Factor 2 (openness, extraversion, agreeableness) discriminated marijuana and marijuana+nicotine users from controls and nicotine-only users with high predictability. Additional ANOVA results showed that the openness dimension discriminated marijuana users from nicotine users. These findings suggest that personality dimensions distinguish marijuana users from nicotine users and should be considered in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

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.

Multiple degree of freedom object recognition using optical relational graph decision nets

NASA Technical Reports Server (NTRS)

Casasent, David P.; Lee, Andrew J.

1988-01-01

Multiple-degree-of-freedom object recognition concerns objects with no stable rest position with all scale, rotation, and aspect distortions possible. It is assumed that the objects are in a fairly benign background, so that feature extractors are usable. In-plane distortion invariance is provided by use of a polar-log coordinate transform feature space, and out-of-plane distortion invariance is provided by linear discriminant function design. Relational graph decision nets are considered for multiple-degree-of-freedom pattern recognition. The design of Fisher (1936) linear discriminant functions and synthetic discriminant function for use at the nodes of binary and multidecision nets is discussed. Case studies are detailed for two-class and multiclass problems. Simulation results demonstrate the robustness of the processors to quantization of the filter coefficients and to noise.

The Association Between Perceived Discrimination and Obesity in a Population-Based Multiracial and Multiethnic Adult Sample

PubMed Central

Williams, David R.

2009-01-01

Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults. Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference. Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics. Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health. PMID:18923119

Stigma and discrimination against people living with HIV by healthcare providers, Southwest Ethiopia

PubMed Central

2012-01-01

Background Stigma and discrimination against people living with human immunodeficiency virus (HIV) are obstacles in the way of effective responses to HIV. Understanding the extent of stigma / discrimination and the underlying causes is necessary for developing strategies to reduce them. This study was conducted to explore stigma and discrimination against PLHIV amongst healthcare providers in Jimma zone, Southwest Ethiopia. Methods A cross-sectional study, employing quantitative and qualitative methods, was conducted in 18 healthcare institutions of Jimma zone, during March 14 to April 14, 2011. A total of 255 healthcare providers responded to questionnaires asking about sociodemographic characteristics, HIV knowledge, perceived institutional support and HIV-related stigma and discrimination. Factor analysis was employed to create measurement scales for stigma and factor scores were used in one way analysis of variance (ANOVA), T-tests, Pearson’s correlation and multiple linear regression analyses. Qualitative data collected using key-informant interviews and Focus Group Discussions (FGDs) were employed to triangulate with the findings from the quantitative survey. Results Mean stigma scores (as the percentages of maximum scale scores) were: 66.4 for the extra precaution scale, 52.3 for the fear of work-related HIV transmission, 49.4 for the lack of feelings of safety, 39.0 for the value-driven stigma, 37.4 for unethical treatment of PLHIV, 34.4 for discomfort around PLHIV and 31.1 for unofficial disclosure. Testing and disclosing test results without consent, designating HIV clients and unnecessary referral to other healthcare institutions and refusal to treat clients were identified. Having in-depth HIV knowledge, the perception of institutional support, attending training on stigma and discrimination, educational level of degree or higher, high HIV case loads, the presence of ART service in the healthcare facility and claiming to be non-religious were negative predictors of stigma and discrimination as measured by the seven latent factors. Conclusions Higher levels of stigma and discrimination against PLHIV were associated with lack of in-depth knowledge on HIV and orientation about policies against stigma and discrimination. Hence, we recommend health managers to ensure institutional support through availing of clear policies and guidelines and the provision of appropriate training on the management of HIV/AIDS. PMID:22794201

Accuracy and reliability in sex determination from skulls: a comparison of Fordisc® 3.0 and the discriminant function analysis.

PubMed

Guyomarc'h, Pierre; Bruzek, Jaroslav

2011-05-20

Identification in forensic anthropology and the definition of a biological profile in bioarchaeology are essential to each of those fields and use the same methodologies. Sex, age, stature and ancestry can be conclusive or dispensable, depending on the field. The Fordisc(®) 3.0 computer program was developed to aid in the identification of the sex, stature and ancestry of skeletal remains by exploiting the Forensic Data Bank (FDB) and computing discriminant function analyses (DFAs). Although widely used, this tool has been recently criticised, principally when used to determine ancestry. Two sub-samples of individuals of known sex were drawn from French (n=50) and Thai (n=91) osteological collections and used to assess the reliability of sex determination using Fordisc(®) 3.0 with 12 cranial measurements. Comparisons were made using the whole FDB as well as using select groups, taking into account the posterior and typicality probabilities. The results of Fordisc(®) 3.0 vary between 52.2% and 77.8% depending on the options and groups selected. Tests of published discriminant functions and the computation of specific DFA were performed in order to discuss the applicability of this software and, overall, to question the pertinence of the use of DFA and linear distances in sex determination, in light of the huge cranial morphological variability. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Intraoperative optical biopsy for brain tumors using spectro-lifetime properties of intrinsic fluorophores

NASA Astrophysics Data System (ADS)

Vasefi, Fartash; Kittle, David S.; Nie, Zhaojun; Falcone, Christina; Patil, Chirag G.; Chu, Ray M.; Mamelak, Adam N.; Black, Keith L.; Butte, Pramod V.

2016-04-01

We have developed and tested a system for real-time intra-operative optical identification and classification of brain tissues using time-resolved fluorescence spectroscopy (TRFS). A supervised learning algorithm using linear discriminant analysis (LDA) employing selected intrinsic fluorescence decay temporal points in 6 spectral bands was employed to maximize statistical significance difference between training groups. The linear discriminant analysis on in vivo human tissues obtained by TRFS measurements (N = 35) were validated by histopathologic analysis and neuronavigation correlation to pre-operative MRI images. These results demonstrate that TRFS can differentiate between normal cortex, white matter and glioma.

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

NASA Astrophysics Data System (ADS)

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

2012-01-01

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

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

Signal-Detection Analyses of Conditional Discrimination and Delayed Matching-to-Sample Performance

ERIC Educational Resources Information Center

Alsop, Brent

2004-01-01

Quantitative analyses of stimulus control and reinforcer control in conditional discriminations and delayed matching-to-sample procedures often encounter a problem; it is not clear how to analyze data when subjects have not made errors. The present article examines two common methods for overcoming this problem. Monte Carlo simulations of…

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

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…

Energy-discrimination x-ray computed tomography system utilizing a scanning cadmium-telluride detector

NASA Astrophysics Data System (ADS)

Sato, Eiichi; Abduraxit, Ablajan; Enomoto, Toshiyuki; Watanabe, Manabu; Hitomi, Keitaro; Takahashi, Kiyomi; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2010-04-01

An energy-discrimination K-edge x-ray computed tomography (CT) system is useful for controlling the image contrast of a target region by selecting both the photon energy and the energy width. The CT system has an oscillation-type linear cadmium telluride (CdTe) detectror. CT is performed by repeated linear scans and rotations of an object. Penetrating x-ray photons from the object are detected by a CdTe detector, and event signals of x-ray photons are produced using charge-sensitive and shaping amplifiers. Both photon energy and energy width are selected out using a multichannel analyzer, and the number of photons is counted by a counter card. In energy-discrimination CT, the tube voltage and tube current were 80 kV and 20 μA, respectively, and the x-ray intensity was 1.92 μGy/s at a distance of 1.0 m from the source and a tube voltage of 80 kV. The energy-discrimination CT was carried out by selecting x-ray photon energies.

DISCRIMINATION OF ALTERED BASALTIC ROCKS IN THE SOUTHWESTERN UNITED STATES BY ANALYSIS OF LANDSAT THEMATIC MAPPER DATA.

USGS Publications Warehouse

Davis, Philip A.; Berlin, Graydon L.; Chavez, Pat S.

1987-01-01

Landsat Thematic Mapper image data were analyzed to determine their ability to discriminate red cone basalts from gray flow basalts and sedimentary country rocks for three volcanic fields in the southwestern United States. Analyses of all of the possible three-band combinations of the six nonthermal bands indicate that the combination of bands 1, 4, and 5 best discriminates among these materials. The color-composite image of these three bands unambiguously discriminates 89 percent of the mapped red volcanic cones in the three volcanic fields. Mineralogic and chemical analyses of collected samples indicate that discrimination is facilitated by the presence of hematite as a major mineral phase in the red cone basalts (hematite is only a minor mineral phase in the gray flow basalts and red sedimentary rocks).

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

PubMed

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

2006-01-01

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

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

PubMed

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

2016-01-01

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

Multielement geochemistry identifies the spatial pattern of soil and sediment contamination in an urban parkland, Western Australia.

PubMed

Rate, Andrew W

2018-06-15

Urban environments are dynamic and highly heterogeneous, and multiple additions of potential contaminants are likely on timescales which are short relative to natural processes. The likely sources and location of soil or sediment contamination in urban environment should therefore be detectable using multielement geochemical composition combined with rigorously applied multivariate statistical techniques. Soil, wetland sediment, and street dust was sampled along intersecting transects in Robertson Park in metropolitan Perth, Western Australia. Samples were analysed for near-total concentrations of multiple elements (including Cd, Ce, Co, Cr, Cu, Fe, Gd, La, Mn, Nd, Ni, Pb, Y, and Zn), as well as pH, and electrical conductivity. Samples at some locations within Robertson Park had high concentrations of potentially toxic elements (Pb above Health Investigation Limits; As, Ba, Cu, Mn, Ni, Pb, V, and Zn above Ecological Investigation Limits). However, these concentrations carry low risk due to the main land use as recreational open space, the low proportion of samples exceeding guideline values, and a tendency for the highest concentrations to be located within the less accessible wetland basin. The different spatial distributions of different groups of contaminants was consistent with different inputs of contaminants related to changes in land use and technology over the history of the site. Multivariate statistical analyses reinforced the spatial information, with principal component analysis identifying geochemical associations of elements which were also spatially related. A multivariate linear discriminant model was able to discriminate samples into a-priori types, and could predict sample type with 84% accuracy based on multielement composition. The findings suggest substantial advantages of characterising a site using multielement and multivariate analyses, an approach which could benefit investigations of other sites of concern. Copyright © 2018 Elsevier B.V. All rights reserved.

The INTERPRET Decision-Support System version 3.0 for evaluation of Magnetic Resonance Spectroscopy data from human brain tumours and other abnormal brain masses

PubMed Central

2010-01-01

Background Proton Magnetic Resonance (MR) Spectroscopy (MRS) is a widely available technique for those clinical centres equipped with MR scanners. Unlike the rest of MR-based techniques, MRS yields not images but spectra of metabolites in the tissues. In pathological situations, the MRS profile changes and this has been particularly described for brain tumours. However, radiologists are frequently not familiar to the interpretation of MRS data and for this reason, the usefulness of decision-support systems (DSS) in MRS data analysis has been explored. Results This work presents the INTERPRET DSS version 3.0, analysing the improvements made from its first release in 2002. Version 3.0 is aimed to be a program that 1st, can be easily used with any new case from any MR scanner manufacturer and 2nd, improves the initial analysis capabilities of the first version. The main improvements are an embedded database, user accounts, more diagnostic discrimination capabilities and the possibility to analyse data acquired under additional data acquisition conditions. Other improvements include a customisable graphical user interface (GUI). Most diagnostic problems included have been addressed through a pattern-recognition based approach, in which classifiers based on linear discriminant analysis (LDA) were trained and tested. Conclusions The INTERPRET DSS 3.0 allows radiologists, medical physicists, biochemists or, generally speaking, any person with a minimum knowledge of what an MR spectrum is, to enter their own SV raw data, acquired at 1.5 T, and to analyse them. The system is expected to help in the categorisation of MR Spectra from abnormal brain masses. PMID:21114820

The link between discrimination and telomere length in African American adults.

PubMed

Lee, Daniel B; Kim, Eric S; Neblett, Enrique W

2017-05-01

Prior work shows that discrimination is associated with a wide array of negative health outcomes. However, the biological mechanisms through which this link occurs require more study. We evaluated the association between discrimination and leukocyte telomere length (LTL; a biological marker of systemic aging). Cross-sectional data were from the Health and Retirement study, a study of people aged 51+ in the United States, and included 595 African American males and females. Multiple regression analyses were used to evaluate whether discrimination was independently associated with LTL. We also considered the role of potential confounders including sociodemographic factors, health factors, depressive symptoms, and stress. High discrimination was associated with shorter LTL after controlling for sociodemographic factors (b = -.034, SE = 0.14, p = .017). This association persisted in analyses that further adjusted for health factors, depressive symptoms, and stress. Results suggest that discrimination experiences accelerate biological aging in older African American males and females, alike. This finding helps advance our understanding of how discrimination generates greater disease vulnerability and premature death in African Americans. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Impostor feelings as a moderator and mediator of the relationship between perceived discrimination and mental health among racial/ethnic minority college students.

PubMed

Cokley, Kevin; Smith, Leann; Bernard, Donte; Hurst, Ashley; Jackson, Stacey; Stone, Steven; Awosogba, Olufunke; Saucer, Chastity; Bailey, Marlon; Roberts, Davia

2017-03-01

This study investigated whether impostor feelings would both moderate and mediate the relationship between perceived discrimination and mental health in a sample of diverse ethnic minority college students (106 African Americans, 102 Asian Americans, 108 Latino/a Americans) at an urban public university. African American students reported higher perceived discrimination than Asian American and Latino/a American students, while no racial/ethnic group differences were reported for impostor feelings. Analyses revealed that among African American students, high levels of impostor feelings moderated the perceived discrimination and depression relationship and mediated the perceived discrimination and anxiety relationship. Among Asian American students, impostor feelings mediated the relationship between perceived discrimination and both depression and anxiety. Among Latino/a American students low levels of impostor feelings moderated the relationship between perceived discrimination and both depression and anxiety, and partially mediated the relationship between perceived discrimination and anxiety. Multigroup path analyses revealed a significantly stronger impact of impostor feelings on depression among African American students and a stronger impact of perceived discrimination on impostor feelings among African American and Latino/a American students. Clinical implications and future research directions are discussed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Classification of electroencephalograph signals using time-frequency decomposition and linear discriminant analysis

NASA Astrophysics Data System (ADS)

Szuflitowska, B.; Orlowski, P.

2017-08-01

Automated detection system consists of two key steps: extraction of features from EEG signals and classification for detection of pathology activity. The EEG sequences were analyzed using Short-Time Fourier Transform and the classification was performed using Linear Discriminant Analysis. The accuracy of the technique was tested on three sets of EEG signals: epilepsy, healthy and Alzheimer's Disease. The classification error below 10% has been considered a success. The higher accuracy are obtained for new data of unknown classes than testing data. The methodology can be helpful in differentiation epilepsy seizure and disturbances in the EEG signal in Alzheimer's Disease.

Fast Depiction Invariant Visual Similarity for Content Based Image Retrieval Based on Data-driven Visual Similarity using Linear Discriminant Analysis

NASA Astrophysics Data System (ADS)

Wihardi, Y.; Setiawan, W.; Nugraha, E.

2018-01-01

On this research we try to build CBIRS based on Learning Distance/Similarity Function using Linear Discriminant Analysis (LDA) and Histogram of Oriented Gradient (HoG) feature. Our method is invariant to depiction of image, such as similarity of image to image, sketch to image, and painting to image. LDA can decrease execution time compared to state of the art method, but it still needs an improvement in term of accuracy. Inaccuracy in our experiment happen because we did not perform sliding windows search and because of low number of negative samples as natural-world images.

Comparing Linear Discriminant Function with Logistic Regression for the Two-Group Classification Problem.

ERIC Educational Resources Information Center

Fan, Xitao; Wang, Lin

The Monte Carlo study compared the performance of predictive discriminant analysis (PDA) and that of logistic regression (LR) for the two-group classification problem. Prior probabilities were used for classification, but the cost of misclassification was assumed to be equal. The study used a fully crossed three-factor experimental design (with…

Joint recognition and discrimination in nonlinear feature space

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1997-09-01

A new general method for linear and nonlinear feature extraction is presented. It is novel since it provides both representation and discrimination while most other methods are concerned with only one of these issues. We call this approach the maximum representation and discrimination feature (MRDF) method and show that the Bayes classifier and the Karhunen- Loeve transform are special cases of it. We refer to our nonlinear feature extraction technique as nonlinear eigen- feature extraction. It is new since it has a closed-form solution and produces nonlinear decision surfaces with higher rank than do iterative methods. Results on synthetic databases are shown and compared with results from standard Fukunaga- Koontz transform and Fisher discriminant function methods. The method is also applied to an automated product inspection problem (discrimination) and to the classification and pose estimation of two similar objects (representation and discrimination).

Everyday Discrimination, Diabetes-Related Distress, and Depressive Symptoms Among African Americans and Latinos with Diabetes

PubMed Central

Valerio, Melissa A.; Kieffer, Edith; Sinco, Brandy; Rosland, Ann-Marie; Hawkins, Jaclynn; Espitia, Nicolaus; Palmisano, Gloria; Spencer, Michael

2013-01-01

It is not known how discrimination might affect diabetes-related distress (DRD), an important correlate of diabetes outcomes. We examined correlates of discrimination and the influence of discrimination on DRD and depressive symptoms (DS) for African Americans and Latinos with type 2 diabetes. We analyzed survey data (n = 157) collected at enrollment into a diabetes management intervention. Using multiple linear regression, we examined correlates of discrimination and the association between discrimination and DRD and DS. Discrimination was significantly associated with higher DRD for Latinos (b 1.58, 95 % CI 1.08, 2.31, p < 0.05), but not significant for African Americans (b 0.96, 95 % CI 0.59, 1.57). Discrimination was marginally significantly associated with more DS for Latinos (b 1.43, 95 % CI 0.97, 2.12, p < 0.10), but not significant for African Americans (b 1.21, 95 % CI 0.87, 1.70). These findings suggest the need to address stressors unique to racial/ethnic minorities to improve diabetes-related outcomes. PMID:23689972

AGSuite: Software to conduct feature analysis of artificial grammar learning performance.

PubMed

Cook, Matthew T; Chubala, Chrissy M; Jamieson, Randall K

2017-10-01

To simplify the problem of studying how people learn natural language, researchers use the artificial grammar learning (AGL) task. In this task, participants study letter strings constructed according to the rules of an artificial grammar and subsequently attempt to discriminate grammatical from ungrammatical test strings. Although the data from these experiments are usually analyzed by comparing the mean discrimination performance between experimental conditions, this practice discards information about the individual items and participants that could otherwise help uncover the particular features of strings associated with grammaticality judgments. However, feature analysis is tedious to compute, often complicated, and ill-defined in the literature. Moreover, the data violate the assumption of independence underlying standard linear regression models, leading to Type I error inflation. To solve these problems, we present AGSuite, a free Shiny application for researchers studying AGL. The suite's intuitive Web-based user interface allows researchers to generate strings from a database of published grammars, compute feature measures (e.g., Levenshtein distance) for each letter string, and conduct a feature analysis on the strings using linear mixed effects (LME) analyses. The LME analysis solves the inflation of Type I errors that afflicts more common methods of repeated measures regression analysis. Finally, the software can generate a number of graphical representations of the data to support an accurate interpretation of results. We hope the ease and availability of these tools will encourage researchers to take full advantage of item-level variance in their datasets in the study of AGL. We moreover discuss the broader applicability of the tools for researchers looking to conduct feature analysis in any field.

Assessing size and strength of the clavicle for its usefulness for sex estimation in a British medieval sample.

PubMed

Atterton, Thomas; De Groote, Isabelle; Eliopoulos, Constantine

2016-10-01

The construction of the biological profile from human skeletal remains is the foundation of anthropological examination. However, remains may be fragmentary and the elements usually employed, such as the pelvis and skull, are not available. The clavicle has been successfully used for sex estimation in samples from Iran and Greece. In the present study, the aim was to test the suitability of the measurements used in those previous studies on a British Medieval population. In addition, the project tested whether discrimination between sexes was due to size or clavicular strength. The sample consisted of 23 females and 25 males of pre-determined sex from two medieval collections: Poulton and Gloucester. Six measurements were taken using an osteometric board, sliding calipers and graduated tape. In addition, putty rings and bi-planar radiographs were made and robusticity measures calculated. The resulting variables were used in stepwise discriminant analyses. The linear measurements allowed correct sex classification in 89.6% of all individuals. This demonstrates the applicability of the clavicle for sex estimation in British populations. The most powerful discriminant factor was maximum clavicular length and the best combination of factors was maximum clavicular length and circumference. This result is similar to that obtained by other studies. To further investigate the extent of sexual dimorphism of the clavicle, the biomechanical properties of the polar second moment of area J and the ratio of maximum to minimum bending rigidity are included in the analysis. These were found to have little influence when entered into the discriminant function analysis. Copyright © 2016 Elsevier GmbH. All rights reserved.

Discrimination of side-window glass of Korean autos by laser ablation inductively coupled plasma mass spectrometry.

PubMed

Lee, Sin-Woo; Ryu, Jong-Sik; Min, Ji-Sook; Choi, Man-Yong; Lee, Kwang-Sik; Shin, Woo-Jin

2016-07-15

Fragments of glass from cars are often found at crime scenes and can be crucial evidence for solving the crime. The glass fragments are important as trace evidence at crime scenes related to car accidents and burgled homes. By identifying the origin of glass fragments, it is possible to infer the identity of a suspect. Our results represent a promising approach to a thorough forensic investigation of car glass. Thirty-five samples from the side windows of cars produced and used in South Korea were collected from the official agencies of five car manufacturers and from two glassmakers. In addition, 120 samples from side mirrors were collected from the same suppliers as well as from small businesses. Their chemical compositions (including Pb isotopes) were analyzed using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) and linear discriminant analysis (LDA) was performed. The percentages of major elements (Si, Ca, and Fe) in side-window glass varied within narrow ranges (30.0 ± 2.36%, 5.93 ± 0.52%, and 0.33 ± 0.05%, respectively), while the differences among Pb isotope ratios were not significant. In contrast, light rare earth elements (LREEs) were different from each glassmaker. From the LDA, the types of side-window glass were successfully discriminated according to car manufacturer, glassmaker, and even glass thickness. However, glass from side mirrors cannot be used for good forensic identifiers. Discrimination techniques for side-window glass, although not for side mirrors, using chemical compositions combined with multivariate statistical analyses provide evidence for forensic investigations. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Pattern classification approach to characterizing solitary pulmonary nodules imaged on high-resolution computed tomography

NASA Astrophysics Data System (ADS)

McNitt-Gray, Michael F.; Hart, Eric M.; Goldin, Jonathan G.; Yao, Chih-Wei; Aberle, Denise R.

1996-04-01

The purpose of our study was to characterize solitary pulmonary nodules (SPN) as benign or malignant based on pattern classification techniques using size, shape, density and texture features extracted from HRCT images. HRCT images of patients with a SPN are acquired, routed through a PACS and displayed on a thoracic radiology workstation. Using the original data, the SPN is semiautomatically contoured using a nodule/background threshold. The contour is used to calculate size and several shape parameters, including compactness and bending energy. Pixels within the interior of the contour are used to calculate several features including: (1) nodule density-related features, such as representative Hounsfield number and moment of inertia, and (2) texture measures based on the spatial gray level dependence matrix and fractal dimension. The true diagnosis of the SPN is established by histology from biopsy or, in the case of some benign nodules, extended follow-up. Multi-dimensional analyses of the features are then performed to determine which features can discriminate between benign and malignant nodules. When a sufficient number of cases are obtained two pattern classifiers, a linear discriminator and a neural network, are trained and tested using a select subset of features. Preliminary data from nine (9) nodule cases have been obtained and several features extracted. While the representative CT number is a reasonably good indicator, it is an inconclusive predictor of SPN diagnosis when considered by itself. Separation between benign and malignant nodules improves when other features, such as the distribution of density as measured by moment of inertia, are included in the analysis. Software has been developed and preliminary results have been obtained which show that individual features may not be sufficient to discriminate between benign and malignant nodules. However, combinations of these features may be able to discriminate between these two classes. With additional cases and more features, we will be able to perform a feature selection procedure and ultimately to train and test pattern classifiers in this discrimination task.

Random forests, a novel approach for discrimination of fish populations using parasites as biological tags.

PubMed

Perdiguero-Alonso, Diana; Montero, Francisco E; Kostadinova, Aneta; Raga, Juan Antonio; Barrett, John

2008-10-01

Due to the complexity of host-parasite relationships, discrimination between fish populations using parasites as biological tags is difficult. This study introduces, to our knowledge for the first time, random forests (RF) as a new modelling technique in the application of parasite community data as biological markers for population assignment of fish. This novel approach is applied to a dataset with a complex structure comprising 763 parasite infracommunities in population samples of Atlantic cod, Gadus morhua, from the spawning/feeding areas in five regions in the North East Atlantic (Baltic, Celtic, Irish and North seas and Icelandic waters). The learning behaviour of RF is evaluated in comparison with two other algorithms applied to class assignment problems, the linear discriminant function analysis (LDA) and artificial neural networks (ANN). The three algorithms are used to develop predictive models applying three cross-validation procedures in a series of experiments (252 models in total). The comparative approach to RF, LDA and ANN algorithms applied to the same datasets demonstrates the competitive potential of RF for developing predictive models since RF exhibited better accuracy of prediction and outperformed LDA and ANN in the assignment of fish to their regions of sampling using parasite community data. The comparative analyses and the validation experiment with a 'blind' sample confirmed that RF models performed more effectively with a large and diverse training set and a large number of variables. The discrimination results obtained for a migratory fish species with largely overlapping parasite communities reflects the high potential of RF for developing predictive models using data that are both complex and noisy, and indicates that it is a promising tool for parasite tag studies. Our results suggest that parasite community data can be used successfully to discriminate individual cod from the five different regions of the North East Atlantic studied using RF.

Genetic variation in growth, carbon isotope discrimination, and foliar N concentration in Picea mariana: analyses from a half-diallel mating design using field-grown trees

Treesearch

Kurt H. Johnsen; Lawrence B. Flanagan; Dudley A. Huber; John E. Major

1999-01-01

The authors performed genetic analyses of growth, carbon isotope discrimination (?13C), and foliar N concentration using a half-diallel subset of a 7 × 7 complete diallel planted on three sites ranging in water availability. Trees were 22 years old. Heritabilities; general and...

Adult Discrimination against Children: The Case of Abstinence-Only Education in Twenty-First-Century USA

ERIC Educational Resources Information Center

Greslé-Favier, Claire

2013-01-01

This paper analyses abstinence-only education programmes and discourses within the frame of theories of adult discrimination against children. To begin with, a definition of abstinence-only programmes and of the political context in which they were created will be provided. These programmes will then be analysed through the lens of children's…

[Approach to the Development of Mind and Persona].

PubMed

Sawaguchi, Toshiko

2018-01-01

To access medical specialists by health specialists working in the regional health field, the possibility of utilizing the voice approach for dissociative identity disorder (DID) patients as a health assessment for medical access (HAMA) was investigated. The first step is to investigate whether the plural personae in a single DID patient can be discriminated by voice analysis. Voices of DID patients including these with different personae were extracted from YouTube and were analysed using the software PRAAT with basic frequency, oral factors, chin factors and tongue factors. In addition, RAKUGO story teller voices made artificially and dramatically were analysed in the same manner. Quantitive and qualitative analysis method were carried out and nested logistic regression and a nested generalized linear model was developed. The voice from different personae in one DID patient could be visually and easily distinquished using basic frequency curve, cluster analysis and factor analysis. In the canonical analysis, only Roy's maximum root was <0.01. In the nested generalized linear model, the model using a standard deviation (SD) indicator fit best and some other possibilities are shown here. In DID patients, the short transition time among plural personae could guide to the risky situation such as suicide. So if the voice approach can show the time threshold of changes between the different personae, it would be useful as an Access Assessment in the form of a simple HAMA.

Linear data mining the Wichita clinical matrix suggests sleep and allostatic load involvement in chronic fatigue syndrome.

PubMed

Gurbaxani, Brian M; Jones, James F; Goertzel, Benjamin N; Maloney, Elizabeth M

2006-04-01

To provide a mathematical introduction to the Wichita (KS, USA) clinical dataset, which is all of the nongenetic data (no microarray or single nucleotide polymorphism data) from the 2-day clinical evaluation, and show the preliminary findings and limitations, of popular, matrix algebra-based data mining techniques. An initial matrix of 440 variables by 227 human subjects was reduced to 183 variables by 164 subjects. Variables were excluded that strongly correlated with chronic fatigue syndrome (CFS) case classification by design (for example, the multidimensional fatigue inventory [MFI] data), that were otherwise self reporting in nature and also tended to correlate strongly with CFS classification, or were sparse or nonvarying between case and control. Subjects were excluded if they did not clearly fall into well-defined CFS classifications, had comorbid depression with melancholic features, or other medical or psychiatric exclusions. The popular data mining techniques, principle components analysis (PCA) and linear discriminant analysis (LDA), were used to determine how well the data separated into groups. Two different feature selection methods helped identify the most discriminating parameters. Although purely biological features (variables) were found to separate CFS cases from controls, including many allostatic load and sleep-related variables, most parameters were not statistically significant individually. However, biological correlates of CFS, such as heart rate and heart rate variability, require further investigation. Feature selection of a limited number of variables from the purely biological dataset produced better separation between groups than a PCA of the entire dataset. Feature selection highlighted the importance of many of the allostatic load variables studied in more detail by Maloney and colleagues in this issue [1] , as well as some sleep-related variables. Nonetheless, matrix linear algebra-based data mining approaches appeared to be of limited utility when compared with more sophisticated nonlinear analyses on richer data types, such as those found in Maloney and colleagues [1] and Goertzel and colleagues [2] in this issue.

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis.

PubMed

Nguyen-Kim, Thi Dan Linh; Maurer, Britta; Suliman, Yossra A; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-04-01

To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051-0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients.

Ecomorphological analysis of the astragalo-calcaneal complex in rodents and inferences of locomotor behaviours in extinct rodent species

PubMed Central

Hautier, Lionel; Marivaux, Laurent; Vianey-Liaud, Monique

2016-01-01

Studies linking postcranial morphology with locomotion in mammals are common. However, such studies are mostly restricted to caviomorphs in rodents. We present here data from various families, belonging to the three main groups of rodents (Sciuroidea, Myodonta, and Ctenohystrica). The aim of this study is to define morphological indicators for the astragalus and calcaneus, which allow for inferences to be made about the locomotor behaviours in rodents. Several specimens were dissected and described to bridge the myology of the leg with the morphology of the bones of interest. Osteological characters were described, compared, mechanically interpreted, and correlated with a “functional sequence” comprising six categories linked to the lifestyle and locomotion (jumping, cursorial, generalist, fossorial, climber and semi-aquatic). Some character states are typical of some of these categories, especially arboreal climbers, fossorial and “cursorial-jumping” taxa. Such reliable characters might be used to infer locomotor behaviours in extinct species. Linear discriminant analyses (LDAs) were used on a wider sample of species and show that astragalar and calcaneal characters can be used to discriminate the categories among extant species whereas a posteriori inferences on extinct species should be examined with caution. PMID:27761303

Discrimination against HIV-Infected People and the Spread of HIV: Some Evidence from France

PubMed Central

Peretti-Watel, Patrick; Spire, Bruno; Obadia, Yolande; Moatti, Jean-Paul

2007-01-01

Background Many people living with HIV/AIDS (PLWHA) suffer from stigma and discrimination. There is an ongoing debate, however, about whether stigma, fear and discrimination actually fuel the persisting spread of HIV, or slow it down by reducing contacts between the whole population and high-risk minorities. To contribute to this debate, we analysed the relationship between perceived discrimination and unsafe sex in a large sample of French PLWHAs. Methodology/Principal Findings In 2003, we conducted a national cross-sectional survey among a random sample of HIV-infected patients. The analysis was restricted to sexually active respondents (N = 2,136). Unsafe sex was defined as sexual intercourse without a condom with a seronegative/unknown serostatus partner during the prior 12 months. Separate analyses were performed for each transmission group (injecting drug use (IDU), homosexual contact, heterosexual contact). Overall, 24% of respondents reported experiences of discrimination in their close social environment (relatives, friends and colleagues) and 18% reported unsafe sex during the previous 12 months. Both prevalences were higher in the IDU group (32% for perceived discrimination, 23% for unsafe sex). In multivariate analyses, experience of discrimination in the close social environment was associated with an increase in unsafe sex for both PLWHAs infected through IDU and heterosexual contact (OR = 1.65 and 1.80 respectively). Conclusions Our study clearly confirms a relationship between discrimination and unsafe sex among PLWHAs infected through either IDU or heterosexual contact. This relationship was especially strong in the heterosexual group that has become the main vector of HIV transmission in France, and who is the more likely of sexual mixing with the general population. These results seriously question the hypothesis that HIV-stigma has no effect or could even reduce the infection spread of HIV. PMID:17476333

Discrimination and Depressive Symptoms Among Latina/o Adolescents of Immigrant Parents.

PubMed

Lopez, William D; LeBrón, Alana M W; Graham, Louis F; Grogan-Kaylor, Andrew

2016-01-01

Discrimination is associated with negative mental health outcomes for Latina/o adolescents. While Latino/a adolescents experience discrimination from a number of sources and across contexts, little research considers how the source of discrimination and the context in which it occurs affect mental health outcomes among Latina/o children of immigrants. We examined the association between source-specific discrimination, racial or ethnic background of the source, and school ethnic context with depressive symptoms for Latina/o adolescents of immigrant parents. Using multilevel linear regression with time-varying covariates, we regressed depressive symptoms on source-specific discrimination, racial or ethnic background of the source of discrimination, and school percent Latina/o. Discrimination from teachers (β = 0.06, p < .05), students (β = 0.05, p < .05), Cubans (β = 0.19, p < .001), and Latinas/os (β = 0.19, p < .001) were positively associated with depressive symptoms. These associations were not moderated by school percent Latina/o. The findings indicate a need to reduce discrimination to improve Latina/o adolescents' mental health. © The Author(s) 2016.

Normative data and discriminant validity of Rey's Verbal Learning Test for the Greek adult population.

PubMed

Messinis, Lambros; Tsakona, Ioanna; Malefaki, Sonia; Papathanasopoulos, Panagiotis

2007-08-01

The present study sought to establish normative and discriminant validity data for Rey's Auditory Verbal Learning Test [Rey, A. (1964). L 'examen clinique en psychologie [Clinical tests in psychology]. Paris: Presses Universitaires de France; Schmidt, M. (1996). Rey auditory verbal learning test: A handbook. Los Angeles, CA: Western Psychological Services] using newly adapted learning lists for the Greek adult population. Applying the procedure suggested by Geffen et al. [Geffen, G., Moar, K. J., O'Hanlon, A. P., Clark, C. R., & Geffen, L. N. (1990). Performance measures of 16-86-year-old males and females on the auditory verbal learning test. The Clinical Neuropsychologist, 4, 45-63] we administered the test to 205 healthy participants, aged 18-78 years and two adult patient groups (long-term cannabis users and HIV symptomatic patients). Stepwise linear regression analyses showed that the variables age, education and gender contributed significantly to most trials of the RAVLT. Performance decreased in an age-dependent manner from young adulthood. Women, young adults and higher educated participants outperformed men, older adults and less educated individuals. The test appears to discriminate adequately between the performance of long-term heavy cannabis users and HIV seropositive symptomatic patients and matched healthy controls, as both patient groups performed more poorly than their respective control group. Normative data stratified by age, gender and education for the Greek adult population is presented for use in research and clinical settings.

Inverse associations between perceived racism and coronary artery calcification.

PubMed

Everage, Nicholas J; Gjelsvik, Annie; McGarvey, Stephen T; Linkletter, Crystal D; Loucks, Eric B

2012-03-01

To evaluate whether racial discrimination is associated with coronary artery calcification (CAC) in African-American participants of the Coronary Artery Risk Development in Young Adults (CARDIA) study. The study included American Black men (n = 571) and women (n = 791) aged 33 to 45 years in the CARDIA study. Perceived racial discrimination was assessed based on the Experiences of Discrimination scale (range, 1-35). CAC was evaluated using computed tomography. Primary analyses assessed associations between perceived racial discrimination and presence of CAC using multivariable-adjusted logistic regression analysis, adjusted for age, gender, socioeconomic position (SEP), psychosocial variables, and coronary heart disease (CHD) risk factors. In age- and gender-adjusted logistic regression models, odds of CAC decreased as the perceived racial discrimination score increased (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.90-0.98 per 1-unit increase in Experiences of Discrimination scale). The relationship did not markedly change after further adjustment for SEP, psychosocial variables, or CHD risk factors (OR, 0.93; 95% CI, 0.87-0.99). Perceived racial discrimination was negatively associated with CAC in this study. Estimation of more forms of racial discrimination as well as replication of analyses in other samples will help to confirm or refute these findings. Copyright © 2012 Elsevier Inc. All rights reserved.

Racial Discrimination and Racial Socialization as Predictors of African American Adolescents’ Racial Identity Development using Latent Transition Analysis

PubMed Central

Seaton, Eleanor K.; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M.

2013-01-01

The current study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over three years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing or remaining constant. Racial socialization and perceptions of racial discrimination were examined as covariates to assess the association with changes in racial identity status. The results indicated that perceptions of racial discrimination were not linked to any changes in racial identity. Youth who reported higher levels of racial socialization were less likely to be in Diffuse or Foreclosed compared to the Achieved group. PMID:21875184

Evaluation of volatile aldehydes as discriminating parameters in quality vinegars with protected European geographical indication.

PubMed

Durán-Guerrero, Enrique; Chinnici, Fabio; Natali, Nadia; Riponi, Claudio

2015-09-01

Thirty-six high-quality vinegars with geographical indication belonging to Sherry and Modena areas (vinegars of Jerez, balsamic vinegars of Modena and traditional balsamic vinegars of Modena) with all possible aging periods were analyzed to determine the content of volatile aldehydes. A solid-phase extraction method with in-cartridge derivatization using O-(2,3,4,5,6-pentafluorobenzyl)hydroxylamine followed by gas chromatography-mass spectrometry was employed. Twenty-two volatile aldehydes were identified and determined in the samples. Analysis of variance provided significant differences among the samples as a function of the type of vinegar, aging time and raw material. Principal component analysis and linear discriminant analysis demonstrated the possibility of discriminating the samples in terms of aging time and raw material. Linear aldehydes and compounds such as furfural, methional, nonenal, hexenal, 2-methylbutanal and i-butyraldehyde were the most significant variables able to discriminate the samples. Aldehyde content of premium quality vinegars is a function of both ageing time and raw material. Their evaluation could be a useful tool with a view to ascertaining vinegar origin and genuineness. © 2014 Society of Chemical Industry.

Community-based comprehensive intervention for people with schizophrenia in Guangzhou, China: Effects on clinical symptoms, social functioning, internalized stigma and discrimination.

PubMed

Li, Jie; Huang, Yuan-Guang; Ran, Mao-Sheng; Fan, Yu; Chen, Wen; Evans-Lacko, Sara; Thornicroft, Graham

2018-04-01

Comprehensive interventions including components of stigma and discrimination reduction in schizophrenia in low- and middle-income countries (LMICs) are lacking. We developed a community-based comprehensive intervention to evaluate its effects on clinical symptoms, social functioning, internalized stigma and discrimination among patients with schizophrenia. A randomized controlled trial including an intervention group (n = 169) and a control group (n = 158) was performed. The intervention group received comprehensive intervention (strategies against stigma and discrimination, psycho-education, social skills training and cognitive behavioral therapy) and the control group received face to face interview. Both lasted for nine months. Participants were measured at baseline, 6 months and 9 months using the Internalized Stigma of Mental Illness scale (ISMI), Discrimination and Stigma Scale (DISC-12), Global Assessment of Functioning (GAF), Schizophrenia Quality of Life Scale (SQLS), Self-Esteem Scale (SES), Brief Psychiatric Rating Scale (BPRS) and PANSS negative scale (PANSS-N). Insight and medication compliance were evaluated by senior psychiatrists. Data were analyzed by descriptive statistics, t-test, chi-square test or Fisher's exact test. Linear Mixed Models were used to show intervention effectiveness on scales. General Linear Mixed Models with multinomial logistic link function were used to assess the effectiveness on medication compliance and insight. We found a significant reduction on anticipated discrimination, BPRS and PANSS-N total scores, and an elevation on overcoming stigma and GAF in the intervention group after 9 months. These suggested the intervention may be effective in reducing anticipated discrimination, increasing skills overcoming stigma as well as improving clinical symptoms and social functioning in Chinese patients with schizophrenia. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.

The effect of perceived discrimination on the health of immigrant workers in Spain

PubMed Central

2011-01-01

Background Discrimination is an important determinant of health inequalities, and immigrants may be more vulnerable to certain types of discrimination than the native-born. This study analyses the relationship between immigrants' perceived discrimination and various self-reported health indicators. Methods A cross-sectional survey was conducted (2008) amongst a non-random sample of 2434 immigrants from Ecuador, Morocco, Romania and Colombia in four Spanish cities: Barcelona, Huelva, Madrid and Valencia. A factorial analysis of variables revealed three dimensions of perceived discrimination (due to immigrant status, due to physical appearance, and workplace-related). The association of these dimensions with self-rated health, mental health (GHQ-12), change in self-rated health between origin and host country, and other self-reported health outcomes was analysed. Logistic regression was used adjusting for potential confounders (aOR-95%CI). Subjects with worsening self-reported health status potentially attributable to perceived discrimination was estimated (population attributable proportion, PAP %). Results 73.3% of men and 69.3% of women immigrants reported discrimination due to immigrant status. Moroccans showed the highest prevalence of perceived discrimination. Immigrants reporting discrimination were at significantly higher risk of reporting health problems than those not reporting discrimination. Workplace-related discrimination was associated with poor mental health (aOR 2.97 95%CI 2.45-3.60), and the worsening of self-rated health (aOR 2.20 95%CI 1.73- 2.80). 40% (95% CI 24-53) PAP of those reporting worse self-rated health could be attributable to discrimination due to immigrant status. Conclusions Discrimination may constitute a risk factor for health in immigrant workers in Spain and could explain some health inequalities among immigrant populations in Spanish society. PMID:21849020

The effect of perceived discrimination on the health of immigrant workers in Spain.

PubMed

Agudelo-Suárez, Andrés A; Ronda-Pérez, Elena; Gil-González, Diana; Vives-Cases, Carmen; García, Ana M; Ruiz-Frutos, Carlos; Felt, Emily; Benavides, Fernando G

2011-08-17

Discrimination is an important determinant of health inequalities, and immigrants may be more vulnerable to certain types of discrimination than the native-born. This study analyses the relationship between immigrants' perceived discrimination and various self-reported health indicators. A cross-sectional survey was conducted (2008) amongst a non-random sample of 2434 immigrants from Ecuador, Morocco, Romania and Colombia in four Spanish cities: Barcelona, Huelva, Madrid and Valencia. A factorial analysis of variables revealed three dimensions of perceived discrimination (due to immigrant status, due to physical appearance, and workplace-related). The association of these dimensions with self-rated health, mental health (GHQ-12), change in self-rated health between origin and host country, and other self-reported health outcomes was analysed. Logistic regression was used adjusting for potential confounders (aOR-95%CI). Subjects with worsening self-reported health status potentially attributable to perceived discrimination was estimated (population attributable proportion, PAP %). 73.3% of men and 69.3% of women immigrants reported discrimination due to immigrant status. Moroccans showed the highest prevalence of perceived discrimination. Immigrants reporting discrimination were at significantly higher risk of reporting health problems than those not reporting discrimination. Workplace-related discrimination was associated with poor mental health (aOR 2.97 95%CI 2.45-3.60), and the worsening of self-rated health (aOR 2.20 95%CI 1.73- 2.80). 40% (95% CI 24-53) PAP of those reporting worse self-rated health could be attributable to discrimination due to immigrant status. Discrimination may constitute a risk factor for health in immigrant workers in Spain and could explain some health inequalities among immigrant populations in Spanish society.

[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.

Discrimination, acculturation and other predictors of depression among pregnant Hispanic women.

PubMed

Walker, Janiece L; Ruiz, R Jeanne; Chinn, Juanita J; Marti, Nathan; Ricks, Tiffany N

2012-01-01

The purpose of our study was to examine the effects of socioeconomic status, acculturative stress, discrimination, and marginalization as predictors of depression in pregnant Hispanic women. A prospective observational design was used. Central and Gulf coast areas of Texas in obstetrical offices. A convenience sample of 515 pregnant, low income, low medical risk, and self-identified Hispanic women who were between 22-24 weeks gestation was used to collect data. The predictor variables were socioeconomic status, discrimination, acculturative stress, and marginalization. The outcome variable was depression. Education, frequency of discrimination, age, and Anglo marginality were significant predictors of depressive symptoms in a linear regression model, F (6, 458) = 8.36, P<.0001. Greater frequency of discrimination was the strongest positive predictor of increased depressive symptoms. It is important that health care providers further understand the impact that age and experiences of discrimination throughout the life course have on depressive symptoms during pregnancy.

To 3D or Not to 3D, That Is the Question: Do 3D Surface Analyses Improve the Ecomorphological Power of the Distal Femur in Placental Mammals?

PubMed Central

Gould, Francois D. H.

2014-01-01

Improvements in three-dimensional imaging technologies have renewed interest in the study of functional and ecological morphology. Quantitative approaches to shape analysis are used increasingly to study form-function relationships. These methods are computationally intensive, technically demanding, and time-consuming, which may limit sampling potential. There have been few side-by-side comparisons of the effectiveness of such approaches relative to more traditional analyses using linear measurements and ratios. Morphological variation in the distal femur of mammals has been shown to reflect differences in locomotor modes across clades. Thus I tested whether a geometric morphometric analysis of surface shape was superior to a multivariate analysis of ratios for describing ecomorphological patterns in distal femoral variation. A sample of 164 mammalian specimens from 44 genera was assembled. Each genus was assigned to one of six locomotor categories. The same hypotheses were tested using two methods. Six linear measurements of the distal femur were taken with calipers, from which four ratios were calculated. A 3D model was generated with a laser scanner, and analyzed using three dimensional geometric morphometrics. Locomotor category significantly predicted variation in distal femoral morphology in both analyses. Effect size was larger in the geometric morphometric analysis than in the analysis of ratios. Ordination reveals a similar pattern with arboreal and cursorial taxa as extremes on a continuum of morphologies in both analyses. Discriminant functions calculated from the geometric morphometric analysis were more accurate than those calculated from ratios. Both analysis of ratios and geometric morphometric surface analysis reveal similar, biologically meaningful relationships between distal femoral shape and locomotor mode. The functional signal from the morphology is slightly higher in the geometric morphometric analysis. The practical costs of conducting these sorts of analyses should be weighed against potentially slight increases in power when designing protocols for ecomorphological studies. PMID:24633081

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

PubMed

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

2017-02-01

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

Discrimination, Mastery, and Depressive Symptoms among African American Men

ERIC Educational Resources Information Center

Watkins, Daphne C.; Hudson, Darrell L.; Caldwell, Cleopatra Howard; Siefert, Kristine; Jackson, James S.

2011-01-01

Purpose: This study examines the influence of discrimination and mastery on depressive symptoms for African American men at young (18-34), middle (35-54), and late (55+) adulthood. Method: Analyses are based on responses from 1,271 African American men from the National Survey of American Life (NSAL). Results: Discrimination was significantly…

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...

From Racial Discrimination to Risky Sex: Prospective Relations Involving Peers and Parents

ERIC Educational Resources Information Center

Roberts, Megan E.; Gibbons, Frederick X.; Gerrard, Meg; Weng, Chih-Yuan; Murry, Velma M.; Simons, Leslie G.; Simons, Ronald L.; Lorenz, Frederick O.

2012-01-01

This study investigated how early experience with racial discrimination affected the subsequent risky sexual behaviors of a diverse sample of African American youths (N = 745). The analyses focused on 3 risk-promoting factors thought to mediate the hypothesized discrimination--risky sex relation: negative affect, affiliation with deviant peers,…

Characterizing entanglement with global and marginal entropic measures

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

Adesso, Gerardo; Illuminati, Fabrizio; De Siena, Silvio

2003-12-01

We qualify the entanglement of arbitrary mixed states of bipartite quantum systems by comparing global and marginal mixednesses quantified by different entropic measures. For systems of two qubits we discriminate the class of maximally entangled states with fixed marginal mixednesses, and determine an analytical upper bound relating the entanglement of formation to the marginal linear entropies. This result partially generalizes to mixed states the quantification of entanglement with marginal mixednesses holding for pure states. We identify a class of entangled states that, for fixed marginals, are globally more mixed than product states when measured by the linear entropy. Such statesmore » cannot be discriminated by the majorization criterion.« less

Relationships between stereotyped beliefs about mental illness, discrimination experiences, and distressed mood over 1 year among persons with schizophrenia enrolled in rehabilitation.

PubMed

Lysaker, Paul H; Tunze, Chloe; Yanos, Philip T; Roe, David; Ringer, Jamie; Rand, Kevin

2012-06-01

Research suggests stereotype endorsement or self-stigma serves as a barrier to functioning and well-being among persons with schizophrenia. Little is known about how stable self-stigma is and whether it is linked over time with related constructs such as discrimination experiences and psychological distress. Stereotype endorsement and discrimination experiences were assessed using the Internalized Stigma of Mental Illness Scale and psychological distress was assessed using the Emotional Discomfort component of the Positive and Negative Syndrome Scale, at three points in time across 1 year. Path analyses indicated that the constructs of stereotype endorsement and discrimination experiences are stable over periods of 5-7 months and may fluctuate over 12 months. Further, the constructs of stereotype endorsement and discrimination experiences were related to one another concurrently, but analyses failed to detect a relationship over time. Neither construct was related to psychological distress over time. Self-stigma is a stable construct in the short term, and is distinct from related constructs such as discrimination experiences and psychological distress.

Life satisfaction and trauma in clinical and non-clinical children living in a war-torn environment: A discriminant analysis.

PubMed

Veronese, Guido; Pepe, Alessandro

2017-07-01

The aim of this work was to discriminate between healthy children and children at risk of developing mental impairments by evaluating the impact on contextual and individual factors of a context characterized by war. We tested the hypothesis that a linear discriminant function composed of trauma, life satisfaction, and affect balance has the power to classify the children as community or clinical referred. Membership of the clinical-referred group was associated with poorer life satisfaction and higher levels of trauma. Community-referred profiles were associated with lesser trauma. Perceived life satisfaction regarding family and school was the main contributor to the discriminant function.

Gestational dating by metabolic profile at birth: a California cohort study.

PubMed

Jelliffe-Pawlowski, Laura L; Norton, Mary E; Baer, Rebecca J; Santos, Nicole; Rutherford, George W

2016-04-01

Accurate gestational dating is a critical component of obstetric and newborn care. In the absence of early ultrasound, many clinicians rely on less accurate measures, such as last menstrual period or symphysis-fundal height during pregnancy, or Dubowitz scoring or the Ballard (or New Ballard) method at birth. These measures often underestimate or overestimate gestational age and can lead to misclassification of babies as born preterm, which has both short- and long-term clinical care and public health implications. We sought to evaluate whether metabolic markers in newborns measured as part of routine screening for treatable inborn errors of metabolism can be used to develop a population-level metabolic gestational dating algorithm that is robust despite intrauterine growth restriction and can be used when fetal ultrasound dating is not available. We focused specifically on the ability of these markers to differentiate preterm births (PTBs) (<37 weeks) from term births and to assign a specific gestational age in the PTB group. We evaluated a cohort of 729,503 singleton newborns with a California birth in 2005 through 2011 who had routine newborn metabolic screening and fetal ultrasound dating at 11-20 weeks' gestation. Using training and testing subsets (divided in a ratio of 3:1) we evaluated the association among PTB, target newborn characteristics, acylcarnitines, amino acids, thyroid-stimulating hormone, 17-hydroxyprogesterone, and galactose-1-phosphate-uridyl-transferase. We used multivariate backward stepwise regression to test for associations and linear discriminate analyses to create a linear function for PTB and to assign a specific week of gestation. We used sensitivity, specificity, and positive predictive value to evaluate the performance of linear functions. Along with birthweight and infant age at test, we included 35 of the 51 metabolic markers measured in the final multivariate model comparing PTBs and term births. Using a linear discriminate analyses-derived linear function, we were able to sort PTBs and term births accurately with sensitivities and specificities of ≥95% in both the training and testing subsets. Assignment of a specific week of gestation in those identified as PTBs resulted in the correct assignment of week ±2 weeks in 89.8% of all newborns in the training and 91.7% of those in the testing subset. When PTB rates were modeled using the metabolic dating algorithm compared to fetal ultrasound, PTB rates were 7.15% vs 6.11% in the training subset and 7.31% vs 6.25% in the testing subset. When considered in combination with birthweight and hours of age at test, metabolic profile evaluated within 8 days of birth appears to be a useful measure of PTB and, among those born preterm, of specific week of gestation ±2 weeks. Dating by metabolic profile may be useful in instances where there is no fetal ultrasound due to lack of availability or late entry into care. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Gestational dating by metabolic profile at birth: a California cohort study

PubMed Central

Jelliffe-Pawlowski, Laura L.; Norton, Mary E.; Baer, Rebecca J.; Santos, Nicole; Rutherford, George W.

2016-01-01

Background Accurate gestational dating is a critical component of obstetric and newborn care. In the absence of early ultrasound, many clinicians rely on less accurate measures, such as last menstrual period or symphysis-fundal height during pregnancy, or Dubowitz scoring or the Ballard (or New Ballard) method at birth. These measures often underestimate or overestimate gestational age and can lead to misclassification of babies as born preterm, which has both short- and long-term clinical care and public health implications. Objective We sought to evaluate whether metabolic markers in newborns measured as part of routine screening for treatable inborn errors of metabolism can be used to develop a population-level metabolic gestational dating algorithm that is robust despite intrauterine growth restriction and can be used when fetal ultrasound dating is not available. We focused specifically on the ability of these markers to differentiate preterm births (PTBs) (<37 weeks) from term births and to assign a specific gestational age in the PTB group. Study Design We evaluated a cohort of 729,503 singleton newborns with a California birth in 2005 through 2011 who had routine newborn metabolic screening and fetal ultrasound dating at 11–20 weeks’ gestation. Using training and testing subsets (divided in a ratio of 3:1) we evaluated the association among PTB, target newborn characteristics, acylcarnitines, amino acids, thyroid-stimulating hormone, 17-hydroxyprogesterone, and galactose-1-phosphate-uridyl-transferase. We used multivariate backward stepwise regression to test for associations and linear discriminate analyses to create a linear function for PTB and to assign a specific week of gestation. We used sensitivity, specificity, and positive predictive value to evaluate the performance of linear functions. Results Along with birthweight and infant age at test, we included 35 of the 51 metabolic markers measured in the final multivariate model comparing PTBs and term births. Using a linear discriminate analyses-derived linear function, we were able to sort PTBs and term births accurately with sensitivities and specificities of ≥95% in both the training and testing subsets. Assignment of a specific week of gestation in those identified as PTBs resulted in the correct assignment of week ±2 weeks in 89.8% of all newborns in the training and 91.7% of those in the testing subset. When PTB rates were modeled using the metabolic dating algorithm compared to fetal ultrasound, PTB rates were 7.15% vs 6.11% in the training subset and 7.31% vs 6.25% in the testing subset. Conclusion When considered in combination with birthweight and hours of age at test, metabolic profile evaluated within 8 days of birth appears to be a useful measure of PTB and, among those born preterm, of specific week of gestation ±2 weeks. Dating by metabolic profile may be useful in instances where there is no fetal ultrasound due to lack of availability or late entry into care. PMID:26688490

Medical mistrust as a key mediator in the association between perceived discrimination and adherence to antiretroviral therapy among HIV-positive Latino men.

PubMed

Galvan, Frank H; Bogart, Laura M; Klein, David J; Wagner, Glenn J; Chen, Ying-Tung

2017-10-01

Discrimination has been found to have deleterious effects on physical health. The goal of the present study was to examine the association between perceived discrimination and adherence to antiretroviral therapy (ART) among HIV-positive Latino men and the extent to which medical mistrust serves as a mediator of that association. A series of linear and logistic regression models was used to test for mediation for three types of perceived discrimination (related to being Latino, being perceived as gay and being HIV-positive). Medical mistrust was found to be significantly associated with perceived discrimination based on Latino ethnicity and HIV serostatus. Medical mistrust was found to mediate the associations between two types of perceived discrimination (related to being Latino and being HIV-positive) and ART adherence. Given these findings, interventions should be developed that increase the skills of HIV-positive Latino men to address both perceived discrimination and medical mistrust.

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

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout

PubMed Central

Clery, Stephane; Cumming, Bruce G.

2017-01-01

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal “noise” correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. SIGNIFICANCE STATEMENT Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. PMID:28100751

Pattern classification of fMRI data: applications for analysis of spatially distributed cortical networks.

PubMed

Yourganov, Grigori; Schmah, Tanya; Churchill, Nathan W; Berman, Marc G; Grady, Cheryl L; Strother, Stephen C

2014-08-01

The field of fMRI data analysis is rapidly growing in sophistication, particularly in the domain of multivariate pattern classification. However, the interaction between the properties of the analytical model and the parameters of the BOLD signal (e.g. signal magnitude, temporal variance and functional connectivity) is still an open problem. We addressed this problem by evaluating a set of pattern classification algorithms on simulated and experimental block-design fMRI data. The set of classifiers consisted of linear and quadratic discriminants, linear support vector machine, and linear and nonlinear Gaussian naive Bayes classifiers. For linear discriminant, we used two methods of regularization: principal component analysis, and ridge regularization. The classifiers were used (1) to classify the volumes according to the behavioral task that was performed by the subject, and (2) to construct spatial maps that indicated the relative contribution of each voxel to classification. Our evaluation metrics were: (1) accuracy of out-of-sample classification and (2) reproducibility of spatial maps. In simulated data sets, we performed an additional evaluation of spatial maps with ROC analysis. We varied the magnitude, temporal variance and connectivity of simulated fMRI signal and identified the optimal classifier for each simulated environment. Overall, the best performers were linear and quadratic discriminants (operating on principal components of the data matrix) and, in some rare situations, a nonlinear Gaussian naïve Bayes classifier. The results from the simulated data were supported by within-subject analysis of experimental fMRI data, collected in a study of aging. This is the first study that systematically characterizes interactions between analysis model and signal parameters (such as magnitude, variance and correlation) on the performance of pattern classifiers for fMRI. Copyright © 2014 Elsevier Inc. All rights reserved.

Linear operating region in the ozone dial photon counting system

NASA Technical Reports Server (NTRS)

Andrawis, Madeleine

1995-01-01

Ozone is a relatively unstable molecule found in Earth's atmosphere. An ozone molecule is made up of three atoms of oxygen. Depending on where ozone resides, it can protect or harm life on Earth. High in the atmosphere, about 15 miles up, ozone acts as a shield to protect Earth's surface from the sun's harmful ultraviolet radiation. Without this shield, we would be more susceptible to skin cancer, cataracts, and impaired immune systems. Closer to Earth, in the air we breathe, ozone is a harmful pollutant that causes damage to lung tissue and plants. Since the early 1980's, airborne lidar systems have been used for making measurements of ozone. The differential absorption lidar (DIAL) technique is used in the remote measurement of O3. This system allows the O3 to be measured as function of the range in the atmosphere. Two frequency-doubled Nd:YAG lasers are used to pump tunable dye lasers. The lasers are operating at 289 nm for the DIAL on-line wavelength of O3, and the other one is operated at 300 nm for the off-line wavelength. The DIAL wavelengths are produced in sequential laser pulses with a time separation of 300 micro s. The backscattered laser energy is collected by telescopes and measured using photon counting systems. The photon counting system measures the light signal by making use of the photon nature of light. The output pulse from the Photo-Multiplier Tube (PE), caused by a photon striking the PMT photo-cathode, is amplified and passed to a pulse height discriminator. The peak value of the pulse is compared to a reference voltage (discrimination level). If the pulse amplitude exceeds the discrimination level, the discriminator generates a standard pulse which is counted by the digital counter. Non-linearity in the system is caused by the overlapping of pulses and the finite response time of the electronics. At low count rates one expects the system to register one event for each output pulse from the PMT corresponding to a photon incident upon the photocathode, however, at higher rates the limitations of the discrimination/counting system will cause the observed count rate to be non-linear with respect to the true count rate. Depending on the pulse height distribution and the discriminator level, the overlapping of pulses (pulse pile-up) can cause count loss or even an additional apparent count gain as the signal levels increase. Characterization of the system, including the pulse height distribution, the signal to noise ratio, and the effect of the discriminator threshold level, is critical in maximizing the linear operating region of the system, thus greatly increasing the useful dynamic range of the system.

Effect of americium-241 alpha-particles on the dose-response of chromosome aberrations in human lymphocytes analysed by fluorescence in situ hybridization.

PubMed

Barquinero, J F; Stephan, G; Schmid, E

2004-02-01

To evaluate by the fluorescent in-situ hybridization (FISH) technique the dose-response and intercellular distribution of alpha-particle-induced chromosome aberrations. In particular, the validity of using the yield of characteristic types of chromosome abnormalities in stable cells as quantitative indicators for retrospective dose reconstruction has been evaluated. Monolayers of human peripheral lymphocytes were exposed at doses from 0.02 to 1 Gy to alpha-particles emitted from a source of americium-241. The most probable energy of the alpha-particles entering the cells was 2.7 MeV. FISH painting was performed using DNA probes for chromosomes 2, 4 and 8 in combination with a pan-centromeric probe. In complete first-division cells, identified by harlequin staining, aberrations involving painted target chromosomal material were recorded as well as aberrations involving only unpainted chromosomal material. In total, the percentage of complex aberrations was about 35% and no dose dependence was observed. When complex-type exchanges were reduced to simple base types, the different cell distributions were clearly over-dispersed, and the linear coefficients of the dose-effect curves for translocations were significantly higher than for dicentrics. For past dose reconstruction, only a few complex aberrations were in stable cells. The linear coefficient obtained for transmissible aberrations in stable cells was more than seven times lower than that obtained in all analysed cells, i.e. including unstable cells. FISH-based analysis of complex rearrangements allows discrimination between partial-body exposures to low-linear energy transfer radiation and high-linear energy transfer exposures. In assessing past or chronic exposure to alpha-particles, the use of a dose-effect curve obtained by FISH-based translocation data, which had not excluded data determined in unstable cells, would underestimate the dose. Insertions are ineffective biomarkers because their frequency is too low.

Documenting Differences between Early Stone Age Flake Production Systems: An Experimental Model and Archaeological Verification.

PubMed

Presnyakova, Darya; Archer, Will; Braun, David R; Flear, Wesley

2015-01-01

This study investigates morphological differences between flakes produced via "core and flake" technologies and those resulting from bifacial shaping strategies. We investigate systematic variation between two technological groups of flakes using experimentally produced assemblages, and then apply the experimental model to the Cutting 10 Mid -Pleistocene archaeological collection from Elandsfontein, South Africa. We argue that a specific set of independent variables--and their interactions--including external platform angle, platform depth, measures of thickness variance and flake curvature should distinguish between these two technological groups. The role of these variables in technological group separation was further investigated using the Generalized Linear Model as well as Linear Discriminant Analysis. The Discriminant model was used to classify archaeological flakes from the Cutting 10 locality in terms of their probability of association, within either experimentally developed technological group. The results indicate that the selected independent variables play a central role in separating core and flake from bifacial technologies. Thickness evenness and curvature had the greatest effect sizes in both the Generalized Linear and Discriminant models. Interestingly the interaction between thickness evenness and platform depth was significant and played an important role in influencing technological group membership. The identified interaction emphasizes the complexity in attempting to distinguish flake production strategies based on flake morphological attributes. The results of the discriminant function analysis demonstrate that the majority of flakes at the Cutting 10 locality were not associated with the production of the numerous Large Cutting Tools found at the site, which corresponds with previous suggestions regarding technological behaviors reflected in this assemblage.

Documenting Differences between Early Stone Age Flake Production Systems: An Experimental Model and Archaeological Verification

PubMed Central

Presnyakova, Darya; Archer, Will; Braun, David R.; Flear, Wesley

2015-01-01

This study investigates morphological differences between flakes produced via “core and flake” technologies and those resulting from bifacial shaping strategies. We investigate systematic variation between two technological groups of flakes using experimentally produced assemblages, and then apply the experimental model to the Cutting 10 Mid -Pleistocene archaeological collection from Elandsfontein, South Africa. We argue that a specific set of independent variables—and their interactions—including external platform angle, platform depth, measures of thickness variance and flake curvature should distinguish between these two technological groups. The role of these variables in technological group separation was further investigated using the Generalized Linear Model as well as Linear Discriminant Analysis. The Discriminant model was used to classify archaeological flakes from the Cutting 10 locality in terms of their probability of association, within either experimentally developed technological group. The results indicate that the selected independent variables play a central role in separating core and flake from bifacial technologies. Thickness evenness and curvature had the greatest effect sizes in both the Generalized Linear and Discriminant models. Interestingly the interaction between thickness evenness and platform depth was significant and played an important role in influencing technological group membership. The identified interaction emphasizes the complexity in attempting to distinguish flake production strategies based on flake morphological attributes. The results of the discriminant function analysis demonstrate that the majority of flakes at the Cutting 10 locality were not associated with the production of the numerous Large Cutting Tools found at the site, which corresponds with previous suggestions regarding technological behaviors reflected in this assemblage. PMID:26111251

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.

Perceived discrimination in health care and health status in a racially diverse sample.

PubMed

Hausmann, Leslie R M; Jeong, Kwonho; Bost, James E; Ibrahim, Said A

2008-09-01

Despite the surge of recent research on the association between perceived discrimination and health-related outcomes, few studies have focused on race-based discrimination encountered in health care settings. This study examined the prevalence of such discrimination, and its association with health status, for the 3 largest race/ethnic groups in the United States. Data were drawn from the 2004 Behavioral Risk Factor Surveillance System survey. The primary variables were perceived racial discrimination in health care and self-reported health status. Multivariable logistic regression was used to compare the prevalence of perceived discrimination for whites, African Americans, and Hispanics, and to examine the association between perceived discrimination and health status, controlling for sex, age, income, education, health care coverage, affordability of medical care, racial salience, and state. Perceived discrimination was reported by 2%, 5.2%, and 10.9% of whites, Hispanics, and African Americans, respectively. Only the difference between African Americans and whites remained significant in adjusted analyses [odds ratio (OR) = 3.22, 95% confidence interval (CI) = 2.46-4.21]. Racial/ethnic differences in perceived discrimination depended on income, education, health care coverage, and affordability of medical care. Perceived discrimination was associated with worse health status for the overall sample (OR = 1.71, 95% CI = 1.35-2.16). Stratified analyses revealed that this relationship was significant for whites (OR = 2.00, 95% CI = 1.45-2.77) and African Americans (OR = 1.95, 95% CI = 1.39-2.73), but not for Hispanics (OR = 0.55, 95% CI = 0.24-1.22). Perceived racial discrimination in health care is much more prevalent for African Americans than for whites or Hispanics. Furthermore, such discrimination is associated with worse health both for African Americans and for whites.

Is Perceived Discrimination in Pregnancy Prospectively Linked to Postpartum Depression? Exploring the Role of Education.

PubMed

Stepanikova, Irena; Kukla, Lubomir

2017-08-01

Objectives The role of perceived discrimination in postpartum depression is largely unknown. We investigate whether perceived discrimination reported in pregnancy contributes to postpartum depression, and whether its impact varies by education level. Methods Prospective data are a part of European Longitudinal Study of Pregnancy and Childhood, the Czech Republic. Surveys were collected in mid-pregnancy and at 6 months after delivery. Depression was measured using Edinburgh Postnatal Depression Scale. Generalized linear models were estimated to test the effects of perceived discrimination on postpartum depression. Results Multivariate models revealed that among women with low education, discrimination in pregnancy was prospectively associated with 2.43 times higher odds of postpartum depression (p < .01), after adjusting for antenatal depression, history of earlier depression, and socio-demographic background. In contrast, perceived discrimination was not linked to postpartum depression among women with high education. Conclusions Perceived discrimination is a risk factor for postpartum depression among women with low education. Screening for discrimination and socio-economic disadvantage during pregnancy could benefit women who are at risk for mental health problems.

Racial discrimination and the stress process.

PubMed

Ong, Anthony D; Fuller-Rowell, Thomas; Burrow, Anthony L

2009-06-01

The unique and combined effects of chronic and daily racial discrimination on psychological distress were examined in a sample of 174 African American doctoral students and graduates. Using a daily process design, 5 models of the stress process were tested. Multilevel random coefficient modeling analyses revealed that chronic exposure to racial discrimination predicted greater daily discrimination and psychological distress. Further, results show that differences in daily discrimination and negative events accounted for meaningful variation in daily distress responses. Finally, findings indicate that daily discrimination and negative events mediated the relationship between chronic discrimination and psychological distress. The study provides support for the need to measure chronic strains as distinctive from daily stressors in the lives of African Americans.

A risk analysis approach for using discriminant functions to manage logging-related landslides on granitic terrain

Treesearch

Raymond M. Rice; Norman H. Pillsbury; Kurt W. Schmidt

1985-01-01

Abstract - A linear discriminant function, developed to predict debris avalanches after clearcut logging on a granitic batholith in northwestern California, was tested on data from two batholiths. The equation was inaccurate in predicting slope stability on one of them. A new equation based on slope, crown cover, and distance from a stream (retained from the original...

Identification of Variables Associated with Group Separation in Descriptive Discriminant Analysis: Comparison of Methods for Interpreting Structure Coefficients

ERIC Educational Resources Information Center

Finch, Holmes

2010-01-01

Discriminant Analysis (DA) is a tool commonly used for differentiating among 2 or more groups based on 2 or more predictor variables. DA works by finding 1 or more linear combinations of the predictors that yield maximal difference among the groups. One common goal of researchers using DA is to characterize the nature of group difference by…

Racial discrimination and racial socialization as predictors of African American adolescents' racial identity development using latent transition analysis.

PubMed

Seaton, Eleanor K; Yip, Tiffany; Morgan-Lopez, Antonio; Sellers, Robert M

2012-03-01

The present study examined perceptions of racial discrimination and racial socialization on racial identity development among 566 African American adolescents over 3 years. Latent class analyses were used to estimate identity statuses (Diffuse, Foreclosed, Moratorium, and Achieved). The probabilities of transitioning from one stage to another were examined with latent transition analyses to determine the likelihood of youth progressing, regressing, or remaining constant. Racial socialization and perceptions of racial discrimination were examined as covariates to assess the association with changes in racial identity status. The results indicated that perceptions of racial discrimination were not linked to any changes in racial identity. Youth who reported higher levels of racial socialization were less likely to be in Diffuse or Foreclosed compared with the Achieved group. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Personal discrimination and satisfaction with life: Exploring perceived functional effects of Asian American race/ethnicity as a moderator.

PubMed

Tran, Alisia G T T; Sangalang, Cindy C

2016-01-01

This study aims to understand the relations between experiences of racial/ethnic discrimination, perceptions of the harmful or helpful effects of one's Asian American race/ethnicity within educational and occupational contexts (perceived functional effects), and well-being (i.e., satisfaction with life). A primary focus was to evaluate whether the association between racial/ethnic discrimination and satisfaction with life varied based on the degree to which Asian Americans believe that their race or ethnicity is helpful or harmful to educational and occupational functioning. This study draws on nationally representative data from ethnically diverse Asian American adults (N = 3,335) and utilizes weighted descriptive, correlational, and logistic regression moderation analyses. Ethnic variations emerged across analyses. Logistic regression analyses revealed a significant moderation effect for Chinese and Filipino Americans. Follow-up analyses revealed a protective effect of perceiving more positive or helpful functional effects in nullifying the link between discrimination and dissatisfaction with life for Chinese Americans. By contrast, viewing more harmful functional effects had a buffering effect for Filipino Americans. Results have implications for conceptualizing the potential impact of perspectives that imply Asian American advantage or disadvantage. Opportunities to apply and extend these initial findings are discussed. (c) 2016 APA, all rights reserved).

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

Trace Element Study of H Chondrites: Evidence for Meteoroid Streams.

NASA Astrophysics Data System (ADS)

Wolf, Stephen Frederic

1993-01-01

Multivariate statistical analyses, both linear discriminant analysis and logistic regression, of the volatile trace elemental concentrations in H4-6 chondrites reveal compositionally distinguishable subpopulations. Observed difference in volatile trace element composition between Antarctic and non-Antarctic H4-6 chondrites (Lipschutz and Samuels, 1991) can be explained by a compositionaily distinct subpopulation found in Victoria Land, Antarctica. This population of H4-6 chondrites is compositionally distinct from non-Antarctic H4-6 chondrites and from Antarctic H4 -6 chondrites from Queen Maud Land. Comparisons of Queen Maud Land H4-6 chondrites with non-Antarctic H4-6 chondrites do not give reason to believe that these two populations are distinguishable from each other on the basis of the ten volatile trace element concentrations measured. ANOVA indicates that these differences are not the result of trivial causes such as weathering and analytical bias. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. Given the differences in terrestrial age between Victoria Land, Queen Maud Land, and modern H4-6 chondrite falls, these results are consistent with a variation in H4-6 chondrite flux on a 300 ky timescale. This conclusion requires the existence of co-orbital meteoroid streams. Statistical analyses of the volatile trace elemental concentrations in non-Antarctic modern falls of H4-6 chondrites also demonstrate that a group of 13 H4-6 chondrites, Cluster 1, selected exclusively for their distinct fall parameters (Dodd, 1992) is compositionally distinguishable from a control group of 45 non-Antarctic modern H4-6 chondrites on the basis of the ten volatile trace element concentrations measured. Model-independent randomization-simulations based on both linear discriminant analysis and logistic regression verify these results. While ANOVA identifies two possible causes for this difference, analytical bias and group classification, a test validation experiment verifies that group classification is the more significant cause of compositional difference between Cluster 1 and non-Cluster 1 modern H4-6 chondrite falls. Thermoluminescence properties of these populations parallels the results of volatile trace element comparisons. This suggests that these meteorites are fragments of a co-orbital meteorite stream derived from a single parent body.

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study

PubMed Central

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-01-01

Background Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis Methods The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. Results By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. Conclusion The results of this study suggest that: a) cortical NFT represent the key variable in AD neuropathology; b) the neuropathologic profile of AD subjects is complex, however, c) ANNs can analyze neuropathologic features and differentiate AD cases from controls. PMID:17584929

Neuropathological findings processed by artificial neural networks (ANNs) can perfectly distinguish Alzheimer's patients from controls in the Nun Study.

PubMed

Grossi, Enzo; Buscema, Massimo P; Snowdon, David; Antuono, Piero

2007-06-21

Many reports have described that there are fewer differences in AD brain neuropathologic lesions between AD patients and control subjects aged 80 years and older, as compared with the considerable differences between younger persons with AD and controls. In fact some investigators have suggested that since neurofibrillary tangles (NFT) can be identified in the brains of non-demented elderly subjects they should be considered as a consequence of the aging process. At present, there are no universally accepted neuropathological criteria which can mathematically differentiate AD from healthy brain in the oldest old. The aim of this study is to discover the hidden and non-linear associations among AD pathognomonic brain lesions and the clinical diagnosis of AD in participants in the Nun Study through Artificial Neural Networks (ANNs) analysis The analyses were based on 26 clinically- and pathologically-confirmed AD cases and 36 controls who had normal cognitive function. The inputs used for the analyses were just NFT and neuritic plaques counts in neocortex and hippocampus, for which, despite substantial differences in mean lesions counts between AD cases and controls, there was a substantial overlap in the range of lesion counts. By taking into account the above four neuropathological features, the overall predictive capability of ANNs in sorting out AD cases from normal controls reached 100%. The corresponding accuracy obtained with Linear Discriminant Analysis was 92.30%. These results were consistently obtained in ten independent experiments. The same experiments were carried out with ANNs on a subgroup of 13 non severe AD patients and on the same 36 controls. The results obtained in terms of prediction accuracy with ANNs were exactly the same. Input relevance analysis confirmed the relative dominance of NFT in neocortex in discriminating between AD patients and controls and indicated the lesser importance played by NP in the hippocampus. The results of this study suggest that: a) cortical NFT represent the key variable in AD neuropathology; b) the neuropathologic profile of AD subjects is complex, however, c) ANNs can analyze neuropathologic features and differentiate AD cases from controls.

Predicting implementation from organizational readiness for change: a study protocol

PubMed Central

2011-01-01

Background There is widespread interest in measuring organizational readiness to implement evidence-based practices in clinical care. However, there are a number of challenges to validating organizational measures, including inferential bias arising from the halo effect and method bias - two threats to validity that, while well-documented by organizational scholars, are often ignored in health services research. We describe a protocol to comprehensively assess the psychometric properties of a previously developed survey, the Organizational Readiness to Change Assessment. Objectives Our objective is to conduct a comprehensive assessment of the psychometric properties of the Organizational Readiness to Change Assessment incorporating methods specifically to address threats from halo effect and method bias. Methods and Design We will conduct three sets of analyses using longitudinal, secondary data from four partner projects, each testing interventions to improve the implementation of an evidence-based clinical practice. Partner projects field the Organizational Readiness to Change Assessment at baseline (n = 208 respondents; 53 facilities), and prospectively assesses the degree to which the evidence-based practice is implemented. We will conduct predictive and concurrent validities using hierarchical linear modeling and multivariate regression, respectively. For predictive validity, the outcome is the change from baseline to follow-up in the use of the evidence-based practice. We will use intra-class correlations derived from hierarchical linear models to assess inter-rater reliability. Two partner projects will also field measures of job satisfaction for convergent and discriminant validity analyses, and will field Organizational Readiness to Change Assessment measures at follow-up for concurrent validity (n = 158 respondents; 33 facilities). Convergent and discriminant validities will test associations between organizational readiness and different aspects of job satisfaction: satisfaction with leadership, which should be highly correlated with readiness, versus satisfaction with salary, which should be less correlated with readiness. Content validity will be assessed using an expert panel and modified Delphi technique. Discussion We propose a comprehensive protocol for validating a survey instrument for assessing organizational readiness to change that specifically addresses key threats of bias related to halo effect, method bias and questions of construct validity that often go unexplored in research using measures of organizational constructs. PMID:21777479

Development of a universal water signature for the LANDSAT-3 Multispectral Scanner, part 1

NASA Technical Reports Server (NTRS)

Schlosser, E. H.

1980-01-01

A generalized four channel hyperplane to discriminate water from nonwater was developed using LANDSAT-3 multispectral scaner (MSS) scenes and matching same/next day color infrared aerial photography. The MSS scenes varied in sun elevation angle from 40 to 58 deg. The 28 matching air photo frames contained over 1400 water bodies larger than one surface acre. A preliminary water discriminant, was used to screen the data and eliminate from further consideration all pixels distant from water in MSS spectral space. A linear discriminant was iteratively fitted to the labelled pixels. This discriminant correctly classified 98.7% of the water pixels and 98.6% of the nonwater pixels. The discriminant detected 91.3% of the 414 water bodies over 10 acres in surface area, and misclassified as water 36 groups of contiguous nonwater pixels.

[The influence of perceived discrimination on health in migrants].

PubMed

Igel, Ulrike; Brähler, Elmar; Grande, Gesine

2010-05-01

The aim of the study was to investigate the influence of racial discrimination on subjective health in migrants. The sample included 1.844 migrants from the SOEP. Discrimination was assessed by two items. Socioeconomic status, country of origin, and health behavior were included in multivariate regression models to control for effects on health. Differential models with regard to gender and origin were analysed. Migrants who experienced discrimination report a worse health status. Discrimination determines mental and physical health of migrants. There are differences in models due to gender and origin. In addition to socioeconomic factors experienced discrimination should be taken into account as a psycho-social stressor of migrants.

Predictors of experiences of discrimination and positive treatment in people with mental health problems: findings from an Australian national survey.

PubMed

Reavley, Nicola J; Morgan, Amy J; Jorm, Anthony F

2017-03-01

The aim of the study was to assess the factors predicting experiences of avoidance, discrimination and positive treatment in people with mental health problems. In 2014, telephone interviews were carried out with 5220 Australians aged 18+, 1381 of whom reported a mental health problem or scored highly on a symptom screening questionnaire. Questions covered experiences of avoidance, discrimination and positive treatment by friends, spouse, other family, workplace, educational institution and others in the community; as well as disclosure of mental health problems. Avoidance, discrimination and positive treatment scores were calculated by counting the number of domains in which each occurred. Predictors of avoidance, discrimination and positive treatment were modelled with negative binomial regression analyses. After adjusting for the effects of other predictors in multivariate analyses, symptom severity and a diagnosis of 'any other disorder' (most commonly psychotic disorders or eating disorders) predicted experiences of both avoidance and discrimination but not positive treatment. Disclosing a mental health problem in more settings was also associated with higher rates of avoidance and discrimination, but also with positive treatment. Disclosure of mental health problems to others may increases experiences of discrimination, but may also increase experiences of positive treatment. These findings can help to inform decision making by people with mental health problems about disclosure, particularly in the case of more severe or low-prevalence disorders.

Factors Associated with Medical Doctors' Intentions to Discriminate Against Transgender Patients in Kuala Lumpur, Malaysia.

PubMed

Vijay, Aishwarya; Earnshaw, Valerie A; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L; Wickersham, Jeffrey A

2018-01-01

Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings.

Changes in experiences with discrimination across pregnancy and postpartum: age differences and consequences for mental health.

PubMed

Rosenthal, Lisa; Earnshaw, Valerie A; Lewis, Tené T; Reid, Allecia E; Lewis, Jessica B; Stasko, Emily C; Tobin, Jonathan N; Ickovics, Jeannette R

2015-04-01

We aimed to contribute to growing research and theory suggesting the importance of examining patterns of change over time and critical life periods to fully understand the effects of discrimination on health, with a focus on the period of pregnancy and postpartum and mental health outcomes. We used hierarchical linear modeling to examine changes across pregnancy and postpartum in everyday discrimination and the resulting consequences for mental health among predominantly Black and Latina, socioeconomically disadvantaged young women who were receiving prenatal care in New York City. Patterns of change in experiences with discrimination varied according to age. Among the youngest participants, discrimination increased from the second to third trimesters and then decreased to lower than the baseline level by 1 year postpartum; among the oldest participants, discrimination decreased from the second trimester to 6 months postpartum and then returned to the baseline level by 1 year postpartum. Within-subjects changes in discrimination over time predicted changes in depressive and anxiety symptoms at subsequent points. Discrimination more strongly predicted anxiety symptoms among participants reporting food insecurity. Our results support a life course approach to understanding the impact of experiences with discrimination on health and when to intervene.

Factors Associated with Medical Doctors' Intentions to Discriminate Against Transgender Patients in Kuala Lumpur, Malaysia

PubMed Central

Vijay, Aishwarya; Earnshaw, Valerie A.; Tee, Ying Chew; Pillai, Veena; White Hughto, Jaclyn M.; Clark, Kirsty; Kamarulzaman, Adeeba; Altice, Frederick L.

2018-01-01

Abstract Purpose: Transgender people are frequent targets of discrimination. Discrimination against transgender people in the context of healthcare can lead to poor health outcomes and facilitate the growth of health disparities. This study explores factors associated with medical doctors' intentions to discriminate against transgender people in Malaysia. Methods: A total of 436 physicians at two major university medical centers in Kuala Lumpur, Malaysia, completed an online survey. Sociodemographic characteristics, stigma-related constructs, and intentions to discriminate against transgender people were measured. Bivariate and multivariate linear regression were used to evaluate independent covariates of discrimination intent. Results: Medical doctors who felt more fearful of transgender people and more personal shame associated with transgender people expressed greater intention to discriminate against transgender people, whereas doctors who endorsed the belief that transgender people deserve good care reported lower discrimination intent. Stigma-related constructs accounted for 42% of the variance and 8% was accounted for by sociodemographic characteristics. Conclusions: Constructs associated with transgender stigma play an important role in medical doctors' intentions to discriminate against transgender patients. Development of interventions to improve medical doctors' knowledge about and attitudes toward transgender people are necessary to reduce discriminatory intent in healthcare settings. PMID:29227183

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.

Does perceived discrimination affect health? Longitudinal relationships between work discrimination and women's physical and emotional health.

PubMed

Pavalko, Eliza K; Mossakowski, Krysia N; Hamilton, Vanessa J

2003-03-01

This study uses longitudinal data to examine the causal relationships between perceived work discrimination and women's physical and emotional health. Using data on 1,778 employed women in the National Longitudinal Survey of Mature Women, we investigate the structural and individual characteristics that predict later perceptions of discrimination and the effects of those perceptions on subsequent health. We find that perceptions of discrimination are influenced by job attitudes, prior experiences of discrimination, and work contexts, but prior health is not related to later perceptions. However, perceptions of discrimination do impact subsequent health, and these effects remain significant after controlling for prior emotional health, physical health limitations, discrimination, and job characteristics. Overall, the results provide even stronger support for the health impact of workplace discrimination and suggest a need for further longitudinal analyses of causes and consequences of perceived discrimination.

Forest discrimination with multipolarization imaging radar

NASA Technical Reports Server (NTRS)

Ford, J. P.; Wickland, D. E.

1985-01-01

The use of radar polarization diversity for discriminating forest canopy variables on airborne synthetic-aperture radar (SAR) images is evaluated. SAR images were acquired at L-Band (24.6 cm) simultaneously in four linear polarization states (HH, HV, VH, and VV) in South Carolina on March 1, 1984. In order to relate the polarization signatures to biophysical properties, false-color composite images were compared to maps of forest stands in the timber compartment. In decreasing order, the most useful correlative forest data are stand basal area, forest age, site condition index, and forest management type. It is found that multipolarization images discriminate variation in tree density and difference in the amount of understory, but do not discriminate between evergreen and deciduous forest types.

The mediating effect of discrimination, social support and hopelessness on self-rated health of Roma adolescents in Slovakia.

PubMed

Kolarcik, Peter; Geckova, Andrea Madarasova; Reijneveld, Sijmen A; Van Dijk, Jitse P

2015-11-19

According to the EU-MIDIS report on discrimination, Roma are the most discriminated against group in Europe. Research suggests that experiencing discrimination may itself be detrimental to health. The aim of this paper is to investigate whether discrimination, hopelessness and social support mediate differences in self-rated health (SRH) between Roma and non-Roma adolescents. We conducted a cross-sectional study among Roma from separated and segregated settlements in the eastern part of Slovakia (N = 330; mean age = 14.50; interview) and non-Roma adolescents (N = 722; mean age = 14.86; questionnaire); only non-missing data were used for analyses (n = 759). The effect of perceived discrimination, mother and father social support, and hopelessness on SRH was analysed as crude and adjusted for ethnicity, age, gender, parental education and social desirability. Mediating effects were separately assessed using the Sobel test and structural equation modelling. Roma adolescents reported poorer SRH and more discrimination, mother and father social support, hopelessness and social desirability. Roma ethnicity (Odds ratio/95 %-Confidence interval 3.27/2.40-4.47), discrimination (2.66/1.82-3.88), hopelessness (1.35/1.20-1.51) and mother (0.92/0.88-0.97) and father social support (0.96/0.93 - 0.997) were statistically significant predictors of poor SRH. Perceived discrimination, social support and hopelessness mediated the ethnicity-health association, with adjustment for social support increasing its strength and the other two variables decreasing it. Perceived discrimination, social support and hopelessness mediate a part of the association between Roma ethnicity and poor SRH, with discrimination and hopelessness being risk factors and social support a protective factor.

Player's success prediction in rugby union: From youth performance to senior level placing.

PubMed

Fontana, Federico Y; Colosio, Alessandro L; Da Lozzo, Giorgio; Pogliaghi, Silvia

2017-04-01

The study questioned if and to what extent specific anthropometric and functional characteristics measured in youth draft camps, can accurately predict subsequent career progression in rugby union. Original research. Anthropometric and functional characteristics of 531 male players (U16) were retrospectively analysed in relation to senior level team representation at age 21-24. Players were classified as International (Int: National team and international clubs) or National (Nat: 1st, 2nd and other divisions and dropout). Multivariate analysis of variance (one-way MANOVA) tested differences between Int and Nat, along a combination of anthropometric (body mass, height, body fat, fat-free mass) and functional variables (SJ, CMJ, t 15m , t 30m , VO 2max ). A discriminant function (DF) was determined to predict group assignment based on the linear combination of variables that best discriminate groups. Correct level assignment was expressed as % hit rate. A combination of anthropometric and functional characteristics reflects future level assignment (Int vs. Nat). Players' success can be accurately predicted (hit rate=81% and 77% for Int and Nat respectively) by a DF that combines anthropometric and functional variables as measured at ∼15 years of age, percent body fat and speed being the most influential predictors of group stratification. Within a group of 15 year-olds with exceptional physical characteristics, future players' success can be predicted using a linear combination of anthropometric and functional variables, among which a lower percent body fat and higher speed over a 15m sprint provide the most important predictors of the highest career success. Copyright © 2016 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.

[Cephalometric analysis in individuals with Class II/2 malocclusions].

PubMed

Rak, D

1990-06-01

Various orthodontic anomalies class II/2, classified into several experimental groups, and eugnathic occlusion serving as controls, were studied by roentgencephalometry. The objective of the study was to detect possible distinctions in the quantitative values of the chosen variables and to select those which discriminate the group of class II/2 orthodontic anomalies most significantly. Attempts were made to ascertain whether or not there were sex-related differences. The teleroentgenograma of 241 examines, aged 10 to 18 years, of both sexes, were analyzed. The experimental group consisted of 61 examinees class II/2 orthodontic anomalies. The control group consisted of 180 examinees with eugnathic occlusion. Latero-lateral skull roentgenograms were taken according to the rules of roentgencephalometry. Using acetate paper, the drawings of profile teleroentgenograms were elaborated and the reference points and lineas were entered. A total of 38 variables were analyzed, of which 10 were linear, 19 angular, 8 variables were obtained by mathematical calculations, and the age variable was also analyzed. For statistical analyses and electronic computer was used. The results are presented in tables and graphs. The results obtained have shown: that, when compared to the findings in the control group, the subjects in the experimental groups manifested significant changes in the following craniofacial characteristics: retroposition and retroinclination of the upper incisors; increased difference of the position of the apical basis of the jaw; marked convexity of the osseous profile; mandibular retrognathism and increased proportion of the maxillary compared to mandibular base; that, with regard to the sex of the examines, only linear variables of significantly discriminating character were selected. Thus it could be concluded that there were no significant sex differences among the morphological characteristics of the viscerocranium.

[Cephalometric analysis in cases with Class III malocclusions].

PubMed

Rak, D

1989-01-01

Various orthodontic class III anomalies, classified into several experimental groups, and eugnathic occlusions serving as controls were studied by roentgencephalometry. The objective of the study was to detect possible distinctions in the quantitative values of two variables chosen and to select the variables which most significantly discriminate the group of class III orthodontic anomalies. Attempts were made to ascertain whether or not there were sex-related differences. The teleroentgenograms of 269 examines, aged 10-18 years, of both sexes were analyzed. The experimental group consisted of 89 examinees class III orthodontic anomalies. The control group consisted of 180 examines with eugnathic occlusion. Latero-lateral skull roentgenograms were taken observing the rules of roentgenocephalometry. Using acetate paper, the drawings of profile teleroentgenograms were elaborated and the reference points and lines were entered. A total of 38 variables were analyzed, of which there were 10 linear, 19 angular, and 8 variables were obtained by mathematical calculation; the age variable was also analyzed. In statistical analyses an electronic computer was used. The results are presented in tables and graphs. The results obtained showed that: --compared to the findings in the control group, the subjects in the experimental group displayed significant changes in the following craniofacial characteristics a negative difference in the position of the apical base of the jaw, manifest concavity of the osseous profile and diminished convexity of the profile of soft parts, retroinclination of the lower incisors, mandibular prognathism, increased mandibular angle and increased mandibular proportion compared to maxillary and the anterior cranial base; --with regard to the sex of the examinees, only four linear variables of significantly discriminating character were selected, so that in can be concluded that there were no significant sex differences among the morphological characteristics of the viscerocranium.

Automatic classification of spectral units in the Aristarchus plateau

NASA Astrophysics Data System (ADS)

Erard, S.; Le Mouelic, S.; Langevin, Y.

1999-09-01

A reduction scheme has been recently proposed for the NIR images of Clementine (Le Mouelic et al, JGR 1999). This reduction has been used to build an integrated UVvis-NIR image cube of the Aristarchus region, from which compositional and maturity variations can be studied (Pinet et al, LPSC 1999). We will present an analysis of this image cube, providing a classification in spectral types and spectral units. The image cube is processed with Gmode analysis using three different data sets: Normalized spectra provide a classification based mainly on spectral slope variations (ie. maturity and volcanic glasses). This analysis discriminates between craters plus ejecta, mare basalts, and DMD. Olivine-rich areas and Aristarchus central peak are also recognized. Continuum-removed spectra provide a classification more related to compositional variations, which correctly identifies olivine and pyroxenes-rich areas (in Aristarchus, Krieger, Schiaparelli\\ldots). A third analysis uses spectral parameters related to maturity and Fe composition (reflectance, 1 mu m band depth, and spectral slope) rather than intensities. It provides the most spatially consistent picture, but fails in detecting Vallis Schroeteri and DMDs. A supplementary unit, younger and rich in pyroxene, is found on Aristarchus south rim. In conclusion, Gmode analysis can discriminate between different spectral types already identified with more classic methods (PCA, linear mixing\\ldots). No previous assumption is made on the data structure, such as endmembers number and nature, or linear relationship between input variables. The variability of the spectral types is intrinsically accounted for, so that the level of analysis is always restricted to meaningful limits. A complete classification should integrate several analyses based on different sets of parameters. Gmode is therefore a powerful light toll to perform first look analysis of spectral imaging data. This research has been partly founded by the French Programme National de Planetologie.

Temporal lobe epilepsy: quantitative MR volumetry in detection of hippocampal atrophy.

PubMed

Farid, Nikdokht; Girard, Holly M; Kemmotsu, Nobuko; Smith, Michael E; Magda, Sebastian W; Lim, Wei Y; Lee, Roland R; McDonald, Carrie R

2012-08-01

To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration-cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Quantitative MR imaging-derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%-89.5%) and specificity (92.2%-94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice.

Financial Distress Prediction using Linear Discriminant Analysis and Support Vector Machine

NASA Astrophysics Data System (ADS)

Santoso, Noviyanti; Wibowo, Wahyu

2018-03-01

A financial difficulty is the early stages before the bankruptcy. Bankruptcies caused by the financial distress can be seen from the financial statements of the company. The ability to predict financial distress became an important research topic because it can provide early warning for the company. In addition, predicting financial distress is also beneficial for investors and creditors. This research will be made the prediction model of financial distress at industrial companies in Indonesia by comparing the performance of Linear Discriminant Analysis (LDA) and Support Vector Machine (SVM) combined with variable selection technique. The result of this research is prediction model based on hybrid Stepwise-SVM obtains better balance among fitting ability, generalization ability and model stability than the other models.

Perceptual asymmetry in texture perception.

PubMed

Williams, D; Julesz, B

1992-07-15

A fundamental property of human visual perception is our ability to distinguish between textures. A concerted effort has been made to account for texture segregation in terms of linear spatial filter models and their nonlinear extensions. However, for certain texture pairs the ease of discrimination changes when the role of figure and ground are reversed. This asymmetry poses a problem for both linear and nonlinear models. We have isolated a property of texture perception that can account for this asymmetry in discrimination: subjective closure. This property, which is also responsible for visual illusions, appears to be explainable by early visual processes alone. Our results force a reexamination of the process of human texture segregation and of some recent models that were introduced to explain it.

The Role of Ethnic and National Identifications in Perceived Discrimination for Asian Americans: Toward a Better Understanding of the Buffering Effect of Group Identifications on Psychological Distress

PubMed Central

Huynh, Que-Lam; Devos, Thierry; Goldberg, Robyn

2013-01-01

A robust relationship between perceived racial discrimination and psychological distress has been established. Yet, mixed evidence exists regarding the extent to which ethnic identification moderates this relationship, and scarce attention has been paid to the moderating role of national identification. We propose that the role of group identifications in the perceived discrimination–psychological distress relationship is best understood by simultaneously and interactively considering ethnic and national identifications. A sample of 259 Asian American students completed measures of perceived discrimination, group identifications (specific ethnic identification stated by respondents and national or “mainstream American” identification), and psychological distress (anxiety and depression symptoms). Regression analyses revealed a significant three-way interaction of perceived discrimination, ethnic identification, and national identification on psychological distress. Simple-slope analyses indicated that dual identification (strong ethnic and national identifications) was linked to a weaker relationship between perceived discrimination and psychological distress compared with other group identification configurations. These findings underscore the need to consider the interconnections between ethnic and national identifications to better understand the circumstances under which group identifications are likely to buffer individuals against the adverse effects of racial discrimination. PMID:25258674

Quantum teleportation via quantum channels with non-maximal Schmidt rank

NASA Astrophysics Data System (ADS)

Solís-Prosser, M. A.; Jiménez, O.; Neves, L.; Delgado, A.

2013-03-01

We study the problem of teleporting unknown pure states of a single qudit via a pure quantum channel with non-maximal Schmidt rank. We relate this process to the discrimination of linearly dependent symmetric states with the help of the maximum-confidence discrimination strategy. We show that with a certain probability, it is possible to teleport with a fidelity larger than the fidelity optimal deterministic teleportation.

ASTM clustering for improving coal analysis by near-infrared spectroscopy.

PubMed

Andrés, J M; Bona, M T

2006-11-15

Multivariate analysis techniques have been applied to near-infrared (NIR) spectra coals to investigate the relationship between nine coal properties (moisture (%), ash (%), volatile matter (%), fixed carbon (%), heating value (kcal/kg), carbon (%), hydrogen (%), nitrogen (%) and sulphur (%)) and the corresponding predictor variables. In this work, a whole set of coal samples was grouped into six more homogeneous clusters following the ASTM reference method for classification prior to the application of calibration methods to each coal set. The results obtained showed a considerable improvement of the error determination compared with the calibration for the whole sample set. For some groups, the established calibrations approached the quality required by the ASTM/ISO norms for laboratory analysis. To predict property values for a new coal sample it is necessary the assignation of that sample to its respective group. Thus, the discrimination and classification ability of coal samples by Diffuse Reflectance Infrared Fourier Transform Spectroscopy (DRIFTS) in the NIR range was also studied by applying Soft Independent Modelling of Class Analogy (SIMCA) and Linear Discriminant Analysis (LDA) techniques. Modelling of the groups by SIMCA led to overlapping models that cannot discriminate for unique classification. On the other hand, the application of Linear Discriminant Analysis improved the classification of the samples but not enough to be satisfactory for every group considered.

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

PubMed

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

2017-11-03

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

Comparison Of Eigenvector-Based Statistical Pattern Recognition Algorithms For Hybrid Processing

NASA Astrophysics Data System (ADS)

Tian, Q.; Fainman, Y.; Lee, Sing H.

1989-02-01

The pattern recognition algorithms based on eigenvector analysis (group 2) are theoretically and experimentally compared in this part of the paper. Group 2 consists of Foley-Sammon (F-S) transform, Hotelling trace criterion (HTC), Fukunaga-Koontz (F-K) transform, linear discriminant function (LDF) and generalized matched filter (GMF). It is shown that all eigenvector-based algorithms can be represented in a generalized eigenvector form. However, the calculations of the discriminant vectors are different for different algorithms. Summaries on how to calculate the discriminant functions for the F-S, HTC and F-K transforms are provided. Especially for the more practical, underdetermined case, where the number of training images is less than the number of pixels in each image, the calculations usually require the inversion of a large, singular, pixel correlation (or covariance) matrix. We suggest solving this problem by finding its pseudo-inverse, which requires inverting only the smaller, non-singular image correlation (or covariance) matrix plus multiplying several non-singular matrices. We also compare theoretically the effectiveness for classification with the discriminant functions from F-S, HTC and F-K with LDF and GMF, and between the linear-mapping-based algorithms and the eigenvector-based algorithms. Experimentally, we compare the eigenvector-based algorithms using a set of image data bases each image consisting of 64 x 64 pixels.

Smart smoke alarm

DOEpatents

Warmack, Robert J. Bruce; Wolf, Dennis A; Frank, Steven Shane

2015-04-28

Methods and apparatus for smoke detection are disclosed. In one embodiment, a smoke detector uses linear discriminant analysis (LDA) to determine whether observed conditions indicate that an alarm is warranted.

Data mining methods in the prediction of Dementia: A real-data comparison of the accuracy, sensitivity and specificity of linear discriminant analysis, logistic regression, neural networks, support vector machines, classification trees and random forests

PubMed Central

2011-01-01

Background Dementia and cognitive impairment associated with aging are a major medical and social concern. Neuropsychological testing is a key element in the diagnostic procedures of Mild Cognitive Impairment (MCI), but has presently a limited value in the prediction of progression to dementia. We advance the hypothesis that newer statistical classification methods derived from data mining and machine learning methods like Neural Networks, Support Vector Machines and Random Forests can improve accuracy, sensitivity and specificity of predictions obtained from neuropsychological testing. Seven non parametric classifiers derived from data mining methods (Multilayer Perceptrons Neural Networks, Radial Basis Function Neural Networks, Support Vector Machines, CART, CHAID and QUEST Classification Trees and Random Forests) were compared to three traditional classifiers (Linear Discriminant Analysis, Quadratic Discriminant Analysis and Logistic Regression) in terms of overall classification accuracy, specificity, sensitivity, Area under the ROC curve and Press'Q. Model predictors were 10 neuropsychological tests currently used in the diagnosis of dementia. Statistical distributions of classification parameters obtained from a 5-fold cross-validation were compared using the Friedman's nonparametric test. Results Press' Q test showed that all classifiers performed better than chance alone (p < 0.05). Support Vector Machines showed the larger overall classification accuracy (Median (Me) = 0.76) an area under the ROC (Me = 0.90). However this method showed high specificity (Me = 1.0) but low sensitivity (Me = 0.3). Random Forest ranked second in overall accuracy (Me = 0.73) with high area under the ROC (Me = 0.73) specificity (Me = 0.73) and sensitivity (Me = 0.64). Linear Discriminant Analysis also showed acceptable overall accuracy (Me = 0.66), with acceptable area under the ROC (Me = 0.72) specificity (Me = 0.66) and sensitivity (Me = 0.64). The remaining classifiers showed overall classification accuracy above a median value of 0.63, but for most sensitivity was around or even lower than a median value of 0.5. Conclusions When taking into account sensitivity, specificity and overall classification accuracy Random Forests and Linear Discriminant analysis rank first among all the classifiers tested in prediction of dementia using several neuropsychological tests. These methods may be used to improve accuracy, sensitivity and specificity of Dementia predictions from neuropsychological testing. PMID:21849043

Contrast effects on speed perception for linear and radial motion.

PubMed

Champion, Rebecca A; Warren, Paul A

2017-11-01

Speed perception is vital for safe activity in the environment. However, considerable evidence suggests that perceived speed changes as a function of stimulus contrast, with some investigators suggesting that this might have meaningful real-world consequences (e.g. driving in fog). In the present study we investigate whether the neural effects of contrast on speed perception occur at the level of local or global motion processing. To do this we examine both speed discrimination thresholds and contrast-dependent speed perception for two global motion configurations that have matched local spatio-temporal structure. Specifically we compare linear and radial configurations, the latter of which arises very commonly due to self-movement. In experiment 1 the stimuli comprised circular grating patches. In experiment 2, to match stimuli even more closely, motion was presented in multiple local Gabor patches equidistant from central fixation. Each patch contained identical linear motion but the global configuration was either consistent with linear or radial motion. In both experiments 1 and 2, discrimination thresholds and contrast-induced speed biases were similar in linear and radial conditions. These results suggest that contrast-based speed effects occur only at the level of local motion processing, irrespective of global structure. This result is interpreted in the context of previous models of speed perception and evidence suggesting differences in perceived speed of locally matched linear and radial stimuli. Copyright © 2017 Elsevier Ltd. All rights reserved.

Color Trails Test: normative data and criterion validity for the greek adult population.

PubMed

Messinis, Lambros; Malegiannaki, Amaryllis-Chryssi; Christodoulou, Tessa; Panagiotopoulos, Vassillis; Papathanasopoulos, Panagiotis

2011-06-01

The Color Trails Test (CTT) was developed as a culturally fair analog of the Trail Making Test. In the present study, normative data for the CTT were developed for the Greek adult population and further the criterion validity of the CTT was examined in two clinical groups (29 Parkinson's disease [PD] and 25 acute stroke patients). The instrument was applied to 163 healthy participants, aged 19-75. Stepwise linear regression analyses revealed a significant influence of age and education level on completion time in both parts of the CTT (increased age and decreased educational level contributed to slower completion times for both parts), whereas gender did not influence time to completion of part B. Further, the CTT appears to discriminate adequately between the performance of PD and acute stroke patients and matched healthy controls.

Discrimination, Acculturation and Other Predictors of Depression among Pregnant Hispanic Women

PubMed Central

Walker, Janiece L.; Ruiz, R. Jeanne; Chinn, Juanita J.; Marti, Nathan; Ricks, Tiffany N.

2012-01-01

Objective The purpose of our study was to examine the effects of socioeconomic status, acculturative stress, discrimination, and marginalization as predictors of depression in pregnant Hispanic women. Design A prospective observational design was used. Setting Central and Gulf coast areas of Texas in obstetrical offices. Participants A convenience sample of 515 pregnant, low income, low medical risk, and self-identified Hispanic women who were between 22–24 weeks gestation was used to collect data. Measures The predictor variables were socioeconomic status, discrimination, acculturative stress, and marginalization. The outcome variable was depression. Results Education, frequency of discrimination, age, and Anglo marginality were significant predictors of depressive symptoms in a linear regression model, F (6, 458) = 8.36, P<.0001. Greater frequency of discrimination was the strongest positive predictor of increased depressive symptoms. Conclusions It is important that health care providers further understand the impact that age and experiences of discrimination throughout the life course have on depressive symptoms during pregnancy. PMID:23140083

An electroglottographical analysis-based discriminant function model differentiating multiple sclerosis patients from healthy controls.

PubMed

Vavougios, George D; Doskas, Triantafyllos; Konstantopoulos, Kostas

2018-05-01

Dysarthrophonia is a predominant symptom in many neurological diseases, affecting the quality of life of the patients. In this study, we produced a discriminant function equation that can differentiate MS patients from healthy controls, using electroglottographic variables not analyzed in a previous study. We applied stepwise linear discriminant function analysis in order to produce a function and score derived from electroglottographic variables extracted from a previous study. The derived discriminant function's statistical significance was determined via Wilk's λ test (and the associated p value). Finally, a 2 × 2 confusion matrix was used to determine the function's predictive accuracy, whereas the cross-validated predictive accuracy is estimated via the "leave-one-out" classification process. Discriminant function analysis (DFA) was used to create a linear function of continuous predictors. DFA produced the following model (Wilk's λ = 0.043, χ2 = 388.588, p < 0.0001, Tables 3 and 4): D (MS vs controls) = 0.728*DQx1 mean monologue + 0.325*CQx monologue + 0.298*DFx1 90% range monologue + 0.443*DQx1 90% range reading - 1.490*DQx1 90% range monologue. The derived discriminant score (S1) was used subsequently in order to form the coordinates of a ROC curve. Thus, a cutoff score of - 0.788 for S1 corresponded to a perfect classification (100% sensitivity and 100% specificity, p = 1.67e -22 ). Consistent with previous findings, electroglottographic evaluation represents an easy to implement and potentially important assessment in MS patients, achieving adequate classification accuracy. Further evaluation is needed to determine its use as a biomarker.

Discriminating Among Probability Weighting Functions Using Adaptive Design Optimization

PubMed Central

Cavagnaro, Daniel R.; Pitt, Mark A.; Gonzalez, Richard; Myung, Jay I.

2014-01-01

Probability weighting functions relate objective probabilities and their subjective weights, and play a central role in modeling choices under risk within cumulative prospect theory. While several different parametric forms have been proposed, their qualitative similarities make it challenging to discriminate among them empirically. In this paper, we use both simulation and choice experiments to investigate the extent to which different parametric forms of the probability weighting function can be discriminated using adaptive design optimization, a computer-based methodology that identifies and exploits model differences for the purpose of model discrimination. The simulation experiments show that the correct (data-generating) form can be conclusively discriminated from its competitors. The results of an empirical experiment reveal heterogeneity between participants in terms of the functional form, with two models (Prelec-2, Linear in Log Odds) emerging as the most common best-fitting models. The findings shed light on assumptions underlying these models. PMID:24453406

Temperature Gradient Effect on Gas Discrimination Power of a Metal-Oxide Thin-Film Sensor Microarray

PubMed Central

Sysoev, Victor V.; Kiselev, Ilya; Frietsch, Markus; Goschnick, Joachim

2004-01-01

The paper presents results concerning the effect of spatial inhomogeneous operating temperature on the gas discrimination power of a gas-sensor microarray, with the latter based on a thin SnO2 film employed in the KAMINA electronic nose. Three different temperature distributions over the substrate are discussed: a nearly homogeneous one and two temperature gradients, equal to approx. 3.3 °C/mm and 6.7 °C/mm, applied across the sensor elements (segments) of the array. The gas discrimination power of the microarray is judged by using the Mahalanobis distance in the LDA (Linear Discrimination Analysis) coordinate system between the data clusters obtained by the response of the microarray to four target vapors: ethanol, acetone, propanol and ammonia. It is shown that the application of a temperature gradient increases the gas discrimination power of the microarray by up to 35 %.

Statistical classification approach to discrimination between weak earthquakes and quarry blasts recorded by the Israel Seismic Network

NASA Astrophysics Data System (ADS)

Kushnir, A. F.; Troitsky, E. V.; Haikin, L. M.; Dainty, A.

1999-06-01

A semi-automatic procedure has been developed to achieve statistically optimum discrimination between earthquakes and explosions at local or regional distances based on a learning set specific to a given region. The method is used for step-by-step testing of candidate discrimination features to find the optimum (combination) subset of features, with the decision taken on a rigorous statistical basis. Linear (LDF) and Quadratic (QDF) Discriminant Functions based on Gaussian distributions of the discrimination features are implemented and statistically grounded; the features may be transformed by the Box-Cox transformation z=(1/ α)( yα-1) to make them more Gaussian. Tests of the method were successfully conducted on seismograms from the Israel Seismic Network using features consisting of spectral ratios between and within phases. Results showed that the QDF was more effective than the LDF and required five features out of 18 candidates for the optimum set. It was found that discrimination improved with increasing distance within the local range, and that eliminating transformation of the features and failing to correct for noise led to degradation of discrimination.

Direct discriminant locality preserving projection with Hammerstein polynomial expansion.

PubMed

Chen, Xi; Zhang, Jiashu; Li, Defang

2012-12-01

Discriminant locality preserving projection (DLPP) is a linear approach that encodes discriminant information into the objective of locality preserving projection and improves its classification ability. To enhance the nonlinear description ability of DLPP, we can optimize the objective function of DLPP in reproducing kernel Hilbert space to form a kernel-based discriminant locality preserving projection (KDLPP). However, KDLPP suffers the following problems: 1) larger computational burden; 2) no explicit mapping functions in KDLPP, which results in more computational burden when projecting a new sample into the low-dimensional subspace; and 3) KDLPP cannot obtain optimal discriminant vectors, which exceedingly optimize the objective of DLPP. To overcome the weaknesses of KDLPP, in this paper, a direct discriminant locality preserving projection with Hammerstein polynomial expansion (HPDDLPP) is proposed. The proposed HPDDLPP directly implements the objective of DLPP in high-dimensional second-order Hammerstein polynomial space without matrix inverse, which extracts the optimal discriminant vectors for DLPP without larger computational burden. Compared with some other related classical methods, experimental results for face and palmprint recognition problems indicate the effectiveness of the proposed HPDDLPP.

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

Demonstration of iodine K-edge imaging by use of an energy-discrimination X-ray computed tomography system with a cadmium telluride detector.

PubMed

Abudurexiti, Abulajiang; Kameda, Masashi; Sato, Eiichi; Abderyim, Purkhet; Enomoto, Toshiyuki; Watanabe, Manabu; Hitomi, Keitaro; Tanaka, Etsuro; Mori, Hidezo; Kawai, Toshiaki; Takahashi, Kiyomi; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2010-07-01

An energy-discrimination K-edge X-ray computed tomography (CT) system is useful for increasing the contrast resolution of a target region by utilizing contrast media. The CT system has a cadmium telluride (CdTe) detector, and a projection curve is obtained by linear scanning with use of the CdTe detector in conjunction with an X-stage. An object is rotated by a rotation step angle with use of a turntable between the linear scans. Thus, CT is carried out by repetition of the linear scanning and the rotation of an object. Penetrating X-ray photons from the object are detected by the CdTe detector, and event signals of X-ray photons are produced with use of charge-sensitive and shaping amplifiers. Both the photon energy and the energy width are selected by use of a multi-channel analyzer, and the number of photons is counted by a counter card. For performing energy discrimination, a low-dose-rate X-ray generator for photon counting was developed; the maximum tube voltage and the minimum tube current were 110 kV and 1.0 microA, respectively. In energy-discrimination CT, the tube voltage and the current were 60 kV and 20.0 microA, respectively, and the X-ray intensity was 0.735 microGy/s at 1.0 m from the source and with a tube voltage of 60 kV. Demonstration of enhanced iodine K-edge X-ray CT was carried out by selection of photons with energies just beyond the iodine K-edge energy of 33.2 keV.

Gender classification of running subjects using full-body kinematics

NASA Astrophysics Data System (ADS)

Williams, Christina M.; Flora, Jeffrey B.; Iftekharuddin, Khan M.

2016-05-01

This paper proposes novel automated gender classification of subjects while engaged in running activity. The machine learning techniques include preprocessing steps using principal component analysis followed by classification with linear discriminant analysis, and nonlinear support vector machines, and decision-stump with AdaBoost. The dataset consists of 49 subjects (25 males, 24 females, 2 trials each) all equipped with approximately 80 retroreflective markers. The trials are reflective of the subject's entire body moving unrestrained through a capture volume at a self-selected running speed, thus producing highly realistic data. The classification accuracy using leave-one-out cross validation for the 49 subjects is improved from 66.33% using linear discriminant analysis to 86.74% using the nonlinear support vector machine. Results are further improved to 87.76% by means of implementing a nonlinear decision stump with AdaBoost classifier. The experimental findings suggest that the linear classification approaches are inadequate in classifying gender for a large dataset with subjects running in a moderately uninhibited environment.

Reflex Cough and Disease Duration as Predictors of Swallowing Dysfunction in Parkinson's Disease.

PubMed

Troche, Michelle S; Schumann, Beate; Brandimore, Alexandra E; Okun, Michael S; Hegland, Karen W

2016-12-01

Patients with Parkinson's disease (PD) have progressive and pervasive disorders of airway protection. Recent work has highlighted the relationship between reflex and voluntary cough and swallowing safety. The goal of this study was to test the sensitivity and specificity of several airway protective and disease-specific factors for predicting swallowing safety outcomes in PD. Sixty-four participants (44 males) completed measures of voluntary and reflex cough, and swallowing safety. Clinical predictors included disease severity and duration, and cough airflow and sensitivity measures. ROC and Chi-square analyses identified predictors of swallowing safety (penetration-aspiration score) in PD. Disease duration significantly discriminated between patients with normal and abnormal swallowing safety (p = 0.027, sensitivity: 71 %, specificity: 55.4 %). Cough reflex sensitivity significantly discriminated between patients who penetrated above the level of the vocal folds and those with more severe penetration/aspiration (p = 0.021, sensitivity: 71.0 %, specificity 57.6 %). Urge-to-cough sensitivity (log-log linear slope) was the only variable which significantly discriminated between patients with penetration versus aspiration (p = 0.017, sensitivity: 85.7 %, specificity 73.2 %). It is important to identify the factors which influence airway protective outcomes in PD especially given that aspiration pneumonia is a leading cause of death. Results from this study highlight the ecological validity of reflex cough in the study of airway protection and this study further identifies important factors to consider in the screening of airway protective deficits in PD.

Remote Sensing as a Landscape Epidemiologic Tool to Identify Villages at High Risk for Malaria Transmission

NASA Technical Reports Server (NTRS)

Beck, Louisa R.; Rodriquez, Mario H.; Dister, Sheri W.; Rodriquez, Americo D.; Rejmankova, Eliska; Ulloa, Armando; Meza, Rosa A.; Roberts, Donald R.; Paris, Jack F.; Spanner, Michael A.;

Prototypes and same-gender bias in perceptions of hiring discrimination.

PubMed

Carlsson, Rickard; Sinclair, Samantha

2018-01-01

The present study investigated the relative importance of two explanations behind perceptions of gender discrimination in hiring: prototypes and same-gender bias. According to the prototype explanation, people perceive an event as discrimination to the extent that it fits their preconceptions of typical discrimination. In contrast, the same-gender bias explanation asserts that people more readily detect discrimination toward members of their own gender. In four experiments (n = 797), women and men made considerably stronger discrimination attributions, and were moderately more discouraged from seeking work, when the victim was female rather than male. Further, a series of regressions analyses showed beliefs in discrimination of women to be moderately correlated with discrimination attributions of female victims, but little added explanatory value of participant gender, stigma consciousness, or feminist identification. The results offer strong support for the prototype explanation.

Discriminatory experiences associated with posttraumatic stress disorder symptoms among transgender adults

PubMed Central

Reisner, Sari L.; White Hughto, Jaclyn M.; Gamarel, Kristi E.; Keuroghlian, Alex S.; Mizock, Lauren; Pachankis, John

2016-01-01

Discrimination has been shown to disproportionately burden transgender people; however, there has been a lack of clinical attention to the mental health sequelae of discrimination, including posttraumatic stress disorder (PTSD) symptoms. Additionally, few studies contextualize discrimination alongside other traumatic stressors in predicting PTSD symptomatology. The current study sought to fill these gaps. A community-based sample of 412 transgender adults (mean age 33, SD=13; 63% female-to-male spectrum; 19% people of color; 88% sampled online) completed a cross-sectional self-report survey of everyday discrimination experiences and PTSD symptoms. Multivariable linear regression models examined the association between self-reported everyday discrimination experiences, number of attributed domains of discrimination, and PTSD symptoms, adjusting for prior trauma, sociodemographics, and psychosocial co-morbidity. The mean number of discrimination attributions endorsed was 4.8 (SD=2.4) and the five most frequently reported reasons for discrimination were: gender identity and/or expression (83%), masculine and feminine appearance (79%), sexual orientation (68%), sex (57%), and age (44%). Higher everyday discrimination scores (β=0.25; 95% CL=0.21–0.30) and greater number of attributed reasons for discrimination experiences (β=0.05; 95% CL=0.01–0.10) were independently associated with PTSD symptoms, even after adjusting for prior trauma experiences. Everyday discrimination experiences from multiple sources necessitate clinical consideration in treatment for PTSD symptoms in transgender people. PMID:26866637

Discriminatory experiences associated with posttraumatic stress disorder symptoms among transgender adults.

PubMed

Reisner, Sari L; White Hughto, Jaclyn M; Gamarel, Kristi E; Keuroghlian, Alex S; Mizock, Lauren; Pachankis, John E

2016-10-01

Discrimination has been shown to disproportionately burden transgender people; however, there has been a lack of clinical attention to the mental health sequelae of discrimination, including posttraumatic stress disorder (PTSD) symptoms. Additionally, few studies contextualize discrimination alongside other traumatic stressors in predicting PTSD symptomatology. The current study sought to fill these gaps. A community-based sample of 412 transgender adults (mean age 33, SD = 13; 63% female-to-male spectrum; 19% people of color; 88% sampled online) completed a cross-sectional self-report survey of everyday discrimination experiences and PTSD symptoms. Multivariable linear regression models examined the association between self-reported everyday discrimination experiences, number of attributed domains of discrimination, and PTSD symptoms, adjusting for prior trauma, sociodemographics, and psychosocial comorbidity. The mean number of discrimination attributions endorsed was 4.8 (SD = 2.4) and the 5 most frequently reported reasons for discrimination were: gender identity and/or expression (83%), masculine and feminine appearance (79%), sexual orientation (68%), sex (57%), and age (44%). Higher everyday discrimination scores (β = 0.25; 95% CL [0.21, 0.30]) and greater number of attributed reasons for discrimination experiences (β = 0.05; 95% CL [0.01, 0.10]) were independently associated with PTSD symptoms, even after adjusting for prior trauma experiences. Everyday discrimination experiences from multiple sources necessitate clinical consideration in treatment for PTSD symptoms in transgender people. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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.

A Combinatorial Kin Discrimination System in Bacillus subtilis.

PubMed

Lyons, Nicholas A; Kraigher, Barbara; Stefanic, Polonca; Mandic-Mulec, Ines; Kolter, Roberto

2016-03-21

Multicellularity inherently involves a number of cooperative behaviors that are potentially susceptible to exploitation but can be protected by mechanisms such as kin discrimination. Discrimination of kin from non-kin has been observed in swarms of the bacterium Bacillus subtilis, but the underlying molecular mechanism has been unknown. We used genetic, transcriptomic, and bioinformatic analyses to uncover kin recognition factors in this organism. Our results identified many molecules involved in cell-surface modification and antimicrobial production and response. These genes varied significantly in expression level and mutation phenotype among B. subtilis strains, suggesting interstrain variation in the exact kin discrimination mechanism used. Genome analyses revealed a substantial diversity of antimicrobial genes present in unique combinations in different strains, with many likely acquired by horizontal gene transfer. The dynamic combinatorial effect derived from this plethora of kin discrimination genes creates a tight relatedness cutoff for cooperation that has likely led to rapid diversification within the species. Our data suggest that genes likely originally selected for competitive purposes also generate preferential interactions among kin, thus stabilizing multicellular lifestyles. Copyright © 2016 Elsevier Ltd. All rights reserved.

Near-infrared Raman spectroscopy for estimating biochemical changes associated with different pathological conditions of cervix

NASA Astrophysics Data System (ADS)

Daniel, Amuthachelvi; Prakasarao, Aruna; Ganesan, Singaravelu

2018-02-01

The molecular level changes associated with oncogenesis precede the morphological changes in cells and tissues. Hence molecular level diagnosis would promote early diagnosis of the disease. Raman spectroscopy is capable of providing specific spectral signature of various biomolecules present in the cells and tissues under various pathological conditions. The aim of this work is to develop a non-linear multi-class statistical methodology for discrimination of normal, neoplastic and malignant cells/tissues. The tissues were classified as normal, pre-malignant and malignant by employing Principal Component Analysis followed by Artificial Neural Network (PC-ANN). The overall accuracy achieved was 99%. Further, to get an insight into the quantitative biochemical composition of the normal, neoplastic and malignant tissues, a linear combination of the major biochemicals by non-negative least squares technique was fit to the measured Raman spectra of the tissues. This technique confirms the changes in the major biomolecules such as lipids, nucleic acids, actin, glycogen and collagen associated with the different pathological conditions. To study the efficacy of this technique in comparison with histopathology, we have utilized Principal Component followed by Linear Discriminant Analysis (PC-LDA) to discriminate the well differentiated, moderately differentiated and poorly differentiated squamous cell carcinoma with an accuracy of 94.0%. And the results demonstrated that Raman spectroscopy has the potential to complement the good old technique of histopathology.

Evaluation of linear discriminant analysis for automated Raman histological mapping of esophageal high-grade dysplasia

NASA Astrophysics Data System (ADS)

Hutchings, Joanne; Kendall, Catherine; Shepherd, Neil; Barr, Hugh; Stone, Nicholas

2010-11-01

Rapid Raman mapping has the potential to be used for automated histopathology diagnosis, providing an adjunct technique to histology diagnosis. The aim of this work is to evaluate the feasibility of automated and objective pathology classification of Raman maps using linear discriminant analysis. Raman maps of esophageal tissue sections are acquired. Principal component (PC)-fed linear discriminant analysis (LDA) is carried out using subsets of the Raman map data (6483 spectra). An overall (validated) training classification model performance of 97.7% (sensitivity 95.0 to 100% and specificity 98.6 to 100%) is obtained. The remainder of the map spectra (131,672 spectra) are projected onto the classification model resulting in Raman images, demonstrating good correlation with contiguous hematoxylin and eosin (HE) sections. Initial results suggest that LDA has the potential to automate pathology diagnosis of esophageal Raman images, but since the classification of test spectra is forced into existing training groups, further work is required to optimize the training model. A small pixel size is advantageous for developing the training datasets using mapping data, despite lengthy mapping times, due to additional morphological information gained, and could facilitate differentiation of further tissue groups, such as the basal cells/lamina propria, in the future, but larger pixels sizes (and faster mapping) may be more feasible for clinical application.

Application of recurrence quantification analysis to automatically estimate infant sleep states using a single channel of respiratory data.

PubMed

Terrill, Philip I; Wilson, Stephen J; Suresh, Sadasivam; Cooper, David M; Dakin, Carolyn

2012-08-01

Previous work has identified that non-linear variables calculated from respiratory data vary between sleep states, and that variables derived from the non-linear analytical tool recurrence quantification analysis (RQA) are accurate infant sleep state discriminators. This study aims to apply these discriminators to automatically classify 30 s epochs of infant sleep as REM, non-REM and wake. Polysomnograms were obtained from 25 healthy infants at 2 weeks, 3, 6 and 12 months of age, and manually sleep staged as wake, REM and non-REM. Inter-breath interval data were extracted from the respiratory inductive plethysmograph, and RQA applied to calculate radius, determinism and laminarity. Time-series statistic and spectral analysis variables were also calculated. A nested cross-validation method was used to identify the optimal feature subset, and to train and evaluate a linear discriminant analysis-based classifier. The RQA features radius and laminarity and were reliably selected. Mean agreement was 79.7, 84.9, 84.0 and 79.2 % at 2 weeks, 3, 6 and 12 months, and the classifier performed better than a comparison classifier not including RQA variables. The performance of this sleep-staging tool compares favourably with inter-human agreement rates, and improves upon previous systems using only respiratory data. Applications include diagnostic screening and population-based sleep research.

Prediction of aquatic toxicity mode of action using linear discriminant and random forest models.

PubMed

Martin, Todd M; Grulke, Christopher M; Young, Douglas M; Russom, Christine L; Wang, Nina Y; Jackson, Crystal R; Barron, Mace G

2013-09-23

The ability to determine the mode of action (MOA) for a diverse group of chemicals is a critical part of ecological risk assessment and chemical regulation. However, existing MOA assignment approaches in ecotoxicology have been limited to a relatively few MOAs, have high uncertainty, or rely on professional judgment. In this study, machine based learning algorithms (linear discriminant analysis and random forest) were used to develop models for assigning aquatic toxicity MOA. These methods were selected since they have been shown to be able to correlate diverse data sets and provide an indication of the most important descriptors. A data set of MOA assignments for 924 chemicals was developed using a combination of high confidence assignments, international consensus classifications, ASTER (ASessment Tools for the Evaluation of Risk) predictions, and weight of evidence professional judgment based an assessment of structure and literature information. The overall data set was randomly divided into a training set (75%) and a validation set (25%) and then used to develop linear discriminant analysis (LDA) and random forest (RF) MOA assignment models. The LDA and RF models had high internal concordance and specificity and were able to produce overall prediction accuracies ranging from 84.5 to 87.7% for the validation set. These results demonstrate that computational chemistry approaches can be used to determine the acute toxicity MOAs across a large range of structures and mechanisms.

3-D Ultrasound Vascularity Assessment for Breast Cancer Diagnosis

DTIC Science & Technology

1998-09-01

ultrasound imaging in discriminating benign from malignant known masses . Preliminary data analyses were completed on new trials and contributions were made...specificity of ultrasound imaging in discriminating benign from malignant known masses . Increasingly we and others will look toward expanded roles in...evaluate which Doppler signals might provide discrimination of breast cancer from benign masses and to compare 2D and 3D ultrasound display modes.

An integrated analysis for determining the geographical origin of medicinal herbs using ICP-AES/ICP-MS and (1)H NMR analysis.

PubMed

Kwon, Yong-Kook; Bong, Yeon-Sik; Lee, Kwang-Sik; Hwang, Geum-Sook

2014-10-15

ICP-MS and (1)H NMR are commonly used to determine the geographical origin of food and crops. In this study, data from multielemental analysis performed by ICP-AES/ICP-MS and metabolomic data obtained from (1)H NMR were integrated to improve the reliability of determining the geographical origin of medicinal herbs. Astragalus membranaceus and Paeonia albiflora with different origins in Korea and China were analysed by (1)H NMR and ICP-AES/ICP-MS, and an integrated multivariate analysis was performed to characterise the differences between their origins. Four classification methods were applied: linear discriminant analysis (LDA), k-nearest neighbour classification (KNN), support vector machines (SVM), and partial least squares-discriminant analysis (PLS-DA). Results were compared using leave-one-out cross-validation and external validation. The integration of multielemental and metabolomic data was more suitable for determining geographical origin than the use of each individual data set alone. The integration of the two analytical techniques allowed diverse environmental factors such as climate and geology, to be considered. Our study suggests that an appropriate integration of different types of analytical data is useful for determining the geographical origin of food and crops with a high degree of reliability. Copyright © 2014 Elsevier Ltd. All rights reserved.

Kinematic patterns underlying disguised movements: Spatial and temporal dissimilarity compared to genuine movement patterns.

PubMed

Helm, Fabian; Munzert, Jörn; Troje, Nikolaus F

2017-08-01

This study examined the kinematic characteristics of disguised movements by applying linear discriminant (LDA) and dissimilarity analyses to the motion data from 788 disguised and 792 non-disguised 7-m penalty throws performed by novice and expert handball field players. Results of the LDA showed that discrimination between type of throws (disguised vs. non-disguised) was more error-prone when throws were performed by experts (spatial: 4.6%; temporal: 29.6%) compared to novices (spatial: 1.0%; temporal: 20.2%). The dissimilarity analysis revealed significantly smaller spatial dissimilarities and variations between type of throws in experts compared to novices (p<0.001), but also showed that these spatial dissimilarities and variations increased significantly in both groups the closer the throws came to the moment of (predicted) ball release. In contrast, temporal dissimilarities did not differ significantly between groups. Thus, our data clearly demonstrate that expertise in disguising one's own action intentions results in an ability to perform disguised penalty throws that are highly similar to genuine throws. We suggest that this expertise depends mainly on keeping spatial dissimilarities small. However, the attempt to disguise becomes a challenge the closer one gets to the action outcome (i.e., ball release) becoming visible. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid analysis of Aurantii Fructus Immaturus (Zhishi) using paper spray ionization mass spectrometry.

PubMed

Liu, Xuemei; Gu, Zhixin; Guo, Yuan; Liu, Jingjing; Ma, Ming; Chen, Bo; Wang, Liping

2017-04-15

Paper spray-mass spectrometry (PS-MS) is a rapid, solvent-efficient, and high-throughput analytical method for analyzing complex samples. In this study, a PS-MS method was developed to obtain MS profiles of Aurantii Fructus Immaturus (aka Zhishi in Chinese) in positive and negative ion modes. In combination with multivariate analyses, including principal component analysis and cluster analysis, the PS-MS profiles of 25 batches of Zhishi were discriminated in 25 batches of Citri Reticulatae Pericarpium Viride (aka Qingpi in Chinese; an adulterant of Zhishi). Moreover, a rapid quantitative analysis of synephrine, a prescriptive quality control component of Zhishi listed in the Chinese Pharmacopoeia, was conducted with PS-MS using synephrine-d2 as an internal standard (IS). The linearity range was 1.68-16.8μg/mL (R 2 =0.9985), the limit of quantitation was 0.5μg/mL. Relative standard deviations in the intra- and inter-day precision of the MS were 4.87 and 4.90%, respectively. Compared with HPLC results, there was no significant difference in the quantitation of synephrine. This study demonstrated that the PS-MS method is useful for the rapid discrimination and quality control of Zhishi samples. Copyright © 2017 Elsevier B.V. All rights reserved.

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearinga)

PubMed Central

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-01-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes. PMID:26233047

Comparing auditory filter bandwidths, spectral ripple modulation detection, spectral ripple discrimination, and speech recognition: Normal and impaired hearing.

PubMed

Davies-Venn, Evelyn; Nelson, Peggy; Souza, Pamela

2015-07-01

Some listeners with hearing loss show poor speech recognition scores in spite of using amplification that optimizes audibility. Beyond audibility, studies have suggested that suprathreshold abilities such as spectral and temporal processing may explain differences in amplified speech recognition scores. A variety of different methods has been used to measure spectral processing. However, the relationship between spectral processing and speech recognition is still inconclusive. This study evaluated the relationship between spectral processing and speech recognition in listeners with normal hearing and with hearing loss. Narrowband spectral resolution was assessed using auditory filter bandwidths estimated from simultaneous notched-noise masking. Broadband spectral processing was measured using the spectral ripple discrimination (SRD) task and the spectral ripple depth detection (SMD) task. Three different measures were used to assess unamplified and amplified speech recognition in quiet and noise. Stepwise multiple linear regression revealed that SMD at 2.0 cycles per octave (cpo) significantly predicted speech scores for amplified and unamplified speech in quiet and noise. Commonality analyses revealed that SMD at 2.0 cpo combined with SRD and equivalent rectangular bandwidth measures to explain most of the variance captured by the regression model. Results suggest that SMD and SRD may be promising clinical tools for diagnostic evaluation and predicting amplification outcomes.

Characteristics of Mild Cognitive Impairment Using the Thai Version of the Consortium to Establish a Registry for Alzheimer's Disease Tests: A Multivariate and Machine Learning Study.

PubMed

Tunvirachaisakul, Chavit; Supasitthumrong, Thitiporn; Tangwongchai, Sookjareon; Hemrunroj, Solaphat; Chuchuen, Phenphichcha; Tawankanjanachot, Itthipol; Likitchareon, Yuthachai; Phanthumchinda, Kamman; Sriswasdi, Sira; Maes, Michael

2018-04-04

The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) developed a neuropsychological battery (CERAD-NP) to screen patients with Alzheimer's dementia. Mild cognitive impairment (MCI) has received attention as a pre-dementia stage. To delineate the CERAD-NP features of MCI and their clinical utility to externally validate MCI diagnosis. The study included 60 patients with MCI, diagnosed using the Clinical Dementia Rating, and 63 normal controls. Data were analysed employing receiver operating characteristic analysis, Linear Support Vector Machine, Random Forest, Adaptive Boosting, Neural Network models, and t-distributed stochastic neighbour embedding (t-SNE). MCI patients were best discriminated from normal controls using a combination of Wordlist Recall, Wordlist Memory, and Verbal Fluency Test. Machine learning showed that the CERAD features learned from MCI patients and controls were not strongly predictive of the diagnosis (maximal cross-validation 77.2%), whilst t-SNE showed that there is a considerable overlap between MCI and controls. The most important features of the CERAD-NP differentiating MCI from normal controls indicate impairments in episodic and semantic memory and recall. While these features significantly discriminate MCI patients from normal controls, the tests are not predictive of MCI. © 2018 S. Karger AG, Basel.

Non-targeted 1H NMR fingerprinting and multivariate statistical analyses for the characterisation of the geographical origin of Italian sweet cherries.

PubMed

Longobardi, F; Ventrella, A; Bianco, A; Catucci, L; Cafagna, I; Gallo, V; Mastrorilli, P; Agostiano, A

2013-12-01

In this study, non-targeted (1)H NMR fingerprinting was used in combination with multivariate statistical techniques for the classification of Italian sweet cherries based on their different geographical origins (Emilia Romagna and Puglia). As classification techniques, Soft Independent Modelling of Class Analogy (SIMCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Linear Discriminant Analysis (LDA) were carried out and the results were compared. For LDA, before performing a refined selection of the number/combination of variables, two different strategies for a preliminary reduction of the variable number were tested. The best average recognition and CV prediction abilities (both 100.0%) were obtained for all the LDA models, although PLS-DA also showed remarkable performances (94.6%). All the statistical models were validated by observing the prediction abilities with respect to an external set of cherry samples. The best result (94.9%) was obtained with LDA by performing a best subset selection procedure on a set of 30 principal components previously selected by a stepwise decorrelation. The metabolites that mostly contributed to the classification performances of such LDA model, were found to be malate, glucose, fructose, glutamine and succinate. Copyright © 2013 Elsevier Ltd. All rights reserved.

Discrimination of curvature from motion during smooth pursuit eye movements and fixation.

PubMed

Ross, Nicholas M; Goettker, Alexander; Schütz, Alexander C; Braun, Doris I; Gegenfurtner, Karl R

2017-09-01

Smooth pursuit and motion perception have mainly been investigated with stimuli moving along linear trajectories. Here we studied the quality of pursuit movements to curved motion trajectories in human observers and examined whether the pursuit responses would be sensitive enough to discriminate various degrees of curvature. In a two-interval forced-choice task subjects pursued a Gaussian blob moving along a curved trajectory and then indicated in which interval the curve was flatter. We also measured discrimination thresholds for the same curvatures during fixation. Motion curvature had some specific effects on smooth pursuit properties: trajectories with larger amounts of curvature elicited lower open-loop acceleration, lower pursuit gain, and larger catch-up saccades compared with less curved trajectories. Initially, target motion curvatures were underestimated; however, ∼300 ms after pursuit onset pursuit responses closely matched the actual curved trajectory. We calculated perceptual thresholds for curvature discrimination, which were on the order of 1.5 degrees of visual angle (°) for a 7.9° curvature standard. Oculometric sensitivity to curvature discrimination based on the whole pursuit trajectory was quite similar to perceptual performance. Oculometric thresholds based on smaller time windows were higher. Thus smooth pursuit can quite accurately follow moving targets with curved trajectories, but temporal integration over longer periods is necessary to reach perceptual thresholds for curvature discrimination. NEW & NOTEWORTHY Even though motion trajectories in the real world are frequently curved, most studies of smooth pursuit and motion perception have investigated linear motion. We show that pursuit initially underestimates the curvature of target motion and is able to reproduce the target curvature ∼300 ms after pursuit onset. Temporal integration of target motion over longer periods is necessary for pursuit to reach the level of precision found in perceptual discrimination of curvature. Copyright © 2017 the American Physiological Society.

Combustion monitoring of a water tube boiler using a discriminant radial basis network.

PubMed

Sujatha, K; Pappa, N

2011-01-01

This research work includes a combination of Fisher's linear discriminant (FLD) analysis and a radial basis network (RBN) for monitoring the combustion conditions for a coal fired boiler so as to allow control of the air/fuel ratio. For this, two-dimensional flame images are required, which were captured with a CCD camera; the features of the images-average intensity, area, brightness and orientation etc of the flame-are extracted after preprocessing the images. The FLD is applied to reduce the n-dimensional feature size to a two-dimensional feature size for faster learning of the RBN. Also, three classes of images corresponding to different burning conditions of the flames have been extracted from continuous video processing. In this, the corresponding temperatures, and the carbon monoxide (CO) emissions and those of other flue gases have been obtained through measurement. Further, the training and testing of Fisher's linear discriminant radial basis network (FLDRBN), with the data collected, have been carried out and the performance of the algorithms is presented. Copyright © 2010 ISA. Published by Elsevier Ltd. All rights reserved.

Sex assessment using measurements of the first lumbar vertebra.

PubMed

Zheng, Wen Xu; Cheng, Fu Bo; Cheng, Kai Liang; Tian, Yong; Lai, Ying; Zhang, Wen Song; Zheng, Ya Juan; Li, You Qiong

2012-06-10

Sex determination is a vital part of the medico-legal system but can be difficult in cases where the integrity of the body has been compromised. The purpose of this study was to develop a technique for sex assessment from measurements of the first lumber vertebrate. Twenty-nine linear measurements and five ratios were collected from 113 Chinese adult males and 97 Chinese adult females using digital three-dimensional anthropometry methods. By using discriminant analysis, we found that 23 linear measurements and two ratios identified sexual dimorphism (P<0.01), with predictive accuracy ranging from 57.1% to 86.6%. Using a stepwise method of discriminant function analysis, we found three dimensions predicted sex with 88.6% accuracy: (a) upper end-plate width (EPWu), (b) left pedicle height (PHl), and (c) middle end-plate depth (EPDm). This study shows that a single first lumber vertebra can be used for this purpose, and that the discriminant equation will help forensic determination of sex in the Chinese population. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Discrimination, acculturation, acculturative stress, and Latino psychological distress: a moderated mediational model.

PubMed

Torres, Lucas; Driscoll, Mark W; Voell, Maria

2012-01-01

Prior research has found that perceived discrimination is associated with adverse mental health outcomes among Latinos. However, the process by which this relationship occurs remains an understudied area. The present study investigated the role of acculturative stress in underlying the relationship between perceived discrimination and Latino psychological distress. Also examined was the ability of acculturation to serve as a moderator between perceived discrimination and acculturative stress. Among a sample of Latino adults (N = 669), moderated mediational analyses revealed that acculturative stress mediated the perceived discrimination-psychological distress relationship, and that the link between perceived discrimination and acculturative stress was moderated by Anglo behavioral orientation but not Latino behavioral orientation. The findings are discussed within a stress and coping perspective that identifies the psychological consequences associated with perceived discrimination and acculturative stress.

Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U.

PubMed

Ishii, K; Shinohara, K; Ishikawa, M; Baba, M; Isobe, M; Okamoto, A; Kitajima, S; Sasao, M

2010-10-01

A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-γ pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and γ-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the γ-ray contamination in most of the beam heating phase was negligible compared with the statistical error with 10 ms time resolution.

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.

Fast neutron-gamma discrimination on neutron emission profile measurement on JT-60U

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

Ishii, K.; Okamoto, A.; Kitajima, S.

2010-10-15

A digital signal processing (DSP) system is applied to stilbene scintillation detectors of the multichannel neutron emission profile monitor in JT-60U. Automatic analysis of the neutron-{gamma} pulse shape discrimination is a key issue to diminish the processing time in the DSP system, and it has been applied using the two-dimensional (2D) map. Linear discriminant function is used to determine the dividing line between neutron events and {gamma}-ray events on a 2D map. In order to verify the validity of the dividing line determination, the pulse shape discrimination quality is evaluated. As a result, the {gamma}-ray contamination in most of themore » beam heating phase was negligible compared with the statistical error with 10 ms time resolution.« less

Decision-Related Activity in Macaque V2 for Fine Disparity Discrimination Is Not Compatible with Optimal Linear Readout.

PubMed

Clery, Stephane; Cumming, Bruce G; Nienborg, Hendrikje

2017-01-18

Fine judgments of stereoscopic depth rely mainly on relative judgments of depth (relative binocular disparity) between objects, rather than judgments of the distance to where the eyes are fixating (absolute disparity). In macaques, visual area V2 is the earliest site in the visual processing hierarchy for which neurons selective for relative disparity have been observed (Thomas et al., 2002). Here, we found that, in macaques trained to perform a fine disparity discrimination task, disparity-selective neurons in V2 were highly selective for the task, and their activity correlated with the animals' perceptual decisions (unexplained by the stimulus). This may partially explain similar correlations reported in downstream areas. Although compatible with a perceptual role of these neurons for the task, the interpretation of such decision-related activity is complicated by the effects of interneuronal "noise" correlations between sensory neurons. Recent work has developed simple predictions to differentiate decoding schemes (Pitkow et al., 2015) without needing measures of noise correlations, and found that data from early sensory areas were compatible with optimal linear readout of populations with information-limiting correlations. In contrast, our data here deviated significantly from these predictions. We additionally tested this prediction for previously reported results of decision-related activity in V2 for a related task, coarse disparity discrimination (Nienborg and Cumming, 2006), thought to rely on absolute disparity. Although these data followed the predicted pattern, they violated the prediction quantitatively. This suggests that optimal linear decoding of sensory signals is not generally a good predictor of behavior in simple perceptual tasks. Activity in sensory neurons that correlates with an animal's decision is widely believed to provide insights into how the brain uses information from sensory neurons. Recent theoretical work developed simple predictions to differentiate decoding schemes, and found support for optimal linear readout of early sensory populations with information-limiting correlations. Here, we observed decision-related activity for neurons in visual area V2 of macaques performing fine disparity discrimination, as yet the earliest site for this task. These findings, and previously reported results from V2 in a different task, deviated from the predictions for optimal linear readout of a population with information-limiting correlations. Our results suggest that optimal linear decoding of early sensory information is not a general decoding strategy used by the brain. Copyright © 2017 the authors 0270-6474/17/370715-11$15.00/0.

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

PubMed

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

2010-12-20

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

General methodology for simultaneous representation and discrimination of multiple object classes

NASA Astrophysics Data System (ADS)

Talukder, Ashit; Casasent, David P.

1998-03-01

We address a new general method for linear and nonlinear feature extraction for simultaneous representation and classification. We call this approach the maximum representation and discrimination feature (MRDF) method. We develop a novel nonlinear eigenfeature extraction technique to represent data with closed-form solutions and use it to derive a nonlinear MRDF algorithm. Results of the MRDF method on synthetic databases are shown and compared with results from standard Fukunaga-Koontz transform and Fisher discriminant function methods. The method is also applied to an automated product inspection problem and for classification and pose estimation of two similar objects under 3D aspect angle variations.

Linear photonic frequency discriminator on As₂S₃-ring-on-Ti:LiNbO₃ hybrid platform.

PubMed

Kim, Jaehyun; Sung, Won Ju; Eknoyan, Ohannes; Madsen, Christi K

2013-10-21

We report a photonic frequency discriminator built on the vertically integrated As₂S₃-ring-on-Ti:LiNbO₃ hybrid platform. The discriminator consists of a Mach Zehnder interferometer (MZI) formed by the optical path length difference (OPD) between polarization modes of Ti-diffused waveguide on LiNbO₃ substrate and a vertically integrated As₂S₃ race-track ring resonator on top of the substrate. The figures of merit of the device, enhancement of the signal-to-3rd order intermodulation distortion (IMD3) power ratio and corresponding 3rd order intercept point (IP3) over a traditional MZI, are demonstrated through device characterization.

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

Application of an oscillation-type linear cadmium telluride detector to enhanced gadolinium K-edge computed tomography

NASA Astrophysics Data System (ADS)

Matsukiyo, Hiroshi; Sato, Eiichi; Hagiwara, Osahiko; Abudurexiti, Abulajiang; Osawa, Akihiro; Enomoto, Toshiyuki; Watanabe, Manabu; Nagao, Jiro; Sato, Shigehiro; Ogawa, Akira; Onagawa, Jun

2011-03-01

A linear cadmium telluride (CdTe) detector is useful for carrying out energy-discrimination X-ray imaging, including computed tomography (CT). To perform enhanced gadolinium K-edge CT, we used an oscillation-type linear CdTe detector with an energy resolution of 1.2 keV. CT is performed by repeating the linear scan and the rotation of an object. Penetrating X-ray photons from the object are detected by the CdTe detector, and event signals of X-ray photons are produced using charge-sensitive and shaping amplifiers. Both the photon energy and the energy width are selected using a multichannel analyzer, and the number of photons is counted by a counter card. In energy-discrimination CT, tube voltage and current were 80 kV and 20 μA, respectively, and X-ray intensity was 1.55 μGy/s at 1.0 m from the source at a tube voltage of 80 kV. Demonstration of enhanced gadolinium K-edge X-ray CT was carried out by selecting photons with energies just beyond gadolinium K-edge energy of 50.3 keV.

Sex determination from the mandibular ramus flexure of Koreans by discrimination function analysis using three-dimensional mandible models.

PubMed

Lin, Chenghe; Jiao, Benzheng; Liu, Shanshan; Guan, Feng; Chung, Nak-Eun; Han, Seung-Ho; Lee, U-Young

2014-03-01

It has been known that mandible ramus flexure is an important morphologic trait for sex determination. However, it will be unavailable when mandible is incomplete or fragmented. Therefore, the anthropometric analysis on incomplete or fragmented mandible becomes more important. The aim of this study is to investigate the sex-discriminant potential of mandible ramus flexure on the Korean three-dimensional (3D) mandible models with anthropometric analysis. The sample consists of 240 three dimensional mandibular models obtained from Korean population (M:F; 120:120, mean age 46.2 y), collected by The Catholic Institute for Applied Anatomy, The Catholic University of Korea. Anthropometric information about 11 metric was taken with Mimics, anthropometry libraries toolkit. These parameters were subjected to different discriminant function analyses using SPSS 17.0. Univariate analyses showed that the resubstitution accuracies for sex determination range from 50.4 to 77.1%. Mandibular flexure upper border (MFUB), maximum ramus vertical height (MRVH), and upper ramus vertical height (URVH) expressed the greatest dimorphism, 72.1 to 77.1%. Bivariate analyses indicated that the combination of MFUB and MRVH hold even higher resubstitution accuracy of 81.7%. Furthermore, the direct and stepwise discriminant analyses with the variables on the upper ramus above flexure could predict sex in 83.3 and 85.0%, respectively. When all variables of mandibular ramus flexure were input in stepwise discriminant analysis, the resubstitution accuracy arrived as high as 88.8%. Therefore, we concluded that the upper ramus above flexure hold the larger potentials than the mandibular ramus flexure itself to predict sexes, and that the equations in bivariate and multivariate analysis from our study will be helpful for sex determination on Korean population in forensic science and law. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Changes in Experiences With Discrimination Across Pregnancy and Postpartum: Age Differences and Consequences for Mental Health

PubMed Central

Earnshaw, Valerie A.; Lewis, Tené T.; Reid, Allecia E.; Lewis, Jessica B.; Stasko, Emily C.; Tobin, Jonathan N.; Ickovics, Jeannette R.

2015-01-01

Objectives. We aimed to contribute to growing research and theory suggesting the importance of examining patterns of change over time and critical life periods to fully understand the effects of discrimination on health, with a focus on the period of pregnancy and postpartum and mental health outcomes. Methods. We used hierarchical linear modeling to examine changes across pregnancy and postpartum in everyday discrimination and the resulting consequences for mental health among predominantly Black and Latina, socioeconomically disadvantaged young women who were receiving prenatal care in New York City. Results. Patterns of change in experiences with discrimination varied according to age. Among the youngest participants, discrimination increased from the second to third trimesters and then decreased to lower than the baseline level by 1 year postpartum; among the oldest participants, discrimination decreased from the second trimester to 6 months postpartum and then returned to the baseline level by 1 year postpartum. Within-subjects changes in discrimination over time predicted changes in depressive and anxiety symptoms at subsequent points. Discrimination more strongly predicted anxiety symptoms among participants reporting food insecurity. Conclusions. Our results support a life course approach to understanding the impact of experiences with discrimination on health and when to intervene. PMID:24922166

Linear discriminant analysis based on L1-norm maximization.

PubMed

Zhong, Fujin; Zhang, Jiashu

2013-08-01

Linear discriminant analysis (LDA) is a well-known dimensionality reduction technique, which is widely used for many purposes. However, conventional LDA is sensitive to outliers because its objective function is based on the distance criterion using L2-norm. This paper proposes a simple but effective robust LDA version based on L1-norm maximization, which learns a set of local optimal projection vectors by maximizing the ratio of the L1-norm-based between-class dispersion and the L1-norm-based within-class dispersion. The proposed method is theoretically proved to be feasible and robust to outliers while overcoming the singular problem of the within-class scatter matrix for conventional LDA. Experiments on artificial datasets, standard classification datasets and three popular image databases demonstrate the efficacy of the proposed method.

Spectral discrimination of lithologic facies in the granite of the Pedra Branca Goias using LANDSAT 1 digital imagery

NASA Technical Reports Server (NTRS)

Parada, N. D. J.; Almeido, R., Jr.

1982-01-01

The applicability of LANDSAT MSS imagery for discriminating geobotanical associations observed in zones of cassiterite-rich metasomatic alterations in the granitic body of Serra da Pedra Branca was investigated. Computer compatible tapes of dry and rainy season imagery were analyzed. Image enlargement, corrections, linear contrast stretch, and ratioing of noncorrelated spectral bands were performed using the Image 100 with a grey scale of 256 levels between zero and 255. Only bands 5 and 7 were considered. Band ratioing of noncorrelated channels (5 and 7) of rainy season imagery permits distinction of areas with different vegetation coverage percentage, which corresponds to geobotanial associations in the area studied. The linear contrast stretch of channel 5, especially of the dry season image is very unsatisfactory in this area.

Comparative study on fast classification of brick samples by combination of principal component analysis and linear discriminant analysis using stand-off and table-top laser-induced breakdown spectroscopy

NASA Astrophysics Data System (ADS)

Vítková, Gabriela; Prokeš, Lubomír; Novotný, Karel; Pořízka, Pavel; Novotný, Jan; Všianský, Dalibor; Čelko, Ladislav; Kaiser, Jozef

2014-11-01

Focusing on historical aspect, during archeological excavation or restoration works of buildings or different structures built from bricks it is important to determine, preferably in-situ and in real-time, the locality of bricks origin. Fast classification of bricks on the base of Laser-Induced Breakdown Spectroscopy (LIBS) spectra is possible using multivariate statistical methods. Combination of principal component analysis (PCA) and linear discriminant analysis (LDA) was applied in this case. LIBS was used to classify altogether the 29 brick samples from 7 different localities. Realizing comparative study using two different LIBS setups - stand-off and table-top it is shown that stand-off LIBS has a big potential for archeological in-field measurements.

The association between income, education, and experiences of discrimination in older African American and European American patients.

PubMed

Halanych, Jewell H; Safford, Monika M; Shikany, James M; Cuffee, Yendelela; Person, Sharina D; Scarinci, Isabel C; Kiefe, Catarina I; Allison, Jeroan J

2011-01-01

Racial/ethnic discrimination has adverse effects on health outcomes, as does low income and education, but the relationship between discrimination, income, and education is not well characterized. In this study, we describe the associations of discrimination with income and education in elderly African Americans (AA) and European Americans (EA). Cross-sectional observational study involving computer-assisted telephone survey. Southeastern United States. AA and EA Medicare managed care enrollees. Discrimination was measured with the Experience of Discrimination (EOD) scale (range 0-35). We used zero-inflated negative binomial models to determine the association between self-reported income and education and 1) presence of any discrimination and 2) intensity of discrimination. Among 1,800 participants (45% AA, 56% female, and mean age 73 years), EA reported less discrimination than AA (4% vs. 47%; P < .001). AA men reported more discrimination and more intense discrimination than AA women (EOD scores 4.35 vs. 2.50; P < .001). Both income and education were directly and linearly associated with both presence of discrimination and intensity of discrimination in AA, so that people with higher incomes and education experienced more discrimination. In adjusted models, predicted EOD scores among AA decreased with increasing age categories (3.42, 3.21, 2.99, 2.53; P < .01) and increased with increasing income (2.36, 3.44, 4.17; P < .001) and education categories (2.31, 3.09, 5.12; P < .001). This study suggests future research should focus less on differences between racial/ethnic groups and more on factors within minority populations that may contribute to healthcare disparities.

Variation in the cranial base orientation and facial skeleton in dry skulls sampled from three major populations.

PubMed

Kuroe, Kazuto; Rosas, Antonio; Molleson, Theya

2004-04-01

The aim of this study was to analyse the effects of cranial base orientation on the morphology of the craniofacial system in human populations. Three geographically distant populations from Europe (72), Africa (48) and Asia (24) were chosen. Five angular and two linear variables from the cranial base component and six angular and six linear variables from the facial component based on two reference lines of the vertical posterior maxillary and Frankfort horizontal planes were measured. The European sample presented dolichofacial individuals with a larger face height and a smaller face depth derived from a raised cranial base and facial cranium orientation which tended to be similar to the Asian sample. The African sample presented brachyfacial individuals with a reduced face height and a larger face depth as a result of a lowered cranial base and facial cranium orientation. The Asian sample presented dolichofacial individuals with a larger face height and depth due to a raised cranial base and facial cranium orientation. The findings of this study suggest that cranial base orientation and posterior cranial base length appear to be valid discriminating factors between different human populations.

LCFIPlus: A framework for jet analysis in linear collider studies

NASA Astrophysics Data System (ADS)

Suehara, Taikan; Tanabe, Tomohiko

2016-02-01

We report on the progress in flavor identification tools developed for a future e+e- linear collider such as the International Linear Collider (ILC) and Compact Linear Collider (CLIC). Building on the work carried out by the LCFIVertex collaboration, we employ new strategies in vertex finding and jet finding, and introduce new discriminating variables for jet flavor identification. We present the performance of the new algorithms in the conditions simulated using a detector concept designed for the ILC. The algorithms have been successfully used in ILC physics simulation studies, such as those presented in the ILC Technical Design Report.

Discrimination and adjustment among Chinese American adolescents: family conflict and family cohesion as vulnerability and protective factors.

PubMed

Juang, Linda P; Alvarez, Alvin A

2010-12-01

We examined racial/ethnic discrimination experiences of Chinese American adolescents to determine how discrimination is linked to poor adjustment (i.e., loneliness, anxiety, and somatization) and how the context of the family can buffer or exacerbate these links. We collected survey data from 181 Chinese American adolescents and their parents in Northern California. We conducted hierarchical regression analyses to examine main effects and 2-way interactions of perceived discrimination with family conflict and family cohesion. Discrimination was related to poorer adjustment in terms of loneliness, anxiety, and somatization, but family conflict and cohesion modified these relations. Greater family conflict exacerbated the negative effects of discrimination, and greater family cohesion buffered the negative effects of discrimination. Our findings highlight the importance of identifying family-level moderators to help adolescents and their families handle experiences of discrimination.

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.

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

Multifactorial discrimination as a fundamental cause of mental health inequities.

PubMed

Khan, Mariam; Ilcisin, Misja; Saxton, Katherine

2017-03-04

The theory of fundamental causes explains why health disparities persist over time, even as risk factors, mechanisms, and diseases change. Using an intersectional framework, we evaluated multifactorial discrimination as a fundamental cause of mental health disparities. Using baseline data from the Project STRIDE: Stress, Identity, and Mental Health study, we examined the health effects of discrimination among individuals who self-identified as lesbian, gay, or bisexual. We used logistic and linear regression to assess whether multifactorial discrimination met the four criteria designating a fundamental cause, namely that the cause: 1) influences multiple health outcomes, 2) affects multiple risk factors, 3) involves access to resources that can be leveraged to reduce consequences of disease, and 4) reproduces itself in varied contexts through changing mechanisms. Multifactorial discrimination predicted high depression scores, psychological well-being, and substance use disorder diagnosis. Discrimination was positively associated with risk factors for high depression scores: chronic strain and total number of stressful life events. Discrimination was associated with significantly lower levels of mastery and self-esteem, protective factors for depressive symptomatology. Even after controlling for risk factors, discrimination remained a significant predictor for high depression scores. Among subjects with low depression scores, multifactorial discrimination also predicted anxiety and aggregate mental health scores. Multifactorial discrimination should be considered a fundamental cause of mental health inequities and may be an important cause of broad health disparities among populations with intersecting social identities.

Growth rate and stable carbon and nitrogen isotope trophic discrimination factors of lion and leopard whiskers.

PubMed

Mutirwara, Ruwimbo; Radloff, Frans G T; Codron, Daryl

2018-01-15

Stable isotope analysis (SIA) of whiskers has been used to identify temporal feeding habits, intra-population diet variation, as well as individual dietary specialisation of marine and terrestrial carnivores. However, the potential of the method to disclose such dietary information for large wild felids is hampered by lack of information on species-specific whisker growth rates, whisker growth patterns and whisker-diet trophic discrimination factors (TDFs). Whisker growth rates and growth patterns were measured for four lions (Panthera leo) and one leopard (Panthera pardus) held at the National Zoological Gardens, Pretoria, South Africa. Actively growing whiskers of the felids were 'marked' four times over 185 days using 13 C-depleted, C 3 -based giraffe (Giraffa camelopardalis) meat. The periods with low δ 13 C values, identified following serial sectioning of the regrown whiskers at 1 mm intervals and isotopic analysis, were then correlated to specific giraffe meat feeding bouts and hence growth periods. δ 13 C and δ 15 N whisker-diet TDFs were estimated for five lions whose diet remained consistent over multiple years. The whisker growth rates of three lionesses and the leopard were similar (mean = 0.65 mm day -1 ), despite species, sex and age differences. There was a decrease in whisker growth rate over time, suggesting a non-linear whisker growth pattern. However, linear and non-linear growth simulations showed slight differences between the two growth patterns for the proximal ~50 mm of whiskers. δ 13 C and δ 15 N lion whisker-diet TDFs were also similar amongst individuals (mean = 2.7 ± 0.12 ‰ for δ 13 C values and 2.5 ± 0.08 ‰ for δ 15 N values), irrespective of age and sex. The whisker growth rate and δ 13 C and δ 15 N lion whisker-diet TDFs obtained in this study can be applied in future studies to assign dietary information contained in analysed felid whiskers to the correct time period and improve deductions of prey species consumed by wild felids. Copyright © 2017 John Wiley & Sons, Ltd.

Determining quality of caviar from Caspian Sea based on Raman spectroscopy and using artificial neural networks.

PubMed

Mohamadi Monavar, H; Afseth, N K; Lozano, J; Alimardani, R; Omid, M; Wold, J P

2013-07-15

The purpose of this study was to evaluate the feasibility of Raman spectroscopy for predicting purity of caviars. The 93 wild caviar samples of three different types, namely; Beluga, Asetra and Sevruga were analysed by Raman spectroscopy in the range 1995 cm(-1) to 545 cm(-1). Also, 60 samples from combinations of every two types were examined. The chemical origin of the samples was identified by reference measurements on pure samples. Linear chemometric methods like Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA) were used for data visualisation and classification which permitted clear distinction between different caviars. Non-linear methods like Artificial Neural Networks (ANN) were used to classify caviar samples. Two different networks were tested in the classification: Probabilistic Neural Network with Radial-Basis Function (PNN) and Multilayer Feed Forward Networks with Back Propagation (BP-NN). In both cases, scores of principal components (PCs) were chosen as input nodes for the input layer in PC-ANN models in order to reduce the redundancy of data and time of training. Leave One Out (LOO) cross validation was applied in order to check the performance of the networks. Results of PCA indicated that, features like type and purity can be used to discriminate different caviar samples. These findings were also supported by LDA with efficiency between 83.77% and 100%. These results were confirmed with the results obtained by developed PC-ANN models, able to classify pure caviar samples with 93.55% and 71.00% accuracy in BP network and PNN, respectively. In comparison, LDA, PNN and BP-NN models for predicting caviar types have 90.3%, 73.1% and 91.4% accuracy. Partial least squares regression (PLSR) models were built under cross validation and tested with different independent data sets, yielding determination coefficients (R(2)) of 0.86, 0.83, 0.92 and 0.91 with root mean square error (RMSE) of validation of 0.32, 0.11, 0.03 and 0.09 for fatty acids of 16.0, 20.5, 22.6 and fat, respectively. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

Rainfall induced landslide susceptibility mapping using weight-of-evidence, linear and quadratic discriminant and logistic model tree method

NASA Astrophysics Data System (ADS)

Hong, H.; Zhu, A. X.

2017-12-01

Climate change is a common phenomenon and it is very serious all over the world. The intensification of rainfall extremes with climate change is of key importance to society and then it may induce a large impact through landslides. This paper presents GIS-based new ensemble data mining techniques that weight-of-evidence, logistic model tree, linear and quadratic discriminant for landslide spatial modelling. This research was applied in Anfu County, which is a landslide-prone area in Jiangxi Province, China. According to a literature review and research the study area, we select the landslide influencing factor and their maps were digitized in a GIS environment. These landslide influencing factors are the altitude, plan curvature, profile curvature, slope degree, slope aspect, topographic wetness index (TWI), Stream Power Index (SPI), Topographic Wetness Index (SPI), distance to faults, distance to rivers, distance to roads, soil, lithology, normalized difference vegetation index and land use. According to historical information of individual landslide events, interpretation of the aerial photographs, and field surveys supported by the government of Jiangxi Meteorological Bureau of China, 367 landslides were identified in the study area. The landslide locations were divided into two subsets, namely, training and validating (70/30), based on a random selection scheme. In this research, Pearson's correlation was used for the evaluation of the relationship between the landslides and influencing factors. In the next step, three data mining techniques combined with the weight-of-evidence, logistic model tree, linear and quadratic discriminant, were used for the landslide spatial modelling and its zonation. Finally, the landslide susceptibility maps produced by the mentioned models were evaluated by the ROC curve. The results showed that the area under the curve (AUC) of all of the models was > 0.80. At the same time, the highest AUC value was for the linear and quadratic discriminant model (0.864), followed by logistic model tree (0.832), and weight-of-evidence (0.819). In general, the landslide maps can be applied for land use planning and management in the Anfu area.

Associations Between Perceived Race-based Discrimination and Contraceptive Use Among Women Veterans in the ECUUN Study.

PubMed

MacDonald, Serena; Hausmann, Leslie R M; Sileanu, Florentina E; Zhao, Xinhua; Mor, Maria K; Borrero, Sonya

2017-09-01

To describe perceived race-based discrimination in Veterans Affairs (VA) health care settings and assess its associations with contraceptive use among a sample of women Veterans. This study used data from a national telephone survey of women Veterans aged 18-44 receiving health care in VA who were at risk of unintended pregnancy. Participants were asked about their perceptions of race-based discrimination while seeking VA health care and about their contraceptive use at last heterosexual intercourse. Logistic and multinomial regression analyses were used to examine associations between perceived race-based discrimination with use of prescription contraception. In our sample of 1341 women Veterans, 7.9% report perceived race-based discrimination when receiving VA care, with blacks and Hispanics reporting higher levels of perceived discrimination than white women (11.3% and 11.2% vs. 4.4%; P<0.001). In logistic and multinomial regression analyses adjusting for race/ethnicity, age, income, marital status, parity, and insurance, women who perceived race-based discrimination were less likely to use any prescription birth control than women who did not (odds ratio, 0.65; 95% confidence interval, 0.42-1.00), with the largest difference seen in rates of intrauterine device or implant use (odds ratio, 0.40; 95% confidence interval, 0.20-0.79). In this national sample of women Veterans, over 10% of racial/ethnic minority women perceived race-based discrimination when receiving care in VA settings, and perceived racial/ethnic discrimination was associated with lower likelihood of prescription contraception use, especially intrauterine devices and implants. VA efforts to enhance respectful interactions may not only improve patient health care experiences, but also represent an opportunity to improve reproductive health outcomes for women Veterans.

Odontometric sex estimation from clinically extracted molar teeth in a North Indian population sample.

PubMed

Tabasum, Qutsia; Sehrawat, Jagmahender Singh; Talwar, Manjit Kaur; Pathak, Raj Kamal

2017-01-01

Different dental features have contributed significantly toward sex determination in the forensic anthropological contexts. Population-specific standards (discriminant functions or regression formulae) have been suggested for various population groups to identify the sex of an unknown individual from dental dimensions and other odontometric features. The main purpose of the present investigation was to examine the degree of sexual dimorphism exhibited by the human teeth of North Indians and identify importance as a forensic tool in sex determination. The linear and diagonal dimensions were recorded at both crown and cementoenamel junction levels of 58 upper and 72 lower molars of 130 Northwest Indian subjects (73 males and 57 females). The measurements were subjected to appropriate statistical analyses to estimate the sex estimation accuracy from lower and upper molars separately. Univariate analyses revealed that molar teeth had greater dimensions in males than the females and the mesiodistal cervical diameter (MDCV) was found to be the most suitable variable for sex determination of the molars. The classification results were in agreement with the previously conducted studies. The index of sexual dimorphism (ISD) was calculated to be higher in lower molars than the upper molars, and the highest sex differences were observed for MDCV based on the ISD. The overall sex estimation accuracy obtained from multivariate discriminant function analysis and regression analysis of pooled data was 70.0% (74% males, 64.9% females) and 66.9% (78.1% males, 52.6% females), respectively. Odontometrics can play a significant role in establishing the biological identity of an unknown individual even from a single tooth in the absence of other sophisticated molecular or biochemical techniques used for this purpose.

Odontometric sex estimation from clinically extracted molar teeth in a North Indian population sample

PubMed Central

Tabasum, Qutsia; Sehrawat, Jagmahender Singh; Talwar, Manjit Kaur; Pathak, Raj Kamal

2017-01-01

Background: Different dental features have contributed significantly toward sex determination in the forensic anthropological contexts. Population-specific standards (discriminant functions or regression formulae) have been suggested for various population groups to identify the sex of an unknown individual from dental dimensions and other odontometric features. The main purpose of the present investigation was to examine the degree of sexual dimorphism exhibited by the human teeth of North Indians and identify importance as a forensic tool in sex determination. Materials and Methods: The linear and diagonal dimensions were recorded at both crown and cementoenamel junction levels of 58 upper and 72 lower molars of 130 Northwest Indian subjects (73 males and 57 females). The measurements were subjected to appropriate statistical analyses to estimate the sex estimation accuracy from lower and upper molars separately. Results: Univariate analyses revealed that molar teeth had greater dimensions in males than the females and the mesiodistal cervical diameter (MDCV) was found to be the most suitable variable for sex determination of the molars. The classification results were in agreement with the previously conducted studies. The index of sexual dimorphism (ISD) was calculated to be higher in lower molars than the upper molars, and the highest sex differences were observed for MDCV based on the ISD. The overall sex estimation accuracy obtained from multivariate discriminant function analysis and regression analysis of pooled data was 70.0% (74% males, 64.9% females) and 66.9% (78.1% males, 52.6% females), respectively. Conclusions: Odontometrics can play a significant role in establishing the biological identity of an unknown individual even from a single tooth in the absence of other sophisticated molecular or biochemical techniques used for this purpose. PMID:29657498

Perceived discrimination and longitudinal increases in adolescent substance use: gender differences and mediational pathways.

PubMed

Brody, Gene H; Kogan, Steven M; Chen, Yi-Fu

2012-05-01

This study was designed to test hypotheses about the prospective association of adolescents' perceptions of discrimination with increases in substance use and the processes that mediate this association. African American youths residing in rural Georgia (n = 573; mean age = 16.0 years) provided longitudinal data on their experiences with discrimination, substance use, school engagement, and affiliations with substance-using peers. For male youths, perceived discrimination was significantly related to increases in substance use, and, as hypothesized, this association was mediated by the contributions of perceived discrimination to decreases in school engagement and increases in affiliations with substance-using peers. Analyses also indicated that discrimination influences substance use rather than vice versa. Results are consistent with the hypothesis that high levels of discrimination are linked to increases in substance use for African American male adolescents.

Discrimination, Acculturation, Acculturative Stress, and Latino Psychological Distress: A Moderated Mediational Model

PubMed Central

Torres, Lucas; Driscoll, Mark W.; Voell, Maria

2012-01-01

Prior research has found that perceived discrimination is associated with adverse mental health outcomes among Latinos. However, the process by which this relationship occurs remains an understudied area. The present study investigated the role of acculturative stress in underlying the relationship between perceived discrimination and Latino psychological distress. Also examined was the ability of acculturation to serve as a moderator between perceived discrimination and acculturative stress. Among a sample of Latino adults (N=669), moderated mediational analyses revealed that acculturative stress mediated the perceived discrimination-psychological distress relationship, and that the link between perceived discrimination and acculturative stress was moderated by Anglo behavioral orientation but not Latino behavioral orientation. The findings are discussed within a stress and coping perspective that identifies the psychological consequences associated with perceived discrimination and acculturative stress. PMID:22250895

The impact of slice-reduced computed tomography on histogram-based densitometry assessment of lung fibrosis in patients with systemic sclerosis

PubMed Central

Maurer, Britta; Suliman, Yossra A.; Morsbach, Fabian; Distler, Oliver; Frauenfelder, Thomas

2018-01-01

Background To evaluate usability of slice-reduced sequential computed tomography (CT) compared to standard high-resolution CT (HRCT) in patients with systemic sclerosis (SSc) for qualitative and quantitative assessment of interstitial lung disease (ILD) with respect to (I) detection of lung parenchymal abnormalities, (II) qualitative and semiquantitative visual assessment, (III) quantification of ILD by histograms and (IV) accuracy for the 20%-cut off discrimination. Methods From standard chest HRCT of 60 SSc patients sequential 9-slice-computed tomography (reduced HRCT) was retrospectively reconstructed. ILD was assessed by visual scoring and quantitative histogram parameters. Results from standard and reduced HRCT were compared using non-parametric tests and analysed by univariate linear regression analyses. Results With respect to the detection of parenchymal abnormalities, only the detection of intrapulmonary bronchiectasis was significantly lower in reduced HRCT compared to standard HRCT (P=0.039). No differences were found comparing visual scores for fibrosis severity and extension from standard and reduced HRCT (P=0.051–0.073). All scores correlated significantly (P<0.001) to histogram parameters derived from both, standard and reduced HRCT. Significant higher values of kurtosis and skewness for reduced HRCT were found (both P<0.001). In contrast to standard HRCT histogram parameters from reduced HRCT showed significant discrimination at cut-off 20% fibrosis (sensitivity 88% kurtosis and skewness; specificity 81% kurtosis and 86% skewness; cut-off kurtosis ≤26, cut-off skewness ≤4; both P<0.001). Conclusions Reduced HRCT is a robust method to assess lung fibrosis in SSc with minimal radiation dose with no difference in scoring assessment of lung fibrosis severity and extension in comparison to standard HRCT. In contrast to standard HRCT histogram parameters derived from the approach of reduced HRCT could discriminate at a threshold of 20% lung fibrosis with high sensitivity and specificity. Hence it might be used to detect early disease progression of lung fibrosis in context of monitoring and treatment of SSc patients. PMID:29850118

Discrimination and subjective well-being: protective influences of membership in a discriminated category.

PubMed

Hnilica, Karel

2011-03-01

Research reveals that discrimination has harmful effects on health and quality of life. Among the most frequent types of discrimination pertains gender and age discrimination. Research results show that discriminatory behaviours based on gender afflict predominantly women; age discrimination afflicts mainly older adults. At the same time, it has been found that members of these traditionally discriminated categories often use strategies that mitigate the effects of discrimination. Discrimination will have detrimental effects on subjective well-being. But its effects will be most harmful for persons who are not members of the traditionally discriminated categories. These hypotheses were tested on data from three waves of the European Social Survey that the Czech Republic also participated in. Data were analyzed in a series of multilevel random coefficients regression analyses with respondents nested within states and states nested within years of study. Both perceived gender discrimination and perceived age discrimination have negative effects on subjective well-being. However, gender discrimination had more harmful effects on the subjective well-being of men than women and age discrimination had the most harmful effects on the subjective well-being of people in their middle ages, not the elderly ones. Discrimination does not need to have most harmful effects on the quality of life of members of the categories that are discriminated against most often.

Feature selection from hyperspectral imaging for guava fruit defects detection

NASA Astrophysics Data System (ADS)

Mat Jafri, Mohd. Zubir; Tan, Sou Ching

2017-06-01

Development of technology makes hyperspectral imaging commonly used for defect detection. In this research, a hyperspectral imaging system was setup in lab to target for guava fruits defect detection. Guava fruit was selected as the object as to our knowledge, there is fewer attempts were made for guava defect detection based on hyperspectral imaging. The common fluorescent light source was used to represent the uncontrolled lighting condition in lab and analysis was carried out in a specific wavelength range due to inefficiency of this particular light source. Based on the data, the reflectance intensity of this specific setup could be categorized in two groups. Sequential feature selection with linear discriminant (LD) and quadratic discriminant (QD) function were used to select features that could potentially be used in defects detection. Besides the ordinary training method, training dataset in discriminant was separated in two to cater for the uncontrolled lighting condition. These two parts were separated based on the brighter and dimmer area. Four evaluation matrixes were evaluated which are LD with common training method, QD with common training method, LD with two part training method and QD with two part training method. These evaluation matrixes were evaluated using F1-score with total 48 defected areas. Experiment shown that F1-score of linear discriminant with the compensated method hitting 0.8 score, which is the highest score among all.

Psychometric functions for pure-tone frequency discrimination.

PubMed

Dai, Huanping; Micheyl, Christophe

2011-07-01

The form of the psychometric function (PF) for auditory frequency discrimination is of theoretical interest and practical importance. In this study, PFs for pure-tone frequency discrimination were measured for several standard frequencies (200-8000 Hz) and levels [35-85 dB sound pressure level (SPL)] in normal-hearing listeners. The proportion-correct data were fitted using a cumulative-Gaussian function of the sensitivity index, d', computed as a power transformation of the frequency difference, Δf. The exponent of the power function corresponded to the slope of the PF on log(d')-log(Δf) coordinates. The influence of attentional lapses on PF-slope estimates was investigated. When attentional lapses were not taken into account, the estimated PF slopes on log(d')-log(Δf) coordinates were found to be significantly lower than 1, suggesting a nonlinear relationship between d' and Δf. However, when lapse rate was included as a free parameter in the fits, PF slopes were found not to differ significantly from 1, consistent with a linear relationship between d' and Δf. This was the case across the wide ranges of frequencies and levels tested in this study. Therefore, spectral and temporal models of frequency discrimination must account for a linear relationship between d' and Δf across a wide range of frequencies and levels. © 2011 Acoustical Society of America

Quantifying and visualizing variations in sets of images using continuous linear optimal transport

NASA Astrophysics Data System (ADS)

Kolouri, Soheil; Rohde, Gustavo K.

2014-03-01

Modern advancements in imaging devices have enabled us to explore the subcellular structure of living organisms and extract vast amounts of information. However, interpreting the biological information mined in the captured images is not a trivial task. Utilizing predetermined numerical features is usually the only hope for quantifying this information. Nonetheless, direct visual or biological interpretation of results obtained from these selected features is non-intuitive and difficult. In this paper, we describe an automatic method for modeling visual variations in a set of images, which allows for direct visual interpretation of the most significant differences, without the need for predefined features. The method is based on a linearized version of the continuous optimal transport (OT) metric, which provides a natural linear embedding for the image data set, in which linear combination of images leads to a visually meaningful image. This enables us to apply linear geometric data analysis techniques such as principal component analysis and linear discriminant analysis in the linearly embedded space and visualize the most prominent modes, as well as the most discriminant modes of variations, in the dataset. Using the continuous OT framework, we are able to analyze variations in shape and texture in a set of images utilizing each image at full resolution, that otherwise cannot be done by existing methods. The proposed method is applied to a set of nuclei images segmented from Feulgen stained liver tissues in order to investigate the major visual differences in chromatin distribution of Fetal-Type Hepatoblastoma (FHB) cells compared to the normal cells.

Association between Perceived Discrimination in Healthcare Settings and HIV Medication Adherence: Mediating Psychosocial Mechanisms.

PubMed

Turan, Bulent; Rogers, Anna Joy; Rice, Whitney S; Atkins, Ghislaine C; Cohen, Mardge H; Wilson, Tracey E; Adimora, Adaora A; Merenstein, Daniel; Adedimeji, Adebola; Wentz, Eryka L; Ofotokun, Igho; Metsch, Lisa; Tien, Phyllis C; Johnson, Mallory O; Turan, Janet M; Weiser, Sheri D

2017-12-01

There is insufficient research on the impact of perceived discrimination in healthcare settings on adherence to antiretroviral therapy (ART), particularly among women living with HIV, and even less is known about psychosocial mechanisms that may mediate this association. Cross-sectional analyses were conducted in a sample of 1356 diverse women living with HIV enrolled in the Women's Interagency HIV Study (WIHS), a multi-center cohort study. Indirect effects analysis with bootstrapping was used to examine the potential mediating roles of internalized stigma and depressive symptoms in the association between perceived discrimination in healthcare settings and ART adherence. Perceived discrimination in healthcare settings was negatively associated with optimal (95% or better) ART adherence (adjusted odds ratio (AOR) = 0.81, p = 0.02, 95% confidence interval (CI) [0.68, 0.97]). Furthermore, internalization of stigma and depressive symptoms mediated the perceived discrimination-adherence association: Serial mediation analyses revealed a significant indirect effect of perceived discrimination in healthcare settings on ART adherence, first through internalized HIV stigma, and then through depressive symptoms (B = - 0.08, SE = 0.02, 95% CI [- 0.12, - 0.04]). Perceiving discrimination in healthcare settings may contribute to internalization of HIV-related stigma, which in turn may lead to depressive symptoms, with downstream adverse effects on ART adherence among women. These findings can guide the design of interventions to reduce discrimination in healthcare settings, as well as interventions targeting psychosocial mechanisms that may impact the ability of women living with HIV to adhere to ART regimens.

Discrimination, Racial/Ethnic Identity, and Substance Use Among Latina/os: Are They Gendered?

PubMed

Molina, Kristine M; Jackson, Benita; Rivera-Olmedo, Noemi

2016-02-01

Prior research suggests that stronger racial/ethnic identification offsets negative effects of discrimination on substance use. Yet research in this area and on whether gender modifies this association is limited for Latina/os. The purpose of the present study is to examine whether different sources of discrimination (everyday and racial/ethnic) are associated with substance use (alcohol use disorder, smoking), if racial/ethnic identity buffers this association, and the potential moderating role of gender among these variables. We present cross-sectional, US population-based data from the Latina/o adult sample (1427 females and 1127 males) of the National Latino and Asian American Study. Respondents completed self-reported measures of everyday and racial/ethnic discrimination, racial/ethnic identity, smoking status, and Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) lifetime alcohol use disorder. Weighted logistic regression analyses showed that before inclusion of three-way interactions and adjusting for covariates, everyday discrimination predicted increased risk for any DSM-IV lifetime alcohol use disorders. Moderation analyses revealed that the effect of everyday discrimination on the risk of being a current smoker was strongest for Latino men with high levels of racial/ethnic identity compared to those with low racial/ethnic identity. No differences were noted among Latino women. There were no main or interaction effects of racial/ethnic discrimination for any substance use outcome. Findings suggest differential associations for type of discrimination and outcome and that the role of racial/ethnic identity is gender-specific for smoking, appearing particularly detrimental for Latino men reporting high levels of racial/ethnic identity.

Discrimination and the health of immigrants and refugees: exploring Canada's evidence base and directions for future research in newcomer receiving countries.

PubMed

Edge, Sara; Newbold, Bruce

2013-02-01

Research and practice increasingly suggests discrimination compromises health. Yet the unique experiences and effects facing immigrant and refugee populations remain poorly understood in Canada and abroad. We review current knowledge on discrimination against newcomers in Canada, emphasizing impacts upon health status and service access to identify gaps and research needs. Existing knowledge centers around experiences within health-care settings, differences in perception and coping, mental health impacts, and debates about "non-discriminatory" health-care. There is need for comparative analyses within and across ethno-cultural groups and newcomer classes to better understand factors shaping how discrimination and its health effects are differentially experienced. Women receive greater attention in the literature given their compounded vulnerability. While this must continue, little is known about the experiences of youth and men. Governance and policy discourse analyses would elucidate how norms, institutions and practices shape discriminatory attitudes and responses. Finally, "non-discriminatory health-care" interventions require critical evaluation to determine their effectiveness.

Experiences of stigma, discrimination, care and support among people living with HIV: A four country study

PubMed Central

Neuman, Melissa; Obermeyer, Carla Makhlouf; Cherutich, Peter; Desclaux, Alice; Hardon, Anita; Ky-Zerbo, Odette; Namakhoma, Ireen; Wanyenze, Rhoda

2013-01-01

While it is widely agreed that HIV-related stigma may impede access to treatment and support, there is little evidence describing who is most likely to experience different forms of stigma and discrimination and how these affect disclosure and access to care. This study examined experiences of interpersonal discrimination, internalized stigma, and discrimination at health care facilities among HIV-positive adults aged 18 years and older utilizing health facilities in four countries in Sub-Saharan Africa (N=536). Prevalence of interpersonal discrimination across all countries was 34.6%, with women significantly more likely to experience interpersonal discrimination than men. Prevalences of internalized stigma varied across countries, ranging from 9.6% (Malawi) to 45.0% (Burkina Faso). Prevalence of health care discrimination was 10.4% across all countries. In multivariate analyses, we found positive, significant, and independent associations between disclosure and interpersonal discrimination and support group utilization, and positive associations between both internalized stigma and health care discrimination and referral for medications. PMID:23479002

The impact of racial discrimination and coping strategies on internalizing symptoms in African American youth.

PubMed

Gaylord-Harden, Noni K; Cunningham, Jamila A

2009-04-01

The current study examined the impact of racial discrimination stress on internalizing symptoms and coping strategies in a sample of 268 African American early adolescents (mean age = 12.90; 56% female) from low-income communities. Information about discrimination stress, coping, and internalizing symptoms was obtained via adolescents' self-report. It was predicted that discrimination stress would be positively associated with depression and anxiety, as well as culturally-specific coping. Finally, culturally-relevant coping and mainstream coping were examined as moderators of the association between discrimination stress and internalizing symptoms. Hierarchical regression analyses indicated that discrimination stress was positively associated with depression and anxiety and predicted culturally-relevant coping while controlling for mainstream coping. Communalistic coping moderated the association between discrimination and anxiety, but demonstrated a vulnerability function by increasing anxiety at high levels of discrimination. The results highlight the salience of racial discrimination for African American adolescents and the importance of considering culturally-specific coping behaviors.

Discriminative analysis of schizophrenia using support vector machine and recursive feature elimination on structural MRI images.

PubMed

Lu, Xiaobing; Yang, Yongzhe; Wu, Fengchun; Gao, Minjian; Xu, Yong; Zhang, Yue; Yao, Yongcheng; Du, Xin; Li, Chengwei; Wu, Lei; Zhong, Xiaomei; Zhou, Yanling; Fan, Ni; Zheng, Yingjun; Xiong, Dongsheng; Peng, Hongjun; Escudero, Javier; Huang, Biao; Li, Xiaobo; Ning, Yuping; Wu, Kai

2016-07-01

Structural abnormalities in schizophrenia (SZ) patients have been well documented with structural magnetic resonance imaging (MRI) data using voxel-based morphometry (VBM) and region of interest (ROI) analyses. However, these analyses can only detect group-wise differences and thus, have a poor predictive value for individuals. In the present study, we applied a machine learning method that combined support vector machine (SVM) with recursive feature elimination (RFE) to discriminate SZ patients from normal controls (NCs) using their structural MRI data. We first employed both VBM and ROI analyses to compare gray matter volume (GMV) and white matter volume (WMV) between 41 SZ patients and 42 age- and sex-matched NCs. The method of SVM combined with RFE was used to discriminate SZ patients from NCs using significant between-group differences in both GMV and WMV as input features. We found that SZ patients showed GM and WM abnormalities in several brain structures primarily involved in the emotion, memory, and visual systems. An SVM with a RFE classifier using the significant structural abnormalities identified by the VBM analysis as input features achieved the best performance (an accuracy of 88.4%, a sensitivity of 91.9%, and a specificity of 84.4%) in the discriminative analyses of SZ patients. These results suggested that distinct neuroanatomical profiles associated with SZ patients might provide a potential biomarker for disease diagnosis, and machine-learning methods can reveal neurobiological mechanisms in psychiatric diseases.

Facial Affect Recognition Using Regularized Discriminant Analysis-Based Algorithms

NASA Astrophysics Data System (ADS)

Lee, Chien-Cheng; Huang, Shin-Sheng; Shih, Cheng-Yuan

2010-12-01

This paper presents a novel and effective method for facial expression recognition including happiness, disgust, fear, anger, sadness, surprise, and neutral state. The proposed method utilizes a regularized discriminant analysis-based boosting algorithm (RDAB) with effective Gabor features to recognize the facial expressions. Entropy criterion is applied to select the effective Gabor feature which is a subset of informative and nonredundant Gabor features. The proposed RDAB algorithm uses RDA as a learner in the boosting algorithm. The RDA combines strengths of linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA). It solves the small sample size and ill-posed problems suffered from QDA and LDA through a regularization technique. Additionally, this study uses the particle swarm optimization (PSO) algorithm to estimate optimal parameters in RDA. Experiment results demonstrate that our approach can accurately and robustly recognize facial expressions.

Workplace discrimination and alcohol consumption: findings from the San Francisco Muni Health and Safety Study.

PubMed

Yen, I H; Ragland, D R; Greiner, B A; Fisher, J M

1999-01-01

There is evidence of an association between occupational stress and alcohol consumption. This study investigates the association between workplace racial discrimination and alcohol consumption in a sample of urban transit operators. During 1993-1995, after undergoing a medical exam, 1,542 transit operators completed an interview. Depending on the outcome, we used logistic or linear regression models to examine the cross-sectional relationship between discrimination experience and alcohol consumption. Operators who reported discrimination in at least one situation, out of a possible four, were more likely to have had negative life consequences as a result of drinking (adjusted OR = 1.97; 95% CI, 1.20-3.83) and were more likely to be classified as having an alcohol disorder (OR = 1.56 [0.96-2.54]), compared to those who reported no instances of workplace discrimination. Results adjusted simultaneously for age, sex, race/ethnicity, education, income, marital status, and seniority. There was no association between workplace discrimination and heavy drinking or drinks per month. Cross-sectional data from a sample of urban transit operators indicates an association between workplace racial discrimination and some measures of alcohol consumption.

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.

Racial Discrimination and HIV-related Risk Behaviors in Southeast Louisiana

PubMed Central

Kaplan, Kathryn C.; Hormes, Julia M.; Wallace, Maeve; Rountree, Michele; Theall, Katherine P.

2016-01-01

Objectives We examined the relationship between cumulative experiences of racial discrimination and HIV-related risk taking, and whether these relationships are mediated through alcohol use among African Americans in semi-rural southeast Louisiana. Methods Participants (N = 214) reported on experiences of discrimination, HIV sexual risk-taking, history of sexually transmitted infection (STI), and health behaviors including alcohol use in the previous 90 days. Experiences of discrimination (scaled both by frequency of occurrence and situational counts) as a predictor of a sexual risk composite score as well as a history of STI was assessed using multivariate linear and logistic regression, respectively, including tests for mediation by alcohol use. Results Discrimination was common in this cohort, with respondents confirming their experience on average 7 of the 9 potential situations and on more than 34 separate occasions. After adjustment, discrimination was significantly associated with increasing sexual risk-taking and lifetime history of STI when measured either by frequency of occurrence or number of situations, although there was no evidence that these relationships were mediated through alcohol use. Conclusions Cumulative experiences of discrimination may play a significant role in sexual risk behavior and consequently increase vulnerability to HIV and other STIs. PMID:26685822

A multiple maximum scatter difference discriminant criterion for facial feature extraction.

PubMed

Song, Fengxi; Zhang, David; Mei, Dayong; Guo, Zhongwei

2007-12-01

Maximum scatter difference (MSD) discriminant criterion was a recently presented binary discriminant criterion for pattern classification that utilizes the generalized scatter difference rather than the generalized Rayleigh quotient as a class separability measure, thereby avoiding the singularity problem when addressing small-sample-size problems. MSD classifiers based on this criterion have been quite effective on face-recognition tasks, but as they are binary classifiers, they are not as efficient on large-scale classification tasks. To address the problem, this paper generalizes the classification-oriented binary criterion to its multiple counterpart--multiple MSD (MMSD) discriminant criterion for facial feature extraction. The MMSD feature-extraction method, which is based on this novel discriminant criterion, is a new subspace-based feature-extraction method. Unlike most other subspace-based feature-extraction methods, the MMSD computes its discriminant vectors from both the range of the between-class scatter matrix and the null space of the within-class scatter matrix. The MMSD is theoretically elegant and easy to calculate. Extensive experimental studies conducted on the benchmark database, FERET, show that the MMSD out-performs state-of-the-art facial feature-extraction methods such as null space method, direct linear discriminant analysis (LDA), eigenface, Fisherface, and complete LDA.

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.

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.

Geometric mean for subspace selection.

PubMed

Tao, Dacheng; Li, Xuelong; Wu, Xindong; Maybank, Stephen J

2009-02-01

Subspace selection approaches are powerful tools in pattern classification and data visualization. One of the most important subspace approaches is the linear dimensionality reduction step in the Fisher's linear discriminant analysis (FLDA), which has been successfully employed in many fields such as biometrics, bioinformatics, and multimedia information management. However, the linear dimensionality reduction step in FLDA has a critical drawback: for a classification task with c classes, if the dimension of the projected subspace is strictly lower than c - 1, the projection to a subspace tends to merge those classes, which are close together in the original feature space. If separate classes are sampled from Gaussian distributions, all with identical covariance matrices, then the linear dimensionality reduction step in FLDA maximizes the mean value of the Kullback-Leibler (KL) divergences between different classes. Based on this viewpoint, the geometric mean for subspace selection is studied in this paper. Three criteria are analyzed: 1) maximization of the geometric mean of the KL divergences, 2) maximization of the geometric mean of the normalized KL divergences, and 3) the combination of 1 and 2. Preliminary experimental results based on synthetic data, UCI Machine Learning Repository, and handwriting digits show that the third criterion is a potential discriminative subspace selection method, which significantly reduces the class separation problem in comparing with the linear dimensionality reduction step in FLDA and its several representative extensions.

Taxonomic revision of imitating carpenter ants, Camponotus subgenus Myrmopytia (Hymenoptera, Formicidae) of Madagascar, using morphometry and qualitative traits

PubMed Central

Rasoamanana, Nicole; Csősz, Sándor; Fisher, Brian L.

2017-01-01

Abstract The ant genus Camponotus (Mayr, 1861) is one of the most abundant and species rich ant genera in the Malagasy zoogeographical region. Although this group is commonly encountered, its taxonomy is far from complete. Here, we clarify the taxonomy of the Malagasy-endemic Camponotus subgenus Myrmopytia (Emery, 1920). Species delimitation was based on traditional morphological characters and multivariate morphometric analyses, including exploratory Nest Centroid clustering and confirmatory cross-validated Linear Discriminant Analysis. Four species are recognized: Camponotus imitator (Forel, 1891), Camponotus jodina sp. n., Camponotus karaha sp. n., and Camponotus longicollis sp. n. All four species appear to mimic co-occurring Aphaenogaster species. A diagnosis of the subgenus Myrmopytia, species descriptions, an identification key based on minor and major subcastes of workers, and the known geographical distribution of each species are provided. PMID:28769722

NIR and UV-vis spectroscopy, artificial nose and tongue: comparison of four fingerprinting techniques for the characterisation of Italian red wines.

PubMed

Casale, M; Oliveri, P; Armanino, C; Lanteri, S; Forina, M

2010-06-04

Four rapid and low-cost vanguard analytical systems (NIR and UV-vis spectroscopy, a headspace-mass based artificial nose and a voltammetric artificial tongue), together with chemometric pattern recognition techniques, were applied and compared in addressing a food authentication problem: the distinction between wine samples from the same Italian oenological region, according to the grape variety. Specifically, 59 certified samples belonging to the Barbera d'Alba and Dolcetto d'Alba appellations and collected from the same vintage (2007) were analysed. The instrumental responses, after proper data pre-processing, were used as fingerprints of the characteristics of the samples: the results from principal component analysis and linear discriminant analysis were discussed, comparing the capability of the four analytical strategies in addressing the problem studied. Copyright 2010 Elsevier B.V. All rights reserved.

Volatile profile, lipid oxidation and protein oxidation of irradiated ready-to-eat cured turkey meat products

NASA Astrophysics Data System (ADS)

Feng, Xi; Ahn, Dong Uk

2016-10-01

Irradiation had little effects on the thiobarbituric acid reactive substances (TBARS) values in ready-to-eat (RTE) turkey meat products, while it increased protein oxidation at 4.5 kGy. The volatile profile analyses indicated that the amount of sulfur compounds increased linearly as doses increased in RTE turkey meat products. By correlation analysis, a positive correlation was found between benzene/ benzene derivatives and alcohols with lipid oxidation, while aldehydes, ketones and alkane, alkenes and alkynes were positively correlated with protein oxidation. Principle component analysis showed that irradiated meat samples can be discriminated by two categories of volatile compounds: Strecker degradation products and radiolytic degradation products. The cluster analysis of volatile data demonstrated that low-dose irradiation had minor effects on the volatile profile of turkey sausages (<1.5 kGy). However, as the doses increased, the differences between the irradiated and non-irradiated cured turkey products became significant.

Depression and discrimination in the lives of women, transgender and gender liminal people in Ontario, Canada.

PubMed

Williams, Charmaine C; Curling, Deone; Steele, Leah S; Gibson, Margaret F; Daley, Andrea; Green, Datejie Cheko; Ross, Lori E

2017-05-01

This article uses an intersectionality lens to explore how experiences of race, gender, sexuality, class and their intersections are associated with depression and unmet need for mental healthcare in a population of 704 women and transgender/gender liminal people from Ontario, Canada. A survey collecting demographic information, information about mental health and use of mental healthcare services, and data for the Everyday Discrimination Scale and the PHQ-9 Questionnaire for Depression was completed by 704 people via Internet or pen-and-paper between June 2011 and June 2012. Bivariate and regression analyses were conducted to assess group differences in depression and discrimination experiences, and predictors of depression and unmet need for mental healthcare services. Analyses revealed that race, gender, class and sexuality all corresponded to significant differences in exposure to discrimination, experiences of depression and unmet needs for mental healthcare. Use of interaction terms to model intersecting identities and exclusion contributed to explained variance in both outcome variables. Everyday discrimination was the strongest predictor of both depression and unmet need for mental healthcare. The results suggest lower income and intersections of race with other marginalised identities are associated with more depression and unmet need for mental healthcare; however, discrimination is the factor that contributes the most to those vulnerabilities. Future research can build on intersectionality theory by foregrounding the role of structural inequities and discrimination in promoting poor mental health and barriers to healthcare. © 2017 John Wiley & Sons Ltd.

An effective biometric discretization approach to extract highly discriminative, informative, and privacy-protective binary representation

NASA Astrophysics Data System (ADS)

Lim, Meng-Hui; Teoh, Andrew Beng Jin

2011-12-01

Biometric discretization derives a binary string for each user based on an ordered set of biometric features. This representative string ought to be discriminative, informative, and privacy protective when it is employed as a cryptographic key in various security applications upon error correction. However, it is commonly believed that satisfying the first and the second criteria simultaneously is not feasible, and a tradeoff between them is always definite. In this article, we propose an effective fixed bit allocation-based discretization approach which involves discriminative feature extraction, discriminative feature selection, unsupervised quantization (quantization that does not utilize class information), and linearly separable subcode (LSSC)-based encoding to fulfill all the ideal properties of a binary representation extracted for cryptographic applications. In addition, we examine a number of discriminative feature-selection measures for discretization and identify the proper way of setting an important feature-selection parameter. Encouraging experimental results vindicate the feasibility of our approach.

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

NASA Technical Reports Server (NTRS)

Schlosser, E. H.

1980-01-01

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

Discrimination of almonds (Prunus dulcis) geographical origin by minerals and fatty acids profiling.

PubMed

Amorello, Diana; Orecchio, Santino; Pace, Andrea; Barreca, Salvatore

2016-09-01

Twenty-one almond samples from three different geographical origins (Sicily, Spain and California) were investigated by determining minerals and fatty acids compositions. Data were used to discriminate by chemometry almond origin by linear discriminant analysis. With respect to previous PCA profiling studies, this work provides a simpler analytical protocol for the identification of almonds geographical origin. Classification by using mineral contents data only was correct in 77% of the samples, while, by using fatty acid profiles, the percentages of samples correctly classified reached 82%. The coupling of mineral contents and fatty acid profiles lead to an increased efficiency of the classification with 87% of samples correctly classified.

Probing thyroglobulin in undiluted human serum based on pattern recognition and competitive adsorption of proteins

NASA Astrophysics Data System (ADS)

Wang, Ran; Huang, Shuai; Li, Jing; Chae, Junseok

2014-10-01

Thyroglobulin (Tg) is a sensitive indicator of persistent or recurrent differentiated thyroid cancer of follicular cell origin. Detection of Tg in human serum is challenging as bio-receptors, such as anti-Tg, used in immunoassay have relatively weak binding affinity. We engineer sensing surfaces using the competitive adsorption of proteins, termed the Vroman Effect. Coupled with Surface Plasmon Resonance, the "cross-responsive" interactions of Tg on the engineered surfaces produce uniquely distinguishable multiple signature patterns, which are discriminated using Linear Discriminant Analysis. Tg-spiked samples, down to 2 ng/ml Tg in undiluted human serum, are sensitively and selectively discriminated from the control (undiluted human serum).

Advanced microwave soil moisture studies. [Big Sioux River Basin, Iowa

NASA Technical Reports Server (NTRS)

Dalsted, K. J.; Harlan, J. C.

1983-01-01

Comparisons of low level L-band brightness temperature (TB) and thermal infrared (TIR) data as well as the following data sets: soil map and land cover data; direct soil moisture measurement; and a computer generated contour map were statistically evaluated using regression analysis and linear discriminant analysis. Regression analysis of footprint data shows that statistical groupings of ground variables (soil features and land cover) hold promise for qualitative assessment of soil moisture and for reducing variance within the sampling space. Dry conditions appear to be more conductive to producing meaningful statistics than wet conditions. Regression analysis using field averaged TB and TIR data did not approach the higher sq R values obtained using within-field variations. The linear discriminant analysis indicates some capacity to distinguish categories with the results being somewhat better on a field basis than a footprint basis.

Multivariate calibration on NIR data: development of a model for the rapid evaluation of ethanol content in bakery products.

PubMed

Bello, Alessandra; Bianchi, Federica; Careri, Maria; Giannetto, Marco; Mori, Giovanni; Musci, Marilena

2007-11-05

A new NIR method based on multivariate calibration for determination of ethanol in industrially packed wholemeal bread was developed and validated. GC-FID was used as reference method for the determination of actual ethanol concentration of different samples of wholemeal bread with proper content of added ethanol, ranging from 0 to 3.5% (w/w). Stepwise discriminant analysis was carried out on the NIR dataset, in order to reduce the number of original variables by selecting those that were able to discriminate between the samples of different ethanol concentrations. With the so selected variables a multivariate calibration model was then obtained by multiple linear regression. The prediction power of the linear model was optimized by a new "leave one out" method, so that the number of original variables resulted further reduced.

Perceived Discrimination During Prenatal Care, Labor, and Delivery: An Examination of Data From the Oregon Pregnancy Risk Assessment Monitoring System, 1998–1999, 2000, and 2001

PubMed Central

Thorburn, Sheryl; Zhao, Weiyi

2008-01-01

Although recent research has examined discrimination in health care, no studies have investigated women's experiences during prenatal or obstetrical care. Analyses of data from the Oregon Pregnancy Risk Assessment Monitoring System showed that 18.53% of mothers reported discrimination by providers during prenatal care, labor, or delivery, most commonly because of age or insurance status. Perceived discrimination was associated with maternal characteristics such as age, marital status, and type of insurance, but not with number of subsequent well-baby visits. PMID:18703444

Sex determination of the Acadian Flycatcher using discriminant analysis

USGS Publications Warehouse

Wilson, R.R.

1999-01-01

I used five morphometric variables from 114 individuals captured in Arkansas to develop a discriminant model to predict the sex of Acadian Flycatchers (Empidonax virescens). Stepwise discriminant function analyses selected wing chord and tail length as the most parsimonious subset of variables for discriminating sex. This two-variable model correctly classified 80% of females and 97% of males used to develop the model. Validation of the model using 19 individuals from Louisiana and Virginia resulted in 100% correct classification of males and females. This model provides criteria for sexing monomorphic Acadian Flycatchers during the breeding season and possibly during the winter.

Racial/Ethnic Discrimination and Mental Health in Mexican-Origin Youths and Their Parents: Testing the "Linked Lives" Hypothesis.

PubMed

Park, Irene J K; Du, Han; Wang, Lijuan; Williams, David R; Alegría, Margarita

2018-04-01

Using a life course perspective, the present study tested the concept of "linked lives" applied to the problem of not only how racial/ethnic discrimination may be associated with poor mental health for the target of discrimination but also how discrimination may exacerbate the discrimination-distress link for others in the target's social network-in this case, the family. The discrimination-distress link was investigated among 269 Mexican-origin adolescents and their parents both cross-sectionally and longitudinally. It was hypothesized that parents' discrimination experiences would adversely affect their adolescent children's mental health via a moderating effect on the target adolescent discrimination-distress link. The converse was also hypothesized for the target parents. Multilevel moderation analyses were conducted to test the moderating effect of parents' discrimination experiences on the youth discrimination-distress link. We also tested the moderating effect of youths' discrimination experiences on the parent discrimination-distress link. Parents' discrimination experiences significantly moderated the longitudinal association between youths' discrimination stress appraisals and mental health, such that the father's discrimination experiences exacerbated the youth discrimination-depression link. Youths' discrimination stress appraisals were not a significant moderator of the cross-sectional parent discrimination-mental health association. Implications of these findings are discussed from a linked lives perspective, highlighting how fathers' discrimination experiences can adversely affect youths who are coping with discrimination, in terms of their mental health. Copyright © 2017 The Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Local structure-based image decomposition for feature extraction with applications to face recognition.

PubMed

Qian, Jianjun; Yang, Jian; Xu, Yong

2013-09-01

This paper presents a robust but simple image feature extraction method, called image decomposition based on local structure (IDLS). It is assumed that in the local window of an image, the macro-pixel (patch) of the central pixel, and those of its neighbors, are locally linear. IDLS captures the local structural information by describing the relationship between the central macro-pixel and its neighbors. This relationship is represented with the linear representation coefficients determined using ridge regression. One image is actually decomposed into a series of sub-images (also called structure images) according to a local structure feature vector. All the structure images, after being down-sampled for dimensionality reduction, are concatenated into one super-vector. Fisher linear discriminant analysis is then used to provide a low-dimensional, compact, and discriminative representation for each super-vector. The proposed method is applied to face recognition and examined using our real-world face image database, NUST-RWFR, and five popular, publicly available, benchmark face image databases (AR, Extended Yale B, PIE, FERET, and LFW). Experimental results show the performance advantages of IDLS over state-of-the-art algorithms.

Socialization of Culture and Coping with Discrimination Among American Indian Families: Examining Cultural Correlates of Youth Outcomes

PubMed Central

Yasui, Miwa; Dishion, Thomas J.; Stormshak, Elizabeth; Ball, Alison

2016-01-01

Objective The current study examines the interrelations between observed parental cultural socialization and socialization of coping with discrimination, and youth outcomes among a sample of 92 American Indian adolescents and their parents in a rural reservation. Method Path analysis is used to examine the relationships among observed parental socialization (cultural socialization and socialization of coping with discrimination), and youth-reported perceived discrimination, ethnic identity and depression. Results Findings reveal that higher levels of observed parental cultural socialization and socialization of coping with discrimination predict lower levels of depression as reported by youth 1 year later. Path analyses also show that observed parental cultural socialization and socialization of coping with discrimination are positively associated with youth ethnic identity. Conclusions These findings point to the importance of integrating familial socialization of culture and coping with discrimination in fostering resilience among American Indian youth. PMID:28503256

Perceived discrimination and health among Puerto Rican and Mexican Americans: buffering effect of the Lazo matrimonial?

PubMed

Lee, Min-Ah; Ferraro, Kenneth F

2009-06-01

An emerging body of research shows that perceived discrimination adversely influences the mental health of minority populations, but is it also deleterious to physical health? If yes, can marriage buffer the effect of perceived discrimination on physical health? We address these questions with data from Puerto Rican and Mexican American residents of Chicago. Multivariate regression analyses reveal that perceived discrimination is associated with more physical health problems for both Puerto Rican and Mexican Americans. In addition, an interaction effect between marital status and perceived discrimination was observed: married Mexican Americans with higher perceived discrimination had fewer physical health problems than their unmarried counterparts even after adjusting for differential effects of marriage by nativity. The findings reveal that perceived discrimination is detrimental to the physical health of both Puerto Rican and Mexican Americans, but that the stress-buffering effect of marriage on physical health exists for Mexican Americans only.

Discrimination and mental health among Latinos: variation by place of origin.

PubMed

Held, Mary L; Lee, Sungkyu

2017-10-01

The US Latino population experiences high rates of discrimination, which may contribute to psychiatric disorders. Yet, little is known about the distinctions in this relationship for Latino subgroups. Using data from the National Latino and Asian American study, we examined the association between discrimination and mental health for 2503 Latinos. Logistic regression analyses were used to examine variation in the relationship by place of origin (Cuba, Puerto Rico, Mexico, or Other). Results suggest that perceived discrimination increased the probability of having a psychiatric disorder. The effect of discrimination on having a psychiatric disorder was greater for Mexicans than Puerto Ricans. The findings of this study suggest that variation exists in the relationship between discrimination and mental health by origin. Implications for practice include increasing awareness of place of origin, in addition to discrimination, as a risk factor for mental illness. Future research should examine this relationship longitudinally and consider immigration status.

Anxiety Mediates Perceived Discrimination and Health in African-American Women.

PubMed

Carter, Sierra E; Walker, Rheeda L; Cutrona, Carolyn E; Simons, Ronald L; Beach, Steven R H

2016-11-01

We examined the mediational role of symptoms of anxiety in accounting for the association of discrimination and chronic health conditions among African-American women. Participants were 646 African-American women who completed self-report measures of perceived racial discrimination, symptoms of anxiety, and diagnosed chronic health problems. We examined the mediation hypothesis using a path analytic procedure. Mediational analyses indicated that, above and beyond symptoms of depression, age, and education status, anxiety symptoms were associated with both racial discrimination (β = .03, SE = .01, p < .001) and chronic health problems (β = .33, SE = .09, p < .001) and significantly mediated the discrimination-health association (β = -.01, SE = .01, p = .16). These findings highlight the potentially vital role of symptoms of anxiety in the process that occurs from an individual's perception of discrimination to reported chronic health outcomes. Future research expanding our understanding of the interconnection of psychosocial stressors, discrimination, and their biological sequelae is needed.

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis.

PubMed

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L

2016-01-01

The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n. , Camponotus androy sp. n. , Camponotus bevohitra sp. n. , Camponotus galoko sp. n. , Camponotus matsilo sp. n. , Camponotus mifaka sp. n. , Camponotus orombe sp. n. , Camponotus tafo sp. n. , Camponotus tratra sp. n. , Camponotus varatra sp. n. , and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi . This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases.

Revision of the Malagasy Camponotus edmondi species group (Hymenoptera, Formicidae, Formicinae): integrating qualitative morphology and multivariate morphometric analysis

PubMed Central

Rakotonirina, Jean Claude; Csősz, Sándor; Fisher, Brian L.

2016-01-01

Abstract The Malagasy Camponotus edmondi species group is revised based on both qualitative morphological traits and multivariate analysis of continuous morphometric data. To minimize the effect of the scaling properties of diverse traits due to worker caste polymorphism, and to achieve the desired near-linearity of data, morphometric analyses were done only on minor workers. The majority of traits exhibit broken scaling on head size, dividing Camponotus workers into two discrete subcastes, minors and majors. This broken scaling prevents the application of algorithms that uses linear combination of data to the entire dataset, hence only minor workers were analyzed statistically. The elimination of major workers resulted in linearity and the data meet required assumptions. However, morphometric ratios for the subsets of minor and major workers were used in species descriptions and redefinitions. Prior species hypotheses and the goodness of clusters were tested on raw data by confirmatory linear discriminant analysis. Due to the small sample size available for some species, a factor known to reduce statistical reliability, hypotheses generated by exploratory analyses were tested with extreme care and species delimitations were inferred via the combined evidence of both qualitative (morphology and biology) and quantitative data. Altogether, fifteen species are recognized, of which 11 are new to science: Camponotus alamaina sp. n., Camponotus androy sp. n., Camponotus bevohitra sp. n., Camponotus galoko sp. n., Camponotus matsilo sp. n., Camponotus mifaka sp. n., Camponotus orombe sp. n., Camponotus tafo sp. n., Camponotus tratra sp. n., Camponotus varatra sp. n., and Camponotus zavo sp. n. Four species are redescribed: Camponotus echinoploides Forel, Camponotus edmondi André, Camponotus ethicus Forel, and Camponotus robustus Roger. Camponotus edmondi ernesti Forel, syn. n. is synonymized under Camponotus edmondi. This revision also includes an identification key to species for both minor and major castes, information on geographic distribution and biology, taxonomic discussions, and descriptions of intraspecific variation. Traditional taxonomy and multivariate morphometric analysis are independent sources of information which, in combination, allow more precise species delimitation. Moreover, quantitative characters included in identification keys improve accuracy of determination in difficult cases. PMID:28050160

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

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Characterization of Italian honeys (Marche Region) on the basis of their mineral content and some typical quality parameters

PubMed Central

Conti, Marcelo Enrique; Stripeikis, Jorge; Campanella, Luigi; Cucina, Domenico; Tudino, Mabel Beatriz

2007-01-01

Background The characterization of three types of Marche (Italy) honeys (Acacia, Multifloral, Honeydew) was carried out on the basis of the their quality parameters (pH, sugar content, humidity) and mineral content (Na, K, Ca, Mg, Cu, Fe, and Mn). Pattern recognition methods such as principal components analysis (PCA) and linear discriminant analysis (LDA) were performed in order to classify honey samples whose botanical origins were different, and identify the most discriminant parameters. Lastly, using ANOVA and correlations for all parameters, significant differences between diverse types of honey were examined. Results Most of the samples' water content showed good maturity (98%) whilst pH values were in the range 3.50 – 4.21 confirming the good quality of the honeys analysed. Potassium was quantitatively the most relevant mineral (mean = 643 ppm), accounting for 79% of the total mineral content. The Ca, Na and Mg contents account for 14, 3 and 3% of the total mineral content respectively, while other minerals (Cu, Mn, Fe) were present at very low levels. PCA explained 75% or more of the variance with the first two PC variables. The variables with higher discrimination power according to the multivariate statistical procedure were Mg and pH. On the other hand, all samples of acacia and honeydew, and more than 90% of samples of multifloral type have been correctly classified using the LDA. ANOVA shows significant differences between diverse floral origins for all variables except sugar, moisture and Fe. Conclusion In general, the analytical results obtained for the Marche honeys indicate the products' high quality. The determination of physicochemical parameters and mineral content in combination with modern statistical techniques can be a useful tool for honey classification. PMID:17880749

Discrimination of lichen genera and species using element concentrations

USGS Publications Warehouse

Bennett, James P.

2008-01-01

The importance of organic chemistry in the classification of lichens is well established, but inorganic chemistry has been largely overlooked. Six lichen species were studied over a period of 23 years that were growing in 11 protected areas of the northern Great Lakes ecoregion, which were not greatly influenced by anthropogenic particulates or gaseous air pollutants. The elemental data from these studies were aggregated in order to test the hypothesis that differences among species in tissue element concentrations were large enough to discriminate between taxa faithfully. Concentrations of 16 chemical elements that were found in tissue samples from Cladonia rangiferina, Evernia mesomorpha, Flavopunctelia flaventior, Hypogymnia physodes, Parmelia sulcata, and Punctelia rudecta were analyzed statistically using multivariate discriminant functions and CART analyses, as well as t-tests. Genera and species were clearly separated in element space, and elemental discriminant functions were able to classify 91-100 of the samples correctly into species. At the broadest level, a Zn concentration of 51 ppm in tissues of four of the lichen species effectively discriminated foliose from fruticose species. Similarly, a S concentration of 680 ppm discriminated C. rangiferina and E. mesomorpha, and a Ca concentration of 10 436 ppm discriminated H. physodes from P. sulcata. For the three parmelioid species, a Ca concentration >32 837 ppm discriminated Punctelia rudecta from the other two species, while a Zn concentration of 56 ppm discriminated Parmelia sulcata from F. flaventior. Foliose species also had higher concentrations than did fruticose species of all elements except Na. Elemental signatures for each of the six species were developed using standardized means. Twenty-four mechanisms explaining the differences among species are summarized. Finally, the relationships of four species based on element concentrations, using additive-trees clustering of a Euclidean-distance matrix, produced identical relationships as did analyses based on secondary product chemistry that used additive-trees clustering of a Jaccard similarity matrix. At least for these six species, element composition has taxonomic significance, and may be useful for discriminating other taxa.

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

[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.

ASSESSMENT OF FECAL POLLUTION SOURCES IN PLUM CREEK WATERSHED USING PCR AND PHYLOGENETIC ANALYSES OF BACTEROIDETES 16S RDNA

EPA Science Inventory

Traditional methods for assessing fecal pollution in environmental systems, such as monitoring for fecal coliforms are not capable of discriminating between different sources fecal pollution. Recently, 16S rDNA Bacteroidetes-targeted PCR assays were developed to discriminate betw...

Socioeconomic Status Discrimination is Associated with Poor Sleep in African-Americans, but not Whites

PubMed Central

Van Dyke, Miriam E.; Vaccarino, Viola; Quyyumi, Arshed A.; Lewis, Tené T.

2016-01-01

Rationale Research on self-reported experiences of discrimination and health has grown in recent decades, but has largely focused on racial discrimination or overall mistreatment. Less is known about reports of discrimination on the basis of socioeconomic status (SES), despite the fact that SES is one of the most powerful social determinants of health. Objective We sought to examine the cross-sectional association between self-reported SES discrimination and subjective sleep quality, an emerging risk factor for disease. We further examined whether associations differed by race or SES. Methods We used logistic and linear regression to analyze data from a population-based cohort of 425 African-American and White middle-aged adults (67.5% female) in the Southeastern United States. SES discrimination was assessed with a modified Experiences of Discrimination Scale and poor subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index. Results In logistic regression models adjusted for age, gender, and education, reports of SES discrimination were associated with poor sleep quality among African-Americans (OR=2.39, 95% CI =1.35, 4.24), but not Whites (OR=1.03, 95% CI= 0.57, 1.87), and the race × SES discrimination interaction was significant at p=0.04. After additional adjustments for reports of racial and gender discrimination, other psychosocial stressors, body mass index and depressive symptoms, SES discrimination remained a significant predictor of poor sleep among African-Americans, but not Whites. In contrast to findings by race, SES discrimination and sleep associations did not significantly differ by SES. Conclusion Findings suggest that reports of SES discrimination may be an important risk factor for subjective sleep quality among African-Americans and support the need to consider the health impact of SES-related stressors in the context of race. PMID:26896878

Socioeconomic status discrimination is associated with poor sleep in African-Americans, but not Whites.

PubMed

Van Dyke, Miriam E; Vaccarino, Viola; Quyyumi, Arshed A; Lewis, Tené T

2016-03-01

Research on self-reported experiences of discrimination and health has grown in recent decades, but has largely focused on racial discrimination or overall mistreatment. Less is known about reports of discrimination on the basis of socioeconomic status (SES), despite the fact that SES is one of the most powerful social determinants of health. We sought to examine the cross-sectional association between self-reported SES discrimination and subjective sleep quality, an emerging risk factor for disease. We further examined whether associations differed by race or SES. We used logistic and linear regression to analyze data from a population-based cohort of 425 African-American and White middle-aged adults (67.5% female) in the Southeastern United States. SES discrimination was assessed with a modified Experiences of Discrimination Scale and poor subjective sleep quality was assessed with the Pittsburgh Sleep Quality Index. In logistic regression models adjusted for age, gender, and education, reports of SES discrimination were associated with poor sleep quality among African-Americans (OR = 2.39 95%, CI = 1.35, 4.24), but not Whites (OR = 1.03, 95% CI = 0.57, 1.87), and the race × SES discrimination interaction was significant at p = 0.04. After additional adjustments for reports of racial and gender discrimination, other psychosocial stressors, body mass index and depressive symptoms, SES discrimination remained a significant predictor of poor sleep among African-Americans, but not Whites. In contrast to findings by race, SES discrimination and sleep associations did not significantly differ by SES. Findings suggest that reports of SES discrimination may be an important risk factor for subjective sleep quality among African-Americans and support the need to consider the health impact of SES-related stressors in the context of race. Copyright © 2016 Elsevier Ltd. All rights reserved.

Testing for nonlinearity in time series: The method of surrogate data

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

Theiler, J.; Galdrikian, B.; Longtin, A.

1991-01-01

We describe a statistical approach for identifying nonlinearity in time series; in particular, we want to avoid claims of chaos when simpler models (such as linearly correlated noise) can explain the data. The method requires a careful statement of the null hypothesis which characterizes a candidate linear process, the generation of an ensemble of surrogate'' data sets which are similar to the original time series but consistent with the null hypothesis, and the computation of a discriminating statistic for the original and for each of the surrogate data sets. The idea is to test the original time series against themore » null hypothesis by checking whether the discriminating statistic computed for the original time series differs significantly from the statistics computed for each of the surrogate sets. We present algorithms for generating surrogate data under various null hypotheses, and we show the results of numerical experiments on artificial data using correlation dimension, Lyapunov exponent, and forecasting error as discriminating statistics. Finally, we consider a number of experimental time series -- including sunspots, electroencephalogram (EEG) signals, and fluid convection -- and evaluate the statistical significance of the evidence for nonlinear structure in each case. 56 refs., 8 figs.« less

Integrated InP frequency discriminator for Phase-modulated microwave photonic links.

PubMed

Fandiño, J S; Doménech, J D; Muñoz, P; Capmany, J

2013-02-11

We report the design, fabrication and characterization of an integrated frequency discriminator on InP technology for microwave photonic phase modulated links. The optical chip is, to the best of our knowledge, the first reported in an active platform and the first to include the optical detectors. The discriminator, designed as a linear filter in intensity, features preliminary SFDR values the range between 67 and 79 dB.Hz(2/3) for signal frequencies in the range of 5-9 GHz limited, in principle, by the high value of the optical losses arising from the use of several free space coupling devices in our experimental setup. As discussed, these losses can be readily reduced by the use of integrated spot-size converters improving the SFDR by 17.3 dB (84-96 dB.Hz(2/3)). Further increase up to a range of (104-116 dB.Hz(2/3)) is possible by reducing the system noise eliminating the EDFA employed in the setup and using a commercially available laser source providing higher output power and lower relative intensity noise. Other paths for improvement requiring a filter redesign to be linear in the optical field are also discussed.

Kernel-based discriminant feature extraction using a representative dataset

NASA Astrophysics Data System (ADS)

Li, Honglin; Sancho Gomez, Jose-Luis; Ahalt, Stanley C.

2002-07-01

Discriminant Feature Extraction (DFE) is widely recognized as an important pre-processing step in classification applications. Most DFE algorithms are linear and thus can only explore the linear discriminant information among the different classes. Recently, there has been several promising attempts to develop nonlinear DFE algorithms, among which is Kernel-based Feature Extraction (KFE). The efficacy of KFE has been experimentally verified by both synthetic data and real problems. However, KFE has some known limitations. First, KFE does not work well for strongly overlapped data. Second, KFE employs all of the training set samples during the feature extraction phase, which can result in significant computation when applied to very large datasets. Finally, KFE can result in overfitting. In this paper, we propose a substantial improvement to KFE that overcomes the above limitations by using a representative dataset, which consists of critical points that are generated from data-editing techniques and centroid points that are determined by using the Frequency Sensitive Competitive Learning (FSCL) algorithm. Experiments show that this new KFE algorithm performs well on significantly overlapped datasets, and it also reduces computational complexity. Further, by controlling the number of centroids, the overfitting problem can be effectively alleviated.

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

PubMed

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

2015-11-01

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

Local linear discriminant analysis framework using sample neighbors.

PubMed

Fan, Zizhu; Xu, Yong; Zhang, David

2011-07-01

The linear discriminant analysis (LDA) is a very popular linear feature extraction approach. The algorithms of LDA usually perform well under the following two assumptions. The first assumption is that the global data structure is consistent with the local data structure. The second assumption is that the input data classes are Gaussian distributions. However, in real-world applications, these assumptions are not always satisfied. In this paper, we propose an improved LDA framework, the local LDA (LLDA), which can perform well without needing to satisfy the above two assumptions. Our LLDA framework can effectively capture the local structure of samples. According to different types of local data structure, our LLDA framework incorporates several different forms of linear feature extraction approaches, such as the classical LDA and principal component analysis. The proposed framework includes two LLDA algorithms: a vector-based LLDA algorithm and a matrix-based LLDA (MLLDA) algorithm. MLLDA is directly applicable to image recognition, such as face recognition. Our algorithms need to train only a small portion of the whole training set before testing a sample. They are suitable for learning large-scale databases especially when the input data dimensions are very high and can achieve high classification accuracy. Extensive experiments show that the proposed algorithms can obtain good classification results.

A GPS Phase-Locked Loop Performance Metric Based on the Phase Discriminator Output

PubMed Central

Stevanovic, Stefan; Pervan, Boris

2018-01-01

We propose a novel GPS phase-lock loop (PLL) performance metric based on the standard deviation of tracking error (defined as the discriminator’s estimate of the true phase error), and explain its advantages over the popular phase jitter metric using theory, numerical simulation, and experimental results. We derive an augmented GPS phase-lock loop (PLL) linear model, which includes the effect of coherent averaging, to be used in conjunction with this proposed metric. The augmented linear model allows more accurate calculation of tracking error standard deviation in the presence of additive white Gaussian noise (AWGN) as compared to traditional linear models. The standard deviation of tracking error, with a threshold corresponding to half of the arctangent discriminator pull-in region, is shown to be a more reliable/robust measure of PLL performance under interference conditions than the phase jitter metric. In addition, the augmented linear model is shown to be valid up until this threshold, which facilitates efficient performance prediction, so that time-consuming direct simulations and costly experimental testing can be reserved for PLL designs that are much more likely to be successful. The effect of varying receiver reference oscillator quality on the tracking error metric is also considered. PMID:29351250

Classification of sodium MRI data of cartilage using machine learning.

PubMed

Madelin, Guillaume; Poidevin, Frederick; Makrymallis, Antonios; Regatte, Ravinder R

2015-11-01

To assess the possible utility of machine learning for classifying subjects with and subjects without osteoarthritis using sodium magnetic resonance imaging data. Theory: Support vector machine, k-nearest neighbors, naïve Bayes, discriminant analysis, linear regression, logistic regression, neural networks, decision tree, and tree bagging were tested. Sodium magnetic resonance imaging with and without fluid suppression by inversion recovery was acquired on the knee cartilage of 19 controls and 28 osteoarthritis patients. Sodium concentrations were measured in regions of interests in the knee for both acquisitions. Mean (MEAN) and standard deviation (STD) of these concentrations were measured in each regions of interest, and the minimum, maximum, and mean of these two measurements were calculated over all regions of interests for each subject. The resulting 12 variables per subject were used as predictors for classification. Either Min [STD] alone, or in combination with Mean [MEAN] or Min [MEAN], all from fluid suppressed data, were the best predictors with an accuracy >74%, mainly with linear logistic regression and linear support vector machine. Other good classifiers include discriminant analysis, linear regression, and naïve Bayes. Machine learning is a promising technique for classifying osteoarthritis patients and controls from sodium magnetic resonance imaging data. © 2014 Wiley Periodicals, Inc.

No experience required: Violent crime and anticipated, vicarious, and experienced racial discrimination.

PubMed

Herda, Daniel; McCarthy, Bill

2018-02-01

There is a growing body of evidence linking racial discrimination and juvenile crime, and a number of theories explain this relationship. In this study, we draw on one popular approach, Agnew's general strain theory, and extend prior research by moving from a focus on experienced discrimination to consider two other forms, anticipated and vicarious discrimination. Using data on black, white, and Hispanic youth, from the Project on Human Development in Chicago Neighborhoods (PHDCN), we find that experienced, anticipated, and to a lesser extent, vicarious discrimination, significantly predict violent crime independent of a set of neighborhood, parental, and individual level controls, including prior violent offending. Additional analyses on the specific contexts of discrimination reveal that violence is associated with the anticipation of police discrimination. The effects tend to be larger for African American than Hispanic youth, but the differences are not statistically significant. These findings support the thesis that, like other strains, discrimination may not have to be experienced directly to influence offending. Copyright © 2017. Published by Elsevier Inc.

Relationship of race-, sexual orientation-, and HIV-related discrimination with adherence to HIV treatment: a pilot study.

PubMed

Boarts, Jessica M; Bogart, Laura M; Tabak, Melanie A; Armelie, Aaron P; Delahanty, Douglas L

2008-10-01

Adherence to highly active antiretroviral therapy (HAART) must be close to perfect in order to maintain suppression of HIV viral load, and to prevent the development of drug resistant strains of HIV. People living with HIV (PLWH) often report low levels of adherence. One variable that has been linked to poor adherence is perceived discrimination; however, research has generally not considered the possible unique effects of different types of discrimination on adherence. The present pilot study aimed to examine the association of three types of discrimination (due to HIV+ status, race, or sexual orientation) with adherence among 57 PLWH. Logistic regression analyses were conducted to demonstrate the relationships between each type of discrimination and self-reported adherence. Racial discrimination significantly predicted lower adherence levels, whereas sexual orientation- and HIV-related discrimination did not. Results underscore the importance of addressing discrimination issues, specifically racial, when designing interventions to improve adherence to HAART.

Discrimination and substance use disorders among Latinos: the role of gender, nativity, and ethnicity.

PubMed

Otiniano Verissimo, Angie Denisse; Grella, Christine E; Amaro, Hortensia; Gee, Gilbert C

2014-08-01

We examined the relationship between discrimination and substance use disorders among a diverse sample of Latinos. We also investigated whether the relationship between discrimination and substance use disorders varied by gender, nativity, and ethnicity. Our analyses focused on 6294 Latinos who participated in the National Epidemiologic Survey on Alcohol and Related Conditions from 2004 to 2005. We used multinomial logistic regression to examine the association between discrimination and substance use disorders. Discrimination was significantly associated with increased odds of alcohol and drug use disorders among Latinos. However, the relationship between discrimination and substance use disorders varied by gender, nativity, and ethnicity. Discrimination was associated with increased odds of alcohol and drug use disorders for certain groups, such as women, US-born Latinos, and Mexicans, but this relationship did not follow the same pattern for other subgroups. It is important to determine which subgroups among Latinos may be particularly vulnerable to the negative effects of discrimination to address their needs.

The association of optimism and perceived discrimination with health care utilization in adults with sickle cell disease.

PubMed

Stanton, Michael V; Jonassaint, Charles R; Bartholomew, Frederick B; Edwards, Christopher; Richman, Laura; DeCastro, Laura; Williams, Redford

2010-11-01

We evaluated the effect of perceived discrimination, optimism, and their interaction on health care utilization among African American adults with sickle cell disease (SCD). Measures of optimism and perceived discrimination were obtained in 49 African American SCD patients. Multiple regression analyses controlling for sex and age tested effects of optimism and perceived discrimination on the number of emergency department visits (ED) and number and duration of hospitalizations over the past year. A perceived discrimination-optimism interaction was associated with number of emergency departments visits (b = .29, p = .052), number of hospitalizations (b = .36, p = .019), and duration of hospitalizations (b = .30, p = .045) such that those with high perceived discrimination/high optimism had the greatest health care utilization. African American SCD patients with high perceived discrimination/high optimism had greater health care utilization than patients who reported either low perceived discrimination or low optimism. This study suggests that patient personality and coping styles should be considered when evaluating the effects of stress on SCD-related outcomes.

The costs of racism for marriage: how racial discrimination hurts, and ethnic identity protects, newlywed marriages among Latinos.

PubMed

Trail, Thomas E; Goff, Phillip Atiba; Bradbury, Thomas N; Karney, Benjamin R

2012-04-01

The experience of racial or ethnic discrimination is a salient and severe stressor that has been linked to numerous disparities in important outcomes. Yet, the link between perceived discrimination and marital outcomes has been overlooked by research on relationship stressors. The current study examined this link and tested whether ethnic identity buffered the relation between discrimination and ratings of marital quality and verbal aggression. A sample of 330 Latino newlyweds completed measures of perceived discrimination, ethnic identity, spouse's verbal aggression, and marital quality. Each spouse's interviewer also independently rated marital quality. Dyadic analyses revealed that husbands' experience of discrimination negatively predicted wives' marital quality, but only for husbands with weak ethnic identity. Wives whose husbands had strong ethnic identity were buffered from this effect. Identity also buffered the relation between husbands' discrimination and verbal aggression toward their wives, and this effect mediated the association between discrimination, identity, and marital quality.

Object recognition with hierarchical discriminant saliency networks.

PubMed

Han, Sunhyoung; Vasconcelos, Nuno

2014-01-01

The benefits of integrating attention and object recognition are investigated. While attention is frequently modeled as a pre-processor for recognition, we investigate the hypothesis that attention is an intrinsic component of recognition and vice-versa. This hypothesis is tested with a recognition model, the hierarchical discriminant saliency network (HDSN), whose layers are top-down saliency detectors, tuned for a visual class according to the principles of discriminant saliency. As a model of neural computation, the HDSN has two possible implementations. In a biologically plausible implementation, all layers comply with the standard neurophysiological model of visual cortex, with sub-layers of simple and complex units that implement a combination of filtering, divisive normalization, pooling, and non-linearities. In a convolutional neural network implementation, all layers are convolutional and implement a combination of filtering, rectification, and pooling. The rectification is performed with a parametric extension of the now popular rectified linear units (ReLUs), whose parameters can be tuned for the detection of target object classes. This enables a number of functional enhancements over neural network models that lack a connection to saliency, including optimal feature denoising mechanisms for recognition, modulation of saliency responses by the discriminant power of the underlying features, and the ability to detect both feature presence and absence. In either implementation, each layer has a precise statistical interpretation, and all parameters are tuned by statistical learning. Each saliency detection layer learns more discriminant saliency templates than its predecessors and higher layers have larger pooling fields. This enables the HDSN to simultaneously achieve high selectivity to target object classes and invariance. The performance of the network in saliency and object recognition tasks is compared to those of models from the biological and computer vision literatures. This demonstrates benefits for all the functional enhancements of the HDSN, the class tuning inherent to discriminant saliency, and saliency layers based on templates of increasing target selectivity and invariance. Altogether, these experiments suggest that there are non-trivial benefits in integrating attention and recognition.

A Novel Method to Handle the Effect of Uneven Sampling Effort in Biodiversity Databases

PubMed Central

Pardo, Iker; Pata, María P.; Gómez, Daniel; García, María B.

2013-01-01

How reliable are results on spatial distribution of biodiversity based on databases? Many studies have evidenced the uncertainty related to this kind of analysis due to sampling effort bias and the need for its quantification. Despite that a number of methods are available for that, little is known about their statistical limitations and discrimination capability, which could seriously constrain their use. We assess for the first time the discrimination capacity of two widely used methods and a proposed new one (FIDEGAM), all based on species accumulation curves, under different scenarios of sampling exhaustiveness using Receiver Operating Characteristic (ROC) analyses. Additionally, we examine to what extent the output of each method represents the sampling completeness in a simulated scenario where the true species richness is known. Finally, we apply FIDEGAM to a real situation and explore the spatial patterns of plant diversity in a National Park. FIDEGAM showed an excellent discrimination capability to distinguish between well and poorly sampled areas regardless of sampling exhaustiveness, whereas the other methods failed. Accordingly, FIDEGAM values were strongly correlated with the true percentage of species detected in a simulated scenario, whereas sampling completeness estimated with other methods showed no relationship due to null discrimination capability. Quantifying sampling effort is necessary to account for the uncertainty in biodiversity analyses, however, not all proposed methods are equally reliable. Our comparative analysis demonstrated that FIDEGAM was the most accurate discriminator method in all scenarios of sampling exhaustiveness, and therefore, it can be efficiently applied to most databases in order to enhance the reliability of biodiversity analyses. PMID:23326357

Discrimination and participation in traditional healing for American Indians and Alaska Natives.

PubMed

Moghaddam, Jacquelene F; Momper, Sandra L; Fong, Timothy

2013-12-01

Contemporary American Indians and Alaska Natives (AIs/ANs) who live in urban areas today face the daunting task of navigating an urban landscape while maintaining the facets of their respective Native cultures. While AIs/ANs continue to grapple with the intergenerational trauma associated with forced assimilation, relocation movements, and boarding schools, these traumas have manifested themselves in elevated rates of psychopathology. AIs/ANs have elevated rates of domestic abuse, poverty, suicide, and substance misuse. Furthermore, AIs/ANs, like many other minority cultures often face discrimination in their everyday lives. In light of the aversive experiences they face, AI/AN people have followed the tenets of ritual and traditional healing to address imbalances in the body, mind, and spirit. For providers working with AI/AN clients, it is important to understand who is using traditional healing and why they are using alternative services. Secondary data analyses of survey data from 389 urban AIs/ANs were utilized in order to determine the relationship between experiences of discrimination and traditional healing use. Analyses indicated that experiences of discrimination in healthcare settings were significantly associated with participation in traditional healing. Analyses also indicated that nearly a quarter of the sample reported discrimination in a healthcare setting, roughly half of the sample had used traditional healing, and that the majority of those who had used traditional healing were women, and ages 35-44 (27%). This study calls attention to the socio-demographic factors implicated in traditional healing use by urban AI/AN people, in addition to the clinical and demographic characteristics of this sample.

A novel method to handle the effect of uneven sampling effort in biodiversity databases.

PubMed

Pardo, Iker; Pata, María P; Gómez, Daniel; García, María B

2013-01-01

How reliable are results on spatial distribution of biodiversity based on databases? Many studies have evidenced the uncertainty related to this kind of analysis due to sampling effort bias and the need for its quantification. Despite that a number of methods are available for that, little is known about their statistical limitations and discrimination capability, which could seriously constrain their use. We assess for the first time the discrimination capacity of two widely used methods and a proposed new one (FIDEGAM), all based on species accumulation curves, under different scenarios of sampling exhaustiveness using Receiver Operating Characteristic (ROC) analyses. Additionally, we examine to what extent the output of each method represents the sampling completeness in a simulated scenario where the true species richness is known. Finally, we apply FIDEGAM to a real situation and explore the spatial patterns of plant diversity in a National Park. FIDEGAM showed an excellent discrimination capability to distinguish between well and poorly sampled areas regardless of sampling exhaustiveness, whereas the other methods failed. Accordingly, FIDEGAM values were strongly correlated with the true percentage of species detected in a simulated scenario, whereas sampling completeness estimated with other methods showed no relationship due to null discrimination capability. Quantifying sampling effort is necessary to account for the uncertainty in biodiversity analyses, however, not all proposed methods are equally reliable. Our comparative analysis demonstrated that FIDEGAM was the most accurate discriminator method in all scenarios of sampling exhaustiveness, and therefore, it can be efficiently applied to most databases in order to enhance the reliability of biodiversity analyses.

Generic anthropometric and performance characteristics among elite adolescent boys in nine different sports.

PubMed

Pion, Johan; Segers, Veerle; Fransen, Job; Debuyck, Gijs; Deprez, Dieter; Haerens, Leen; Vaeyens, Roel; Philippaerts, Renaat; Lenoir, Matthieu

2015-01-01

The aim of the present study was to evaluate the Flemish Sports Compass (FSC), a non-sport-specific generic testing battery. It was hypothesised that a set of 22 tests would have sufficient discriminant power to allocate athletes to their own sport based on a unique combination of test scores. First, discriminant analyses were applied to the 22 tests of anthropometry, physical fitness and motor coordination in 141 boys under age 18 (16.1 ± 0.8 years) and post age at peak height velocity (maturity offset = 2.674 ± 0.926) from Flemish Top Sport Academies for badminton, basketball, gymnastics, handball, judo, soccer, table tennis, triathlon and volleyball. Second, nine sequential discriminant analyses were used to assess the ability of a set of relevant performance characteristics classifying participants and non-participants for the respective sports. Discriminant analyses resulted in a 96.4% correct classification of all participants for the nine different sports. When focusing on relevant performance characteristics, 80.1% to 97.2% of the total test sample was classified correctly within their respective disciplines. The discriminating characteristics were briefly the following: flexibility in gymnastics, explosive lower-limb strength in badminton and volleyball, speed and agility in badminton, judo, soccer and volleyball, upper-body strength in badminton, basketball and gymnastics, cardiorespiratory endurance in triathletes, dribbling skills in handball, basketball and soccer and overhead-throwing skills in badminton and volleyball. The generic talent characteristics of the FSC enable the distinction of adolescent boys according to their particular sport. Implications for talent programmes are discussed.

Discrimination, Racial/Ethnic Identity, and Substance Use Among Latina/os: Are They Gendered?

PubMed Central

Jackson, Benita; Rivera-Olmedo, Noemi

2016-01-01

Background Prior research suggests that stronger racial/ethnic identification offsets negative effects of discrimination on substance use. Yet research in this area and on whether gender modifies this association is limited for Latina/os. Purpose The purpose of the present study is to examine whether different sources of discrimination (everyday and racial/ethnic) are associated with substance use (alcohol use disorder, smoking), if racial/ethnic identity buffers this association, and the potential moderating role of gender among these variables. Methods We present cross-sectional, US population-based data from the Latina/o adult sample (1427 females and 1127 males) of the National Latino and Asian American Study. Respondents completed self-reported measures of everyday and racial/ethnic discrimination, racial/ethnic identity, smoking status, and Diagnostic and Statistical Manual of Mental Disorders, 4th edition (DSM-IV) lifetime alcohol use disorder. Results Weighted logistic regression analyses showed that before inclusion of three-way interactions and adjusting for covariates, everyday discrimination predicted increased risk for any DSM-IV lifetime alcohol use disorders. Moderation analyses revealed that the effect of everyday discrimination on the risk of being a current smoker was strongest for Latino men with high levels of racial/ethnic identity compared to those with low racial/ethnic identity. No differences were noted among Latino women. There were no main or interaction effects of racial/ethnic discrimination for any substance use outcome. Conclusions Findings suggest differential associations for type of discrimination and outcome and that the role of racial/ethnic identity is gender-specific for smoking, appearing particularly detrimental for Latino men reporting high levels of racial/ethnic identity. PMID:26489844

Race, life course socioeconomic position, racial discrimination, depressive symptoms and self-rated health.

PubMed

Hudson, Darrell L; Puterman, Eli; Bibbins-Domingo, Kirsten; Matthews, Karen A; Adler, Nancy E

2013-11-01

Greater levels of socioeconomic position (SEP) are generally associated with better health. However results from previous studies vary across race/ethnicity and health outcomes. Further, the majority of previous studies do not account for the effects of life course SEP on health nor the effects of racial discrimination, which could moderate the effects of SEP on health. Using data from the Coronary Artery Risk Development in Young Adults (CARDIA) study, we examined the relationship between a life course SEP measure on depressive symptoms and self-rated health. A life course SEP was constructed for each participant, using a framework that included parental education and occupation along with respondents' highest level of education and occupation. Interaction terms were created between life course SEP and racial discrimination to determine whether the association between SEP and health was moderated by experiences of racial discrimination. Analyses revealed that higher levels of life course SEP were inversely related to depressive symptoms. Greater life course SEP was positively associated with favorable self-rated health. Racial discrimination was associated with more depressive symptoms and poorer self-rated health. Analyses indicated a significant interaction between life course SEP and racial discrimination on depressive symptoms in the full sample. This suggested that for respondents with greater levels of SEP, racial discrimination was associated with reports of more depressive symptoms. Future research efforts should be made to examine whether individuals' perceptions and experiences of racial discrimination at the interpersonal and structural levels limits their ability to acquire human capital as well as their advancement in education and occupational status. Copyright © 2013 Elsevier Ltd. All rights reserved.

Darker Skin Tone Increases Perceived Discrimination among Male but Not Female Caribbean Black Youth.

PubMed

Assari, Shervin; Caldwell, Cleopatra Howard

2017-12-12

Among most minority groups, males seem to report higher levels of exposure and vulnerability to racial discrimination. Although darker skin tone may increase exposure to racial discrimination, it is yet unknown whether skin tone similarly influences perceived discrimination among male and female Caribbean Black youth. The current cross-sectional study tests the role of gender on the effects of skin tone on perceived discrimination among Caribbean Black youth. Data came from the National Survey of American Life-Adolescent Supplement (NSAL-A), 2003-2004, which included 360 Caribbean Black youth (ages 13 to 17). Demographic factors (age and gender), socioeconomic status (SES; family income, income to needs ratio, and subjective SES), skin tone, and perceived everyday discrimination were measured. Linear regressions were used for data analysis. In the pooled sample, darker skin tone was associated with higher levels of perceived discrimination among Caribbean Black youth ( b = 0.48; 95% Confidence Interval (CI) = 0.07-0.89). A significant interaction was found between gender and skin tone ( b = 1.17; 95% CI = 0.49-1.86), suggesting a larger effect of skin tone on perceived discrimination for males than females. In stratified models, darker skin tone was associated with more perceived discrimination for males ( b = 1.20; 95% CI = 0.69-0.72) but not females ( b = 0.06; 95% CI = -0.42-0.55). Similar to the literature documenting male gender as a vulnerability factor to the effects of racial discrimination, we found that male but not female Caribbean Black youth with darker skin tones perceive more discrimination.

The association between discrimination and PTSD in African Americans: exploring the role of gender.

PubMed

Brooks Holliday, Stephanie; Dubowitz, Tamara; Haas, Ann; Ghosh-Dastidar, Bonnie; DeSantis, Amy; Troxel, Wendy M

2018-02-28

Research has demonstrated the adverse impact that discrimination has on physical and mental health. However, few studies have examined the association between discrimination and symptoms of posttraumatic stress disorder (PTSD). There is evidence that African Americans experience higher rates of PTSD and are more likely to develop PTSD following trauma exposure than Whites, and discrimination may be one reason for this disparity. To examine the association between discrimination and PTSD among a cross-sectional sample largely comprising African American women, controlling for other psychosocial stressors (psychological distress, neighborhood safety, crime). A sample of 806 participants was recruited from two low-income predominantly African American neighborhoods. Participants completed self-report measures of PTSD symptoms, perceived discrimination, perceived safety, and psychological distress. Information on neighborhood crime was obtained through data requested from the city. Multivariate linear regression models were estimated to assess adjusted relationships between PTSD symptoms and discrimination. Discrimination was significantly associated with PTSD symptoms with a small effect size, controlling for relevant sociodemographic variables. This association remained consistent after controlling for psychological distress, perceived safety, and total neighborhood crime. There was no evidence of a gender by discrimination interaction. Participants who experienced any discrimination were significantly more likely to screen positive for PTSD. Discrimination may contribute to the disparate rates of PTSD experienced by African Americans. PTSD is associated with a range of negative consequences, including poorer physical health, mental health, and quality of life. These results suggest the importance of finding ways to promote resilience in this at-risk population.

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.

Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber

PubMed Central

Zaghloul, Mohamed A. S.; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P.

2018-01-01

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores’ temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μϵ/MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%). PMID:29649148

DISCRIMINATION OF GRANITOIDS AND MINERALIZED GRANITOIDS IN THE MIDYAN REGION, NORTHWESTERN ARABIAN SHIELD, SAUDI ARABIA, BY LANDSAT MSS DATA-ANALYSIS.

USGS Publications Warehouse

Davis, Philip A.; Grolier, Maurice J.

1984-01-01

Landsat multispectral scanner (MSS) band and band-ratio databases of two scenes covering the Midyan region of northwestern Saudi Arabia were examined quantitatively and qualitatively to determine which databases best discriminate the geologic units of this semi-arid and arid region. Unsupervised, linear-discriminant cluster-analysis was performed on these two band-ratio combinations and on the MSS bands for both scenes. The results for granitoid-rock discrimination indicated that the classification images using the MSS bands are superior to the band-ratio classification images for two reasons, discussed in the paper. Yet, the effects of topography and material type (including desert varnish) on the MSS-band data produced ambiguities in the MSS-band classification results. However, these ambiguities were clarified by using a simulated natural-color image in conjunction with the MSS-band classification image.

Discrimination of Temperature and Strain in Brillouin Optical Time Domain Analysis Using a Multicore Optical Fiber.

PubMed

Zaghloul, Mohamed A S; Wang, Mohan; Milione, Giovanni; Li, Ming-Jun; Li, Shenping; Huang, Yue-Kai; Wang, Ting; Chen, Kevin P

2018-04-12

Brillouin optical time domain analysis is the sensing of temperature and strain changes along an optical fiber by measuring the frequency shift changes of Brillouin backscattering. Because frequency shift changes are a linear combination of temperature and strain changes, their discrimination is a challenge. Here, a multicore optical fiber that has two cores is fabricated. The differences between the cores' temperature and strain coefficients are such that temperature (strain) changes can be discriminated with error amplification factors of 4.57 °C/MHz (69.11 μ ϵ /MHz), which is 2.63 (3.67) times lower than previously demonstrated. As proof of principle, using the multicore optical fiber and a commercial Brillouin optical time domain analyzer, the temperature (strain) changes of a thermally expanding metal cylinder are discriminated with an error of 0.24% (3.7%).

Impact of elicited mood on movement expressivity during a fitness task.

PubMed

Giraud, Tom; Focone, Florian; Isableu, Brice; Martin, Jean-Claude; Demulier, Virginie

2016-10-01

The purpose of the present study was to evaluate the impact of four mood conditions (control, positive, negative, aroused) on movement expressivity during a fitness task. Motion capture data from twenty individuals were recorded as they performed a predefined motion sequence. Moods were elicited using task-specific scenarii to keep a valid context. Movement qualities inspired by Effort-Shape framework (Laban & Ullmann, 1971) were computed (i.e., Impulsiveness, Energy, Directness, Jerkiness and Expansiveness). A reduced number of computed features from each movement quality was selected via Principal Component Analyses. Analyses of variance and Generalized Linear Mixed Models were used to identify movement characteristics discriminating the four mood conditions. The aroused mood condition was strongly associated with increased mean Energy compared to the three other conditions. The positive and negative mood conditions showed more subtle differences interpreted as a result of their moderate activation level. Positive mood was associated with more impulsive movements and negative mood was associated with more tense movements (i.e., reduced variability and increased Jerkiness). Findings evidence the key role of movement qualities in capturing motion signatures of moods and highlight the importance of task context in their interpretations. Copyright © 2016 Elsevier B.V. All rights reserved.

Developmental dyslexia and phonological processing in European Portuguese orthography.

PubMed

Moura, Octávio; Moreno, Joana; Pereira, Marcelino; Simões, Mário R

2015-02-01

This study analysed the performance of phonological processing, the diagnostic accuracy and the influence on reading in children who were native speakers of an orthography of intermediate depth. Portuguese children with developmental dyslexia (DD; N=24; aged 10-12 years), chronological age (CA)-matched controls (N=24; aged 10-12 years) and reading level (RL)-matched controls (N=24; aged 7-9 years) were tested on measures of phonological processing (phonological awareness, naming speed and verbal short-term memory) and reading. The results indicated that the children with DD performed significantly poorer in all measures compared with the CA and RL. Phonological awareness and naming speed showed a high accuracy (receiver operating characteristics curve analysis) for discriminating the children with DD from the CA and RL, whereas the presence of abnormally low scores in phonological awareness and naming speed was more frequent in the DD group than in the controls and the normative population. Hierarchical linear regression analyses revealed that phonological awareness was the most important predictor of all reading accuracy measures, whereas naming speed was particularly related to text reading fluency. Copyright © 2014 John Wiley & Sons, Ltd.

Racial discrimination, racial identity, and impostor phenomenon: A profile approach.

PubMed

Bernard, Donte L; Hoggard, Lori S; Neblett, Enrique W

2018-01-01

This study examined the association between racial discrimination and the impostor phenomenon (IP) and the moderating influence of racial identity on this relationship. One hundred fifty-seven African American college students (68% female; mean age = 18.63) completed measures of racial discrimination, racial identity, and IP during 2 waves of data collection. Utilizing latent profile analyses, 4 patterns of racial identity were identified: Undifferentiated, Multiculturalist, Race-Focused, and Humanist. Racial discrimination predicted higher subsequent levels of IP. Racial identity did not moderate the impact of racial discrimination; however, students in the Multiculturalist and Humanist groups reported the lowest and highest levels of IP at Wave 2, respectively. IP is influenced by racial discrimination experiences as well as by the significance and meaning that individuals ascribe to being African American. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Racial and ethnic health disparities: evidence of discrimination's effects across the SEP spectrum.

PubMed

D'Anna, Laura Hoyt; Ponce, Ninez A; Siegel, Judith M

2010-04-01

Perceived discrimination is a psychosocial stressor that plays a role in explaining racial/ethnic disparities in self-reported physical and mental health. The purpose of this paper is: (1) to investigate the association between perceived discrimination in receiving healthcare and racial/ethnic disparities in self-rated health status, physical, and emotional functional limitations among a diverse sample of California adults; (2) to assess whether discrimination effects vary by racial/ethnic group and gender; and (3) to evaluate how the effects of discrimination on health are manifest across the socioeconomic position (SEP) spectrum. Data were drawn from the 2001 California Health Interview Survey adult file (n=55,428). The analytic approach employed multivariate linear and logistic regressions. Discrimination is qualitatively identified into two types: (1) discrimination due to race/ethnicity, language, or accent, and (2) other discrimination. Findings show that both types of discrimination negatively influenced self-rated health, and were associated with a two to three-fold odds of limitations in physical and emotional health. Further, these effects varied by racial/ethnic group and gender, and the effects were mixed. Most notably, for emotional health, racial/ethnic discrimination penalized Latinas more than non-Latina Whites, but for physical health, other discrimination was less detrimental to Latinas than it was to non-Latina Whites. At higher levels of SEP, the effects of racial/ethnic discrimination on self-rated health and other discriminations' effects on physical health were attenuated. Higher SEP may serve as an important mitigator, particularly when comparing the medium to the low SEP categories. It is also possible that SEP effects cannot be extracted from the relationships of interest in that SEP is an expression of social discrimination. In fact, negative health effects associated with discrimination are evident across the SEP spectrum. This study highlights the complexity of the relationships between discrimination and racial/ethnic identity, gender, and SEP.

Multispectral imaging burn wound tissue classification system: a comparison of test accuracies between several common machine learning algorithms

NASA Astrophysics Data System (ADS)

Squiers, John J.; Li, Weizhi; King, Darlene R.; Mo, Weirong; Zhang, Xu; Lu, Yang; Sellke, Eric W.; Fan, Wensheng; DiMaio, J. Michael; Thatcher, Jeffrey E.

2016-03-01

The clinical judgment of expert burn surgeons is currently the standard on which diagnostic and therapeutic decisionmaking regarding burn injuries is based. Multispectral imaging (MSI) has the potential to increase the accuracy of burn depth assessment and the intraoperative identification of viable wound bed during surgical debridement of burn injuries. A highly accurate classification model must be developed using machine-learning techniques in order to translate MSI data into clinically-relevant information. An animal burn model was developed to build an MSI training database and to study the burn tissue classification ability of several models trained via common machine-learning algorithms. The algorithms tested, from least to most complex, were: K-nearest neighbors (KNN), decision tree (DT), linear discriminant analysis (LDA), weighted linear discriminant analysis (W-LDA), quadratic discriminant analysis (QDA), ensemble linear discriminant analysis (EN-LDA), ensemble K-nearest neighbors (EN-KNN), and ensemble decision tree (EN-DT). After the ground-truth database of six tissue types (healthy skin, wound bed, blood, hyperemia, partial injury, full injury) was generated by histopathological analysis, we used 10-fold cross validation to compare the algorithms' performances based on their accuracies in classifying data against the ground truth, and each algorithm was tested 100 times. The mean test accuracy of the algorithms were KNN 68.3%, DT 61.5%, LDA 70.5%, W-LDA 68.1%, QDA 68.9%, EN-LDA 56.8%, EN-KNN 49.7%, and EN-DT 36.5%. LDA had the highest test accuracy, reflecting the bias-variance tradeoff over the range of complexities inherent to the algorithms tested. Several algorithms were able to match the current standard in burn tissue classification, the clinical judgment of expert burn surgeons. These results will guide further development of an MSI burn tissue classification system. Given that there are few surgeons and facilities specializing in burn care, this technology may improve the standard of burn care for patients without access to specialized facilities.

Racial Discrimination, John Henryism, and Depression Among African Americans

PubMed Central

Hudson, Darrell L.; Neighbors, Harold W.; Geronimus, Arline T.; Jackson, James S.

2016-01-01

Evidence from previous studies indicates that racial discrimination is significantly associated with depression and that African Americans with higher levels of socioeconomic status (SES) report greater exposure to racial discrimination compared to those with lower SES levels. Coping strategies could alter the relationship between racial discrimination and depression among African Americans. This study first examined whether greater levels of SES were associated with increased reports of racial discrimination and ratings of John Henryism, a measure of high-effort coping, among African Americans. Second, we examined whether high-effort coping moderated the relationship between racial discrimination and depression. Data were drawn from the National Survey of American Life Reinterview (n = 2,137). Analyses indicated that greater levels of education were positively associated with racial discrimination (p < .001) and increased levels of racial discrimination were positively related to depression (p < .001), controlling for all sociodemographic factors. Greater levels of John Henryism were associated with increased odds of depression but there was no evidence to suggest that the relationship between discrimination and depression was altered by the effects of John Henryism. PMID:27529626

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

PubMed Central

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

2011-01-01

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

Linear high-boost fusion of Stokes vector imagery for effective discrimination and recognition of real targets in the presence of multiple identical decoys

NASA Astrophysics Data System (ADS)

El-Saba, Aed; Sakla, Wesam A.

2010-04-01

Recently, the use of imaging polarimetry has received considerable attention for use in automatic target recognition (ATR) applications. In military remote sensing applications, there is a great demand for sensors that are capable of discriminating between real targets and decoys. Accurate discrimination of decoys from real targets is a challenging task and often requires the fusion of various sensor modalities that operate simultaneously. In this paper, we use a simple linear fusion technique known as the high-boost fusion method for effective discrimination of real targets in the presence of multiple decoys. The HBF assigns more weight to the polarization-based imagery in forming the final fused image that is used for detection. We have captured both intensity and polarization-based imagery from an experimental laboratory arrangement containing a mixture of sand/dirt, rocks, vegetation, and other objects for the purpose of simulating scenery that would be acquired in a remote sensing military application. A target object and three decoys that are identical in physical appearance (shape, surface structure and color) and different in material composition have also been placed in the scene. We use the wavelet-filter joint transform correlation (WFJTC) technique to perform detection between input scenery and the target object. Our results show that use of the HBF method increases the correlation performance metrics associated with the WFJTC-based detection process when compared to using either the traditional intensity or polarization-based images.

Prediction of Depression in Cancer Patients With Different Classification Criteria, Linear Discriminant Analysis versus Logistic Regression.

PubMed

Shayan, Zahra; Mohammad Gholi Mezerji, Naser; Shayan, Leila; Naseri, Parisa

2015-11-03

Logistic regression (LR) and linear discriminant analysis (LDA) are two popular statistical models for prediction of group membership. Although they are very similar, the LDA makes more assumptions about the data. When categorical and continuous variables used simultaneously, the optimal choice between the two models is questionable. In most studies, classification error (CE) is used to discriminate between subjects in several groups, but this index is not suitable to predict the accuracy of the outcome. The present study compared LR and LDA models using classification indices. This cross-sectional study selected 243 cancer patients. Sample sets of different sizes (n = 50, 100, 150, 200, 220) were randomly selected and the CE, B, and Q classification indices were calculated by the LR and LDA models. CE revealed the a lack of superiority for one model over the other, but the results showed that LR performed better than LDA for the B and Q indices in all situations. No significant effect for sample size on CE was noted for selection of an optimal model. Assessment of the accuracy of prediction of real data indicated that the B and Q indices are appropriate for selection of an optimal model. The results of this study showed that LR performs better in some cases and LDA in others when based on CE. The CE index is not appropriate for classification, although the B and Q indices performed better and offered more efficient criteria for comparison and discrimination between groups.

Influence of age, sex, and education on the Visual Object and Space Perception Battery (VOSP) in a healthy normal elderly population.

PubMed

Herrera-Guzmán, I; Peña-Casanova, J; Lara, J P; Gudayol-Ferré, E; Böhm, P

2004-08-01

The assessment of visual perception and cognition forms an important part of any general cognitive evaluation. We have studied the possible influence of age, sex, and education on a normal elderly Spanish population (90 healthy subjects) in performance in visual perception tasks. To evaluate visual perception and cognition, we have used the subjects performance with The Visual Object and Space Perception Battery (VOSP). The test consists of 8 subtests: 4 measure visual object perception (Incomplete Letters, Silhouettes, Object Decision, and Progressive Silhouettes) while the other 4 measure visual space perception (Dot Counting, Position Discrimination, Number Location, and Cube Analysis). The statistical procedures employed were either simple or multiple linear regression analyses (subtests with normal distribution) and Mann-Whitney tests, followed by ANOVA with Scheffe correction (subtests without normal distribution). Age and sex were found to be significant modifying factors in the Silhouettes, Object Decision, Progressive Silhouettes, Position Discrimination, and Cube Analysis subtests. Educational level was found to be a significant predictor of function for the Silhouettes and Object Decision subtests. The results of the sample were adjusted in line with the differences observed. Our study also offers preliminary normative data for the administration of the VOSP to an elderly Spanish population. The results are discussed and compared with similar studies performed in different cultural backgrounds.

Heavy metals in edible seaweeds commercialised for human consumption

NASA Astrophysics Data System (ADS)

Besada, Victoria; Andrade, José Manuel; Schultze, Fernando; González, Juan José

2009-01-01

Though seaweed consumption is growing steadily across Europe, relatively few studies have reported on the quantities of heavy metals they contain and/or their potential effects on the population's health. This study focuses on the first topic and analyses the concentrations of six typical heavy metals (Cd, Pb, Hg, Cu, Zn, total As and inorganic As) in 52 samples from 11 algae-based products commercialised in Spain for direct human consumption ( Gelidium spp.; Eisenia bicyclis; Himanthalia elongata; Hizikia fusiforme; Laminaria spp.; Ulva rigida; Chondrus crispus; Porphyra umbilicales and Undaria pinnatifida). Samples were ground, homogenised and quantified by atomic absorption spectrometry (Cu and Zn by flame AAS; Cd, Pb and total As by electrothermal AAS; total mercury by the cold vapour technique; and inorganic As by flame-hydride generation). Accuracy was assessed by participation in periodic QUASIMEME (Quality Assurance of Information in Marine Environmental Monitoring in Europe) and IAEA (International Atomic Energy Agency) intercalibration exercises. To detect any objective differences existing between the seaweeds' metal concentrations, univariate and multivariate studies (principal component analysis, cluster analysis and linear discriminant analysis) were performed. It is concluded that the Hizikia fusiforme samples contained the highest values of total and inorganic As and that most Cd concentrations exceeded the French Legislation. The two harvesting areas (Atlantic and Pacific oceans) were differentiated using both univariate studies (for Cu, total As, Hg and Zn) and a multivariate discriminant function (which includes Zn, Cu and Pb).

Luminescent screen composition and apparatus

NASA Technical Reports Server (NTRS)

Hilborn, E. H.

1970-01-01

Ultraviolet light projects photographically produced images on a screen composed of a mixture of linear and nonlinear phosphors whose spectral emissions are different. This allows the display of polychromatic luminescent images, which gives better discrimination of the objects being viewed.

Electronic circuit delivers pulse of high interval stability

NASA Technical Reports Server (NTRS)

Fisher, B.

1966-01-01

Circuit generates a pulse of high interval stability with a complexity level considerably below systems of comparable stability. This circuit is being used as a linear frequency discriminator in the signal conditioner of the Apollo command module.

Automated discrimination of dementia spectrum disorders using extreme learning machine and structural T1 MRI features.

PubMed

Jongin Kim; Boreom Lee

2017-07-01

The classification of neuroimaging data for the diagnosis of Alzheimer's Disease (AD) is one of the main research goals of the neuroscience and clinical fields. In this study, we performed extreme learning machine (ELM) classifier to discriminate the AD, mild cognitive impairment (MCI) from normal control (NC). We compared the performance of ELM with that of a linear kernel support vector machine (SVM) for 718 structural MRI images from Alzheimer's Disease Neuroimaging Initiative (ADNI) database. The data consisted of normal control, MCI converter (MCI-C), MCI non-converter (MCI-NC), and AD. We employed SVM-based recursive feature elimination (RFE-SVM) algorithm to find the optimal subset of features. In this study, we found that the RFE-SVM feature selection approach in combination with ELM shows the superior classification accuracy to that of linear kernel SVM for structural T1 MRI data.

Principle component analysis and linear discriminant analysis of multi-spectral autofluorescence imaging data for differentiating basal cell carcinoma and healthy skin

NASA Astrophysics Data System (ADS)

Chernomyrdin, Nikita V.; Zaytsev, Kirill I.; Lesnichaya, Anastasiya D.; Kudrin, Konstantin G.; Cherkasova, Olga P.; Kurlov, Vladimir N.; Shikunova, Irina A.; Perchik, Alexei V.; Yurchenko, Stanislav O.; Reshetov, Igor V.

2016-09-01

In present paper, an ability to differentiate basal cell carcinoma (BCC) and healthy skin by combining multi-spectral autofluorescence imaging, principle component analysis (PCA), and linear discriminant analysis (LDA) has been demonstrated. For this purpose, the experimental setup, which includes excitation and detection branches, has been assembled. The excitation branch utilizes a mercury arc lamp equipped with a 365-nm narrow-linewidth excitation filter, a beam homogenizer, and a mechanical chopper. The detection branch employs a set of bandpass filters with the central wavelength of spectral transparency of λ = 400, 450, 500, and 550 nm, and a digital camera. The setup has been used to study three samples of freshly excised BCC. PCA and LDA have been implemented to analyze the data of multi-spectral fluorescence imaging. Observed results of this pilot study highlight the advantages of proposed imaging technique for skin cancer diagnosis.

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

PubMed

D'Archivio, Angelo Antonio; Maggi, Maria Anna

2017-03-15

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

Combining features from ERP components in single-trial EEG for discriminating four-category visual objects.

PubMed

Wang, Changming; Xiong, Shi; Hu, Xiaoping; Yao, Li; Zhang, Jiacai

2012-10-01

Categorization of images containing visual objects can be successfully recognized using single-trial electroencephalograph (EEG) measured when subjects view images. Previous studies have shown that task-related information contained in event-related potential (ERP) components could discriminate two or three categories of object images. In this study, we investigated whether four categories of objects (human faces, buildings, cats and cars) could be mutually discriminated using single-trial EEG data. Here, the EEG waveforms acquired while subjects were viewing four categories of object images were segmented into several ERP components (P1, N1, P2a and P2b), and then Fisher linear discriminant analysis (Fisher-LDA) was used to classify EEG features extracted from ERP components. Firstly, we compared the classification results using features from single ERP components, and identified that the N1 component achieved the highest classification accuracies. Secondly, we discriminated four categories of objects using combining features from multiple ERP components, and showed that combination of ERP components improved four-category classification accuracies by utilizing the complementarity of discriminative information in ERP components. These findings confirmed that four categories of object images could be discriminated with single-trial EEG and could direct us to select effective EEG features for classifying visual objects.

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

PubMed

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

2010-04-01

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

From Racial Discrimination to Risky Sex: Prospective Relations Involving Peers and Parents

PubMed Central

Roberts, Megan E.; Gibbons, Frederick X.; Gerrard, Meg; Weng, Chih-Yuan; Murry, Velma M.; Simons, Leslie G.; Simons, Ronald L.; Lorenz, Frederick O.

2013-01-01

This study investigated how early experience with racial discrimination affected the subsequent risky sexual behaviors of a diverse sample of African American youths (N = 745). The analyses focused on 3 risk-promoting factors thought to mediate the hypothesized discrimination → risky sex relation: negative affect, affiliation with deviant peers, and favorable attitudes toward risky sex. In addition, attentive parenting was examined as a protective factor. Analyses using structural equation modeling revealed that youths who perceived more racial discrimination at age 10 or 11 were engaging in more sexual risk taking at age 18 or 19. This relation was mediated by the hypothesized risk-promoting factors via pathways that were consistent with our conceptual model. Results also indicated a prospective reciprocal relation between parenting and children’s deviant affiliations: deviant peer affiliations at age 10 or 11 predicted more attentive parenting behaviors by the parents; this response from the parents, in turn, predicted relatively fewer deviant affiliations when the youths were 15 or 16. Study findings are discussed in terms of their relevance to the disproportionately high rates of sexually transmitted infections among African Americans. PMID:21942666

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.

Discriminative illumination: per-pixel classification of raw materials based on optimal projections of spectral BRDF.

PubMed

Liu, Chao; Gu, Jinwei

2014-01-01

Classifying raw, unpainted materials--metal, plastic, ceramic, fabric, and so on--is an important yet challenging task for computer vision. Previous works measure subsets of surface spectral reflectance as features for classification. However, acquiring the full spectral reflectance is time consuming and error-prone. In this paper, we propose to use coded illumination to directly measure discriminative features for material classification. Optimal illumination patterns--which we call "discriminative illumination"--are learned from training samples, after projecting to which the spectral reflectance of different materials are maximally separated. This projection is automatically realized by the integration of incident light for surface reflection. While a single discriminative illumination is capable of linear, two-class classification, we show that multiple discriminative illuminations can be used for nonlinear and multiclass classification. We also show theoretically that the proposed method has higher signal-to-noise ratio than previous methods due to light multiplexing. Finally, we construct an LED-based multispectral dome and use the discriminative illumination method for classifying a variety of raw materials, including metal (aluminum, alloy, steel, stainless steel, brass, and copper), plastic, ceramic, fabric, and wood. Experimental results demonstrate its effectiveness.

A Comparison of Potential IM-CW Lidar Modulation Techniques for ASCENDS CO2 Column Measurements From Space

NASA Technical Reports Server (NTRS)

Campbell, Joel F.; Lin, Bing; Nehrir, Amin R.; Harrison, F. Wallace; Obland, Michael D.; Ismail, Syed

2014-01-01

Global atmospheric carbon dioxide (CO2) measurements through the Active Sensing of CO2 Emissions over Nights, Days, and Seasons (ASCENDS) Decadal Survey recommended space mission are critical for improving our understanding of CO2 sources and sinks. IM-CW (Intensity Modulated Continuous Wave) lidar techniques are investigated as a means of facilitating CO2 measurements from space to meet the ASCENDS science requirements. In previous laboratory and flight experiments we have successfully used linear swept frequency modulation to discriminate surface lidar returns from intermediate aerosol and cloud contamination. Furthermore, high accuracy and precision ranging to the surface as well as to the top of intermediate clouds, which is a requirement for the inversion of the CO2 column-mixing ratio from the instrument optical depth measurements, has been demonstrated with the linear swept frequency modulation technique. We are concurrently investigating advanced techniques to help improve the auto-correlation properties of the transmitted waveform implemented through physical hardware to make cloud rejection more robust in special restricted scenarios. Several different carrier based modulation techniques are compared including orthogonal linear swept, orthogonal non-linear swept, and Binary Phase Shift Keying (BPSK). Techniques are investigated that reduce or eliminate sidelobes. These techniques have excellent auto-correlation properties while possessing a finite bandwidth (by way of a new cyclic digital filter), which will reduce bias error in the presence of multiple scatterers. Our analyses show that the studied modulation techniques can increase the accuracy of CO2 column measurements from space. A comparison of various properties such as signal to noise ratio (SNR) and time-bandwidth product are discussed.

Racial discrimination as race-based trauma, coping strategies, and dissociative symptoms among emerging adults.

PubMed

Polanco-Roman, Lillian; Danies, Ashley; Anglin, Deidre M

2016-09-01

The race-based traumatic stress theory (Carter, 2007) suggests that some racial- and ethnic-minority individuals experience racial discrimination as psychological trauma, as it may elicit a response comparable to posttraumatic stress. In the present study, we examined this further by determining the relation between racial discrimination and dissociation, a common response to trauma exposure. Further, we examined whether active coping strategies specifically employed to cope with racial discrimination related to less dissociative symptomatology. The predominant racial- and ethnic-minority sample (N = 743) of emerging adults, ages 18-29, recruited from a public university in northeastern United States completed a battery of self-report measures on racial discrimination, responses to racial discrimination, traumatic life events, and dissociative symptoms. Frequency of racial discrimination was positively associated with dissociative symptoms in regression analyses adjusted for demographics and other traumatic life events. In addition, more active coping strategies in response to racial discrimination were negatively associated with dissociative symptoms. Racial- and ethnic-minority emerging adults who experience racial discrimination, possibly as traumatic, may be more vulnerable to dissociative symptoms. However, different strategies of coping with racial discrimination may differentially impact risk for dissociation. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Racial discrimination as race-based trauma, coping strategies and dissociative symptoms among emerging adults

PubMed Central

Polanco-Roman, Lillian; Danies, Ashley; Anglin, Deidre M.

2016-01-01

Objective The race-based traumatic stress theory (Carter, 2007) suggests that some racial and ethnic minority individuals may experience racial discrimination as a psychological trauma, as it may elicit a response comparable to posttraumatic stress. The present study examined this further by determining the relation between racial discrimination and dissociation, a common response to trauma exposure. Further, we examined whether active coping strategies specifically employed to cope with racial discrimination related to less dissociative symptomatology. Methods The predominant racial and ethnic minority sample (N=743) of emerging adults (i.e., ages 18-29) recruited from a public university in Northeastern U.S. completed a battery of self-report measures on racial discrimination, responses to racial discrimination, traumatic life events and dissociative symptoms. Results Frequency of racial discrimination was positively associated with dissociative symptoms in regression analyses adjusted for demographics and other traumatic life events. Additionally, more active coping strategies in response to racial discrimination were negatively associated with dissociative symptoms. Conclusion Racial and ethnic minority emerging adults who experience racial discrimination, possibly as traumatic, may be more vulnerable to dissociative symptoms. However, different strategies of coping with racial discrimination may differentially impact risk for dissociation. PMID:26963957

Implementation of projective measurements with linear optics and continuous photon counting

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

Takeoka, Masahiro; Sasaki, Masahide; Loock, Peter van

2005-02-01

We investigate the possibility of implementing a given projection measurement using linear optics and arbitrarily fast feedforward based on the continuous detection of photons. In particular, we systematically derive the so-called Dolinar scheme that achieves the minimum-error discrimination of binary coherent states. Moreover, we show that the Dolinar-type approach can also be applied to projection measurements in the regime of photonic-qubit signals. Our results demonstrate that for implementing a projection measurement with linear optics, in principle, unit success probability may be approached even without the use of expensive entangled auxiliary states, as they are needed in all known (near-)deterministic linear-opticsmore » proposals.« less

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

A Nationwide Study of Discrimination and Chronic Health Conditions Among Asian Americans

PubMed Central

Gee, Gilbert C.; Spencer, Michael S.; Chen, Juan; Takeuchi, David

2007-01-01

Objectives. We examined whether self-reported everyday discrimination was associated with chronic health conditions among a nationally representative sample of Asian Americans. Methods. Data were from the Asian American subsample (n = 2095) of the National Latino and Asian American Study conducted in 2002 and 2003. Regression techniques (negative binomial and logistic) were used to examine the association between discrimination and chronic health conditions. Analyses were conducted for the entire sample and 3 Asian subgroups (Chinese, Vietnamese, and Filipino). Results. Reports of everyday discrimination were associated with many chronic conditions, after we controlled for age, gender, region, per capita income, education, employment, and social desirability bias. Discrimination was also associated with indicators of heart disease, pain, and respiratory illnesses. There were some differences by Asian subgroup. Conclusions. Everyday discrimination may contribute to stress experienced by racial/ethnic minorities and could lead to chronic illness. PMID:17538055

Racial discrimination and substance use: longitudinal associations and identity moderators.

PubMed

Fuller-Rowell, Thomas E; Cogburn, Courtney D; Brodish, Amanda B; Peck, Stephen C; Malanchuk, Oksana; Eccles, Jacquelynne S

2012-12-01

Current research indicates that racial discrimination is pervasive in the lives of African Americans. Although there are a variety of ways in which discrimination may contribute to health, one potentially important pathway is through its impact on substance use. Addressing the paucity of longitudinal research on this topic, the present study examined the influence of teacher discrimination on changes in substance use over time among African American adolescents and considered three dimensions of racial identity as moderators of this association (centrality, private regard, and public regard). Latent variable SEM analyses indicated that, on average, levels of discrimination were associated with increases in substance use across the high school years. However, public regard was found to moderate this association such that discrimination was less strongly associated with increases in substance use for individual who reported lower levels of public regard. The implications of these findings are discussed.

Temporal Lobe Epilepsy: Quantitative MR Volumetry in Detection of Hippocampal Atrophy

PubMed Central

Farid, Nikdokht; Girard, Holly M.; Kemmotsu, Nobuko; Smith, Michael E.; Magda, Sebastian W.; Lim, Wei Y.; Lee, Roland R.

2012-01-01

Purpose: To determine the ability of fully automated volumetric magnetic resonance (MR) imaging to depict hippocampal atrophy (HA) and to help correctly lateralize the seizure focus in patients with temporal lobe epilepsy (TLE). Materials and Methods: This study was conducted with institutional review board approval and in compliance with HIPAA regulations. Volumetric MR imaging data were analyzed for 34 patients with TLE and 116 control subjects. Structural volumes were calculated by using U.S. Food and Drug Administration–cleared software for automated quantitative MR imaging analysis (NeuroQuant). Results of quantitative MR imaging were compared with visual detection of atrophy, and, when available, with histologic specimens. Receiver operating characteristic analyses were performed to determine the optimal sensitivity and specificity of quantitative MR imaging for detecting HA and asymmetry. A linear classifier with cross validation was used to estimate the ability of quantitative MR imaging to help lateralize the seizure focus. Results: Quantitative MR imaging–derived hippocampal asymmetries discriminated patients with TLE from control subjects with high sensitivity (86.7%–89.5%) and specificity (92.2%–94.1%). When a linear classifier was used to discriminate left versus right TLE, hippocampal asymmetry achieved 94% classification accuracy. Volumetric asymmetries of other subcortical structures did not improve classification. Compared with invasive video electroencephalographic recordings, lateralization accuracy was 88% with quantitative MR imaging and 85% with visual inspection of volumetric MR imaging studies but only 76% with visual inspection of clinical MR imaging studies. Conclusion: Quantitative MR imaging can depict the presence and laterality of HA in TLE with accuracy rates that may exceed those achieved with visual inspection of clinical MR imaging studies. Thus, quantitative MR imaging may enhance standard visual analysis, providing a useful and viable means for translating volumetric analysis into clinical practice. © RSNA, 2012 Supplemental material: http://radiology.rsna.org/lookup/suppl/doi:10.1148/radiol.12112638/-/DC1 PMID:22723496

The Influence of Discrimination on Smoking Cessation among Latinos

PubMed Central

Kendzor, Darla E.; Businelle, Michael S.; Reitzel, Lorraine R.; Castro, Yessenia; Vidrine, Jennifer I.; Mazas, Carlos A.; Cinciripini, Paul M.; Lam, Cho Y.; Adams, Claire E.; Correa-Fernández, Virmarie; Cano, Miguel Ángel; Wetter, David W.

2014-01-01

Background: Although studies have shown a cross-sectional link between discrimination and smoking, the prospective influence of discrimination on smoking cessation has yet to be evaluated. Thus, the purpose of the current study was to determine the influence of everyday and major discrimination on smoking cessation among Latinos making a quit attempt. Methods: Participants were 190 Spanish speaking smokers of Mexican Heritage recruited from the Houston, TX metropolitan area who participated in the study between 2009 and 2012. Logistic regression analyses were conducted to evaluate the associations of everyday and major discrimination with smoking abstinence at 26 weeks post-quit. Results: Most participants reported at least some everyday discrimination (64.4%), and at least one major discrimination event (56%) in their lifetimes. Race/ethnicity/nationality was the most commonly perceived reason for both everyday and major discrimination. Everyday discrimination was not associated with post-quit smoking status. However, experiencing a greater number of major discrimination events was associated with a reduced likelihood of achieving 7-day point prevalence smoking abstinence, OR = .51, p = .004, and continuous smoking abstinence, OR = .29, p = .018, at 26 weeks post-quit. Conclusions: Findings highlight the high frequency of exposure to discrimination among Latinos, and demonstrate the negative impact of major discrimination events on a smoking cessation attempt. Efforts are needed to attenuate the detrimental effects of major discrimination events on smoking cessation outcomes. PMID:24485880

Racial discrimination's influence on smoking rates among American Indian Alaska Native two-spirit individuals: does pain play a role?

PubMed

Johnson-Jennings, Michelle D; Belcourt, Annie; Town, Matthew; Walls, Melissa L; Walters, Karina L

2014-11-01

High rates of racial discrimination and non-ceremonial tobacco smoking exist among American Indian/Alaska Native (AIAN) Two-Spirit/LGBT (Lesbian, Gay, Bisexual, Transgender) populations. The authors examined whether or not pain mediates between racial discrimination and smoking among Two-Spirits. Two-Spirit adults (n=447) from seven urban U.S. locations were surveyed during the HONOR project. The Indigenist stress coping model was used as framework in which to conduct descriptive, bivariate and regression analyses. A majority of the participants reported smoking (45.2%) and pain (57%). Pain was found to mediate the association between racial discrimination and smoking. Racial discrimination appears to be a significant factor influencing tobacco smoking and health behaviors within Two-Spirit populations. Effective tobacco cessation and/or prevention planning for Two-Spirits and others who experience frequent racial discrimination, stress, and trauma should also consider the influence of pain. Pain may serve as the embodiment of discrimination, and this possibility requires future research

Moderating effects of three coping strategies and self-esteem on perceived discrimination and depressive symptoms: A minority stress model for Asian international students.

PubMed

Wei, Meifen; Ku, Tsun-Yao; Russell, Daniel W; Mallinckrodt, Brent; Liao, Kelly Yu-Hsin

2008-10-01

This study examined 3 coping strategies (reflective, suppressive, and reactive), along with self-esteem, as moderators of the relation between perceived discrimination and depressive symptoms. International students (N = 354) from China, India, Korea, Taiwan, and Hong Kong provided data via an online survey. The role of perceived general stress was statistically controlled. Hierarchical regression analyses indicated a significant direct effect of perceived discrimination, a significant 2-way interaction of perceived discrimination and suppressive coping, and a significant 3-way interaction of perceived discrimination, reactive coping, and self-esteem in predicting depressive symptoms. An increased tendency to use suppressive coping appeared to strengthen the association between perceived discrimination and depressive symptoms. In contrast, the association between perceived discrimination and depressive symptoms was not significant when reactive coping was infrequently used, but only for students with relatively high self-esteem. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Visual discrimination in the pigeon (Columba livia): effects of selective lesions of the nucleus rotundus

NASA Technical Reports Server (NTRS)

Laverghetta, A. V.; Shimizu, T.

1999-01-01

The nucleus rotundus is a large thalamic nucleus in birds and plays a critical role in many visual discrimination tasks. In order to test the hypothesis that there are functionally distinct subdivisions in the nucleus rotundus, effects of selective lesions of the nucleus were studied in pigeons. The birds were trained to discriminate between different types of stationary objects and between different directions of moving objects. Multiple regression analyses revealed that lesions in the anterior, but not posterior, division caused deficits in discrimination of small stationary stimuli. Lesions in neither the anterior nor posterior divisions predicted effects in discrimination of moving stimuli. These results are consistent with a prediction led from the hypothesis that the nucleus is composed of functional subdivisions.

Perceived discrimination, psychological distress, and current smoking status: results from the Behavioral Risk Factor Surveillance System Reactions to Race module, 2004-2008.

PubMed

Purnell, Jason Q; Peppone, Luke J; Alcaraz, Kassandra; McQueen, Amy; Guido, Joseph J; Carroll, Jennifer K; Shacham, Enbal; Morrow, Gary R

2012-05-01

We examined the association between perceived discrimination and smoking status and whether psychological distress mediated this relationship in a large, multiethnic sample. We used 2004 through 2008 data from the Behavioral Risk Factor Surveillance System Reactions to Race module to conduct multivariate logistic regression analyses and tests of mediation examining associations between perceived discrimination in health care and workplace settings, psychological distress, and current smoking status. Regardless of race/ethnicity, perceived discrimination was associated with increased odds of current smoking. Psychological distress was also a significant mediator of the discrimination-smoking association. Our results indicate that individuals who report discriminatory treatment in multiple domains may be more likely to smoke, in part, because of the psychological distress associated with such treatment.

Experimental variability and data pre-processing as factors affecting the discrimination power of some chemometric approaches (PCA, CA and a new algorithm based on linear regression) applied to (+/-)ESI/MS and RPLC/UV data: Application on green tea extracts.

PubMed

Iorgulescu, E; Voicu, V A; Sârbu, C; Tache, F; Albu, F; Medvedovici, A

2016-08-01

The influence of the experimental variability (instrumental repeatability, instrumental intermediate precision and sample preparation variability) and data pre-processing (normalization, peak alignment, background subtraction) on the discrimination power of multivariate data analysis methods (Principal Component Analysis -PCA- and Cluster Analysis -CA-) as well as a new algorithm based on linear regression was studied. Data used in the study were obtained through positive or negative ion monitoring electrospray mass spectrometry (+/-ESI/MS) and reversed phase liquid chromatography/UV spectrometric detection (RPLC/UV) applied to green tea extracts. Extractions in ethanol and heated water infusion were used as sample preparation procedures. The multivariate methods were directly applied to mass spectra and chromatograms, involving strictly a holistic comparison of shapes, without assignment of any structural identity to compounds. An alternative data interpretation based on linear regression analysis mutually applied to data series is also discussed. Slopes, intercepts and correlation coefficients produced by the linear regression analysis applied on pairs of very large experimental data series successfully retain information resulting from high frequency instrumental acquisition rates, obviously better defining the profiles being compared. Consequently, each type of sample or comparison between samples produces in the Cartesian space an ellipsoidal volume defined by the normal variation intervals of the slope, intercept and correlation coefficient. Distances between volumes graphically illustrates (dis)similarities between compared data. The instrumental intermediate precision had the major effect on the discrimination power of the multivariate data analysis methods. Mass spectra produced through ionization from liquid state in atmospheric pressure conditions of bulk complex mixtures resulting from extracted materials of natural origins provided an excellent data basis for multivariate analysis methods, equivalent to data resulting from chromatographic separations. The alternative evaluation of very large data series based on linear regression analysis produced information equivalent to results obtained through application of PCA an CA. Copyright © 2016 Elsevier B.V. All rights reserved.

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

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.

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

PubMed

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

2012-08-15

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

Application of ERTS-1 imagery to the study of caribou movements and winter dispersal in relation to prevailing snowcover

NASA Technical Reports Server (NTRS)

Lent, P. C. (Principal Investigator)

1973-01-01

The author has identified the following significant results. Step-wise discriminate analysis has demonstrated the feasibility of feature identification using linear discriminate functions of ERTS-1 MSS band densities and their ratios. The analysis indicated that features such as small streams can be detected even when they are in dark mountain shadow. The potential utility of this and similar analytic techniques appears considerable, and the limits it can be applied to analysis of ERTS-1 imagery are not yet fully known.

Analysis of Greek small coinage from the classic period

NASA Astrophysics Data System (ADS)

Šmit, Ž.; Šemrov, A.

2018-02-01

A series of 25 Greek coins from the 6th to 4th centuries BC was studied by PIXE for their trace element composition, with an aim to discover the origin of their silver ore. The procedure revealed a counterfeited coin, and then concentrated on distinguishing the coins minted from the ore of Laurion on the Attica peninsula and the coins minted from other sources. Linear discriminant analysis based on the impurities and alloying elements of copper, gold, lead and bismuth revealed that discrimination is indeed possible according to a single canonical variable.

Perceived discrimination and depressive symptoms among US Latinos: the modifying role of educational attainment.

PubMed

Ward, Julia B; Feinstein, Lydia; Vines, Anissa I; Robinson, Whitney R; Haan, Mary N; Aiello, Allison E

2017-04-12

Despite growing evidence that discrimination may contribute to poor mental health, few studies have assessed this association among US Latinos. Furthermore, the interaction between discrimination and educational attainment in shaping Latino mental health is virtually unexplored. This study aims to examine the association between perceived discrimination and depressive symptoms and the modifying role of education among a population of Mexican-origin adults. We utilized population-based data from 629 Mexican-origin adults (mean age = 52.8 years) participating the Niños Lifestyle and Diabetes Study (2013-2014). Perceived discrimination was defined as responding 'sometimes' or 'often' to at least one item on the 9-item Everyday Discrimination Scale. High depressive symptoms were defined as scoring ≥10 on the CESD-10. We used log-binomial and linear-binomial models to estimate prevalence ratios (PR) and prevalence differences (PD), respectively, of high depressive symptoms for levels of perceived discrimination. Final models were adjusted for age, sex, education, cultural orientation, and nativity. General estimating equations were employed to account for within-family clustering. Prevalence of perceived discrimination and high depressive symptoms were 49.5% and 29.2%, respectively. Participants experiencing discrimination had higher depressive symptom prevalence than those never or rarely experiencing discrimination [PR = 1.94, 95% confidence interval (CI): 1.46-2.58; PD = 0.19, 95% CI: 0.12-0.27]. The strength of this association varied by education level. The association between discrimination and depressive symptoms was stronger among those with >12 years of education (PR = 2.69; PD = 0.24) compared to those with ≤12 years of education (PR = 1.36; PD = 0.09). US Latinos suffer a high burden of depressive symptoms, and discrimination may be an important driver of this burden. Our results suggest that effortful coping strategies, such as achieving high education despite high perceived discrimination, may magnify discrimination's adverse effect on Latino mental health.

Darker Skin Tone Increases Perceived Discrimination among Male but Not Female Caribbean Black Youth

PubMed Central

Caldwell, Cleopatra Howard

2017-01-01

Background: Among most minority groups, males seem to report higher levels of exposure and vulnerability to racial discrimination. Although darker skin tone may increase exposure to racial discrimination, it is yet unknown whether skin tone similarly influences perceived discrimination among male and female Caribbean Black youth. Objective: The current cross-sectional study tests the role of gender on the effects of skin tone on perceived discrimination among Caribbean Black youth. Methods: Data came from the National Survey of American Life-Adolescent Supplement (NSAL-A), 2003–2004, which included 360 Caribbean Black youth (ages 13 to 17). Demographic factors (age and gender), socioeconomic status (SES; family income, income to needs ratio, and subjective SES), skin tone, and perceived everyday discrimination were measured. Linear regressions were used for data analysis. Results: In the pooled sample, darker skin tone was associated with higher levels of perceived discrimination among Caribbean Black youth (b = 0.48; 95% Confidence Interval (CI) = 0.07–0.89). A significant interaction was found between gender and skin tone (b = 1.17; 95% CI = 0.49–1.86), suggesting a larger effect of skin tone on perceived discrimination for males than females. In stratified models, darker skin tone was associated with more perceived discrimination for males (b = 1.20; 95% CI = 0.69–0.72) but not females (b = 0.06; 95% CI = −0.42–0.55). Conclusion: Similar to the literature documenting male gender as a vulnerability factor to the effects of racial discrimination, we found that male but not female Caribbean Black youth with darker skin tones perceive more discrimination. PMID:29231903

Meta-analytic review of the development of face discrimination in infancy: Face race, face gender, infant age, and methodology moderate face discrimination.

PubMed

Sugden, Nicole A; Marquis, Alexandra R

2017-11-01

Infants show facility for discriminating between individual faces within hours of birth. Over the first year of life, infants' face discrimination shows continued improvement with familiar face types, such as own-race faces, but not with unfamiliar face types, like other-race faces. The goal of this meta-analytic review is to provide an effect size for infants' face discrimination ability overall, with own-race faces, and with other-race faces within the first year of life, how this differs with age, and how it is influenced by task methodology. Inclusion criteria were (a) infant participants aged 0 to 12 months, (b) completing a human own- or other-race face discrimination task, (c) with discrimination being determined by infant looking. Our analysis included 30 works (165 samples, 1,926 participants participated in 2,623 tasks). The effect size for infants' face discrimination was small, 6.53% greater than chance (i.e., equal looking to the novel and familiar). There was a significant difference in discrimination by race, overall (own-race, 8.18%; other-race, 3.18%) and between ages (own-race: 0- to 4.5-month-olds, 7.32%; 5- to 7.5-month-olds, 9.17%; and 8- to 12-month-olds, 7.68%; other-race: 0- to 4.5-month-olds, 6.12%; 5- to 7.5-month-olds, 3.70%; and 8- to 12-month-olds, 2.79%). Multilevel linear (mixed-effects) models were used to predict face discrimination; infants' capacity to discriminate faces is sensitive to face characteristics including race, gender, and emotion as well as the methods used, including task timing, coding method, and visual angle. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The assessment of biases in the acoustic discrimination of individuals

PubMed Central

Šálek, Martin

2017-01-01

Animal vocalizations contain information about individual identity that could potentially be used for the monitoring of individuals. However, the performance of individual discrimination is subjected to many biases depending on factors such as the amount of identity information, or methods used. These factors need to be taken into account when comparing results of different studies or selecting the most cost-effective solution for a particular species. In this study, we evaluate several biases associated with the discrimination of individuals. On a large sample of little owl male individuals, we assess how discrimination performance changes with methods of call description, an increasing number of individuals, and number of calls per male. Also, we test whether the discrimination performance within the whole population can be reliably estimated from a subsample of individuals in a pre-screening study. Assessment of discrimination performance at the level of the individual and at the level of call led to different conclusions. Hence, studies interested in individual discrimination should optimize methods at the level of individuals. The description of calls by their frequency modulation leads to the best discrimination performance. In agreement with our expectations, discrimination performance decreased with population size. Increasing the number of calls per individual linearly increased the discrimination of individuals (but not the discrimination of calls), likely because it allows distinction between individuals with very similar calls. The available pre-screening index does not allow precise estimation of the population size that could be reliably monitored. Overall, projects applying acoustic monitoring at the individual level in population need to consider limitations regarding the population size that can be reliably monitored and fine-tune their methods according to their needs and limitations. PMID:28486488

Using the MMPI-2-RF to discriminate psychometrically identified schizotypic college students from a matched comparison sample.

PubMed

Hunter, Helen K; Bolinskey, P Kevin; Novi, Jonathan H; Hudak, Daniel V; James, Alison V; Myers, Kevin R; Schuder, Kelly M

2014-01-01

This study investigates the extent to which the Minnesota Multiphasic Personality Inventory-2 Restructured Form (MMPI-2-RF) profiles of 52 individuals making up a psychometrically identified schizotypes (SZT) sample could be successfully discriminated from the protocols of 52 individuals in a matched comparison (MC) sample. Replication analyses were performed with an additional 53 pairs of SZT and MC participants. Results showed significant differences in mean T-score values between these 2 groups across a variety of MMPI-2-RF scales. Results from discriminant function analyses indicate that schizotypy can be predicted effectively using 4 MMPI-2-RF scales and that this method of classification held up on replication. Additional results demonstrated that these MMPI-2-RF scales nominally outperformed MMPI-2 scales suggested by previous research as being indicative of schizophrenia liability. Directions for future research with the MMPI-2-RF are suggested.

Chemometrical characterization of four italian rice varieties based on genetic and chemical analyses.

PubMed

Brandolini, Vincenzo; Coïsson, Jean Daniel; Tedeschi, Paola; Barile, Daniela; Cereti, Elisabetta; Maietti, Annalisa; Vecchiati, Giorgio; Martelli, Aldo; Arlorio, Marco

2006-12-27

This paper describes a method for achieving qualitative identification of four rice varieties from two different Italian regions. To estimate the presence of genetic diversity among the four rice varieties, we used polymerase chain reaction-randomly amplified polymorphic DNA (PCR-RAPD) markers, and to elucidate whether a relationship exists between the ground and the specific characteristics of the product, we studied proximate composition, fatty acid composition, mineral content, and total antioxidant capacity. Using principal component analysis on genomic and compositional data, we were able to classify rice samples according to their variety and their district of production. This work also examined the discrimination ability of different parameters. It was found that genomic data give the best discrimination based on varieties, indicating that RAPD assays could be useful in discriminating among closely related species, while compositional analyses do not depend on the genetic characters only but are related to the production area.

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

PubMed

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

2015-05-01

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

Breast cancer survivorship: the role of perceived discrimination and sexual orientation.

PubMed

Jabson, Jennifer M; Donatelle, Rebecca J; Bowen, Deborah

2011-03-01

Breast cancer disproportionately affects sexual minority women (SMW) compared to heterosexual women and a small but growing literature indicates that SMW may have diminished survivorship outcomes; outcomes that are measurably and importantly different from heterosexual breast cancer survivors. However, it remains unknown how sexual orientation influences breast cancer survivorship outcomes such as quality of life. One possible route of influence is SMW's perceived discrimination in the health care setting. This cross-sectional study examines SMW perceptions of discrimination as one of the multiple facets of the breast cancer survivorship process. This study assessed SMW breast cancer survivor's perceptions of discrimination during their breast cancer treatment experience and secondarily, examined the role of this perceived discrimination on SMW's quality of life. Sixty-eight purposefully sampled sexual minority breast cancer survivors completed assessments of quality of life, perceived discrimination, perceived social support and perceived stress via an online survey. Statistical analyses point to perceived discrimination and perceived social support as important indicators for predicting SMW's quality of life. Future research on SMW's breast cancer survivorship should include measures of perceived discrimination.

Patterns of Racial Socialization and Psychological Adjustment: Can Parental Communications about Race Reduce the Impact of Racial Discrimination?

ERIC Educational Resources Information Center

Neblett, Enrique W., Jr.; White, Rhonda L.; Ford, Kahlil R.; Philip, Cheri L.; Nguye-N, Hoa X.; Sellers, Robert M.

2008-01-01

This study uses two waves of data to examine the relations among racial discrimination experiences, patterns of racial socialization practices, and psychological adjustment in a sample of 361 African American adolescents. Using latent class analyses, we identified four patterns of child-reported racial socialization experiences: Moderate Positive,…

Deep Hashing for Scalable Image Search.

PubMed

Lu, Jiwen; Liong, Venice Erin; Zhou, Jie

2017-05-01

In this paper, we propose a new deep hashing (DH) approach to learn compact binary codes for scalable image search. Unlike most existing binary codes learning methods, which usually seek a single linear projection to map each sample into a binary feature vector, we develop a deep neural network to seek multiple hierarchical non-linear transformations to learn these binary codes, so that the non-linear relationship of samples can be well exploited. Our model is learned under three constraints at the top layer of the developed deep network: 1) the loss between the compact real-valued code and the learned binary vector is minimized, 2) the binary codes distribute evenly on each bit, and 3) different bits are as independent as possible. To further improve the discriminative power of the learned binary codes, we extend DH into supervised DH (SDH) and multi-label SDH by including a discriminative term into the objective function of DH, which simultaneously maximizes the inter-class variations and minimizes the intra-class variations of the learned binary codes with the single-label and multi-label settings, respectively. Extensive experimental results on eight widely used image search data sets show that our proposed methods achieve very competitive results with the state-of-the-arts.

Longitudinal data analyses using linear mixed models in SPSS: concepts, procedures and illustrations.

PubMed

Shek, Daniel T L; Ma, Cecilia M S

2011-01-05

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented.

Longitudinal Data Analyses Using Linear Mixed Models in SPSS: Concepts, Procedures and Illustrations

PubMed Central

Shek, Daniel T. L.; Ma, Cecilia M. S.

2011-01-01

Although different methods are available for the analyses of longitudinal data, analyses based on generalized linear models (GLM) are criticized as violating the assumption of independence of observations. Alternatively, linear mixed models (LMM) are commonly used to understand changes in human behavior over time. In this paper, the basic concepts surrounding LMM (or hierarchical linear models) are outlined. Although SPSS is a statistical analyses package commonly used by researchers, documentation on LMM procedures in SPSS is not thorough or user friendly. With reference to this limitation, the related procedures for performing analyses based on LMM in SPSS are described. To demonstrate the application of LMM analyses in SPSS, findings based on six waves of data collected in the Project P.A.T.H.S. (Positive Adolescent Training through Holistic Social Programmes) in Hong Kong are presented. PMID:21218263

Quantifying the chemical composition of soil organic carbon with solid-state 13C NMR

NASA Astrophysics Data System (ADS)

Baldock, J. A.; Sanderman, J.

2011-12-01

The vulnerability of soil organic carbon (SOC) to biological decomposition and mineralisation to CO2 is defined at least partially by its chemical composition. Highly aromatic charcoal-like SOC components are more stable to biological decomposition than other forms of carbon including cellulose. Solid-state 13C NMR has gained wide acceptance as a method capable of defining SOC chemical composition and mathematical fitting processes have been developed to estimate biochemical composition. Obtaining accurate estimates depends on an ability to quantitatively detect all carbon present in a sample. Often little attention has been paid to defining the proportion of organic carbon present in a soil that is observable in solid-state 13C NMR analyses of soil samples. However, if such data is to be used to inform carbon cycling studies, it is critical that quantitative assessments of SOC observability be undertaken. For example, it is now well established that a significant discrimination exists against the detection of the low proton content polyaromatic structures typical of charcoal using cross polarisation 13C NMR analyses. Such discrimination does not exist where direct polarisation analyses are completed. In this study, the chemical composition of SOC as defined by cross polarisation and direct polarisation13C NMR analyses will be compared for Australian soils collected from under a diverse range of agricultural managements and climatic conditions. Results indicate that where significant charcoal C contents exist, it is highly under-represented in the acquired CP spectra. For some soils, a discrimination against alkyl carbon was also evident. The ability to derive correction factors to compensate for such discriminations will be assessed and presented.

Discrimination of lichen genera and species using element concentrations

USGS Publications Warehouse

Bennett, J.P.

2008-01-01

The importance of organic chemistry in the classification of lichens is well established, but inorganic chemistry has been largely overlooked. Six lichen species were studied over a period of 23 years that were growing in 11 protected areas of the northern Great Lakes ecoregion, which were not greatly influenced by anthropogenic particulates or gaseous air pollutants. The elemental data from these studies were aggregated in order to test the hypothesis that differences among species in tissue element concentrations were large enough to discriminate between taxa faithfully. Concentrations of 16 chemical elements that were found in tissue samples from Cladonia rangiferina, Evernia mesomorpha, Flavopunctelia flaventior, Hypogymnia physodes, Parmelia sulcata, and Punctelia rudecta were analyzed statistically using multivariate discriminant functions and CART analyses, as well as t-tests. Genera and species were clearly separated in element space, and elemental discriminant functions were able to classify 91-100 of the samples correctly into species. At the broadest level, a Zn concentration of 51 ppm in tissues of four of the lichen species effectively discriminated foliose from fruticose species. Similarly, a S concentration of 680 ppm discriminated C. rangiferina and E. mesomorpha, and a Ca concentration of 10 436 ppm discriminated H. physodes from P. sulcata. For the three parmelioid species, a Ca concentration >32 837 ppm discriminated Punctelia rudecta from the other two species, while a Zn concentration of 56 ppm discriminated Parmelia sulcata from F. flaventior. Foliose species also had higher concentrations than did fruticose species of all elements except Na. Elemental signatures for each of the six species were developed using standardized means. Twenty-four mechanisms explaining the differences among species are summarized. Finally, the relationships of four species based on element concentrations, using additive-trees clustering of a Euclidean-distance matrix, produced identical relationships as did analyses based on secondary product chemistry that used additive-trees clustering of a Jaccard similarity matrix. At least for these six species, element composition has taxonomic significance, and may be useful for discriminating other taxa. ?? 2008 British Lichen Society.

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

Differential Effects of Personal-Level vs Group-Level Racial Discrimination on Health among Black Americans.

PubMed

Hagiwara, Nao; Alderson, Courtney J; Mezuk, Briana

2016-07-21

Racial/ethnic minorities in the United States not only experience discrimination personally but also witness or hear about fellow in-group members experiencing discrimination (ie, group-level discrimination). The objective of our study was to examine whether the effects of group-level discrimination on mental and physical health are different from those of personal-level discrimination among Black Americans by drawing upon social psychology research of the Personal/Group Discrimination Discrepancy. We conducted a secondary analysis of cross-sectional survey data from a larger study. One hundred and twenty participants, who self-identified as Black/African Americans during the laboratory sessions (57.5% women, mean age = 48.97, standard deviation = 8.58) in the parent study, were included in our analyses. Perceived personal-level discrimination was assessed with five items that were taken from two existing measures, and group-level racial discrimination was assessed with three items. Self-reported physical and mental health were assessed with a modified version of SF-8. Perceived personal-level racial discrimination was associated with worse mental health. In contrast, perceived group-level racial discrimination was associated with better mental as well as physical health. Perceived group-level racial discrimination may serve as one of several health protective factors even when individuals perceive personal-level racial discrimination. The present findings demonstrate the importance of examining both personal- and group-level experiences of racial discrimination as they independently relate to health outcomes for Black Americans.

Drugs and Drug-Like Compounds: Discriminating Approved Pharmaceuticals from Screening-Library Compounds

NASA Astrophysics Data System (ADS)

Schierz, Amanda C.; King, Ross D.

Compounds in drug screening-libraries should resemble pharmaceuticals. To operationally test this, we analysed the compounds in terms of known drug-like filters and developed a novel machine learning method to discriminate approved pharmaceuticals from “drug-like” compounds. This method uses both structural features and molecular properties for discrimination. The method has an estimated accuracy of 91% in discriminating between the Maybridge HitFinder library and approved pharmaceuticals, and 99% between the NATDiverse collection (from Analyticon Discovery) and approved pharmaceuticals. These results show that Lipinski’s Rule of 5 for oral absorption is not sufficient to describe “drug-likeness” and be the main basis of screening-library design.

EEO Implications of Job Analyses.

ERIC Educational Resources Information Center

Lacy, D. Patrick, Jr.

1979-01-01

Discusses job analyses as they relate to the requirements of Title VII of the Civil Rights Act of 1964, the Equal Pay Act of 1963, and the Rehabilitation Act of 1973. Argues that job analyses can establish the job-relatedness of entrance requirements and aid in defenses against charges of discrimination. Journal availability: see EA 511 615.

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

PubMed

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

2018-03-01

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

The differential impact of discrimination on health among Black and White women.

PubMed

Versey, H Shellae; Curtin, Nicola

2016-05-01

Despite a large body of research examining the impact of discrimination on health, the ways in which perceived discrimination may lead to disparate health outcomes through a sense of self and system consciousness is less understood. The current paper is concerned with both mental and physical health consequences of discrimination, as well as mediating pathways among African American and White women. Indirect effects analyses examine mediating paths from discrimination to health outcomes via structural awareness and self-esteem, using data from the Women's Life Path Study (N = 237). Our findings suggest that discrimination is both directly and indirectly associated with health outcomes for both Black and White women, mediated by individual (self-esteem) and group-level (structural awareness) processes. Evidence from this study indicates that discrimination is associated with heightened structural awareness, as well as lower self-esteem - both of which are related to poorer health. Discrimination negatively affected health across three domains, although the mechanisms varied somewhat for Black and White women. Broad implications of this research for interdisciplinary scholarship on the effects of discrimination on health and health disparities are discussed. Copyright © 2016 Elsevier Inc. All rights reserved.

Individual bioaerosol particle discrimination by multi-photon excited fluorescence.

PubMed

Kiselev, Denis; Bonacina, Luigi; Wolf, Jean-Pierre

2011-11-21

Femtosecond laser induced multi-photon excited fluorescence (MPEF) from individual airborne particles is tested for the first time for discriminating bioaerosols. The fluorescence spectra, analysed in 32 channels, exhibit a composite character originating from simultaneous two-photon and three-photon excitation at 790 nm. Simulants of bacteria aggregates (clusters of dyed polystyrene microspheres) and different pollen particles (Ragweed, Pecan, Mulberry) are clearly discriminated by their MPEF spectra. This demonstration experiment opens the way to more sophisticated spectroscopic schemes like pump-probe and coherent control. © 2011 Optical Society of America

Chiral analyses of dextromethorphan/levomethorphan and their metabolites in rat and human samples using LC-MS/MS.

PubMed

Kikura-Hanajiri, Ruri; Kawamura, Maiko; Miyajima, Atsuko; Sunouchi, Momoko; Goda, Yukihiro

2011-04-01

In order to develop an analytical method for the discrimination of dextromethorphan (an antitussive medicine) from its enantiomer, levomethorphan (a narcotic) in biological samples, chiral analyses of these drugs and their O-demethyl and/or N-demethyl metabolites in rat plasma, urine, and hair were carried out using LC-MS/MS. After the i.p. administration of dextromethorphan or levomethorphan to pigmented hairy male DA rats (5 mg/kg/day, 10 days), the parent compounds and their three metabolites in plasma, urine and hair were determined using LC-MS/MS. Complete chiral separation was achieved in 12 min on a Chiral CD-Ph column in 0.1% formic acid-acetonitrile by a linear gradient program. Most of the metabolites were detected as being the corresponding O-demethyl and N, O-didemethyl metabolites in the rat plasma and urine after the hydrolysis of O-glucuronides, although obvious differences in the amounts of these metabolites were found between the dextro and levo forms. No racemation was observed through O- and/or N-demethylation. In the rat hair samples collected 4 weeks after the first administration, those differences were more clearly detected and the concentrations of the parent compounds, their O-demethyl, N-demethyl, and N, O-didemethyl metabolites were 63.4, 2.7, 25.1, and 0.7 ng/mg for the dextro forms and 24.5, 24.6, 2.6, and 0.5 ng/mg for the levo forms, respectively. In order to fully investigate the differences of their metabolic properties between dextromethorphan and levomethorphan, DA rat and human liver microsomes were studied. The results suggested that there might be an enantioselective metabolism of levomethorphan, especially with regard to the O-demethylation, not only in DA rat but human liver microsomes as well. The proposed chiral analyses might be applied to human samples and could be useful for discriminating dextromethorphan use from levomethorphan use in the field of forensic toxicology, although further studies should be carried out using authentic human samples.

Pharmaceutical Raw Material Identification Using Miniature Near-Infrared (MicroNIR) Spectroscopy and Supervised Pattern Recognition Using Support Vector Machine

PubMed Central

Hsiung, Chang; Pederson, Christopher G.; Zou, Peng; Smith, Valton; von Gunten, Marc; O’Brien, Nada A.

2016-01-01

Near-infrared spectroscopy as a rapid and non-destructive analytical technique offers great advantages for pharmaceutical raw material identification (RMID) to fulfill the quality and safety requirements in pharmaceutical industry. In this study, we demonstrated the use of portable miniature near-infrared (MicroNIR) spectrometers for NIR-based pharmaceutical RMID and solved two challenges in this area, model transferability and large-scale classification, with the aid of support vector machine (SVM) modeling. We used a set of 19 pharmaceutical compounds including various active pharmaceutical ingredients (APIs) and excipients and six MicroNIR spectrometers to test model transferability. For the test of large-scale classification, we used another set of 253 pharmaceutical compounds comprised of both chemically and physically different APIs and excipients. We compared SVM with conventional chemometric modeling techniques, including soft independent modeling of class analogy, partial least squares discriminant analysis, linear discriminant analysis, and quadratic discriminant analysis. Support vector machine modeling using a linear kernel, especially when combined with a hierarchical scheme, exhibited excellent performance in both model transferability and large-scale classification. Hence, ultra-compact, portable and robust MicroNIR spectrometers coupled with SVM modeling can make on-site and in situ pharmaceutical RMID for large-volume applications highly achievable. PMID:27029624

Centered Kernel Alignment Enhancing Neural Network Pretraining for MRI-Based Dementia Diagnosis

PubMed Central

Cárdenas-Peña, David; Collazos-Huertas, Diego; Castellanos-Dominguez, German

2016-01-01

Dementia is a growing problem that affects elderly people worldwide. More accurate evaluation of dementia diagnosis can help during the medical examination. Several methods for computer-aided dementia diagnosis have been proposed using resonance imaging scans to discriminate between patients with Alzheimer's disease (AD) or mild cognitive impairment (MCI) and healthy controls (NC). Nonetheless, the computer-aided diagnosis is especially challenging because of the heterogeneous and intermediate nature of MCI. We address the automated dementia diagnosis by introducing a novel supervised pretraining approach that takes advantage of the artificial neural network (ANN) for complex classification tasks. The proposal initializes an ANN based on linear projections to achieve more discriminating spaces. Such projections are estimated by maximizing the centered kernel alignment criterion that assesses the affinity between the resonance imaging data kernel matrix and the label target matrix. As a result, the performed linear embedding allows accounting for features that contribute the most to the MCI class discrimination. We compare the supervised pretraining approach to two unsupervised initialization methods (autoencoders and Principal Component Analysis) and against the best four performing classification methods of the 2014 CADDementia challenge. As a result, our proposal outperforms all the baselines (7% of classification accuracy and area under the receiver-operating-characteristic curve) at the time it reduces the class biasing. PMID:27148392

Component-based subspace linear discriminant analysis method for face recognition with one training sample

NASA Astrophysics Data System (ADS)

Huang, Jian; Yuen, Pong C.; Chen, Wen-Sheng; Lai, J. H.

2005-05-01

Many face recognition algorithms/systems have been developed in the last decade and excellent performances have also been reported when there is a sufficient number of representative training samples. In many real-life applications such as passport identification, only one well-controlled frontal sample image is available for training. Under this situation, the performance of existing algorithms will degrade dramatically or may not even be implemented. We propose a component-based linear discriminant analysis (LDA) method to solve the one training sample problem. The basic idea of the proposed method is to construct local facial feature component bunches by moving each local feature region in four directions. In this way, we not only generate more samples with lower dimension than the original image, but also consider the face detection localization error while training. After that, we propose a subspace LDA method, which is tailor-made for a small number of training samples, for the local feature projection to maximize the discrimination power. Theoretical analysis and experiment results show that our proposed subspace LDA is efficient and overcomes the limitations in existing LDA methods. Finally, we combine the contributions of each local component bunch with a weighted combination scheme to draw the recognition decision. A FERET database is used for evaluating the proposed method and results are encouraging.

A general soft label based linear discriminant analysis for semi-supervised dimensionality reduction.

PubMed

Zhao, Mingbo; Zhang, Zhao; Chow, Tommy W S; Li, Bing

2014-07-01

Dealing with high-dimensional data has always been a major problem in research of pattern recognition and machine learning, and Linear Discriminant Analysis (LDA) is one of the most popular methods for dimension reduction. However, it only uses labeled samples while neglecting unlabeled samples, which are abundant and can be easily obtained in the real world. In this paper, we propose a new dimension reduction method, called "SL-LDA", by using unlabeled samples to enhance the performance of LDA. The new method first propagates label information from the labeled set to the unlabeled set via a label propagation process, where the predicted labels of unlabeled samples, called "soft labels", can be obtained. It then incorporates the soft labels into the construction of scatter matrixes to find a transformed matrix for dimension reduction. In this way, the proposed method can preserve more discriminative information, which is preferable when solving the classification problem. We further propose an efficient approach for solving SL-LDA under a least squares framework, and a flexible method of SL-LDA (FSL-LDA) to better cope with datasets sampled from a nonlinear manifold. Extensive simulations are carried out on several datasets, and the results show the effectiveness of the proposed method. Copyright © 2014 Elsevier Ltd. All rights reserved.

Radar image processing for rock-type discrimination

NASA Technical Reports Server (NTRS)

Blom, R. G.; Daily, M.

1982-01-01

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

Discrimination of rectal cancer through human serum using surface-enhanced Raman spectroscopy

NASA Astrophysics Data System (ADS)

Li, Xiaozhou; Yang, Tianyue; Li, Siqi; Zhang, Su; Jin, Lili

2015-05-01

In this paper, surface-enhanced Raman spectroscopy (SERS) was used to detect the changes in blood serum components that accompany rectal cancer. The differences in serum SERS data between rectal cancer patients and healthy controls were examined. Postoperative rectal cancer patients also participated in the comparison to monitor the effects of cancer treatments. The results show that there are significant variations at certain wavenumbers which indicates alteration of corresponding biological substances. Principal component analysis (PCA) and parameters of intensity ratios were used on the original SERS spectra for the extraction of featured variables. These featured variables then underwent linear discriminant analysis (LDA) and classification and regression tree (CART) for the discrimination analysis. Accuracies of 93.5 and 92.4 % were obtained for PCA-LDA and parameter-CART, respectively.

Discriminative functions and over-training as class-enhancing determinants of meaningful stimuli.

PubMed

Travis, Robert W; Fields, Lanny; Arntzen, Erik

2014-07-01

Likelihood of equivalence class formation (yield) was influenced by pre-class formation of simultaneous and successive discriminations, their mastery criteria, and overtraining of the successive discriminations. Each undergraduate in seven groups attempted to form two 3-node, 5-member equivalence classes (ABCDE). In the pictorial (PIC) group, meaningless nonsense syllables were used as the A, B, D, and E stimuli and meaningful pictures as the C stimuli. Nonsense syllables only were used in the other groups. The abstract (ABS) or 0-0-0 group involved no pre-class training. In the 84-0-0, 84-5-0 and 84-20-0 groups, simultaneous discriminations were trained among C stimuli to a mastery criterion of 84 trials, followed by successive discriminations trained to mastery criteria of 0, 5, and 20 trials, respectively. In the 84-20-0, 84-20-100, and 84-20-500 groups, simultaneous and successive discriminations were trained as noted, followed by overtraining with 0, 100, 500 successive-discrimination trials, respectively. The ABS group produced a 6% yield with the 84-0-0, 84-5-0, and 84-20-0 groups producing further modest increments. Overtraining produced a linear increase in yield, reaching 85% after 500 overtraining trials, a yield matching that produced by classes containing pictures as C stimuli (PIC). Thus, acquired discriminative functions and the overtraining of at least one function can account for class enhancement by meaningful stimuli. © Society for the Experimental Analysis of Behavior.

The development of global motion discrimination in school aged children

PubMed Central

Bogfjellmo, Lotte-Guri; Bex, Peter J.; Falkenberg, Helle K.

2014-01-01

Global motion perception matures during childhood and involves the detection of local directional signals that are integrated across space. We examine the maturation of local directional selectivity and global motion integration with an equivalent noise paradigm applied to direction discrimination. One hundred and three observers (6–17 years) identified the global direction of motion in a 2AFC task. The 8° central stimuli consisted of 100 dots of 10% Michelson contrast moving 2.8°/s or 9.8°/s. Local directional selectivity and global sampling efficiency were estimated from direction discrimination thresholds as a function of external directional noise, speed, and age. Direction discrimination thresholds improved gradually until the age of 14 years (linear regression, p < 0.05) for both speeds. This improvement was associated with a gradual increase in sampling efficiency (linear regression, p < 0.05), with no significant change in internal noise. Direction sensitivity was lower for dots moving at 2.8°/s than at 9.8°/s for all ages (paired t test, p < 0.05) and is mainly due to lower sampling efficiency. Global motion perception improves gradually during development and matures by age 14. There was no change in internal noise after the age of 6, suggesting that local direction selectivity is mature by that age. The improvement in global motion perception is underpinned by a steady increase in the efficiency with which direction signals are pooled, suggesting that global motion pooling processes mature for longer and later than local motion processing. PMID:24569985

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.

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Shao, Yongni; He, Yong; Hu, Xingyue

2007-12-01

An optical system based on visible/near-infrared spectroscopy (Vis/NIRS) for variety discrimination of ginkgo (Ginkgo biloba L.) tablets was developed. This system consisted of a light source, beam splitter system, sample chamber, optical detector (diffuse reflection detector), and data collection. The tablet varieties used in the research include Da na kang, Xin bang, Tian bao ning, Yi kang, Hua na xing, Dou le, Lv yuan, Hai wang, and Ji yao. All samples (n=270) were scanned in the Vis/NIR region between 325 and 1075 nm using a spectrograph. The chemometrics method of principal component artificial neural network (PC-ANN) was used to establish discrimination models of them. In PC-ANN models, the scores of the principal components were chosen as the input nodes for the input layer of ANN, and the best discrimination rate of 91.1% was reached. Principal component analysis was also executed to select several optimal wavelengths based on loading values. Wavelengths at 481, 458, 466, 570, 1000, 662, and 400 nm were then used as the input data of stepwise multiple linear regression, the regression equation of ginkgo tablets was obtained, and the discrimination rate was researched 84.4%. The results indicated that this optical system could be applied to discriminating ginkgo (Ginkgo biloba L.) tablets, and it supplied a new method for fast ginkgo tablet variety discrimination.

Measurements of the talus in the assessment of population affinity.

PubMed

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

2018-06-01

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

Assessment of Ethylene Vinyl-Acetato Copolymer (EVA) Samples Bombarded by Gamma Radiation via Linearity Analyses

NASA Astrophysics Data System (ADS)

de Oliveira, L. N.; do Nascimento, E. O.; Schimidt, F.; Antonio, P. L.; Caldas, L. V. E.

2018-03-01

Materials with the potential to become dosimeters are of interest in radiation physics. In this research, the materials were analyzed and compared in relation to their linearity ranges. Samples of ethylene vinyl-acetate copolymer (EVA) were irradiated with doses from 10 Gy to 10 kGy using a 60Co Gamma-Cell system 220 and evaluated with the FTIR technique. The linearity analyses were applied through two methodologies, searching for linear regions in their response. The results show that both applied analyses indicate linear regions in defined dose interval. The radiation detectors EVA can be useful for radiation dosimetry in intermediate and high doses.

Binge drinking and perceived ethnic discrimination among Hispanics/Latinos: Results from the Hispanic community health study/study of Latinos sociocultural ancillary study.

PubMed

Ornelas, India J; Lapham, Gwen T; Salgado, Hugo; Williams, Emily C; Gotman, Nathan; Womack, Veronica; Davis, Sonia; Penedo, Frank; Smoller, Sylvia; Gallo, Linda C

2016-01-01

The study assessed whether overall perceived ethnic discrimination and four unique discrimination types were associated with binge drinking in participants from the Hispanic Community Health Study/Study of Latinos who also completed the Hispanic Community Health Study/Study of Latinos Sociocultural Ancillary Study (n = 5,313). In unadjusted analyses that were weighted for sampling strategy and design, each unit increase in discrimination type was associated with a 12-63% increase in odds of binge drinking; however, after adjusting for important demographic variables including age, sex, heritage group, language, and duration of U.S. residence, there was no longer an association between discrimination and binge drinking. Further research still needs to identify the salient factors that contribute to increased risk for binge drinking among Hispanics/Latinos.

Binge Drinking and Perceived Ethnic Discrimination among Hispanics/Latinos: Results from the Hispanic Community Health Study/Study of Latinos Sociocultural Ancillary Study

PubMed Central

Ornelas, India J.; Lapham, Gwen T.; Salgado, Hugo; Williams, Emily C.; Gotman, Nathan; Womack, Veronica; Davis, Sonia; Penedo, Frank; Smoller, Sylvia; Gallo, Linda C.

2016-01-01

The study assessed whether overall perceived ethnic discrimination and four unique discrimination types were associated with binge drinking in participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) who also completed the HCHS/SOL Sociocultural Ancillary Study (n = 5,313). In unadjusted analyses that were weighted for sampling strategy and design, each unit increase in discrimination type was associated with a 12 - 63% increase in odds of binge drinking; however, after adjusting for important demographic variables including age, sex, heritage group, language, and duration of US residence, there was no longer an association between discrimination and binge drinking. Further research still needs to identify the salient factors that contribute to increased risk for binge drinking among Hispanics/Latinos. PMID:26643869

Place of birth effects on self-reported discrimination: Variations by type of discrimination.

PubMed

Brondolo, Elizabeth; Rahim, Reanne; Grimaldi, Stephanie; Ashraf, Amina; Bui, Nini; Schwartz, Joseph

2015-11-01

Researchers have suggested that perceptions of discrimination may vary depending on place of birth and the length of time spent living in the U.S., variables related to acculturation. However, the existing literature provides a mixed picture, with data suggesting that the effects of acculturation on perceptions of discrimination vary by race and other sociodemographic factors. This study evaluated the role of place of birth (POB: defined as U.S.-born vs. foreign-born), age at immigration, and length of residence in the U.S. on self-reported discrimination in a sample of urban-dwelling Asian and Black adults (n= 1454). Analyses examined POB effects on different types of discrimination including race-related stigmatization, exclusion, threat, and workplace discrimination. Sociodemographic variables (including age, gender, employment status and education level) were tested as potential moderators of the relationship between POB and discrimination. The results revealed a significant main effect for POB on discrimination, with U.S.-born individuals reporting significantly more discrimination than foreign-born individuals, although the effect was reduced when sociodemographic variables were controlled. Across the sample, POB effects were seen only for race-related stigmatization and exclusion, not for threat and workplace discrimination. With the exception of limited effects for gender, sociodemographic variables did not moderate these effects. Younger age at immigration and greater years of residence in the U.S. were also positively associated with higher levels of perceived discrimination. These findings suggest increasing acculturation may shape the experience and perception of racial and ethnic discrimination.

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

PubMed

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

2013-11-01

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

Modeling of an 8-12 GHz receiver front-end based on an in-line MEMS frequency discriminator

NASA Astrophysics Data System (ADS)

Chu, Chenlei; Liao, Xiaoping

2018-06-01

This paper focuses on the modeling of an 8-12 GHz RF (radio frequency) receiver front-end based on an in-line MEMS (microelectromechanical systems) frequency discriminator. Actually, the frequency detection is realized by measuring the output dc thermal voltage generated by the MEMS thermoelectric power sensor. Based on this thermal voltage, it has a great potential to tune the resonant frequency of the VCO (voltage controlled oscillator) in the RF receiver front-end application. The equivalent circuit model of the in-line frequency discriminator is established and the measurement verification is also implemented. Measurement and simulation results show that the output dc thermal voltage has a nearly linear relation with frequency. A new construction of RF receiver front-end is then obtained by connecting the in-line frequency discriminator with the voltage controlling port of VCO. Lastly, a systemic simulation is processed by computer-aided software and the real-time simulation waveform at each key point is observed clearly.

Spectral Regression Discriminant Analysis for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Pan, Y.; Wu, J.; Huang, H.; Liu, J.

2012-08-01

Dimensionality reduction algorithms, which aim to select a small set of efficient and discriminant features, have attracted great attention for Hyperspectral Image Classification. The manifold learning methods are popular for dimensionality reduction, such as Locally Linear Embedding, Isomap, and Laplacian Eigenmap. However, a disadvantage of many manifold learning methods is that their computations usually involve eigen-decomposition of dense matrices which is expensive in both time and memory. In this paper, we introduce a new dimensionality reduction method, called Spectral Regression Discriminant Analysis (SRDA). SRDA casts the problem of learning an embedding function into a regression framework, which avoids eigen-decomposition of dense matrices. Also, with the regression based framework, different kinds of regularizes can be naturally incorporated into our algorithm which makes it more flexible. It can make efficient use of data points to discover the intrinsic discriminant structure in the data. Experimental results on Washington DC Mall and AVIRIS Indian Pines hyperspectral data sets demonstrate the effectiveness of the proposed method.

Racial discrimination & cardiovascular disease risk: my body my story study of 1005 US-born black and white community health center participants (US).

PubMed

Krieger, Nancy; Waterman, Pamela D; Kosheleva, Anna; Chen, Jarvis T; Smith, Kevin W; Carney, Dana R; Bennett, Gary G; Williams, David R; Thornhill, Gisele; Freeman, Elmer R

2013-01-01

To date, limited and inconsistent evidence exists regarding racial discrimination and risk of cardiovascular disease (CVD). Cross-sectional observational study of 1005 US-born non-Hispanic black (n = 504) and white (n = 501) participants age 35-64 randomly selected from community health centers in Boston, MA (2008-2010; 82.4% response rate), using 3 racial discrimination measures: explicit self-report; implicit association test (IAT, a time reaction test for self and group as target vs. perpetrator of discrimination); and structural (Jim Crow status of state of birth, i.e. legal racial discrimination prior 1964). Black and white participants both had adverse cardiovascular and socioeconomic profiles, with black participants most highly exposed to racial discrimination. Positive crude associations among black participants occurred for Jim Crow birthplace and hypertension (odds ratio (OR) 1.92, 95% confidence interval (CI) 1.28, 2.89) and for explicit self-report and the Framingham 10 year CVD risk score (beta = 0.04; 95% CI 0.01, 0.07); among white participants, only negative crude associations existed (for IAT for self, for lower systolic blood pressure (SBP; beta = -4.86; 95% CI -9.08, -0.64) and lower Framingham CVD score (beta = -0.36, 95% CI -0.63, -0.08)). All of these associations were attenuated and all but the white IAT-Framingham risk score association were rendered null in analyses that controlled for lifetime socioeconomic position and additional covariates. Controlling for racial discrimination, socioeconomic position, and other covariates did not attenuate the crude black excess risk for SBP and hypertension and left unaffected the null excess risk for the Framingham CVD score. Despite worse exposures among the black participants, racial discrimination and socioeconomic position were not associated, in multivariable analyses, with risk of CVD. We interpret results in relation to constrained variability of exposures and outcomes and discuss implications for valid research on social determinants of health.

Sensitivity and specificity of subacute computerized neurocognitive testing and symptom evaluation in predicting outcomes after sports-related concussion.

PubMed

Lau, Brian C; Collins, Michael W; Lovell, Mark R

2011-06-01

Concussions affect an estimated 136 000 high school athletes yearly. Computerized neurocognitive testing has been shown to be appropriately sensitive and specific in diagnosing concussions, but no studies have assessed its utility to predict length of recovery. Determining prognosis during subacute recovery after sports concussion will help clinicians more confidently address return-to-play and academic decisions. To quantify the prognostic ability of computerized neurocognitive testing in combination with symptoms during the subacute recovery phase from sports-related concussion. Cohort study (prognosis); Level of evidence, 2. In sum, 108 male high school football athletes completed a computer-based neurocognitive test battery within 2.23 days of injury and were followed until returned to play as set by international guidelines. Athletes were grouped into protracted recovery (>14 days; n = 50) or short-recovery (≤14 days; n = 58). Separate discriminant function analyses were performed using total symptom score on Post-Concussion Symptom Scale, symptom clusters (migraine, cognitive, sleep, neuropsychiatric), and Immediate Postconcussion Assessment and Cognitive Testing neurocognitive scores (verbal memory, visual memory, reaction time, processing speed). Multiple discriminant function analyses revealed that the combination of 4 symptom clusters and 4 neurocognitive composite scores had the highest sensitivity (65.22%), specificity (80.36%), positive predictive value (73.17%), and negative predictive value (73.80%) in predicting protracted recovery. Discriminant function analyses of total symptoms on the Post-Concussion Symptom Scale alone had a sensitivity of 40.81%; specificity, 79.31%; positive predictive value, 62.50%; and negative predictive value, 61.33%. The 4 symptom clusters alone discriminant function analyses had a sensitivity of 46.94%; specificity, 77.20%; positive predictive value, 63.90%; and negative predictive value, 62.86%. Discriminant function analyses of the 4 computerized neurocognitive scores alone had a sensitivity of 53.20%; specificity, 75.44%; positive predictive value, 64.10%; and negative predictive value, 66.15%. The use of computerized neurocognitive testing in conjunction with symptom clusters results improves sensitivity, specificity, positive predictive value, and negative predictive value of predicting protracted recovery compared with each used alone. There is also a net increase in sensitivity of 24.41% when using neurocognitive testing and symptom clusters together compared with using total symptoms on Post-Concussion Symptom Scale alone.

Discrimination against Students with Foreign Backgrounds: Evidence from Grading in Swedish Public High Schools

ERIC Educational Resources Information Center

Hinnerich, Bjorn Tyrefors; Höglin, Erik; Johannesson, Magnus

2015-01-01

We rigorously test for discrimination against students with foreign backgrounds in high school grading in Sweden. We analyse a random sample of national tests in the Swedish language graded both non-blindly by the student's own teacher and blindly without any identifying information. The increase in the test score due to non-blind grading is…

Discriminant Analysis Between Four Different Self Measures and Sex-Role Identity with Junior Year College Students.

ERIC Educational Resources Information Center

Wallace, Gaylen R.; Goodwin-Adam, Sharon

A review of the literature concerning the relationship between sex role and self measure identity includes a discussion of issues confronted in measurement. The methodology and analyses of data for the study are explained. The research was designed to determine which self referent measure most effectively discriminates among sex role identities.…

Discriminant and Incremental Validity of Self-Concept and Academic Self-Efficacy: A Meta-Analysis

ERIC Educational Resources Information Center

Huang, Chiungjung

2012-01-01

Two studies examined the discriminant and incremental validity of self-concept and academic self-efficacy. Study 1, which meta-analysed 64 studies comprising 74 independent samples (N = 24,773), found a strong mean correlation of 0.43 between self-concept and academic self-efficacy. The domains of self-concept and self-efficacy, and the domain…

Is Obesity Stigmatizing? Body Weight, Perceived Discrimination, and Psychological Well-Being in the United States

ERIC Educational Resources Information Center

Carr, Deborah; Friedman, Michael A.

2005-01-01

We investigate the frequency and psychological correlates of institutional and interpersonal discrimination reported by underweight, normal weight, overweight, obese I, and obese II/III Americans. Analyses use data from the Midlife Development in the United States study, a national survey of more than 3,000 adults ages 25 to 74 in 1995. Compared…

"Say It Loud--I'm Black and I'm Proud": Parents' Messages about Racial Discrimination, and Academic Achievement in African American Boys

ERIC Educational Resources Information Center

Neblett, Enrique W., Jr.; Chavous, Tabbye M.; Nguyen, Hoa X.; Sellers, Robert M.

2009-01-01

This study uses two waves of data to examine the relationships among racial socialization, racial discrimination, and academic achievement outcomes in a sample of 144 African American male adolescents. Using latent class analyses, the authors identified four patterns of adolescent-reported racial socialization experiences: Positive Socialization,…