scholarly journals Principal Components Analysis of Atopy-Related Traits in a Random Sample of Children

ISRN Allergy ◽  
2011 ◽  
Vol 2011 ◽  
pp. 1-4
Author(s):  
Simon Francis Thomsen ◽  
Vibeke Backer
Keyword(s):  
Atopic Dermatitis ◽  
Principal Components Analysis ◽  
Random Sample ◽  
Skin Test ◽  
Principal Components ◽  
Skin Test Reactivity ◽  
Total Ige ◽  
Components Analysis ◽  
Serum Total Ige ◽  
The Relationship

Aim. To study the relationship between atopy-related traits in a random sample of children. Methods. A total of 1007 randomly selected children, 7–17 years of age, from Copenhagen, Denmark were studied. The children were interviewed about symptoms of atopic diseases, and skin test reactivity, serum total IgE, lung function, and airway responsiveness were measured. Principal components analysis was performed in order to examine the relationship between the different traits. Results. Most of the studied traits were significantly correlated. A three-component solution explained about 55% of the variation in the observed traits. The first component loaded most strongly on hay fever, serum total IgE, skin test reactivity and sensitisation to grass, cat and house dust mite allergen; the second factor was most associated with asthma, airway obstruction, and airway hyperresponsiveness, whereas the third factor corresponded most strongly to atopic dermatitis. There was some indication of cross-relations between the three components with respect to serum total IgE. Conclusion. Asthma, hay fever, and atopic dermatitis are characterised by different sets of biomarkers suggestive of a high degree of heterogeneity within the atopic syndrome.

Face Recognition Algorithm Based on Kernel Collaborative Representation

2013 ◽  
Vol 756-759 ◽  
pp. 3590-3595
Author(s):  
Liang Zhang ◽  
Ji Wen Dong
Keyword(s):  
Face Recognition ◽  
Principal Components Analysis ◽  
Principal Components ◽  
Recognition Algorithm ◽  
Experimental Results ◽  
Collaborative Representation ◽  
Nonlinear Structures ◽  
Components Analysis ◽  
Kernel Principal Components Analysis ◽  
The Relationship

Aiming at solving the problems of occlusion and illumination in face recognition, a new method of face recognition based on Kernel Principal Components Analysis (KPCA) and Collaborative Representation Classifier (CRC) is developed. The KPCA can obtain effective discriminative information and reduce the feature dimensions by extracting faces nonlinear structures features, the decisive factor. Considering the collaboration among the samples, the CRC which synthetically consider the relationship among samples is used. Experimental results demonstrate that the algorithm obtains good recognition rates and also improves the efficiency. The KCRC algorithm can effectively solve the problem of illumination and occlusion in face recognition.

scholarly journals Racial differences in the association of CD14 polymorphisms with serum total IgE levels and allergen skin test reactivity

2013 ◽  
pp. 81 ◽  
Author(s):  
Sophie Wang ◽  
John Sundy ◽  
Catherine M. Foss ◽  
Huiman X. Barnhart ◽  
Scott M. Palmer ◽  
...  
Keyword(s):  
Racial Differences ◽  
Skin Test ◽  
Skin Test Reactivity ◽  
Total Ige ◽  
Serum Total Ige

Personality Trait Absorption: An Exploratory Study of Opportunity and Capacity in Relation to Cannabis Use

1995 ◽  
Vol 15 (1) ◽  
pp. 75-101
Author(s):  
Peter L. Nelson
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Personality Trait ◽  
Exploratory Study ◽  
Cannabis Use ◽  
Components Analysis ◽  
Relationship Of ◽  
The Relationship ◽  
Tellegen Absorption Scale ◽  
Motivation Loss

Although the Tellegen Absorption Scale has been widely employed in recent years as a measure of personality Trait Absorption, it is argued that this simple score does not sufficiently discriminate true capacity for Absorption nor does it reveal the level of opportunity made for absorptive experiencing. This study operationalizes Capacity and Opportunity as two additional subscales appended to the Tellegen scale and, by employing the technique of Principal Components Analysis, five useful sub-dimensions are generated. Following on from this Author's earlier suggestion that personality Trait Absorption may be linked to cannabis use and depression, an exploratory study was conducted into the relationship of cannabis use, gender, self-perceived motivation loss and depression to observed levels of overall Absorption as well as to levels of Capacity and Opportunity for absorptive experiencing.

The psycholexical approach to the structure of interpersonal traits

1995 ◽  
Vol 9 (2) ◽  
pp. 89-102 ◽  
Author(s):  
Boele de Raad
Keyword(s):  
Principal Components Analysis ◽  
Big Five ◽  
Principal Components ◽  
Interpersonal Circumplex ◽  
Factor Solution ◽  
Peer Ratings ◽  
Interpersonal Factors ◽  
Components Analysis ◽  
Relationship Of ◽  
The Relationship

In this study the structure of interpersonal behaviour is investigated following the principles of the so‐called psycholexical approach. The interpersonal trait descriptors are selected from a comprehensive set of 1203 trait descriptive adjectives, constructed by Brokken (1978). Self‐ratings and peer ratings (N = 400) on the subset of 454 interpersonal trait adjectives were subjected to Principal Components analysis. The main results centre around a two‐factor solution, approximately reflecting the axis of the traditional interpersonal circumplex, Dominance and Nurturance. The relationship of the two interpersonal factors with the Big Five is discussed, as well as the relationship with the set of traits judged non‐interpersonal.

Anhedonia and Alexithymia: Distinct or Overlapping Constructs

1997 ◽  
Vol 84 (2) ◽  
pp. 415-425 ◽  
Author(s):  
Gwenolé Loas ◽  
Didier Fremaux ◽  
Patrice Boyer
Keyword(s):  
Principal Components Analysis ◽  
Principal Components ◽  
Correlation Matrix ◽  
Healthy Subjects ◽  
Factor Solution ◽  
Toronto Alexithymia Scale ◽  
Factor Loadings ◽  
Components Analysis ◽  
Physical Anhedonia ◽  
The Relationship

The aim was to examine the relationship between alexithymia, anhedonia, and capacity for displeasure in a group of 133 healthy subjects using principal components analysis. A correlation matrix comprised of items from both the Communication and Identification scale of the 20-item Toronto Alexithymia Scale and the Physical Pleasure-Displeasure Scale yielded a four-factor solution (one Communication-Identification, two Pleasure, and one Displeasure factor) with no overlap of the significant factor loadings for the items from each scale. Moreover, there were no positive significant correlations between the Communication and Identification Scales and the Physical Anhedonia Scale. Our findings support the view that physical anhedonia is a construct distinct and separate from alexithymia.

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