scholarly journals Age-seroprevalence curves for the multi-strain structure of influenza A virus

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Dao Nguyen Vinh ◽  
Nguyen Thi Duy Nhat ◽  
Erwin de Bruin ◽  
Nguyen Ha Thao Vy ◽  
Tran Thi Nhu Thao ◽  
...  
Keyword(s):  
Principal Components ◽  
Attack Rate ◽  
Influenza A ◽  
Principal Component ◽  
Human Antibody ◽  
Birth Cohorts ◽  
Serum Samples ◽  
The Relationship ◽  
Subtype H1 ◽  
Variable Group

AbstractThe relationship between age and seroprevalence can be used to estimate the annual attack rate of an infectious disease. For pathogens with multiple serologically distinct strains, there is a need to describe composite exposure to an antigenically variable group of pathogens. In this study, we assay 24,402 general-population serum samples, collected in Vietnam between 2009 to 2015, for antibodies to eleven human influenza A strains. We report that a principal components decomposition of antibody titer data gives the first principal component as an appropriate surrogate for seroprevalence; this results in annual attack rate estimates of 25.6% (95% CI: 24.1% – 27.1%) for subtype H3 and 16.0% (95% CI: 14.7% – 17.3%) for subtype H1. The remaining principal components separate the strains by serological similarity and associate birth cohorts with their particular influenza histories. Our work shows that dimensionality reduction can be used on human antibody profiles to construct an age-seroprevalence relationship for antigenically variable pathogens.

scholarly journals Age-seroprevalence curves for the multi-strain structure of influenza A virus

2021 ◽  
Author(s):  
Dao Nguyen Vinh ◽  
Nguyen Thi Duy Nhat ◽  
Erwin de Bruin ◽  
Nguyen Ha Thao Vy ◽  
Tran Thi Nhu Thao ◽  
...  
Keyword(s):  
Influenza A Virus ◽  
Principal Components ◽  
Influenza A ◽  
Principal Component ◽  
Population Exposure ◽  
Human Antibody ◽  
Human Influenza ◽  
Serum Samples ◽  
Tropical Country ◽  
Data Set

AbstractThe relationship between age and seroprevalence provides the simplest and least expensive approach to computing the annual attack rate of an infectious disease. However, many pathogens circulate as multiple serologically distinct strains, with no single assay able to determine seropositivity or seronegativity to an entire clade or family of co-circulating pathogens. An approach is needed to describe population exposure to an antigenically variable group of pathogens without focusing on any particular strain or serotype in the group. In this study, we focus on the two-subtype multi-strain taxonomy of human influenza A virus. We describe a data set of 24,402 general-population serum samples collected in central and southern Vietnam between 2009 to 2015, and assayed for influenza HA1 antibodies to eleven different strains of human influenza A (both H3 and H1 subtypes). We find that a principal components decomposition of the data results in the first principal component PC1 being an appropriate surrogate for seroprevalence (or composite antibody titer) which can be further decomposed for H1 and H3 contribution to the serological profile. Using this approach, we are able to provide the first ELISA-based standardized measurements of serology to reconstruct population exposure history, which correlates well with known influenza epidemiology. Annual attack rates in Vietnam are estimated at 25.6% (95% CI: 24.1% – 27.1%) for H3 and 16.0% (95% CI: 14.7% – 17.3%) for H1, with some variation in location-specific attack rates. The remaining principal components act as descriptors of influenza history and sort the population by birth year. The novel contributions of this analysis are (1) the introduction of dimensionality reduction on human antibody profiles to construct an age-seroprevalence relationship for an antigenically variable pathogen, (2) an analysis of >24,000 individuals, using >260,000 serological data points in total, allowing us to construct age-seroprevalence relationships with the precision of modern big data studies, and (3) a description of long-term attack rates in a non-vaccinated setting showing the natural history of influenza A virus in a densely-populated tropical country.

scholarly journals Analysis of the delivery plane in the golf swing using principal components

2018 ◽  
Vol 232 (4) ◽  
pp. 295-304 ◽  
Author(s):  
Andrew Morrison ◽  
Denise McGrath ◽  
Eric S Wallace
Keyword(s):  
Regression Analysis ◽  
Multiple Regression Analysis ◽  
Multiple Regression ◽  
Principal Components ◽  
Principal Component ◽  
Golf Swing ◽  
Ball Impact ◽  
Impact Location ◽  
The Relationship

Although the swing plane has been a popular area of golf biomechanics research, the movement of the club relative to the swing plane has yet to be shown experimentally to have a relationship with performance. This study used principal component and subsequent multiple regression analysis to investigate the relationship between the movement of the club relative to the delivery plane and clubhead characteristics at ball impact. The principal components reflected deviations from an individual swing plane, and lower values of these components were associated with less variability in the clubface impact location. In the event that a golf coach wants to improve the precision of ball striking, the results from this study suggest that both simplicity of the route and alignment of the club to the final trajectory before impact could be advantageous. However, this does not suggest that the technique should be based on a ‘model’ swing plane.

scholarly journals Clustering of ingredients with amino acid composition similar to the nutritional requirement of Nile tilapia

2010 ◽  
Vol 67 (5) ◽  
pp. 517-523 ◽  
Author(s):  
Álvaro José de Almeida Bicudo ◽  
Luis Fernando Batista Pinto ◽  
José Eurico Possebon Cyrino
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Principal Components ◽  
Nile Tilapia ◽  
Principal Component ◽  
Essential Amino Acids ◽  
Amino Acid Profile ◽  
Nutritional Requirement ◽  
Dietary Amino Acids ◽  
The Relationship

The search for balanced diets, which may elicit improved growth of fish, requires appropriate selection of available protein sources. This study aims at clustering feedstuffs according to amino acid profile, determining which ones show essential amino acids (EAA) profiles closer to the ideal dietary amino acids requirements of Nile tilapia (Oreochromis niloticus), and studying the relationship among amino acids feedstuffs groups. Tabled data on EAA more cystine and tyrosine, in relation to lysine contents, of 40 feedstuffs ordinarily used to formulate fish diets were studied. Feedstuffs were grouped according to amino acids profile by cluster analysis of Euclidean distances. The principal components analysis was used to determine the relationship among amino acids in each feedstuff group. Three groups of ingredients were parted and two ingredients, low tannin sorghum and corn gluten meal 60%, did not go with any group. Dietary amino acids requirements of Nile tilapia were similar to the amino acid profile of 22 feedstuffs. The principal component analysis explained with three principal components more than 75% of total variance of amino acids in three feedstuff groups. Therefore, until additional, detailed information on amino acids availability of different ingredients is consolidated, total amino acids profiles will continue to be important information to select and use conventional or surrogate ingredients for formulating and processing feeds for tilapia.

Exploring the relationship between spatial morphology characteristics and scenic beauty preference of landscape open space unit by using point cloud data

2020 ◽  
pp. 239980832094988
Author(s):  
Yijing Wang ◽  
Sisi Zlatanova ◽  
Jinjin Yan ◽  
Ziqiao Huang ◽  
Yuning Cheng
Keyword(s):  
Principal Components ◽  
Point Cloud ◽  
Open Space ◽  
Multiple Linear Regression Model ◽  
Principal Component ◽  
Point Cloud Data ◽  
Cloud Data ◽  
Scenic Beauty ◽  
Relationship Analysis ◽  
The Relationship

To explore the relationship between the objective morphological features and subjective scenic beauty preference of landscape open space units, this study improves the research method for morphology quantification, scenic beauty preference survey and relationship analysis. Fourteen morphology factors representing the features of boundary, domain and enclosure are quantified based on the point cloud data of 35 open space units. Scenic beauty evaluation is conducted online with dynamic panoramic photos. Principal component analysis is implemented to convert 14 correlated form factors into five principal components representing morphological principle. The multiple linear regression model explains the contribution of each principal component to scenic beauty preference values, showing a significance sequence of penetration, scale, naturalness, complexity and rhythm. The first three principal components have positive impacts on scenic beauty preference, while the last two principal components are negative. This work aims to reveal the regularity of public’s scenic beauty preference for open space morphology.

scholarly journals Southwest monsoon rainfall in India : Part II - Principal components in temporal domain

MAUSAM ◽  
2021 ◽  
Vol 49 (3) ◽  
pp. 301-308
Author(s):  
A. B. MAZUMDAR
Keyword(s):  
Principal Components ◽  
Monsoon Rainfall ◽  
Principal Component ◽  
Southwest Monsoon ◽  
Temporal Domain ◽  
Synoptic Features ◽  
Southwest Monsoon Rainfall ◽  
Relationship Of ◽  
The Relationship ◽  
Low Pressure Systems

An attempt has been made towards objective identification of phases of the southwest monsoon by principal component analysis (PCA) in temporal domain (T-mode). The method utilizes the relationship of weekly rainfall activities with principal components (PCs) of southwest monsoon. Based on the relationships, subgroup of weeks with similar spatial patterns have been identified. Synoptic features of these subgroups have been brought out with the help of synoptic charts. The first four significant PCs are associated with four kinds of active phases of the southwest monsoon when the low pressure systems have typical characteristics corresponding to each PC. Thus, the study suggests a method of interpretation of PCs with the help of synoptic charts by objective identification of phases of southwest monsoon.

scholarly journals COVID-19 Data Imputation by Multiple Function-on-Function Principal Component Regression

Mathematics ◽  
2021 ◽  
Vol 9 (11) ◽  
pp. 1237
Author(s):  
Christian Acal ◽  
Manuel Escabias ◽  
Ana M. Aguilera ◽  
Mariano J. Valderrama
Keyword(s):  
Intensive Care ◽  
Principal Components ◽  
Missing Values ◽  
Principal Component Regression ◽  
Principal Component ◽  
Prediction Equation ◽  
Functional Responses ◽  
Principal Components Regression ◽  
Functional Principal Components ◽  
The Relationship

The aim of this paper is the imputation of missing data of COVID-19 hospitalized and intensive care curves in several Spanish regions. Taking into account that the curves of cases, deceases and recovered people are completely observed, a function-on-function regression model is proposed to estimate the missing values of the functional responses associated with hospitalized and intensive care curves. The estimation of the functional coefficient model in terms of principal components’ regression with the completely observed data provides a prediction equation for the imputation of the unobserved data for the response. An application with data from the first wave of COVID-19 in Spain is developed after properly homogenizing, registering and smoothing the data in a common interval so that the observed curves become comparable. Finally, Canonical Correlation Analysis is performed on the functional principal components to interpret the relationship between hospital occupancy rate and illness response variables.

What Does Human Development Index Rating Mean in Terms of Individualism/Collectivism?

2003 ◽  
Vol 8 (2) ◽  
pp. 97-100 ◽  
Author(s):  
Maria José Sotelo ◽  
Luis Gimeno
Keyword(s):  
Human Development ◽  
Human Development Index ◽  
Principal Component ◽  
General Idea ◽  
Development Index ◽  
Low Levels ◽  
The Relationship

The authors explore an alternative way of analyzing the relationship between human development and individualism. The method is based on the first principal component of Hofstede's individualism index in the Human Development Index rating domain. Results suggest that the general idea that greater wealth brings more individualism is only true for countries with high levels of development, while for middle or low levels of development the inverse is true.

Structuring Assessments of Psychopathology

2006 ◽  
Vol 27 (2) ◽  
pp. 87-92 ◽  
Author(s):  
Willem K.B. Hofstee ◽  
Dick P.H. Barelds ◽  
Jos M.F. Ten Berge
Keyword(s):  
Principal Components ◽  
Personality Assessment ◽  
Clinical Sample ◽  
Principal Component ◽  
Normal Sample ◽  
Normative Sample ◽  
Assessment Data ◽  
Obsessive Compulsive ◽  
Oblique Rotation ◽  
Two Samples

Hofstee and Ten Berge (2004a) have proposed a new look at personality assessment data, based on a bipolar proportional (-1, .. . 0, .. . +1) scale, a corresponding coefficient of raw-scores likeness L = ΢XY/N, and raw-scores principal component analysis. In a normal sample, the approach resulted in a structure dominated by a first principal component, according to which most people are faintly to mildly socially desirable. We hypothesized that a more differentiated structure would arise in a clinical sample. We analyzed the scores of 775 psychiatric clients on the 132 items of the Dutch Personality Questionnaire (NPV). In comparison to a normative sample (N = 3140), the eigenvalue for the first principal component appeared to be 1.7 times as small, indicating that such clients have less personality (social desirability) in common. Still, the match between the structures in the two samples was excellent after oblique rotation of the loadings. We applied the abridged m-dimensional circumplex design, by which persons are typed by their two highest scores on the principal components, to the scores on the first four principal components. We identified five types: Indignant (1-), Resilient (1-2+), Nervous (1-2-), Obsessive-Compulsive (1-3-), and Introverted (1-4-), covering 40% of the psychiatric sample. Some 26% of the individuals had negligible scores on all type vectors. We discuss the potential and the limitations of our approach in a clinical context.

Comparison of Principal Component Solutions in Two Populations

Methodology ◽  
2016 ◽  
Vol 12 (1) ◽  
pp. 11-20 ◽  
Author(s):  
Gregor Sočan
Keyword(s):  
Simulation Study ◽  
Principal Components ◽  
Common Factor ◽  
Principal Component ◽  
Component Model ◽  
Bootstrap Procedure ◽  
Factor Loadings ◽  
Component Loadings ◽  
Principal Component Model ◽  
Two Populations

Abstract. When principal component solutions are compared across two groups, a question arises whether the extracted components have the same interpretation in both populations. The problem can be approached by testing null hypotheses stating that the congruence coefficients between pairs of vectors of component loadings are equal to 1. Chan, Leung, Chan, Ho, and Yung (1999) proposed a bootstrap procedure for testing the hypothesis of perfect congruence between vectors of common factor loadings. We demonstrate that the procedure by Chan et al. is both theoretically and empirically inadequate for the application on principal components. We propose a modification of their procedure, which constructs the resampling space according to the characteristics of the principal component model. The results of a simulation study show satisfactory empirical properties of the modified procedure.

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