Evidence of parallel evolution in the dental elements of
            Sweetognathus
            conodonts

The repeated emergence of similar morphologies in the dental elements of Permian Sweetognathus conodonts has been a hypothesized example of parallel evolution. To test if morphological parallelisms occur between isolated Sweetognathus lineages, this study uses two-dimensional-based geometric morphometrics combined with a revised and expanded phylogeny of Permian Sweetognathus conodonts to quantify dental element trait distributions and compare the phenotypic trajectories between lineages. A hierarchical clustering method was used to identify recurrent species pairs based on principal component scores describing their morphological variation, with the further incorporation of widely used ecological metrics such as limiting similarity and morphological overlap. Our research implies that a major contributor to conodont diversity in Palaeozoic marine trophic networks is the emergence of recurrent parallel morphologies via disruptive and directional selection. This study illustrates the mechanisms through which conodonts achieved their status as hyper-diverse predators and scavengers, contributing substantially to the complexity of Palaeozoic marine communities.

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Using Principal Component Scores to Enhance the Validity and Reliability of Big Five Personality Measures

Journal of Individual Differences ◽

10.1027/1614-0001/a000225 ◽

2017 ◽

Vol 38 (2) ◽

pp. 83-93

Author(s):

Jeffrey M. Cucina ◽

Nicholas L. Vasilopoulos ◽

Arwen H. DeCostanza

Keyword(s):

Big Five ◽

Discriminant Validity ◽

Reliability And Validity ◽

Principal Component ◽

Big Five Personality ◽

Validity And Reliability ◽

Scoring Method ◽

Five Factors ◽

Big Five Factors ◽

Component Scores

Abstract. Varimax rotated principal component scores (VRPCS) have previously been offered as a possible solution to the non-orthogonality of scores for the Big Five factors. However, few researchers have examined the reliability and validity of VRPCS. To address this gap, we use a lab study and a field study to investigate whether using VRPCS increase orthogonality, reliability, and criterion-related validity. Compared to the traditional unit-weighting scoring method, the use of VRPCS enhanced the reliability and discriminant validity of the Big Five factors, although there was little improvement in criterion-related validity. Results are discussed in terms of the benefit of using VRPCS instead of traditional unit-weighted sum scores.

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Using principal component scores for Big Five personality measures

PsycEXTRA Dataset ◽

10.1037/e518422013-866 ◽

2009 ◽

Author(s):

Jeffrey M. Cucina ◽

Nicholas L. Vasilopoulos

Keyword(s):

Big Five ◽

Principal Component ◽

Big Five Personality ◽

Personality Measures ◽

Component Scores

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Multivariate Analysis, Genetic Diversity and Phenotypic Correlation of Nineteen Exotic Groundnut Accessions

Journal of AgriSearch ◽

10.21921/jas.v3i1.11400 ◽

2016 ◽

Vol 3 (1) ◽

Author(s):

YPJ AMARASINGHE ◽

G . WIJESINGHE ◽

R W PUSHPAKUMARA

Keyword(s):

Genetic Diversity ◽

Principal Component Analysis ◽

Growth Parameters ◽

Principal Component ◽

Phenotypic Correlation ◽

Clustering Method ◽

Yield Parameters ◽

Arachis Hypogaea L ◽

Semi Arid ◽

Number Of Branches

19 Groundnut ( Arachis hypogaea L. ) genotypes receiv ed from International Crops Research Institute for Semi Arid T ropics (ICRISA T) India w ere ev aluated in a non replicated trial and the characters w ere subjected to multiv ariate analysis to study the v ariability within the genotypes. The first 5 axes of the principal component analysis captured 78% of the total v ariability and identified yield parameters such as number of pods per plant, pod w eight per plant and growth parameters such as number of branches per plant, plant spread, and pod characteristics as the characters contributing most to total v ariation. Phenotypic correlation analysis rev ealed that the yield has positiv e correlation with the characters such as number of pods per plant and number of branches per plant. W ards clustering method has grouped the genotypes into 3 distinct clusters. The results can be applied in order to strengthen the breeding program

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Influences of Smoking in Traditional and Industrial Conditions on Flavour Profile of Harbin Red Sausages by Comprehensive Two-Dimensional Gas Chromatography Mass Spectrometry

Foods ◽

10.3390/foods10061180 ◽

2021 ◽

Vol 10 (6) ◽

pp. 1180

Author(s):

Xiaoyu Yin ◽

Qian Chen ◽

Qian Liu ◽

Yan Wang ◽

Baohua Kong

Keyword(s):

Mass Spectrometry ◽

Gas Chromatography ◽

Volatile Compounds ◽

Solid Phase ◽

Meat Products ◽

Principal Component ◽

Quality Characteristics ◽

Gas Chromatography Mass Spectrometry ◽

Two Dimensional ◽

Chromatography Mass Spectrometry

Smoking is mainly used to impart desirable flavour, colour and texture to the products. Various food smoking methods can be divided into traditional and industrial methods. The influences of three different smoking methods, including traditional smouldering smoke (TSS), industrial smouldering smoke (ISS) and industrial liquid smoke (ILS), on quality characteristics, sensory attributes and flavour profiles of Harbin red sausages were studied. The smoking methods had significant effects on the moisture content (55.74–61.72 g/100 g), L*-value (53.85–57.61), a*-value (11.97–13.15), b*-value (12.19–12.92), hardness (24.25–29.17 N) and chewiness (13.42–17.32). A total of 86 volatile compounds were identified by headspace solid phase microextraction combined with comprehensive two-dimensional gas chromatography mass spectrometry (GC × GC-qMS). Among them, phenolic compounds were the most abundant compounds in the all sausages. Compared with sausages smoked with smouldering smoke, the ILS sausages showed the highest content of volatile compounds, especially phenols, alcohols, aldehydes and ketones. Principal component analysis showed that the sausages smoked with different methods had a good separation based on the quality characteristics and GC × GC-qMS data. These results will facilitate optimising the smoking methods in the industrial production of smoked meat products.

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Multi-objective parametrization of interatomic potentials for large deformation pathways and fracture of two-dimensional materials

npj Computational Materials ◽

10.1038/s41524-021-00573-x ◽

2021 ◽

Vol 7 (1) ◽

Author(s):

Xu Zhang ◽

Hoang Nguyen ◽

Jeffrey T. Paci ◽

Subramanian K. R. S. Sankaranarayanan ◽

Jose L. Mendoza-Cortes ◽

...

Keyword(s):

Large Deformation ◽

Functional Form ◽

Principal Component ◽

Interatomic Potentials ◽

Two Dimensional ◽

Multi Objective ◽

Multi Objective Genetic Algorithm ◽

Two Dimensional Materials ◽

Definition Of

AbstractThis investigation presents a generally applicable framework for parameterizing interatomic potentials to accurately capture large deformation pathways. It incorporates a multi-objective genetic algorithm, training and screening property sets, and correlation and principal component analyses. The framework enables iterative definition of properties in the training and screening sets, guided by correlation relationships between properties, aiming to achieve optimal parametrizations for properties of interest. Specifically, the performance of increasingly complex potentials, Buckingham, Stillinger-Weber, Tersoff, and modified reactive empirical bond-order potentials are compared. Using MoSe2 as a case study, we demonstrate good reproducibility of training/screening properties and superior transferability. For MoSe2, the best performance is achieved using the Tersoff potential, which is ascribed to its apparent higher flexibility embedded in its functional form. These results should facilitate the selection and parametrization of interatomic potentials for exploring mechanical and phononic properties of a large library of two-dimensional and bulk materials.

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Spatial clustering analysis of green economy based on knowledge graph

Journal of Intelligent & Fuzzy Systems ◽

10.3233/jifs-219074 ◽

2021 ◽

pp. 1-10

Author(s):

Shiyuan Zhou ◽

Xiaoqin Yang ◽

Qianli Chang

Keyword(s):

Spatial Data ◽

Clustering Analysis ◽

Spatial Clustering ◽

Evaluation Model ◽

Principal Component ◽

Green Economy ◽

Membership Degree ◽

Two Dimensional ◽

Dimensional Graph ◽

Improved Algorithm

By organically combining principal component analysis, spatial autocorrelation algorithm and two-dimensional graph theory clustering algorithm, the comprehensive evaluation model of regional green economy is explored and established. Based on the evaluation index system of regional green economy, this paper evaluates the development of regional green economy comprehensively by using principal component analysis, and evaluates the competitive advantage of green economy and analyzes the spatial autocorrelation based on the evaluation results. Finally, the green economy and local index score as observed values, by using the method of two-dimensional graph clustering analysis of spatial clustering. In view of the fuzzy k –modes cluster membership degree measure method without considering the defects of the spatial distribution of object, double the distance and density measurement of measure method is introduced into the fuzzy algorithm of k –modes, thus in a more reasonable way to update the membership degree of the object. Vote, MUSH-ROOM and ZOO data sets in UCI machine learning library were used for testing, and the F value of the improved algorithm was better than that of the previous one, indicating that the improved algorithm had good clustering effect. Finally, the improved algorithm is applied to the spatial data collected from Baidu Map to cluster, and a good clustering result is obtained, which shows the feasibility and effectiveness of the algorithm applied to spatial data. Results show that the development of green economy using the analysis method of combining quantitative analysis and qualitative analysis, explores the connotation of green economy with space evaluation model is feasible, small make up for the qualitative analysis of the green economy in the past, can objective system to reflect the regional green economic development level, will help policy makers scientific formulating regional economic development strategy, green integrated development of regional green economy from the macroscopic Angle, the development of network system.

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