scholarly journals Isolation-By-Distance-and-Time in a stepping-stone model

2015 ◽  
Author(s):  
Nicolas Duforet-Frebourg ◽  
Montgomery Slatkin
Keyword(s):  
Principal Component Analysis ◽  
Population Genetics ◽  
Population Structure ◽  
Isolation By Distance ◽  
Principal Component ◽  
Joint Effect ◽  
Stepping Stone ◽  
Ancient Times ◽  
The Impact ◽  
Stepping Stone Model

With the great advances in ancient DNA extraction, population genetics data are now made of geographically separated individuals from both present and ancient times. However, population genetics theory about the joint effect of space and time has not been thoroughly studied. Based on the classical stepping--stone model, we develop the theory of Isolation by Distance and Time. We derive the correlation of allele frequencies between demes in the case where ancient samples are present in the data, and investigate the impact of edge effects with forward-in-time simulations. We also derive results about coalescent times in circular/toroidal models. As one of the most common way to investigate population structure is to apply principal component analysis, we evaluate the impact of this theory on plots of principal components. Our results demonstrate that time between samples is a non-negligible factor that requires new attention in population genetics.

Evaluation of the Aging Behavior of High Density Polyethylene in Thermal Oxidative Environment by Principal Component Analysis

2017 ◽  
Vol 727 ◽  
pp. 447-449 ◽  
Author(s):  
Jun Dai ◽  
Hua Yan ◽  
Jian Jian Yang ◽  
Jun Jun Guo
Keyword(s):  
Principal Component Analysis ◽  
Impact Strength ◽  
High Density Polyethylene ◽  
Tensile Modulus ◽  
Principal Component ◽  
Component Analysis ◽  
High Density ◽  
Aging Behavior ◽  
Data Set ◽  
The Impact

To evaluate the aging behavior of high density polyethylene (HDPE) under an artificial accelerated environment, principal component analysis (PCA) was used to establish a non-dimensional expression Z from a data set of multiple degradation parameters of HDPE. In this study, HDPE samples were exposed to the accelerated thermal oxidative environment for different time intervals up to 64 days. The results showed that the combined evaluating parameter Z was characterized by three-stage changes. The combined evaluating parameter Z increased quickly in the first 16 days of exposure and then leveled off. After 40 days, it began to increase again. Among the 10 degradation parameters, branching degree, carbonyl index and hydroxyl index are strongly associated. The tensile modulus is highly correlated with the impact strength. The tensile strength, tensile modulus and impact strength are negatively correlated with the crystallinity.

scholarly journals Simulasi Metode Statistik untuk Seleksi Single Nucleotide Polymorphism pada Populasi Plasmodium

Life Science ◽  
2019 ◽  
Vol 8 (1) ◽  
pp. 54-64
Author(s):  
Mohamad Ikhsan Nurulloh ◽  
Yustinus Ulung Anggraito ◽  
Hidayat Trimarsanto ◽  
Endah Peniati ◽  
R. Susanti
Keyword(s):  
Principal Component Analysis ◽  
Single Nucleotide Polymorphism ◽  
Population Structure ◽  
Principal Component ◽  
Selection Method ◽  
Principal Coordinate Analysis ◽  
Neighbor Joining ◽  
Nucleotide Polymorphism ◽  
Single Nucleotide ◽  
Informative Snps

Plasmodium is a pathogen that causes malaria which has high genetic diversity and resistance to antimalarial drugs. Information on the population structure of Plasmodium can be used as molecular markers, one of which is Single Nucleotide Polymorphism (SNP). SNP markers are in large numbers and not entirely informative. The existing method has not been effective in producing informative SNPs, therefore it is necessary to develop an effective SNP selection method. The SNP selection method is developed using FST as the main filter (filter) and combines Linkage Disequilibrium (LD). The population structure of the SNP is known to use Principal Component Analysis (PCA), Principal Coordinate Analysis (PCoA), pairwise FST, and neighbor-joining population trees. Informative SNP criteria known by calculating FST and Minor Allele Frequency (MAF). Statistical methods were tested to determine their effectiveness in producing informative SNPs. The method testing was carried out using genetic data simulation of the Plasmodium population. The results of the study show that the statistical method is effective in producing informative SNPs. The informative SNP criteria are SNPs with MAF 0.2-0.4 and FST 0.1-0.4 and 0.8-1.0.   Plasmodium merupakan patogen penyebab malaria dengan keanekaragaman genetik tinggi dan memiliki resistensi terhadap obat antimalaria. Informasi sturuktur populasi Plasmodium dapat dimanfaatkan sebagai marka molekuler seperti Single Nucleotide Polymorphism (SNP). Marka SNP terdapat dalam jumlah yang banyak dan tidak seluruhnya informatif. Metode yang telah ada belum efektif dalam menghasilkan SNP informatif sehingga perlu dilakukan pengembangan metode seleksi SNP yang efektif. Metode seleksi SNP dikembangkan menggunakan FST sebagai filter (penyaring) utamanya dan gabungkan Linkage Disequilibrium (LD). Struktur populasi dari SNP diketahui menggunakan Principal Component Analysis (PCA), Principal Coordinate Analysis (PCoA), pairwise FST, dan neighbor-joining population tree. Kriteria SNP informatif yang diketahui dengan menghitung FST dan Minor Allele Frequency (MAF). Metode statistika diuji untuk mengetahui keefektifannya dalam menghasilkan SNP informatif. Pengujian metode dilakukan menggunakan simulasi data genetik populasi Plasmodium. Hasil penelitian menunjukkan metode statistika efektif dalam menghasilkan SNP informatif. Kriteria SNP informatif adalah SNP dengan MAF 0.2-0.4 serta FST 0.1-0.4 dan 0.8-1.0.

Remote communication in Scrum teams – a COVID-19 preventive measure or work time optimisation?

e-mentor ◽  
2021 ◽  
Vol 92 (5) ◽  
pp. 81-90
Author(s):  
Kamil Brodnicki ◽  
Keyword(s):  
Principal Component Analysis ◽  
Cluster Analysis ◽  
Principal Component ◽  
Preventive Measure ◽  
Remote Work ◽  
Remote Communication ◽  
Work Time ◽  
Research Material ◽  
And Cluster Analysis ◽  
The Impact

The article presents the impact of remote work, resulting from the COVID-19 pandemic, on the functioning of Scrum teams. Attempts have been made to analyse the positive and negative aspects of remote work. The article also looks at the impact of remote work on the level of communication and efficiency of Scrum teams. For this purpose, the author conducted research on a sample of 40 organisations that declared to use Scrum methodology, using 187 questionnaires as the research material. The study was carried out at the turn of April and May 2021 and was carried out using the CAWI technique. The obtained results were analysed using the Principal Component Analysis and Cluster Analysis methods, and enable defining a picture of an organisation’s readiness to work remotely. In addition, they also allowed for an assessment of how the infrastructure used for remote work communication translates into the organisation of Sprint meetings. This paper presents conclusions aimed at counteracting the observed irregularities detected during the tests. At the end, the author proposes solutions that could improve communication within Scrum teams, with remote work in mind.

Reply to the comment by Morales et al. on “Population genetics reveal Myotis keenii (Keen’s myotis) and Myotis evotis (long-eared myotis) to be a single species”

2021 ◽  
pp. 423-432
Author(s):  
C.L. Lausen ◽  
Michael F. Proctor ◽  
David Paetkau ◽  
David W. Nagorsen ◽  
Purnima Govindarajulu ◽  
...  
Keyword(s):  
Population Genetics ◽  
Population Structure ◽  
Single Species ◽  
Distinct Species ◽  
Background Information ◽  
Distribution Data ◽  
Supporting Evidence ◽  
Post Mortem ◽  
The Impact ◽  
New Evidence

A.E. Morales et al. (2021. Can. J. Zool. 99(5): 415–422) provided no new evidence to alter the conclusions of C.L. Lausen et al. (2019. Can. J. Zool. 97(3): 267–279). We present background information, relevant comparisons, and clarification of analyses to further strengthen our conclusions. The genesis of the original “evotis–keenii” study in British Columbia (Canada) was to differentiate Myotis keenii (Merriam, 1895) (Keen’s myotis), with one of the smallest North American bat distributions, from sympatric Myotis evotis (H. Allen, 1864) (long-eared myotis), using something other than the suggested post-mortem skull size comparison, but no differentiating trait could be found, leading to the molecular genetics examination of C.L. Lausen et al. (2019). We present cumulative data that rejects the 1979 hypothesis of M. keenii as a distinct species. A.E. Morales et al. (2021) inaccurately portray C.L. Lausen et al.’s (2019) question and results; present inaccurate morphological and outdated distribution data; overstate the impact of homoplasy without supporting evidence; and misinterpret evidence of population structure.

scholarly journals Hydrodynamic and frictional modulation of deformations in switchable colloidal crystallites

2020 ◽  
Vol 117 (23) ◽  
pp. 12700-12706
Author(s):  
Young Ki Lee ◽  
Xiaoguai Li ◽  
Paris Perdikaris ◽  
John C. Crocker ◽  
Celia Reina ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Diffusion Coefficients ◽  
Particle Shape ◽  
Colloidal Crystals ◽  
Principal Component ◽  
Nucleation And Growth ◽  
Spherically Symmetric ◽  
Dynamical Models ◽  
Micrometer Scale ◽  
The Impact

Displacive transformations in colloidal crystals may offer a pathway for increasing the diversity of accessible configurations without the need to engineer particle shape or interaction complexity. To date, binary crystals composed of spherically symmetric particles at specific size ratios have been formed that exhibit floppiness and facile routes for transformation into more rigid structures that are otherwise not accessible by direct nucleation and growth. There is evidence that such transformations, at least at the micrometer scale, are kinetically influenced by concomitant solvent motion that effectively induces hydrodynamic correlations between particles. Here, we study quantitatively the impact of such interactions on the transformation of binary bcc-CsCl analog crystals into close-packed configurations. We first employ principal-component analysis to stratify the explorations of a bcc-CsCl crystallite into orthogonal directions according to displacement. We then compute diffusion coefficients along the different directions using several dynamical models and find that hydrodynamic correlations, depending on their range, can either enhance or dampen collective particle motions. These two distinct effects work synergistically to bias crystallite deformations toward a subset of the available outcomes.

Stepping stone models of finite length

1970 ◽  
Vol 2 (02) ◽  
pp. 229-258 ◽  
Author(s):  
Takeo Maruyama
Keyword(s):  
Monte Carlo ◽  
Population Structure ◽  
Finite Length ◽  
Correlation Coefficients ◽  
Gene Frequencies ◽  
Explicit Formulas ◽  
Stepping Stone ◽  
Monte Carlo Experiments ◽  
Stepping Stone Models ◽  
Stepping Stone Model

The stepping stone model of population structure, of finite length, is analysed with special reference to the variance, and correlation coefficients of gene frequencies. Explicit formulas for these quantities are obtained. The model is also analysed for the genetic variability maintained in the population. In order to check the validity of the analytical results, several numerical computations were carried out using two different methods: iterations and Monte Carlo experiments. The values obtained by these numerical methods agree well with the theoretical values obtained by formulas derived analytically.

Reconceptualizing Church and State: A Theoretical and Empirical Analysis of the Impact of Separation of Religion and State on Democracy

2011 ◽  
Vol 4 (2) ◽  
pp. 229-263 ◽  
Author(s):  
Robert Brathwaite ◽  
Andrew Bramsen
Keyword(s):  
Principal Component Analysis ◽  
Empirical Analysis ◽  
Church And State ◽  
Principal Component ◽  
Set Covering ◽  
Data Set ◽  
Religion And State ◽  
The Impact ◽  
The Relationship ◽  
State Separation

AbstractThis article argues that the relationship between democracy and the separation of religion and state needs to be reexamined. We argue that previous studies have misconceptualized the impact that a lack of church-state separation can have on democracy, or have taken a narrow focus by concentrating on specific cases. We use principal component analysis and a large-ndata set covering 125 countries to show that the separation of religion and state should be conceptualized multi-dimensionally and that it should be considered a component of democracy. Our findings show that as separation of religion and state increases, the level of democracy also increases.

scholarly journals Board of directors, capital structure, investment decisions and firm-performance: An empirical study of Nordic firms

2020 ◽  
Vol 17 (4, Special Issue) ◽  
pp. 377-390
Author(s):  
Shab Hundal ◽  
Anne Eskola
Keyword(s):  
Principal Component Analysis ◽  
Corporate Governance ◽  
Firm Performance ◽  
Capital Structure ◽  
Corporate Finance ◽  
Board Of Directors ◽  
Boards Of Directors ◽  
Investment Decisions ◽  
Principal Component ◽  
The Impact

Firms’ financing, boards of directors’ characteristics, investments, and firm-performance (financial and non-financial) occupy a pivotal place in corporate finance and corporate governance literature. The current study explores if causalities between the abovementioned four distinct albeit inter-related phenomena follow any pattern. The data comprising of 1240 firm-years belonging to Finland, Norway, Sweden, and Denmark for the period of 2003 to 2018 have been analyzed by applying multivariate linear regression and principal component analysis. The findings show that the impact of boards of directors’ characteristics is stronger on capital structure, however, weaker on investments and financial performance. The major contribution of the article is creating a set orderly and sequential causalities between financing, boards of directors’ characteristics, investments, and firm-performance.

scholarly journals Analysis of 46,046 SARS-CoV-2 whole-genomes leveraging principal component analysis (PCA)

2020 ◽  
Author(s):  
Christiane Scherer ◽  
James Grover ◽  
Darby Kammeraad ◽  
Gabe Rudy ◽  
Andreas Scherer
Keyword(s):  
Principal Component Analysis ◽  
Population Genetics ◽  
Phylogenetic Analysis ◽  
Principal Component ◽  
Large Data ◽  
Component Analysis ◽  
Comprehensive Analysis ◽  
Large Data Sets ◽  
Data Sets ◽  
Whole Genomes

AbstractSince the beginning of the global SARS-CoV-2 pandemic, there have been a number of efforts to understand the mutations and clusters of genetic lines of the SARS-CoV-2 virus. Until now, phylogenetic analysis methods have been used for this purpose. Here we show that Principal Component Analysis (PCA), which is widely used in population genetics, can not only help us to understand existing findings about the mutation processes of the virus, but can also provide even deeper insights into these processes while being less sensitive to sequencing gaps. Here we describe a comprehensive analysis of a 46,046 SARS-CoV-2 genome sequence dataset downloaded from the GISAID database in June of this year.SummaryPCA provides deep insights into the analysis of large data sets of SARS-CoV-2 genomes, revealing virus lineages that have thus far been unnoticed.

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