scholarly journals A New Method for Landmark-Based Studies of the Dynamic Stability of Growth, with Implications for Evolutionary Analyses

2021 ◽  
Author(s):  
Fred L. Bookstein
Keyword(s):  
Growth Regulation ◽  
Pattern Analysis ◽  
Developmental Time ◽  
Dynamical Stability ◽  
New Method ◽  
Data Sets ◽  
Data Set ◽  
Landmark Data ◽  
Study Designs ◽  
Changes Over Time

AbstractA matrix manipulation new to the quantitative study of develomental stability reveals unexpected morphometric patterns in a classic data set of landmark-based calvarial growth. There are implications for evolutionary studies. Among organismal biology’s fundamental postulates is the assumption that most aspects of any higher animal’s growth trajectories are dynamically stable, resilient against the types of small but functionally pertinent transient perturbations that may have originated in genotype, morphogenesis, or ecophenotypy. We need an operationalization of this axiom for landmark data sets arising from longitudinal data designs. The present paper introduces a multivariate approach toward that goal: a method for identification and interpretation of patterns of dynamical stability in longitudinally collected landmark data. The new method is based in an application of eigenanalysis unfamiliar to most organismal biologists: analysis of a covariance matrix of Boas coordinates (Procrustes coordinates without the size standardization) against their changes over time. These eigenanalyses may yield complex eigenvalues and eigenvectors (terms involving $$i=\sqrt{-1}$$ i = - 1 ); the paper carefully explains how these are to be scattered, gridded, and interpreted by their real and imaginary canonical vectors. For the Vilmann neurocranial octagons, the classic morphometric data set used as the running example here, there result new empirical findings that offer a pattern analysis of the ways perturbations of growth are attenuated or otherwise modified over the course of developmental time. The main finding, dominance of a generalized version of dynamical stability (negative autoregressions, as announced by the negative real parts of their eigenvalues, often combined with shearing and rotation in a helpful canonical plane), is surprising in its strength and consistency. A closing discussion explores some implications of this novel pattern analysis of growth regulation. It differs in many respects from the usual way covariance matrices are wielded in geometric morphometrics, differences relevant to a variety of study designs for comparisons of development across species.

scholarly journals Relationships between body reserve dynamics and rearing performances in meat ewes1

2019 ◽  
Vol 97 (10) ◽  
pp. 4076-4084
Author(s):  
Tiphaine Macé ◽  
Dominique Hazard ◽  
Fabien Carrière ◽  
Sebastien Douls ◽  
Didier Foulquié ◽  
...  
Keyword(s):  
Genetic Relationships ◽  
Genetic Correlations ◽  
Repeated Measurements ◽  
Production Cycle ◽  
Data Sets ◽  
Data Set ◽  
Litter Weight ◽  
Significant Relationships ◽  
Physiological Stage ◽  
Changes Over Time

Abstract The main objective of this work was to study the relationships between body reserve (BR) dynamics and rearing performance (PERF) traits in ewes from a Romane meat sheep flock managed extensively on “Causse” rangelands in the south of France. Flock records were used to generate data sets covering 14 lambing years (YR). The data set included 1,146 ewes with 2 ages of first lambing (AGE), 3 parities (PAR), and 4 litter sizes (LS). Repeated measurements of the BW and BCS were used as indicators of BR. The ewe PERF traits recorded were indirect measurements for maternal abilities and included prolificacy, litter weight and lamb BW at lambing and weaning, ADG at 1, 2, and 3 mo after lambing, and litter survival from lambing to weaning. The effects of different BW and BCS trajectories (e.g., changes in BW and BCS across the production cycle), previously been characterized in the same animals, on PERF traits were investigated. Such trajectories reflected different profiles at the intraflock level in the dynamics of BR mobilization–accretion cycles. Genetic relationships between BR and PERF traits were assessed. All the fixed variables considered (i.e., YR, AGE, PAR, LS, and SEX ratio of the litter) have significant effects on the PERF traits. Similarly, BW trajectories had an effect on the PERF traits across the 3 PARs studied, particularly during the first cycle (PAR 1). The BCS trajectories only affected prolificacy, lamb BW at birth, and litter survival. Most of the PERF traits considered here showed moderate heritabilities (0.17–0.23) except for prolificacy, the lamb growth rate during the third month and litter survival which showed very low heritabilities. With exception of litter survival and prolificacy, ewe PERF traits were genetically, strongly, and positively correlated with BW whatever the physiological stage. A few weak genetic correlations were found between BCS and PERF traits. As illustrated by BW and BCS changes over time, favorable genetic correlations were found, even if few and moderate, between BR accretion or mobilization and PERF traits, particularly for prolificacy and litter weight at birth. In conclusion, our results show significant relationships between BR dynamics and PERF traits in ewes, which could be considered in future sheep selection programs aiming to improve robustness.

scholarly journals Shape Dimensionality Metrics for Landmark Data

2020 ◽  
Author(s):  
F. Robin O’Keefe
Keyword(s):  
Permutation Test ◽  
Data Sets ◽  
Data Set ◽  
Geometric Morphometric ◽  
Current Test ◽  
Landmark Data ◽  
Measures Of Dispersion ◽  
Effective Dimensionality ◽  
Dire Wolf ◽  
Rancho La Brea

AbstractThe study of modularity in geometric morphometric landmark data has focused attention on an underlying question, that of whole-shape modularity, or the pattern and strength of covariation among all landmarks. Measuring whole-shape modularity allows measurement of the dimensionality of the shape, but current methods used to measure this dimensionality are limited in application. This paper proposes a metric for measuring the “effective dimensionality”, De, of geometric morphometric landmark data based on the Shannon entropy of the eigenvalue vector of the covariance matrix of GPA landmark data. A permutation test to establish null rank deficiency is developed to allow standardization for comparing dimensionality metrics between data sets, and a bootstrap test is employed for measures of dispersion. These novel methods are applied to a data set of 14 landmarks taken from 119 dire wolf jaws from Rancho La Brea. Comparison with the current test based on eigenvalue dispersion demonstrates that the new metric is more sensitive to detecting population differences in whole-shape modularity. The effective dimensionality metric is extended, in the dense semilandmark case, to a measure of “latent dimensionality”, Dl. Latent dimensionality should be comparable among landmark spaces, whether they are homologous or not.

scholarly journals A Probabilistic Procedure for Anonymisation, for Assessing the Risk of Re-identification and for the Analysis of Perturbed Data Sets

2020 ◽  
Vol 36 (1) ◽  
pp. 89-115 ◽  
Author(s):  
Harvey Goldstein ◽  
Natalie Shlomo
Keyword(s):  
Random Noise ◽  
Secondary Analysis ◽  
New Method ◽  
Parameter Estimates ◽  
Model Parameters ◽  
Data Sets ◽  
Data Set ◽  
Second Stage ◽  
True Model ◽  
Consistent Parameter

AbstractThe requirement to anonymise data sets that are to be released for secondary analysis should be balanced by the need to allow their analysis to provide efficient and consistent parameter estimates. The proposal in this article is to integrate the process of anonymisation and data analysis. The first stage uses the addition of random noise with known distributional properties to some or all variables in a released (already pseudonymised) data set, in which the values of some identifying and sensitive variables for data subjects of interest are also available to an external ‘attacker’ who wishes to identify those data subjects in order to interrogate their records in the data set. The second stage of the analysis consists of specifying the model of interest so that parameter estimation accounts for the added noise. Where the characteristics of the noise are made available to the analyst by the data provider, we propose a new method that allows a valid analysis. This is formally a measurement error model and we describe a Bayesian MCMC algorithm that recovers consistent estimates of the true model parameters. A new method for handling categorical data is presented. The article shows how an appropriate noise distribution can be determined.

Detection and treatment of twinning: an improvement and new results

1999 ◽  
Vol 55 (6) ◽  
pp. 1179-1187 ◽  
Author(s):  
P. Dumas ◽  
E. Ennifar ◽  
P. Walter
Keyword(s):  
Correlation Coefficients ◽  
Initiation Site ◽  
Accurate Estimate ◽  
New Method ◽  
Data Sets ◽  
Additional Parameter ◽  
Data Set ◽  
Space Groups ◽  
Experimental Errors ◽  
Dimerization Initiation Site

This work deals with two aspects of the twinning problem. Firstly, an improvement of a known statistical test aimed at detecting twinning is presented and, secondly, a new parametrization of twinning is described, as well as a new method to obtain an accurate estimate of the degreee of twinning. During work on crystals of the dimerization-initiation site of the HIV-1 genomic RNA, perfectly twinned crystals were obtained which were not immediately recognized as such by use of a known statistical method. This method, reminiscent of Wilson tests for the detection of centrosymmetric space groups, relies on the calculation of 〈F^{2}〉/〈F〉2 or, equivalently, of 〈I 2〉/〈I〉2. It is shown that overlooking experimental errors may lead to erroneously large values of this index and, in turn, to ambiguous or incorrect conclusions. An immediate solution to this problem is presented. Independently, an alternative parametrization which expresses both the effect of twinning on intensities and the operation of untwinning to recover the correct intensities is proposed. A new method for estimating the degree of twinning is also presented. It is based upon maximization of the cross-correlation coefficients between intensities of all available data sets, and yields a fully analytical solution. Tests made with experimental data are quite satisfactory. It is suggested that the latter results could be used efficiently within the MIR method by allowing refinement, through one additional parameter only, of the twinning ratios of all data sets considered for phasing. Finally, the new parametrization of twinning has striking consequences in this correlation-based twinning determination: very unexpectedly, it yields a novel estimate of the `twinning ratio' of a potentially twinned crystal which is fully independent of the data set used for the comparison.

scholarly journals How is �hearing loss� and �hearing aid(s)� represented in the United States newspaper media? (Preprint)

2018 ◽  
Author(s):  
Vinaya Manchaiah ◽  
Pierre Ratinaud ◽  
Eldre Beukes
Keyword(s):  
United States ◽  
Cluster Analysis ◽  
Hearing Loss ◽  
Research And Development ◽  
Pattern Analysis ◽  
Hearing Aid ◽  
Data Sets ◽  
Data Set ◽  
Loss Data ◽  
The U.S

BACKGROUND News media plays an important role in formulating peoples knowledge and opinions about various aspects including health. OBJECTIVE The current study explored how “hearing loss” and “hearing aid(s)” are represented in United States newspaper media. METHODS A cross-sectional study design was selected to analyze publicly available newspaper media data. The data sets were generated from the database, the U.S. Major Dailies by ProQuest by searching the key words for newspapers published during 1990-2017. Cluster analysis (i.e., text pattern analysis) and Chi square tests were performed using Iramuteq software. RESULTS The hearing loss data set had 1,527 texts (i.e., articles). The cluster analysis resulted in seven clusters, which were named as: (1) causes and consequences (26.1%); (2) early identification and diagnosis (9%); (3) health promotion and prevention (22.1%); (4) recreational noise exposure (10.4%); (5) prevalence (14.3%); (6) research and development (12.4%); and (7) cognitive hearing science (5.6%). The hearing aid(s) data set had 2,667 texts. The cluster analysis resulted in eight clusters, which were named as: (1) signal processing (20.2%); (2) insurance (8.9%); (3) prevalence (12.4%); (4) research and development (5.4%); (5) activities and relation (16.2%); (6) environment (13.8%); (7) innovation (12%); and (8) wireless and connectivity (11.1%). Time series analysis of clusters in both “hearing loss” and “hearing aid(s)” data sets indicated that the change in pattern of information presented in newspaper media during 1990-2016 (e.g., cluster 7 focusing on cognitive hearing science in hearing loss data set emerging only since the year 2012 and growing rapidly). CONCLUSIONS The text pattern analysis showed that the U.S. newspaper media focuses on a range of issues when considering “hearing loss” and “hearing aid(s),” and the pattern or trends change over time. The study results can be helpful for hearing healthcare professionals to understand what presuppositions society in general may have as the media has the ability to influence societal perception and opinions.

scholarly journals Reevaluation of stratospheric ozone trends from SAGE II data using a simultaneous temporal and spatial analysis

2014 ◽  
Vol 14 (12) ◽  
pp. 17681-17725 ◽  
Author(s):  
R. P. Damadeo ◽  
J. M. Zawodny ◽  
L. W. Thomason
Keyword(s):  
Spatial Analysis ◽  
Stratospheric Ozone ◽  
Recovery Period ◽  
Stratospheric Aerosol ◽  
New Method ◽  
Data Sets ◽  
Sampled Data ◽  
Data Set ◽  
Multiple Data Sets ◽  
Temporal And Spatial

Abstract. This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for any potential diurnal variation. Results show declines in ozone similar to other studies but very different trends in the recovery period. The regression model allows for a variable turnaround time and reveals a~hemispheric asymmetry in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

scholarly journals Reevaluation of stratospheric ozone trends from SAGE II data using a simultaneous temporal and spatial analysis

2014 ◽  
Vol 14 (24) ◽  
pp. 13455-13470 ◽  
Author(s):  
R. P. Damadeo ◽  
J. M. Zawodny ◽  
L. W. Thomason
Keyword(s):  
Spatial Analysis ◽  
Stratospheric Ozone ◽  
Recovery Period ◽  
New Method ◽  
Data Sets ◽  
Sampled Data ◽  
Data Set ◽  
Multiple Data Sets ◽  
Temporal And Spatial

Abstract. This paper details a new method of regression for sparsely sampled data sets for use with time-series analysis, in particular the Stratospheric Aerosol and Gas Experiment (SAGE) II ozone data set. Non-uniform spatial, temporal, and diurnal sampling present in the data set result in biased values for the long-term trend if not accounted for. This new method is performed close to the native resolution of measurements and is a simultaneous temporal and spatial analysis that accounts for potential diurnal ozone variation. Results show biases, introduced by the way data are prepared for use with traditional methods, can be as high as 10%. Derived long-term changes show declines in ozone similar to other studies but very different trends in the presumed recovery period, with differences up to 2% per decade. The regression model allows for a variable turnaround time and reveals a hemispheric asymmetry in derived trends in the middle to upper stratosphere. Similar methodology is also applied to SAGE II aerosol optical depth data to create a new volcanic proxy that covers the SAGE II mission period. Ultimately this technique may be extensible towards the inclusion of multiple data sets without the need for homogenization.

The social wasp Vespula germanica (Fabricius) (Hymenoptera: Vespidae) population dynamics in England over 39 years.

2018 ◽  
Vol 154 (2) ◽  
pp. 149-155
Author(s):  
Michael Archer
Keyword(s):  
Population Dynamics ◽  
Population Dynamic ◽  
Ecological Factors ◽  
Social Wasp ◽  
Data Sets ◽  
Data Set ◽  
Vespula Germanica ◽  
The Social ◽  
Minimum Number ◽  
Suction Traps

1. Yearly records of worker Vespula germanica (Fabricius) taken in suction traps at Silwood Park (28 years) and at Rothamsted Research (39 years) are examined. 2. Using the autocorrelation function (ACF), a significant negative 1-year lag followed by a lesser non-significant positive 2-year lag was found in all, or parts of, each data set, indicating an underlying population dynamic of a 2-year cycle with a damped waveform. 3. The minimum number of years before the 2-year cycle with damped waveform was shown varied between 17 and 26, or was not found in some data sets. 4. Ecological factors delaying or preventing the occurrence of the 2-year cycle are considered.

A New Approach for the Analysis of Mixture Toxicity Data

1992 ◽  
Vol 26 (9-11) ◽  
pp. 2345-2348 ◽  
Author(s):  
C. N. Haas
Keyword(s):  
Quantitative Analysis ◽  
Mixture Toxicity ◽  
New Method ◽  
Metal Exposure ◽  
Positive Interactions ◽  
Toxicity Data ◽  
Data Set ◽  
New Approach ◽  
Negative Interactions

A new method for the quantitative analysis of multiple toxicity data is described and illustrated using a data set on metal exposure to copepods. Positive interactions are observed for Ni-Pb and Pb-Cr, with weak negative interactions observed for Ni-Cr.

Predictive and Descriptive CoMFA Models: The Effect of Variable Selection

2018 ◽  
Vol 21 (2) ◽  
pp. 117-124 ◽  
Author(s):  
Bakhtyar Sepehri ◽  
Nematollah Omidikia ◽  
Mohsen Kompany-Zareh ◽  
Raouf Ghavami
Keyword(s):  
Variable Selection ◽  
Predictive Power ◽  
Selection Method ◽  
Data Sets ◽  
Data Set ◽  
Comfa Model ◽  
Variable Selection Method

Aims & Scope: In this research, 8 variable selection approaches were used to investigate the effect of variable selection on the predictive power and stability of CoMFA models. Materials & Methods: Three data sets including 36 EPAC antagonists, 79 CD38 inhibitors and 57 ATAD2 bromodomain inhibitors were modelled by CoMFA. First of all, for all three data sets, CoMFA models with all CoMFA descriptors were created then by applying each variable selection method a new CoMFA model was developed so for each data set, 9 CoMFA models were built. Obtained results show noisy and uninformative variables affect CoMFA results. Based on created models, applying 5 variable selection approaches including FFD, SRD-FFD, IVE-PLS, SRD-UVEPLS and SPA-jackknife increases the predictive power and stability of CoMFA models significantly. Result & Conclusion: Among them, SPA-jackknife removes most of the variables while FFD retains most of them. FFD and IVE-PLS are time consuming process while SRD-FFD and SRD-UVE-PLS run need to few seconds. Also applying FFD, SRD-FFD, IVE-PLS, SRD-UVE-PLS protect CoMFA countor maps information for both fields.

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