Compact Multiview Representation of Documents Based on the Total Variability Space

AbstractLavas erupted at hotspot volcanoes provide evidence of mantle heterogeneity. Samoan Island lavas with high 87Sr/86Sr (>0.706) typify a mantle source incorporating ancient subducted sediments. To further characterize this source, we target a single high 87Sr/86Sr lava from Savai’i Island, Samoa for detailed analyses of 87Sr/86Sr and 143Nd/144Nd isotopes and major and trace elements on individual magmatic clinopyroxenes. We show the clinopyroxenes exhibit a remarkable range of 87Sr/86Sr—including the highest observed in an oceanic hotspot lava—encompassing ~30% of the oceanic mantle’s total variability. These new isotopic data, data from other Samoan lavas, and magma mixing calculations are consistent with clinopyroxene 87Sr/86Sr variability resulting from magma mixing between a high silica, high 87Sr/86Sr (up to 0.7316) magma, and a low silica, low 87Sr/86Sr magma. Results provide insight into the composition of magmas derived from a sediment-infiltrated mantle source and document the fate of sediment recycled into Earth’s mantle.

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Automatic 3D dense phenotyping provides reliable and accurate shape quantification of the human mandible

Scientific Reports ◽

10.1038/s41598-021-88095-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Pieter-Jan Verhelst ◽

H. Matthews ◽

L. Verstraete ◽

F. Van der Cruyssen ◽

D. Mulier ◽

...

Keyword(s):

Repeated Measures ◽

Intraclass Correlation ◽

Three Dimensional ◽

Correlation Coefficients ◽

Surface Registration ◽

Anatomical Landmarks ◽

Centroid Size ◽

Intraclass Correlation Coefficients ◽

Total Variability ◽

Automatic Phenotyping

AbstractAutomatic craniomaxillofacial (CMF) three dimensional (3D) dense phenotyping promises quantification of the complete CMF shape compared to the limiting use of sparse landmarks in classical phenotyping. This study assesses the accuracy and reliability of this new approach on the human mandible. Classic and automatic phenotyping techniques were applied on 30 unaltered and 20 operated human mandibles. Seven observers indicated 26 anatomical landmarks on each mandible three times. All mandibles were subjected to three rounds of automatic phenotyping using Meshmonk. The toolbox performed non-rigid surface registration of a template mandibular mesh consisting of 17,415 quasi landmarks on each target mandible and the quasi landmarks corresponding to the 26 anatomical locations of interest were identified. Repeated-measures reliability was assessed using root mean square (RMS) distances of repeated landmark indications to their centroid. Automatic phenotyping showed very low RMS distances confirming excellent repeated-measures reliability. The average Euclidean distance between manual and corresponding automatic landmarks was 1.40 mm for the unaltered and 1.76 mm for the operated sample. Centroid sizes from the automatic and manual shape configurations were highly similar with intraclass correlation coefficients (ICC) of > 0.99. Reproducibility coefficients for centroid size were < 2 mm, accounting for < 1% of the total variability of the centroid size of the mandibles in this sample. ICC’s for the multivariate set of 325 interlandmark distances were all > 0.90 indicating again high similarity between shapes quantified by classic or automatic phenotyping. Combined, these findings established high accuracy and repeated-measures reliability of the automatic approach. 3D dense CMF phenotyping of the human mandible using the Meshmonk toolbox introduces a novel improvement in quantifying CMF shape.

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The Fear of COVID-19 Scale: A Reliability Generalization Meta-Analysis

Assessment ◽

10.1177/1073191121994164 ◽

2021 ◽

pp. 107319112199416

Author(s):

Desirée Blázquez-Rincón ◽

Juan I. Durán ◽

Juan Botella

Keyword(s):

Predictive Model ◽

Meta Analysis ◽

Classical Test Theory ◽

Measurement Model ◽

Rasch Measurement ◽

Test Theory ◽

Reliability Estimate ◽

Reliability Generalization ◽

Reliability Estimates ◽

Total Variability

A reliability generalization meta-analysis was carried out to estimate the average reliability of the seven-item, 5-point Likert-type Fear of COVID-19 Scale (FCV-19S), one of the most widespread scales developed around the COVID-19 pandemic. Different reliability coefficients from classical test theory and the Rasch Measurement Model were meta-analyzed, heterogeneity among the most reported reliability estimates was examined by searching for moderators, and a predictive model to estimate the expected reliability was proposed. At least one reliability estimate was available for a total of 44 independent samples out of 42 studies, being that Cronbach’s alpha was most frequently reported. The coefficients exhibited pooled estimates ranging from .85 to .90. The moderator analyses led to a predictive model in which the standard deviation of scores explained 36.7% of the total variability among alpha coefficients. The FCV-19S has been shown to be consistently reliable regardless of the moderator variables examined.

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Genetic diversity of Avena strigosa Schreb. ecotypes on the basis of isoenzyme markers

Biodiversity Research and Conservation ◽

10.2478/v10119-009-0013-3 ◽

2009 ◽

Vol 15 (1) ◽

pp. 23-28 ◽

Cited By ~ 4

Author(s):

Katarzyna Kubiak

Keyword(s):

Genetic Diversity ◽

Genetic Similarity ◽

Avena Strigosa ◽

Total Genetic Diversity ◽

Geographical Regions ◽

The World ◽

Total Variability ◽

The Mean ◽

Intrapopulation Diversity ◽

Very High

Genetic diversity ofAvena strigosaSchreb. ecotypes on the basis of isoenzyme markersGenetic diversity was analyzed in 19 ecotypes of the diploid oatA. strigosaoriginating from various geographical regions of the world. Six isoenzyme systems (AAT, ACP, EST, LAP, MDH, PX) were studied and 16 loci were identified. Only two loci (Est4andMdh2) were polymorphic. Ecotypes were characterized by the percentage of polymorphic loci (P=3.3%), the mean number of alleles per locus (A=1.04) and intrapopulation diversity (HS=0.013). Total genetic diversity (HT=0.07) and interpopulation diversity (DST=0.057) were examined as well. The value of the coefficient of gene differentiation (GST=0.821) indicated that diversity among populations was an important contributor to total variability. Genetic similarity betweenA. strigosapopulations was very high (IN=0.94). Cluster analysis did not demonstrate strongly differentiated groups among the ecotypes examined.

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Unraveling city-specific signature and identifying sample origin locations for the data from CAMDA MetaSUB challenge

Biology Direct ◽

10.1186/s13062-020-00284-1 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Runzhi Zhang ◽

Alejandro R. Walker ◽

Susmita Datta

Keyword(s):

Machine Learning ◽

Error Rates ◽

Average Error ◽

Importance Score ◽

Learning Methods ◽

Principal Coordinates Analysis ◽

Principal Coordinates ◽

Total Variability ◽

The Common ◽

Feature Selecting

Abstract Background Composition of microbial communities can be location-specific, and the different abundance of taxon within location could help us to unravel city-specific signature and predict the sample origin locations accurately. In this study, the whole genome shotgun (WGS) metagenomics data from samples across 16 cities around the world and samples from another 8 cities were provided as the main and mystery datasets respectively as the part of the CAMDA 2019 MetaSUB “Forensic Challenge”. The feature selecting, normalization, three methods of machine learning, PCoA (Principal Coordinates Analysis) and ANCOM (Analysis of composition of microbiomes) were conducted for both the main and mystery datasets. Results Features selecting, combined with the machines learning methods, revealed that the combination of the common features was effective for predicting the origin of the samples. The average error rates of 11.93 and 30.37% of three machine learning methods were obtained for main and mystery datasets respectively. Using the samples from main dataset to predict the labels of samples from mystery dataset, nearly 89.98% of the test samples could be correctly labeled as “mystery” samples. PCoA showed that nearly 60% of the total variability of the data could be explained by the first two PCoA axes. Although many cities overlapped, the separation of some cities was found in PCoA. The results of ANCOM, combined with importance score from the Random Forest, indicated that the common “family”, “order” of the main-dataset and the common “order” of the mystery dataset provided the most efficient information for prediction respectively. Conclusions The results of the classification suggested that the composition of the microbiomes was distinctive across the cities, which could be used to identify the sample origins. This was also supported by the results from ANCOM and importance score from the RF. In addition, the accuracy of the prediction could be improved by more samples and better sequencing depth.

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UBM fused total variability modeling for language identification

10.21437/interspeech.2014-607 ◽

2014 ◽

Author(s):

Maarten van Segbroeck ◽

Ruchir Travadi ◽

Shrikanth S. Narayanan

Keyword(s):

Language Identification ◽

Variability Modeling ◽

Total Variability

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Methanogenesis in freshwater sediments: inherent variability and effects of environmental contaminants

Canadian Journal of Microbiology ◽

10.1139/m81-031 ◽

1981 ◽

Vol 27 (2) ◽

pp. 198-205 ◽

Cited By ~ 18

Author(s):

D. Pedersen ◽

G. S. Sayler

Keyword(s):

Relative Concentration ◽

Environmental Contaminants ◽

Significant Inhibition ◽

Freshwater Sediments ◽

Temporal And Spatial Variation ◽

Temporal And Spatial Variability ◽

Total Variability ◽

Temporal And Spatial ◽

High Concentrations ◽

Freshwater Reservoir

Temporal and spatial variability of methanogenesis and the effects of environmental contamination on methanogenesis were examined in freshwater sediments. Temporal and spatial variation was found to be significant in uncontaminated freshwater reservoir sediments. The relative concentration of organic matter and temperature explained approximately 43% of the total variability. Known environmental contaminants marginally inhibited methanogenesis and only a coal conversion effluent and phenanthrene, 100 mg L−1, demonstrated statistically significant inhibition of methanogenesis under acute dosing conditions. Methyl viologen, a potent inhibitor of pure culture methanogenesis, inhibited sediment methanogenesis at high concentrations, i.e., 2570 mg L−1, indicating that the sediment environment protected the methanogenic population from the toxic effects of the environmental contaminants.

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Feed efficiency of lactating Holstein cows is less reproducible when changing dietary starch and fibre concentrations than within diet over subsequent lactation stages

10.1101/2021.02.10.430560 ◽

2021 ◽

Author(s):

Amélie Fischer ◽

Philippe Gasnier ◽

Philippe Faverdin

Keyword(s):

Principal Components ◽

Feed Efficiency ◽

Nir Spectroscopy ◽

Principal Component ◽

Holstein Cows ◽

Diet Change ◽

Total Variability ◽

The One ◽

The Individual ◽

Starch Diet

ABSTRACTBackgroundImproving feed efficiency has become a common target for dairy farmers to meet the requirement of producing more milk with fewer resources. To improve feed efficiency, a prerequisite is to ensure that the cows identified as most or least efficient will remain as such, independently of diet composition. Therefore, the current research analysed the ability of lactating dairy cows to maintain their feed efficiency while changing the energy density of the diet by changing its concentration in starch and fibre. A total of 60 lactating Holstein cows, including 33 primiparous cows, were first fed a high starch diet (diet E+P+), then switched over to a low starch diet (diet E−P−). Near infra-red (NIR) spectroscopy was performed on each individual feed ingredient, diet and individual refusals to check for sorting behaviour. A principal component analysis (PCA) was performed to analyse if the variability in NIR spectra of the refusals was explained by the differences in feed efficiency.ResultsThe error of reproducibility of feed efficiency across diets was 2.95 MJ/d. This error was significantly larger than the errors of repeatability estimated within diet over two subsequent lactation stages, which were 2.01 MJ/d within diet E−P− and 2.40 MJ/d within diet E+P+. The coefficient of correlation of concordance (CCC) was 0.64 between feed efficiency estimated within diet E+P+ and feed efficiency estimated within diet E−P−. This CCC was smaller than the one observed for feed efficiency estimated within diet between two subsequent lactation stages (CCC = 0.72 within diet E+P+ and 0.85 within diet E−P−). The first two principal components of the PCA explained 90% of the total variability of the NIR spectra of the individual refusals. Feed efficiency was poorly correlated to those principal components, which suggests that feed sorting behaviour did not explain differences in feed efficiency.ConclusionsFeed efficiency was significantly less reproducible across diets than repeatable within the same diet over subsequent lactation stages, but cow’s ranking for feed efficiency was not significantly affected by diet change. The differences in sorting behaviour between cows were not associated to feed efficiency differences in this trial neither with the E+P+ diet nor with the E−P− diet. Those results have to be confirmed with cows fed with more extreme diets (for example roughage only) to ensure that the least and most efficient cows will not change.

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Modelling the number of olive groves in Spanish municipalities

Spanish Journal of Agricultural Research ◽

10.5424/sjar/2016141-7687 ◽

2016 ◽

Vol 14 (1) ◽

pp. e0201

Author(s):

Maria-Dolores Huete ◽

Juan A. Marmolejo

Keyword(s):

Goodness Of Fit ◽

Likelihood Estimation ◽

External Factors ◽

Discrete Distributions ◽

Future Research ◽

Total Output ◽

Goodness Of Fit Test ◽

Chi Square ◽

Total Variability ◽

Olive Groves

<p>The univariate generalized Waring distribution (UGWD) is presented as a new model to describe the goodness of fit, applicable in the context of agriculture. In this paper, it was used to model the number of olive groves recorded in Spain in the 8,091 municipalities recorded in the 2009 Agricultural Census, according to which the production of oil olives accounted for 94% of total output, while that of table olives represented 6% (with an average of 44.84 and 4.06 holdings per Spanish municipality, respectively). UGWD is suitable for fitting this type of discrete data, with strong left-sided asymmetry. This novel use of UGWD can provide the foundation for future research in agriculture, with the advantage over other discrete distributions that enables the analyst to split the variance. After defining the distribution, we analysed various methods for fitting the parameters associated with it, namely estimation by maximum likelihood, estimation by the method of moments and a variant of the latter, estimation by the method of frequencies and moments. For oil olives, the chi-square goodness of fit test gives <em>p</em>-values of 0.9992, 0.9967 and 0.9977, respectively. However, a poor fit was obtained for the table olive distribution. Finally, the variance was split, following Irwin, into three components related to random factors, external factors and internal differences. For the distribution of the number of olive grove holdings, this splitting showed that random and external factors only account about 0.22% and 0.05%. Therefore, internal differences within municipalities play an important role in determining total variability.</p>

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