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290 results for “variance”
SABER gravity wave temperature variances for the global monsoon seasons 2016-2020
<p>This is a near-global dataset of gravity wave temperature variances at 50km altitude derived from SABER satellite observations using the method described in Ern et al. (2018). It covers the months of JJA and DJF, starting with December 2016, and ending with August 2020.</p> <p>Dimensions: 1 vertical level (z=50km), 37 longitudes, and 37 latitudes.</p> <p>Variables: gravity wave temperature variances</p>
Population structure and genetic variance among local populations of an non-native earthworm species in Minnesota, USA
<p>A variety of human activities have been identified as driving factors for the release and spread of invasive earthworm species in North America. Population genetic markers can help to identify locally relevant anthropogenic vectors and provide insights into the processes of population dispersal and establishment. We sampled the invasive European earthworm species <em>Lumbricus terrestris</em> at nine sites and several bait shops within the metropolitan area of Minneapolis-St. Paul in Minnesota, USA. We used microsatellite markers to infer genetic diversity and population structure, and 16S rDNA to address multiple introduction events, including bait dumping, which is a common source of <em>L. terrestris</em> introductions into the wild. Our results indicate multiple introductions but not from current bait dumping. Overall, genetic structure was low and earthworms >5000 m apart were genetically differentiated, except for one sampling location, indicating jump-dispersal followed by population establishment. Further, earthworms at one location north of Minneapolis established from one or few founder individuals, suggesting that earthworm invasions are ongoing. We therefore encourage further monitoring of earthworm populations using molecular markers, in order to disentangle the different human-related vectors contributing to the spread of earthworms and their establishment, which is essential to develop adequate management strategies.</p>
Variance in offspring sex ratio and maternal allocation in a highly invasive mammal
<p>Skewed sex ratios at birth are widely reported in wild populations, however the extent to which parents are able to modulate the sex ratio of offspring to maximize their own fitness remains unclear. This is particularly true for highly polytocous species as maximizing fitness may include trade-offs between sex ratio and the size and number of offspring in litters. In such cases, it may be adaptive for mothers to adjust both the number of offspring per litter and offspring sex to maximize individual fitness. Investigating maternal sex allocation in wild pigs (<em>Sus scrofa</em>) under stochastic environmental conditions, we predicted that, under favorable conditions, high quality mothers (larger, older) would produce male-biased litters and invest more in producing larger litters with more males. We also predicted sex ratio would vary relative to litter size, with a male-bias among smaller litters. We found evidence that increasing wild boar ancestry, maternal age and condition, and resource availability may weakly contribute to male-biased sex ratio, however, unknown factors not measured in this study are assumed to be more influential. High quality mothers allocated more resources in litter production, but this relationship was driven by adjustment of litter size, not sex ratio. There was no relationship between sex ratio and litter size. Collectively, our results emphasized that adjustment of litter size appeared to be the primary reproductive characteristic manipulated in wild pigs to increase fitness rather than adjustment of offspring sex ratio.</p>
Parcel level temporal variance of remotely sensed spectral reflectance predicts plant diversity
<p>Over the last two decades, considerable research has built on remote sensing of spectral diversity to assess plant diversity. The spectral variation hypothesis (SVH) proposes that spatial variation in reflectance data of an area is positively associated with plant diversity. While the SVH has exhibited validity in dense forests, it performs poorly in highly fragmented and temporally dynamic agricultural landscapes covered mainly by grasslands. Such underperformance can be attributed to the mosaic-like spatial structure of human-dominated landscapes with fields in varying phenological and management stages. Therefore, we argued for re-evaluating SVH's flawed window-based spatial analysis and underutilized temporal component. In particular, In particular, we captured the spatial and temporal variation in reflectance and assessed the relationships between spatial and temporal components of spectral diversity and plant diversity at the parcel level as a unit that relates to management patterns. Our investigation spanned three grasslands on two continents covering a wide spectrum of agricultural usage intensities. To calculate different components of spectral diversity, we used multi-temporal spaceborne Sentinel-2 data. We showed that plant diversity was negatively associated with the temporal component of spectral diversity across all sites. In contrast, the spatial component of spectral diversity was related to plant diversity in sites with larger parcels. Our findings highlighted that in agricultural landscapes, the temporal component of spectral diversity drives the spectral diversityplant diversity associations. Consequently, our results offer a novel perspective for remote sensing of plant diversity globally.</p>
Towards Robust Hemolysis Modeling with Uncertainty Quantification: A Universal Approach to Address Experimental Variance
<p>This repository contains the implementation of <strong>Robust Hemolysis Modeling with Uncertainty Quantification: A Universal Approach to Address Experimental Variance</strong>.</p> <p>The provided Python script demonstrates the construction of the MCMC (Markov Chain Monte Carlo) method and illustrates how to use MCMC for generating hemolysis distributions. Please note that the actual hemolysis calculations should be performed using your preferred CFD (Computational Fluid Dynamics) software.</p> <p>If there are any questions, please contact:</p> <p>blum@ame.rwth-aachen.de </p>
Animated Plots of the variance of observed data from LOFAR Station IE613
<p>This series of animated plots illustrates the variation of the linear polarisation channels and Stokes parameters for an observation of CasA from LOFAR station IE613 against altitude and azimuth throughout the frequency range of LOFAR HBA.</p>
Data for Understanding the moisture variance in precipitating shallow cumulus convection
<p>Data accompanying the paper titled: Understanding the moisture variance in precipitating shallow cumulus convection .</p> <p> </p> <p>This repository contains configuration files and output statistics for three idealized simulations run with LES model MicroHH (van Heerwaarden et al., 2017). </p> <p><br> The experimental setup of all cases is based on the Rain in Cumulus over the Ocean (RICO) field experiment as used in the GEWEX Cloud System Study (GCSS) RICO model inter comparison study (Rauber et al., 2007; vanZanten et al, 2011). The experiment, defined as the standard case (referenced as STD), uses the GCSS configuration, while the second experiment, termed as the moist case (referenced as MST), is initialized with an increased moisture content in the cloud layer and above of about 2 g/kg. Both of these experiments cover a domain size of 50 x 50 x 6 km with an isotropic grid spacing of 25 m. The control simulation (referenced as CTRL) is a non-precipitating reference simulation. The setup for the control case is identical to the setup of the standard case, except for a smaller domain size of 8 x 8 x 6 km.</p> <p> </p> <p> </p> <p>The files are organized in the following way: </p> <p>Each case has its own folder (CTRL, MST, and STD). </p> <p>Each such folder contains a 'setup' sub-folder with the configuration files for the microHH simulation: an '.ini' file and a '.py' file that generates initial conditions and forcings. </p> <p>Output statistics are located in the 'statistics_output' sub-folders. They contain '.nc' files with statistics from 30 h to 35 h of the simulation. Conditional spatial averaging was performed in order to understand the significance of the convective regions. Files valid for cloud active regions are marked with '_CA'. Files valid for non active regions are marked with '_NA' (Bastak Duran, Geleyn, Vana, Schmidli, & Brozkova, 2018). Files without '_CA' or '_NA' are valid for the whole domain.</p>
1.Figure cut off value of NLRP3 calculation process by R 2.Normality check results and Variance homogeneity.
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Supplementary Table S1. Combined analysis of variance containing the degrees of freedom (DF), mean squares (MS), P value (P val.), mean, coefficient of experimental variation (CEV%) and selective accuracy (SA) for the traits of luminosity (L*), chromaticity a* (a*), chromaticity b* (b*), grain length (length, mm), grain width (width, mm), grain thickness (thickness, mm), mass of 100 grains (Mass, g), normal grains (Ng, %), water absorption (absorption, %), cooking time (Ct, min:s), and concentrations of potassium (K, g kg-1 dry matter - DM), phosphorus (P, g kg-1 DM), calcium (Ca, g kg-1 DM), magnesium (Mg, g kg-1 DM), iron (Fe, mg kg-1 DM), zinc (Zn, mg kg-1 DM), and copper (Cu, mg kg-1 DM) obtained in 25 common bean cultivars evaluated in four experiments carried out from 2019 to 2021
<p><strong><span>Table S1.</span></strong><span> Combined analysis of variance.</span></p> <p><strong><span>Indirect selection for multiple technological and nutritional traits in common bean cultivars under different degrees of multicollinearity</span></strong></p> <p><strong><span>Bragantia, 2024.</span></strong></p>
Dataset and script to: Morphometric variance, evolutionary constraints and their change through time in Late Devonian Palmatolepis conodonts
<p>Phenotypic variation is the raw material of evolution. Standing variation can facilitate response to selection along "lines of least evolutionary resistance", but selection itself might alter the structure of the variance. Shape was quantified using 2D geometric morphometrics in <i>Palmatolepis </i>conodonts through the Late Devonian period. Patterns of variance were characterized along the record by the variance-covariance matrix (P-matrix) and its first axis (Pmax). The Late Frasnian was marked by environmental oscillations culminating with the Frasnian/Famennian mass extinction. A shape response was associated with these fluctuations, together with a deflection of the Pmax and the P-matrix. Thereafter, along the Famennian, <i>Palmatolepis </i>mean shape shifted from broad elements with a large platform to slender elements devoid of platform. This shift in shape was associated with a reorientation of Pmax and the P-matrix, due to profound changes in the functioning of the elements selecting for new types of variants. Both cases provide empirical evidences that moving adaptive optimum can reorient phenotypic variation, boosting response to environmental changes. On such time scales, the question seems thus not to be whether the P-matrix is stable, but how it is varying in response to changes in selection regimes and shifts in adaptive optimum.</p>
Data, sample sizes, and R code for analysis of: Variation in mutation (co)variances
<p>Because of pleiotropy, mutations affect the expression and inheritance of multiple traits and, together with selection, are expected to shape standing genetic covariances between traits and eventual phenotypic divergence between populations. It is therefore important to find if the M matrix, describing mutational variances of each trait and covariances between traits, varies between genotypes. We here estimate the M matrix for six locomotion behavior traits in lines of two genotypes of the nematode <em>Caenorhabditis elegans </em>that accumulated mutations in a nearly-neutral manner for 250 generations. We find significant mutational variance along at least one phenotypic dimension of the M matrices, but neither their size nor their orientation had detectable differences between genotypes. The number of generations of mutation accumulation, or the number of MA lines measured, was likely insufficient to sample enough mutations and detect potentially small differences between the two M matrices. We then tested if the M matrices were similar to one G matrix describing the standing genetic (co)variances of a population derived by the hybridization of several genotypes, including the two measured for M, and domesticated to a lab-defined environment for 140 generations. We found that the M and G were different because the genetic covariances caused by mutational pleiotropy in the two genotypes are smaller than those caused by linkage disequilibrium in the lab population. We further show that M matrices differed in their alignment with the lab population G matrix. If generalized to other founder genotypes of the lab population, these observations indicate that selection does not shape the evolution of the M matrix for locomotion behavior in the short-term of a few tens to hundreds of generations and suggests that the hybridization of <em>C. elegans </em>genotypes allows selection on new phenotypic dimensions of locomotion behavior.</p>
Data from: Direct generation of spatially entangled qudits using quantum nonlinear holography - variances
<p>Nonlinear holography shapes the amplitude and phase of generated new harmonics using nonlinear processes. Classical nonlinear holography influenced many fields in optics, from information storage, de-multiplexing of spatial information and all-optical control of accelerating beams. Here, we extend the concept of nonlinear holography to the quantum regime. We directly shape the spatial quantum correlations of entangled photon pairs in two-dimensional patterned nonlinear photonic crystals using spontaneous parametric down conversion, without any pump shaping. The generated signal-idler pair obeys a parity conservation law that is governed by the nonlinear crystal. Furthermore, the quantum states exhibit quantum correlations and violate the Clauser-Horne-Shimony-Holt inequality, thus enabling entanglement-based quantum key distribution. Our demonstration paves the way for controllable on-chip quantum optics schemes utilizing the high-dimensional spatial degree of freedom.</p>
Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: A case study in Drosophila serrata
<p>Additive genetic variance, <em>V<sub>A</sub></em>, is the key parameter for predicting adaptive and neutral phenotypic evolution. Changes in demography (e.g., increased close-relative inbreeding) can alter <em>V<sub>A</sub></em>, but how depends on the, typically unknown, gene action and allele frequencies across many loci. For example, <em>V<sub>A</sub></em> increases proportionally with the inbreeding coefficient when allelic effects are additive, but larger (or smaller) increases can occur when allele frequencies are unequal at causal loci with dominance effects. Here, we describe an experimental approach to assess the potential for rare, recessive alleles to inflate <em>V<sub>A</sub></em> under inbreeding. Applying a powerful paired pedigree design in <em>Drosophila serrata</em>, we measured 11 wing traits on half-sibling families bred via either random or sibling mating, differing only in homozygosity (not allele frequency). Despite close inbreeding and substantial power to detect small <em>V<sub>A</sub></em>, we detected no deviation from the expected additive effect of inbreeding on genetic (co)variances. Our results suggest the average dominance coefficient is very small relative to the additive effect, or that allele frequencies are relatively equal at loci affecting wing traits. We outline the further opportunities for this paired pedigree approach to reveal the characteristics of <em>V<sub>A</sub></em>, providing insight into historical selection and future evolutionary potential.</p>
A sexually-selected male weapon characterised by strong additive genetic variance and no evidence for sexually antagonistic polyphenic maintenance
<p><span>Sexual selection and sexual antagonism are important drivers of eco-evolutionary processes. The evolution of traits shaped by these processes depends on their genetic architecture, which remains poorly studied. Here, implementing a quantitative genetics approach using diallel crosses of the bulb mite, <em>Rhizoglyphus</em> <em>robini</em>, we investigated the genetic variance that underlies a sexually-selected weapon that is dimorphic among males and female fecundity. Previous studies indicated that a negative genetic correlation between these two traits likely exists. We found male morph showed considerable additive genetic variance, which is unlikely to be explained solely by mutation-selection balance, indicating the likely presence of large-effect loci. However, a significant magnitude of inbreeding depression also indicates that morph expression is likely to be condition-dependent to some degree and that deleterious recessives can simultaneously contribute to morph expression. Female fecundity also showed a high degree of inbreeding depression, but variance in female fecundity was mostly explained by epistatic effects, with very little contribution from additive effects. We found no significant genetic correlation, nor any evidence for dominance reversal, between male morph and female fecundity. The complex genetic architecture underlying male morph and female fecundity in this system has important implications for our understanding of the evolutionary interplay between purifying selection and sexually antagonistic selection.</span></p>
Table 5. Results of calculation of the percentage of wound healing analysis of variance (ANOVA) one way with SPSS 23.00
<p>Table 5. Results of calculation of the percentage of wound healing analysis of variance (ANOVA) one way with SPSS 23.00</p>
Table 11. Results of statistical calculation of hydroxyproline levels analysis of variance (ANOVA) two way spss 23.00
<p>Table 11. Results of statistical calculation of hydroxyproline levels analysis of variance (ANOVA) two way spss 23.00</p> <p> </p>
Wavelet variance coefficients of children and adolescents with and without ADHD
<p>Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that often persists into adulthood. One hallmark in the characterization of pathological processing in ADHD is that attention skills are not impaired per se but more inconsistent and with higher variability compared to typically developing children (TDC). Increased variability in ADHD patients has been found in reaction times, as well as resting-state fMRI (rs-fMRI) brain signals. High variability has been assumed to reflect occasional lapses in attention, linked to intrusions of distracting activity during task performance and/or reduced anti-correlation between regions in the DMN and attention networks. Therefore, Dajani et al. (2019) concluded that it is more likely the dynamics between and within neural networks [i.e., the variability of network processing across time- and frequency-scales], that are affected in ADHD, than functional connectivity [in terms of one coefficient describing the (averaged) correlation between two regions over time]. </p> <p>We determined wavelet variance to quantify these dynamics. We determined wVar at rest and under task in fMRI timeseries of regions of the DMN and the FPN in three different frequency bands: 0.02 to 0.04Hz, 0.04 to 0.08Hz, and 0.08-0.16Hz.</p> <p>We found that wVar differed group specifically between rest and task (significant group X condition interaction: whereas wVar was higher at rest compared to task in TDC, wVar was comparable or even decreased at rest in ADHD. For an external validation of group comparisons in wVar at rest, we determined wVar in rs-fMRI timeseries of a subsample of the Child Mind Institute data set (Functional Connectomes Project International Neuroimaging Data-Sharing Initiative http://dx.doi.org/10.15387/CMI_HBN (2017)). Results replicated our findings in terms of no significant group differences in wVar at rest in combination with similar or lower absolute values in ADHD patients compared to control subjects. </p> <p>In normal processing, high wVar at rest was interpreted as reflecting free fluctuating brain signaling, in comparison to small wVar under task indicating focussed processing. Thus, we conclude that wVar is a sensitive measure of cognitive processing and is even capable of detecting deviant processing in pathological brain function.</p>
Sexually antagonistic selection maintains genetic variance when sexual dimorphism evolves
<p>Breeding design data for body size in seed beetles (a sexually antagonistic trait) after 10 generations under different artificial selection conditions to test the effects of selection on the genetic variance of body size. The breeding design and sample size of the study allow us to partition genetic variances into additive autosomal, additive sex-linked, autosomal dominance and X-linked dominance variance.<br><br>See related dataset for body size data of the ancestral population before selection.</p>
A sexually-selected male weapon characterised by strong additive genetic variance and no evidence for sexually antagonistic polyphenic maintenance
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Using inbreeding to test the contribution of non-additive genetic effects to additive genetic variance: A case study in Drosophila serrata
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