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The aim of this article is to verify whether a relationship exists between partly laws and party organizational change. While the prevailing contextualist perspective enhances the weight of social, economic and technological factors in shaping party change, we maintain that the intensity of party regulation plays a major role in this respect. Based on some basic assumption of Organizational Institutionalism, the article adopts the rationale of the Political Parties Database (PPDB): we thus conduct an in-depth empirical analysis of three core party organisational dimensions (Resources, Representative Strategies, Structures), over a total of nineteen parties in four Western European democracies (Germany, the Netherlands, Sweden and the UK), from 1970s to 2010s. Our empirical findings show that, while a growing number of party laws have been introduced in the countries under consideration, their impact on party organizational convergence is far from univocal: we thus provide different possible explanations of these results. [ABSTRACT FROM AUTHOR]

The article focuses on the challenges faced by external practitioners in validating selection tools against performance ratings. It explores the need for a deeper understanding of the variance in performance ratings, the importance of aligning selection systems with true job performance, and the practical constraints of implementing these recommendations in real-world settings.

The article focuses on the sources of predictable variance in job performance ratings. It argues that multiple sources, including person x source interactions, significantly impact the reliability and predictability of performance ratings, and provides empirical evidence indicating that the actual predictable variance is much higher than previously estimated.

The article focuses on the predictive power of selection tests in relation to job performance ratings, emphasizing that these tests may account for more variance in performance than previously estimated when considering ratee-related variance. It highlights the need for caution in interpreting the effectiveness of selection tests due to potential overestimation in regression analyses.

This work presents a complete workflow for the parameter identification of an MBS model representing a vibratory conveying system. First, the MBS model built within the multibody dynamics tool HOTINT is shown. Essential components, such as contact modeling and adaptive time step control, are explained in detail. The model includes a considerable amount of parameters that need to be identified. Altough, this model is fully deterministic, the complex contact dynamics can cause major effect on results by minor parameter variations. Thus, parameter variations usually show statistical variance, which is characteristic for real conveying processes too. For parameter identification it is important to detect parameters that significantly correlate with results. A method that allows to distinguish significant and non-significant parameters is presented. The application to the multibody system shows that stiffness, restitution and sliding friction of the contact model are the essential parameters. Next, the parameter identification is discussed with particular attention to multimodal distributions, that can occur in conveying systems. Furthermore, the integration of statistics into the deterministic simulation model is discussed. In order to demonstrate the applicability of the proposed methods, a parameter identification is performed based on measurement data of a single part on a real conveying system in the development site of STIWA Automation GmbH. Finally, the validity of the fully parametrized simulation model is shown by investigating geometric adjustments of the conveyor. In order to further verify the identified set of parameters, a conveying process with multiple parts is analyzed and compared in measurement and simulation. [ABSTRACT FROM AUTHOR]

In one-way analysis of variance models, performing simultaneous multiple comparisons of treatment groups with a control group may be of interest. Dunnett's test is used to test such differences and assumes equal variances of the response variable for each group. This assumption is not always met even after transformation. A parametric bootstrap (PB) method is developed here for comparing multiple treatment group means against the control group with unequal variances and unbalanced data. In simulation studies, the proposed method outperformed Dunnett's test in controlling the type I error under various settings, particularly when data have heteroscedastic variance and unbalanced design. Simulations show that power is often lower for the PB method than for Dunnett's test under equal variance, balanced data, or smaller sample size, but similar to or higher than for Dunnett's test with unequal variance, unbalanced data and larger sample size. The method is applied to a dataset concerning isotope levels found in elephant tusks from various geographical areas. These data have very unbalanced group sizes and unequal variances. This example illustrates that the PB method is easy to implement and avoids the need for transforming data to meet the equal variance assumption, simplifying interpretation of results. [ABSTRACT FROM AUTHOR]

Proper variance partitioning and estimation of genetic parameters at appropriate time interval is crucial for understanding the dynamics of trait variance and genetic correlations and for deciding the future breeding strategy of the population. This study was conducted on the same premise to estimate genetic parameters of major economic traits in a White Leghorn strain IWH using Bayesian approach and to identify the role of maternal effects in the regulation of trait variance. Three different models incorporating the direct additive effect (Model 1), direct additive and maternal genetic effect (Model 2) and direct additive, maternal genetic and maternal permanent environmental effects (Model 3) were tried to estimate the genetic parameters for body weight traits (birth weight, body weight at 16, 20, 40 and 52 weeks), Age at sexual maturity (ASM), egg production traits (egg production up to 24, 28, 40, 52, 64 and 72 weeks) and egg weight traits (egg weight at 28, 40 and 52 weeks). Model 2 and Model 3 with maternal effects were found to be the best having the highest accuracy for almost all the traits. The direct additive genetic heritability was moderate for ASM, moderate to high for body weight traits and egg weight traits and low to moderate for egg production traits. Though the maternal heritability (h2mat) and permanent environmental effect (c2mpe) was low (<0.1) for most of the traits, they formed an important component of trait variance. Traits like egg weight at 28 weeks (0.14±0.06) and egg production at 72 weeks (0.13±0.07) reported comparatively higher values for c2mpe and h2mat respectively. Additive genetic correlation was high and positive between body weight traits, between egg weight traits, between consecutive egg production traits and between body weight and egg weight traits. However, a negative genetic correlation existed between egg production and egg weight traits, egg production and body weight traits, ASM and early egg production traits. Overall, a moderate positive genetic correlation was estimated between ASM and body weight traits and ASM and egg weight traits. Based on our findings, we can deduce that maternal effects constitute an important source of variation for all the major economic traits in White Leghorn and should be necessarily considered in genetic evaluation programs. [ABSTRACT FROM AUTHOR]

There is a dearth of statistical models that adequately capture the total signal attributed to whole-brain imaging features. The total signal is often widely distributed across the brain, with individual imaging features exhibiting small effect sizes for predicting neurobehavioral phenotypes. The challenge of capturing the total signal is compounded by the distribution of neurobehavioral data, particularly responses to psychological questionnaires, which often feature zero-inflated, highly skewed outcomes. To close this gap, we have developed a novel Variational Bayes algorithm that characterizes the total signal captured by whole-brain imaging features for zero-inflated outcomes. Our zero-inflated variance (ZIV) estimator estimates the fraction of variance explained (FVE) and the proportion of non-null effects (PNN) from large-scale imaging data. In simulations, ZIV demonstrates superior performance over other linear models. When applied to data from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study, we found that whole-brain imaging features contribute to a larger FVE for externalizing behaviors compared to internalizing behaviors. Moreover, focusing on features contributing to the PNN, ZIV estimator localized key neurocircuitry associated with neurobehavioral traits. To the best of our knowledge, the ZIV estimator is the first specialized method for analyzing zero-inflated neuroimaging data, enhancing future studies on brain-behavior relationships and improving the understanding of neurobehavioral disorders. The ZIV estimator, a novel Variational Bayes algorithm, enhances whole-brain imaging analysis for zero-inflated outcomes, revealing key neurocircuitry and greater variance for externalizing behaviors in the ABCD Study [ABSTRACT FROM AUTHOR]

Purpose: Quality of Life (QoL) is associated with a bandwidth of lifestyle factors that can be subdivided into fixed and potentially modifiable ones. We know too little about the role of potentially modifiable factors in comparison to fixed ones. This study examines four aspects of QoL and its associations with 15 factors in a sample of elderly primary care patients with a high risk of dementia. The main objectives are (a) to determine the role of the factors in this particular group and (b) to assess the proportion of fixed and potentially modifiable factors. Method: A high-risk group of 1030 primary care patients aged between 60 and 77 years (52.1% females) were enrolled in "AgeWell.de," a cluster-randomized, controlled trial. This paper refers to the baseline data. The multi-component intervention targets to decrease the risk of dementia by optimization of associated lifestyle factors. 8 fixed and 7 modifiable factors potentially influencing QoL served as predictors in multiple linear regressions. Results: The highest proportion of explained variance was found in psychological health and age-specific QoL. In comparison to health-related QoL and physical health, the modifiable predictors played a major role (corr. R2: 0.35/0.33 vs. 0.18), suggesting that they hold a greater potential for improving QoL. Conclusion: Social engagement, body weight, instrumental activities of daily living, and self-efficacy beliefs appeared as lifestyle factors eligible to be addressed in an intervention program for improving QoL. Trial registration: German Clinical Trials Register, reference number: DRKS00013555. Date of registration: 07.12.2017. [ABSTRACT FROM AUTHOR]

Gene–environment (GE) interactions are essential in understanding human complex traits. Identifying these interactions is necessary for deciphering the biological basis of such traits. In this study, we review state-of-art methods for estimating the proportion of phenotypic variance explained by genome-wide GE interactions and introduce a novel statistical method Linkage-Disequilibrium Eigenvalue Regression for Gene–Environment interactions (LDER-GE). LDER-GE improves the accuracy of estimating the phenotypic variance component explained by genome-wide GE interactions using large-scale biobank association summary statistics. LDER-GE leverages the complete Linkage Disequilibrium (LD) matrix, as opposed to only the diagonal squared LD matrix utilized by LDSC (Linkage Disequilibrium Score)-based methods. Our extensive simulation studies demonstrate that LDER-GE performs better than LDSC-based approaches by enhancing statistical efficiency by ~23%. This improvement is equivalent to a sample size increase of around 51%. Additionally, LDER-GE effectively controls type-I error rate and produces unbiased results. We conducted an analysis using UK Biobank data, comprising 307 259 unrelated European-Ancestry subjects and 966 766 variants, across 217 environmental covariate-phenotype (E-Y) pairs. LDER-GE identified 34 significant E-Y pairs while LDSC-based method only identified 23 significant E-Y pairs with 22 overlapped with LDER-GE. Furthermore, we employed LDER-GE to estimate the aggregated variance component attributed to multiple GE interactions, leading to an increase in the explained phenotypic variance with GE interactions compared to considering main genetic effects only. Our results suggest the importance of impacts of GE interactions on human complex traits. [ABSTRACT FROM AUTHOR]

Purpose: To examine the parenthood desire, perceived parenthood stigma, and barriers to achieving parenthood among sexual minority men (SMM) in Canada, and to investigate factors influencing their fertility and assisted reproductive knowledge. Methods: Data were collected from March to mid-June 2023 using a 78-item anonymous online survey. Childless cisgender SMM (age 18+) living in Canada were recruited from the LGBTQIA+ community outside the fertility care networks. Chi-square, t-tests, ANOVA, reliability tests, Spearman's correlation, and hierarchical regression model were used for analysis. Results: Over 160 people clicked the survey hyperlink during the study period and 112 completed surveys were analyzed. The mean age of participants was 33.2±8.5 (range: 19.7–60.0). Having a child by any means was "quite"/"very" important to 35.7% (n=40), yet 56.0% (n=61) thought it was "unlikely" to achieve parenthood. Financial readiness (n=90, 85.7%) and relationship stability (n=86, 81.9%) were the two most "important" parenthood considerations. Participants who were non-white (p=0.017), under age 30 (p=0.008), and had no siblings (p=0.024) had significantly higher means of parenthood desire compared to others. The final hierarchical regression model explained 43% of the variance in the knowledge scores (R2adj =0.353), predicted by the levels of (i) education (β=0.37, p<0.001), (ii) family acceptance of sexual orientation (β=0.39, p=0.004), and (iii) parenthood desire (β=0.27, p=0.002). Conclusions: With an increasing number of SMM desiring children, it is pivotal to advance family-building equality through improving their fertility and assisted reproductive knowledge, removing disparities in accessing adoption and assisted reproductive services, and decreasing social stigma against SMM having children. [ABSTRACT FROM AUTHOR]

In this paper, a new class of variance estimators based on a two-step designed weights technique in the presence of non-response is proposed. The proposed estimator is designed to be robust against extreme values or outliers. In the first step, the calibration weights of the new class of estimators are set proportional to the design weights of the existing finite population variance estimator for a mailed survey design characterized by the presence of non-response. In the second step, the constants of proportionality are determined based on different objectives of the investigator such as bias reduction or minimum mean squared error. Many estimators available in the literature can be shown to be special cases of the proposed two-step calibrated estimator. The properties of the proposed estimators are studied theoretically and numerically. Empirical studies were conducted using ten simulated data to illustrate the performance of proposed estimators over existing ones. The results of the numerical comparison depicted the superiority of two members of the proposed estimator in all cases of data considered. [ABSTRACT FROM AUTHOR]

Subjective health ratings are associated with dementia risk such that those who rate their health more poorly have increased risk for dementia. The genetic and environmental mechanisms underlying this association are unclear, as prior research cannot rule out whether the association is due to genetic confounds. The current study addresses this gap in two samples of twins, one from Sweden (N = 548) and one from Denmark (N = 4,373). Using genetically-informed, bivariate regression models, we assessed whether additive genetic effects explained the association between subjective health and dementia risk as indexed by a latent variable proxy measure. Age at intake, sex, education, depressive symptomatology, and follow-up time between subjective health and dementia risk assessments were included as covariates. Results indicate that genetic variance and other sources of confounding accounted for the majority of the effect of subjective health ratings on dementia risk. After adjusting for genetic confounding and other covariates, a small correlation was observed between subjective health and latent dementia risk in the Danish sample (rE = −.09, p <.05). The results provide further support for the genetic association between subjective health and dementia risk, and also suggest that subjective ratings of health measures may be useful for predicting dementia risk. [ABSTRACT FROM AUTHOR]

The study aimed to assess performance traits in Hardhenu cattle by analysing data from 445 animals born to 59 sires and 227 dams. The investigation focused on estimating (co)variance components and genetic parameters for reproduction and production traits in dairy cattle. Results from least‐squares analysis indicated a significant effect (p <.01) of the period of calving (POC) on key production traits, including first lactation milk yield (FLMY), 300‐day milk yield (FLMY300), first peak yield (FPY) and total lactation milk yield (TLMY) in studied population. The least squares means for these traits were reported as follows: FLMY (2665.68 ± 45.66 kg), FLMY300 (2425.52 ± 34.41 kg), FLL (312.95 ± 3.83 days), FPY (11.52 ± 0.15 kg) and TLMY (9282.44 ± 167.03 kg) in Hardhenu cattle. In the studied population, only additive genetic variability was found to be present and there was absence of any significant maternal effect with respect to targeted traits in the resource population. Direct heritability estimates (h2) for FLMY, FLMY300, FLL, FPY, TLMY and other traits ranged from 0.03 to 0.41 in Hardhenu cattle. These findings offer valuable insights into the genetic factors influencing performance traits, contributing to the enhancement of breeding and management practices in Hardhenu cattle. [ABSTRACT FROM AUTHOR]

LD score regression (LDSC) is a method to estimate narrow-sense heritability from genome-wide association study (GWAS) summary statistics alone, making it a fast and popular approach. In this work, we present interaction-LD score (i-LDSC) regression: an extension of the original LDSC framework that accounts for interactions between genetic variants. By studying a wide range of generative models in simulations, and by re-analyzing 25 well-studied quantitative phenotypes from 349,468 individuals in the UK Biobank and up to 159,095 individuals in BioBank Japan, we show that the inclusion of a cis-interaction score (i.e. interactions between a focal variant and proximal variants) recovers genetic variance that is not captured by LDSC. For each of the 25 traits analyzed in the UK Biobank and BioBank Japan, i-LDSC detects additional variation contributed by genetic interactions. The i-LDSC software and its application to these biobanks represent a step towards resolving further genetic contributions of sources of non-additive genetic effects to complex trait variation. [ABSTRACT FROM AUTHOR]

This study aimed to determine a typical profile of elite breath-hold divers (BHDs), in relation to loss of consciousness (LOC) and episodic memory. Forty-four BHDs were evaluated during a world championship with anthropometric and physiological measurements, psychosociological factors and memory assessment. Seventy-five percent of the BHDs had at least one LOC with the predominance being men (p < 0.05). Thirty six percent of BHDs presented a low-risk profile and 64% a high-risk profile with no particular psychological pattern. Stepwise multiple linear regression showed that body fat, years of BH practice, age and forced vital capacity explained a significant amount of the variance of LOC for all BHDs (F(4,39) = 16.03, p < 0.001, R2 = 0.622, R2Adjusted = 0.583). No correlation was found between resting physiological parameters and their training or depth performances. In conclusion, anthropometric data, pulmonary factors and breath-holding experience were predictive of LOC in elite BHDs, with men taking more risks. BHDs episodic memory was not impaired. [ABSTRACT FROM AUTHOR]

Introduction: Mental complications of diabetes are one of the main obstacles to the implementation of self -care behaviors that have been less studied. Therefore, this study was conducted to survey the effective factors in predicting burnout and self-care behaviors among patients with type 2 diabetes. Methods: In this Path analysis, 1280 patients with type 2 diabetes were selected from Mashhad (Iran) in 2023 to 2024. Four scales, the mental health literacy (MHL) scale, diabetes burnout scale, diabetes distress scale, and self-care behavior scale were used for data gathering. AMOS software checked the direct and indirect paths between the variables. Results: In the path analysis, variables of MHL and diabetes distress predicted 25% variance of diabetes burnout (R2 = 0.25), and diabetes distress (total effect = 0.491) had the greatest impact on predicting diabetes burnout. Variables of MHL, diabetes distress, and diabetes burnout predicted 12% variance of Self-care behaviors (R2 = 0.12) and MHL (total effect = -0.256), age of onset of diabetes (total effect = 0.199), and diabetes burnout (total effect = − 0.167) had the greatest impact on prediction of self-care behaviors. Conclusion: MHL could reduce diabetes distress and burnout and eventually promote self-care behaviors among patients with type 2 diabetes. Therefore, screening and identifying psychological problems (such as distress and burnout) and designing interventions to increase MHL can ultimately increase the health of patients with diabetes. [ABSTRACT FROM AUTHOR]

Background: Linear models that are commonly used to predict breeding values in livestock species consider paternal influence solely as a genetic effect. However, emerging evidence in several species suggests the potential effect of non-genetic semen-mediated paternal effects on offspring phenotype. This study contributes to such research by analyzing the extent of non-genetic paternal effects on the performance of Holstein, Montbéliarde, and Normande dairy cows. Insemination data, including semen Batch Identifier (BI, a combination of bull identification and collection date), was associated with various traits measured in cows born from the insemination. These traits encompassed stature, milk production (milk, fat, and protein yields), udder health (somatic cell score and clinical mastitis), and female fertility (conception rates of heifers and cows). We estimated (1) the effects of age at collection and heat stress during spermatogenesis, and (2) the variance components associated with BI or Weekly aggregated BI (WBI). Results: Overall, the non-genetic paternal effect estimates were small and of limited biological importance. However, while heat stress during spermatogenesis did not show significant associations with any of the traits studied in daughters, we observed significant effects of bull age at semen collection on the udder health of daughters. Indeed, cows born from bulls collected after 1500 days of age had higher somatic cell scores compared to those born from bulls collected at a younger age (less than 400 days old) in both Holstein and Normande breeds (+ 3% and + 5% of the phenotypic mean, respectively). In addition, across all breeds and traits analyzed, the estimates of non-genetic paternal variance were consistently low, representing on average 0.13% and 0.09% of the phenotypic variance for BI and WBI, respectively (ranging from 0 to 0.7%). These estimates did not significantly differ from zero, except for milk production traits (milk, fat, and protein yields) in the Holstein breed and protein yield in the Montbéliarde breed when WBI was considered. Conclusions: Our findings indicate that non-genetic paternal information transmitted through semen does not substantially influence the offspring phenotype in dairy cattle breeds for routinely measured traits. This lack of substantial impact may be attributed to limited transmission or minimal exposure of elite bulls to adverse conditions. [ABSTRACT FROM AUTHOR]

Analysis of Variance (ANOVA) is a popular method to infer, based on the sampled data, whether the true means of a set of subpopulations differ from each other. The variance of conditional expectation (VOCE) is the variance of these effects in sub-populations, and this is estimated by sampling a sub-population of size n k , for each sub-population labeled k, and by sampling K such sub-populations in the experiment. For the general case of varying n k , it is unknown what the variance of the VOCE estimator is, though it is known for the special case n k = n , n ≥ 2 for all k ∈ 1 , 2 , ... , K as derived in the literature. The following derivation settles the former question and is of value in situations where sampling has constraints or only a skewed sampling budget is available. Our first application is with regard to the decision of whether samples from pilot simulation can be included in the regular simulation to estimate VOCE. The second application is an estimation technique where the estimate of optimal inner-loop size n * can be updated throughout the duration of simulation. We demonstrate with these 2 applications where we observe a 20% reduction in the variance of the VOCE estimate, when the proposed method is applied. [ABSTRACT FROM AUTHOR]

The primary focus of all sample surveys is on providing point estimates for the parameters of primary interest, and also estimating the variance associated with those point estimates to quantify the uncertainty. Larger samples and important measurement tools can help to reduce the point estimates' uncertainty. Numerous effective stratification criteria may be used in survey to reduce variance within stratum. In fine stratification design, the population is divided into numerous small strata, each containing a relatively small number of sampling units as one or two. This is done to ensure that certain characteristics or subgroups of the population are well-represented in the sample. But with many strata, the sample size within each stratum can become small, potentially resulting in higher errors and less stable estimates. The variance estimation process becomes difficult when we only have one unit per stratum. In that case, the collapsed stratum technique is the classical methods for estimating variance. This method, however, is biased and results in an overestimation of the variance. This paper proposes a bootstrap-based variance estimator for the total population under fine stratification, which overcomes the drawbacks of the previously explored estimation approach. Also, the estimator's properties were investigated. A simulation study and practical application on survey of mental health organizations data were done to investigate properties of the proposed estimators. The results show that the proposed estimator performs well. [ABSTRACT FROM AUTHOR]

Frailty is a complex trait. Twin studies and high-powered Genome Wide Association Studies conducted in the UK Biobank have demonstrated a strong genetic basis of frailty. The present study utilized summary statistics from a Genome Wide Association Study on the Frailty Index to create and test the predictive power of frailty polygenic risk scores (PRS) in two independent samples – the Lothian Birth Cohort 1936 (LBC1936) and the English Longitudinal Study of Ageing (ELSA) aged 67–84 years. Multiple regression models were built to test the predictive power of frailty PRS at five time points. Frailty PRS significantly predicted frailty, measured via the FI, at all-time points in LBC1936 and ELSA, explaining 2.1% (β = 0.15, 95%CI, 0.085–0.21) and 1.8% (β = 0.14, 95%CI, 0.10–0.17) of the variance, respectively, at age ~ 68/ ~ 70 years (p < 0.001). This work demonstrates that frailty PRS can predict frailty in two independent cohorts, particularly at early ages (~ 68/ ~ 70). PRS have the potential to be valuable instruments for identifying those at risk for frailty and could be important for controlling for genetic confounders in epidemiological studies. [ABSTRACT FROM AUTHOR]

Objective: To estimate the associations between height, weight, and three estimates of skeletal age (SA) and the strength and motor performance of male soccer players in two chronological age (CA) groups, 9–12 (n = 60) and 13–16 (n = 52) years. Methods: Height, weight, strength (grip), speed (5 m, 20 m sprints), acceleration (time at crossing 10 m in 20 m sprint), agility (figure‐of‐eight run), power (vertical jump), and endurance (intermittent shuttle run) were measured. SA was assessed with the TW2 RUS, TW3 RUS, and Fels methods; each SA was expressed as the standardized residual of the regression of SA on CA (SAsr). Hierarchical multiple regression was used. Results: Body size accounted for ≥50% of the variance in grip strength in both CA groups; the body size × SAsr for each method and SAsr alone added little to the explained variance. Body size, body size × SAsr interactions, and SAsr per se with each method accounted for small percentages of variance in motor tasks among players 9–12 years, while body size explained a larger proportion of variance in motor tasks (except the endurance run) among players 13–16 years; body size × SAsr interactions for TW2 and TW3 more so than Fels added to the explained variances. For the endurance run, only SAsr per se with each method accounted for significant portions of the variance. Conclusion: Body size and the three estimates of SA significantly influenced strength and motor performance, but the explained variance varied between CA groups and among SA methods and performance tasks. [ABSTRACT FROM AUTHOR]

Understanding the evolution of traits subject to trade-offs is challenging because phenotypes can (co)vary at both the among- and within-individual levels. Among-individual covariation indicates consistent, possibly genetic, differences in how individuals resolve the trade-off, while within-individual covariation indicates trait plasticity. There is also the potential for consistent among-individual differences in behavioral plasticity, although this has rarely been investigated. We studied the sources of (co)variance in two characteristics of an acoustic advertisement signal that trade-off with one another and are under sexual selection in the gray treefrog, Hyla chrysoscelis : call duration and call rate. We recorded males on multiple nights calling spontaneously and in response to playbacks simulating different competition levels. Call duration, call rate, and their product, call effort, were all repeatable both within and across social contexts. Call duration and call rate covaried negatively, and the largest covariance was at the among-individual level. There was extensive plasticity in calling with changes in social competition, and we found some evidence for among-individual variance in call rate plasticity. The significant negative among-individual covariance in trait values is perpendicular to the primary direction of sexual selection in this species, indicating potential limits on the response to selection. [ABSTRACT FROM AUTHOR]

Insertion/Deletion (InDel) polymorphisms, characterized by their smaller amplicons, reduced mutation rates, and compatibility with the prevalent capillary electrophoresis (CE) platforms in forensic laboratories, significantly contribute to the advancement and application of genetic analysis. Guizhou province in China serves as an important region for investigating the genetic structure, ethnic group origins, and human evolution. However, DNA data and the sampling of present-day populations are lacking, especially about the InDel markers. Here, we reported data on 47 autosomal InDels from 592 individuals from four populations in Guizhou (Han, Dong, Yi, and Chuanqing). Genotyping was performed with the AGCU InDel 50 kit to evaluate their utility for forensic purposes and to explore the population genetic structure. Our findings showed no significant deviations from Hardy-Weinberg and linkage equilibriums. The combined power of discrimination (CPD) and the combined power of exclusion (CPE) for each population demonstrated that the kit could be applied to forensic individual identification and was an effective supplement for parentage testing. Genetic structure analyses, including principal component analysis, multidimensional scaling, genetic distance calculation, STRUCTURE, and phylogenetic analysis, highlighted that the genetic proximity of the studied populations correlates with linguistic, geographical, and cultural factors. The observed genetic variances within four research populations were less pronounced than those discerned between populations across different regions. Notably, the Guizhou Han, Dong, and Chuanqing populations showed closer genetic affiliations with linguistically similar groups than the Guizhou Yi. These results underscore the potential of InDel markers in forensic science and provide insights into the genetic landscape and human evolution in multi-ethnic regions like Guizhou. Key points InDel markers show promise for forensic individual identification and parentage testing via the AGCU InDel 50 kit. Genetic analysis of Guizhou populations reveals correlations with linguistic, geographical, and cultural factors. Guizhou Han, Dong, and Chuanqing populations showed closer genetic affiliations with linguistically similar groups than the Guizhou Yi. [ABSTRACT FROM AUTHOR]

Background: Breeding programs are judged by the genetic level of animals that are used to disseminate genetic progress. These animals are typically the best ones of the population. To maximise the genetic level of very good animals in the next generation, parents that are more likely to produce top performing offspring need to be selected. The ability of individuals to produce high-performing progeny differs because of differences in their breeding values and gametic variances. Differences in gametic variances among individuals are caused by differences in heterozygosity and linkage. The use of the gametic Mendelian sampling variance has been proposed before, for use in the usefulness criterion or Index5, and in this work, we extend existing approaches by not only considering the gametic Mendelian sampling variance of individuals, but also of their potential offspring. Thus, the criteria developed in this study plan one additional generation ahead. For simplicity, we assumed that the true quantitative trait loci (QTL) effects, genetic map and the haplotypes of all animals are known. Results: In this study, we propose a new selection criterion, ExpBVSelGrOff, which describes the genetic level of selected grand-offspring that are produced by selected offspring of a particular mating. We compare our criterion with other published criteria in a stochastic simulation of an ongoing breeding program for 21 generations for proof of concept. ExpBVSelGrOff performed better than all other tested criteria, like the usefulness criterion or Index5 which have been proposed in the literature, without compromising short-term gains. After only five generations, when selection is strong (1%), selection based on ExpBVSelGrOff achieved 5.8% more commercial genetic gain and retained 25% more genetic variance without compromising inbreeding rate compared to selection based only on breeding values. Conclusions: Our proposed selection criterion offers a new tool to accelerate genetic progress for contemporary genomic breeding programs. It retains more genetic variance than previously published criteria that plan less far ahead. Considering future gametic Mendelian sampling variances in the selection process also seems promising for maintaining more genetic variance. [ABSTRACT FROM AUTHOR]

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci. We developed MVtest to simultaneously model the mean and log variance of quantitative traits as functions of genotypes and covariates by using estimating equations. MVtest can detect effect modification, and association statistics can be meta-analyzed. MVtest is applicable to studies of complex quantitative traits and provides an opportunity to detect novel vQTLs. [ABSTRACT FROM AUTHOR]

Physical defence investment in seeds varies greatly among plant species and is associated with many potential factors. Exploring the factors explaining the interspecific variation in physical defence has long attracted particular attention in both ecology and evolution studies. However, the relative importance of the factors has not yet been quantitatively evaluated, which may lead to the misunderstanding of the main driver generating such interspecific variation.Here, by compiling a global database of the seed coat ratio (SCR), a proxy of seed physical defence, for 1362 species, we provided the first quantification of the relative explanations of six factors that have been commonly considered to be associated with the interspecific variation in SCR: seed mass, seed desiccation response (desiccation‐sensitive vs. desiccation‐tolerant), seed dormancy (nondormant, physical dormant or other dormant types), growth form (herbaceous vs. woody), fruit type (dry vs. fleshy) and climate (19 bioclimatic variables representing temperature and precipitation). Using partial R2 calculation that can estimate the reduction in explained variance of a given factor after removing it from a full model containing all the other factors, we disentangled the relative contribution of each factor to explain variation in the SCR.Seed desiccation response was the most important factor associating with SCR variation, followed by seed dormancy, with a partial R2lik value of 9.70% and 1.41%, respectively. Plant growth form, seed mass, climate and fruit type showed little power to explain SCR variation, although they are often cited in the literature as potential factors.Our results highlight the important roles of seed desiccation response in shaping interspecific variation in the SCR. These findings provide a detailed interpretation of ecological patterns underlying the physical defence mechanisms and allocation strategies of plant seeds. Read the free Plain Language Summary for this article on the Journal blog. [ABSTRACT FROM AUTHOR]

Although research shows a strong positive association between perceived stress and loneliness, the genetic and environmental etiology underlying their association remains unknown. People with a genetic predisposition to perceived stress, for example, may be more prone to feeling lonely and vice versa. Conversely, unique factors in people's lives may explain differences in perceived stress levels that, in turn, affect feelings of loneliness. We tested whether genetic factors, environmental factors, or both account for the association between perceived stress and loneliness. Participants were 3,066 individual twins (nFemale = 2,154, 70.3%) from the Washington State Twin Registry who completed a survey during April–May, 2020. Structural equation modeling was used to analyze the item-level perceived stress and loneliness measures. The correlation between latent perceived stress and latent loneliness was.68. Genetic and nonshared environmental variance components underlying perceived stress accounted for 3.71% and 23.26% of the total variance in loneliness, respectively. The genetic correlation between loneliness and perceived stress was.45 and did not differ significantly between men and women. The nonshared environmental correlation was.54 and also did not differ between men and women. Findings suggest that holding constant the strong genetic association between perceived stress and loneliness, unique life experiences underlying people's perceived stress account for individual differences in loneliness. [ABSTRACT FROM AUTHOR]

Background: Recursive models are a category of structural equation models that propose a causal relationship between traits. These models are more parameterized than multiple trait models, and they require imposing restrictions on the parameter space to ensure statistical identification. Nevertheless, in certain situations, the likelihood of recursive models and multiple trait models are equivalent. Consequently, the estimates of variance components derived from the multiple trait mixed model can be converted into estimates under several recursive models through LDL′ or block-LDL′ transformations. Results: The procedure was employed on a dataset comprising five traits (birth weight—BW, weight at 90 days—W90, weight at 210 days—W210, cold carcass weight—CCW and conformation—CON) from the Pirenaica beef cattle breed. These phenotypic records were unequally distributed among 149,029 individuals and had a high percentage of missing data. The pedigree used consisted of 343,753 individuals. A Bayesian approach involving a multiple-trait mixed model was applied using a Gibbs sampler. The variance components obtained at each iteration of the Gibbs sampler were subsequently used to estimate the variance components within three distinct recursive models. Conclusions: The LDL′ or block-LDL′ transformations applied to the variance component estimates achieved from a multiple trait mixed model enabled inference across multiple sets of recursive models, with the sole prerequisite of being likelihood equivalent. Furthermore, the aforementioned transformations simplify the handling of missing data when conducting inference within the realm of recursive models. [ABSTRACT FROM AUTHOR]

Background: This study aims to examine the relationship between functional movements and golf performance using the Golf Specific Functional Movement Screen (GSFMS). Methods: This cross-sectional study included a total of 56 collegiate golfers (aged 20.89 ± 0.99 years, height of 174.55 ± 7.76 cm, and weight 68.48 ± 9.30 kg) who met the criteria, and were recruited from Hainan Normal University in June 2022. The participants' golf motor skills (1-yard putt, 10-yard putt, 25-yard chip, 130/100-yard set shot, driver, and 9-hole stroke play) were tested and the GSFMS (e.g., pelvic tilt, pelvic rotation, and torso rotation) was used. Results: There were significant weak or moderate correlations between the variables. Furthermore, a multiple linear regression analysis found that pelvic rotation and lower-body rotation abilities can significantly predict golf skill levels, which collectively explain 31.2% of the variance in golf skill levels among collegiate golfers (Adjusted R2 = 0.312, F = 2.663, p < 0.05). Standardised β values indicate that pelvic rotation (β = 0.398) has a more substantial impact on golf skill levels than lower-body rotation (β = 0.315). Conclusions: This study found the weak to moderate correlations between the GSFMS and golf performance, and pelvic rotation and lower-body rotation abilities, thus predicting golf skills. Our findings provide novel insights into the relationship between functional abilities and comprehensive skill performance within the context of the Gray Cook's Movement Pyramid model, and provide theoretical support and practical reference for collegiate golf motor-skill learning and sports injury prevention. [ABSTRACT FROM AUTHOR]

Animal models of brain function are critical for the study of human diseases and development of effective interventions. Resting-state network (RSN) analysis is a powerful tool for evaluating brain function and performing comparisons across animal species. Several studies have reported RSNs in the common marmoset (Callithrixjacchus; marmoset), a non-human primate. However, it is necessary to identify RSNs and evaluate commonality and inter-individual variance through analyses using a larger amount of data. In this study, we present marmoset RSNs detected using > 100,000 time-course image volumes of resting-state functional magnetic resonance imaging data with careful preprocessing. In addition, we extracted brain regions involved in the composition of these RSNs to understand the differences between humans and marmosets. We detected 16 RSNs in major marmosets, three of which were novel networks that have not been previously reported in marmosets. Since these RSNs possess the potential for use in the functional evaluation of neurodegenerative diseases, the data in this study will significantly contribute to the understanding of the functional effects of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Aim: Insular environments theoretically promote within‐species phenotypic variance, in part but not only because insular species enjoy a lower number of trophic interactions than their mainland counterparts. However, environmental factors apparently confound empirical comparisons between insular and mainland systems. To address this issue, we studied sympatric, congeneric species from the same small island, but that stemmed from separate colonization events. We predicted that the time since the species had colonized the island would correlate positively with the within‐species variance in morphometrics. Location: Lifu island, New Caledonia, South Pacific. Taxa: Zosterops inornatus, Z. minutus, Z. lateralis (Passeriformes). Methods: We measured seven morphological traits and used principal component analysis to compute axes of variation. Results: The within‐species variance in bill size and in feet/tail ratio corrected for body size increased with the estimated time since the species had been on the island. A similar but non‐significant trend existed for body size and bill width. Main Conclusions: The morphometrics of the three species of Zosterops birds from Lifu supported the hypothesis that insular environments promote within‐species phenotypic variance, and cast a new light on the role of competition in the erosion of phenotypic variance. [ABSTRACT FROM AUTHOR]

Although children display strong individual differences in emotion expression, they also engage in emotional synchrony or reciprocity with interaction partners. To understand this paradox between trait-like and dyadic influences, the goal of the current study was to investigate children's emotion expression using a Social Relations Model (SRM) approach. Playgroups consisting typically of four same-sex unfamiliar nine-year-old children (N = 202) interacted in a round-robin format (6 dyads per group). Each dyad completed two 5-minute tasks, a challenging frustration task and a cooperative planning task. Observers coded children's emotions during the tasks (happy, sad, angry, anxious, neutral) on a second-by-second basis. SRM analyses provided substantial evidence of both the trait-like nature of children's emotion expression (through significant effects for actor variance, multivariate actor-actor correlations, and multivariate intrapersonal correlations) and the dyadic nature of their emotion expression (through significant effects for partner variance, relationship variance, dyadic reciprocity correlations, and multivariate interpersonal correlations). [ABSTRACT FROM AUTHOR]

We aimed to estimate genetic parameters and select sorghum lines for forage purposes based on agronomic and chemical traits. A total of 100 inbred lines, comprising the biomass/bmr, biomass, dual purpose (sweet/forage), and forage types, were evaluated in the 2020/2021 and 2021/2022 crop years. We analyzed the data using a linear mixed model approach. Genetic variance, line mean-based heritability, selection accuracy, genetic correlation between traits and crops and the coefficient of experimental variation were estimated. The breeding values of the lines were predicted, and the factor analysis and genotype-ideotype distance index based on BLUP (FAI-BLUP) were applied for multi-trait selection. Biomass production and cell wall composition traits were measured. There was genetic variation among the lines, with moderate to high heritability. The lines selected by the FAI-BLUP index resulted in significant genetic gains expected with selection for all traits. [ABSTRACT FROM AUTHOR]

The current study aimed to evaluate Y chromosome haplotypes obtained from 1353 unrelated Iranian males using the AmpFlSTRTM YfilerTM kit; 1353 out of the 1353 identified haplotypes were unique. The haplotype diversity (HD) and discriminating capacity (DC) values were 1.00000 and 0.997, respectively. Analysis of genetic distance was performed using molecular variance (AMOVA) and multidimensional scaling plots (MDS), revealing a statistically significant difference between the study population and previous data reported for other Iranian populations and other neighboring countries. The present findings are likely to be useful for forensic casework analyses and kinship investigations. [ABSTRACT FROM AUTHOR]

Docynia delavayi (Franch.) Schneid. is a wild fruit tree that can be widely used for medicinal and edible purpose and has a high value of exploitation and utilization. We analyzed the growth traits of 62 half-sib families from 10 provenances in order to acquire more information about the genetic variance of growth traits in D. delavayi. Variation analysis, correlation analysis, principal component analysis, estimation of genetic parameters and comprehensive analysis were all done based on the data on growth traits. The results of the variance analysis revealed that all traits, with the exception of branch length, differed significantly or extremely significantly between provenances, whereas only leaf length did not differ significantly between families. The results of the correlation analysis showed that all growth traits, except for branch length and petiole length, had a significant or extremely significant correlation with the geo-climatic factors. Three principal components were extracted by principal component analysis; they were used as indicators for the comprehensive evaluation of D. delavayi from different provenances, and five excellent provenances were selected: Lancang (LC), Lianghe (LH), Shidian (SD), Yingjiang (YJ) and Xiangyun (XY). The results of genetic parameter estimation showed that all indicators except leaf length and leaf width had a high potential for genetic improvement. Therefore, five traits (seedling height (SH), ground diameter (GD), branch length (BL), petiole length (PL) and the total number of leaves (TNL)) were used as comprehensive index to select superior families, and a total of 20 superior families were selected. This study will lay a theoretical foundation and practical guidance for the genetic improvement of D. delavayi. [ABSTRACT FROM AUTHOR]

Camouflage is frequently used by animals for concealment and thereby improves survival. Typically, it is the animal's own colour and patterning that are expected to affect its detectability; however, the complexity of the background can also have an influence. Although there is a growing literature examining this, the underlying exact mechanism is unknown. In this study we addressed this issue by using humans as proxy 'predators' in a computer-based search task and monitoring their detection times for targets on varying backgrounds. By using artificial greyscale targets and backgrounds, we were able to isolate and manipulate the normally covarying factors that comprise 'complexity' in natural habitats. We show that reduced detection was explained not by greater information content (entropy) or higher variance in the background's features per se, but instead by reduced signal-to-noise ratio in the visual features that potentially distinguish target from background. This raises questions about when the term complexity should be used, and how observers learn the characteristics of a background. • Human detection time was examined on a greyscale computer-based search task. • Detection differences were not due to background information content or variance. • The SNR that potentially discerns target from background had the greater effect. • How observers learn the characteristics of a background is important to understand. • Caution should be used when using the term complexity. [ABSTRACT FROM AUTHOR]

Statistical downscaling of climate data has been widely described in the literature, with the aim of improving the reliability of local climatic parameters from coarse-resolution (often >20 km) global datasets. In this article, we present ClimateDT, a dynamic downscaling web tool for monthly historical and future time series at a global scale. The core of ClimateDT is the 1 km 1981–2010 climatology from CHELSA Climate (version 2.1), where the CRU-TS layers for the period 1901-current are overlayed to generate a historic time series. ClimateDT also provides future scenarios from CMIP5 using UKCP18 projections (rcp2.6 and rcp8.5) and CMIP6 using 5 GCMs, also available on the CHELSA website. The system can downscale the grids using a dynamic approach (scale-free) by computing a local environmental lapse rate for each location as an adjustment for spatial interpolation. Local predictions of temperature and precipitation obtained by ClimateDT were compared with climate time series assembled from 12,000 meteorological stations, and the Mean Absolute Error (MAE) and the explained variance (R2) were used as indicators of performance. The average MAEs for monthly values on the whole temporal scale (1901–2022) were around 1.26 °C for the maximum monthly temperature, 0.80 °C for the average monthly temperature, and 1.32 °C for the minimum monthly temperature. Regarding monthly total precipitation, the average MAE was 19 mm. As for the proportion of variance explained, average R2 values were always greater than 0.95 for temperatures and around 0.70 for precipitation due to the different degrees of temporal autocorrelation of precipitation data across time and space, which makes the estimation more complex. The elevation adjustment resulted in very accurate estimates in mountainous regions and areas with complex topography and substantially improved the local climatic parameter estimations in the downscaling process. Since its first release in November 2022, more than 1300 submissions have been processed. It takes less than 2 min to calculate 45 locations and around 8 min for the full dataset (512 records). [ABSTRACT FROM AUTHOR]

Performing joint genomic predictions for multiple breeds (MBGP) to expand the reference size is a promising strategy for improving the prediction for limited population sizes or phenotypic records for a single breed. This study proposes an MBGP model—mbBayesAB, which treats the same traits of different breeds as potentially genetically related but different, and divides chromosomes into independent blocks to fit heterogeneous genetic (co)variances. Best practices of random effect (co)variance matrix priors in mbBayesAB were analyzed, and the prediction accuracies of mbBayesAB were compared with within-breed (WBGP) and other commonly used MBGP models. The results showed that assigning an inverse Wishart prior to the random effect and obtaining information on the scale of the inverse Wishart prior from the phenotype enabled mbBayesAB to achieve the highest accuracy. When combining two cattle breeds (Limousin and Angus) in reference, mbBayesAB achieved higher accuracy than the WBGP model for two weight traits. For the marbling score trait in pigs, MBGP of the Yorkshire and Landrace breeds led to a 6.27% increase in accuracy for Yorkshire validation using mbBayesAB compared to that using the WBGP model. Therefore, considering heterogeneous genetic (co)variance in MBGP is advantageous. However, determining appropriate priors for (co)variance and hyperparameters is crucial for MBGP. [ABSTRACT FROM AUTHOR]

Assortative mating – the non-random mating of individuals with similar traits – is known to increase trait-specific genetic variance and genetic similarity between relatives. However, empirical evidence is limited for many traits, and the implications hinge on whether assortative mating has started recently or many generations ago. Here we show theoretically and empirically that genetic similarity between relatives can provide evidence on the presence and history of assortative mating. First, we employed path analysis to understand how assortative mating affects genetic similarity between family members across generations, finding that similarity between distant relatives is more affected than close relatives. Next, we correlated polygenic indices of 47,135 co-parents from the Norwegian Mother, Father, and Child Cohort Study (MoBa) and found genetic evidence of assortative mating in nine out of sixteen examined traits. The same traits showed elevated similarity between relatives, especially distant relatives. Six of the nine traits, including educational attainment, showed greater genetic variance among offspring, which is inconsistent with stable assortative mating over many generations. These results suggest an ongoing increase in familial similarity for these traits. The implications of this research extend to genetic methodology and the understanding of social and economic disparities. Non-random mating can complicate genetic studies, but implications hinge on its history in prior generations. Here, the authors use genetic similarity between relatives to investigate which traits show evidence of recent changes in mating behavior. [ABSTRACT FROM AUTHOR]

Climate change-induced pan-financial market and the contagion of systemic financial risks are becoming important issues in the financial sector. The paper measures the temperature difference in terms of the degree and direction of deviation of the actual temperature relative to the average temperature of the same historical period. Based on the high-dimensional time-series variable LASSO-VAR-DY framework, we construct a pan-financial market volatility correlation network consisting of 112 Chinese listed companies in banking, insurance, securities, real estate, traditional energy, and new energy, use eigenvector centrality to measure the systematic risk of each firm, and then empirically test the effect of temperature difference on systematic risk under pan-financial market scenario. The results of the study show that (ⅰ) There is a significant difference among the systemic risk of financial sectors such as banking, insurance, and securities in the financial market pan-financial market scenario and the systemic risk when the financial market pan-financial market is not taken into account;(ⅱ) Higher temperature significantly exacerbates systemic financial risk, while colder temperature significantly mitigates systemic risk, but both have an asymmetric effect on systemic risk, and there is sectoral heterogeneity.(ⅲ) From the dynamic evolutionary characteristics, there are significant differences in the response of systemic financial risk to positive and negative temperature shocks;(iv) The results of the systemic risk variance decomposition indicate that the temperature change contributes more to the variance of systemic risk in the banking and securities sectors in pan-financial market;(ⅴ) The contagion source of financial systemic risk shows an obvious path of leaping and changing characteristics, and the contagion source of systemic risk (source of impact) shows the evolution law of "bank → real estate → new energy → temperature difference," which means that the temperature difference has become the contagion source of systemic financial risk. This study provides a reference for preventing and resolving systemic risks under pan-financial market scenario and provides a basis for improving the current macroprudential regulatory framework. [ABSTRACT FROM AUTHOR]

Given the universality of autopolyploid species in nature, it is crucial to develop genomic selection methods that consider different allele dosages for autopolyploid breeding. However, no method has been developed to deal with autopolyploid data regardless of the ploidy level. In this study, we developed a modified genomic best linear unbiased prediction (GBLUP) model (polyGBLUP) through constructing additive and dominant genomic relationship matrices based on different allele dosages. polyGBLUP could carry out genomic prediction for autopolyploid species regardless of the ploidy level. Through comprehensive simulations and analysis of real data of autotetraploid blueberry and guinea grass and autohexaploid sweet potato , the results showed that polyGBLUP achieved higher prediction accuracy than GBLUP and its superiority was more obvious when the ploidy level of autopolyploids is high. Furthermore, when the dominant effect was added to polyGBLUP (polyGDBLUP), the greater the dominance degree, the more obvious the advantages of polyGDBLUP over the diploid models in terms of prediction accuracy, bias, mean squared error and mean absolute error. For real data, the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population due to the high correlation coefficients between diploid and polyploidy genomic relationship matrices. In addition, polyGDBLUP did not produce higher prediction accuracy than polyGBLUP for most traits of real data as dominant genetic variance was not captured for these traits. Our study will be a significant promising method for genomic prediction of autopolyploid species. [ABSTRACT FROM AUTHOR]

We consider a non-inferiority test conducted in the three-arm trials with coefficient of variations (CV) in sample means. A procedure for this non-inferiority test is proposed based on the generalized p-value (GPV) based method under normality assumption and heteroskedasticity. We demonstrated that first, the GPV-based method outperforms the comparable alternative, the Delta method in terms of empirical sizes and powers. Second, under GPV-based method, when the population mean of groups in the trial is estimated by the sample mean with CV, the empirical sizes control the significance level better than when CV is not included, especially when the ratio of the variance of the reference group to that of the experimental group and the ratio of the variance of the placebo group to that of the experimental group are not too small and that the sample size is small. Third, when the CV is included in the sample mean, the empirical powers are always higher, regardless of the sample size and methods. Additionally, when the data violates the normality assumption, it is found that the proposed GPV-based method in conjunction with CV appear to be highly acceptable through simulation results. Finally, the proposed method is illustrated with two data examples. [ABSTRACT FROM AUTHOR]

In this study, we have proposed memory-type ratio and product estimators for the estimation of population variance based on exponentially weighted moving averages (EWMA) statistic. The EWMA statistic simultaneously utilizes the current and previous information in time-scaled surveys. The equations of approximate mean square errors are established for proposed memory-type ratio and product estimators. The performance of the proposed estimators is evaluated mathematically by deriving the conditions in which memory-type ratio and product estimators are better than the conventional ratio and product estimators. The results of simulation study and real data application revealed that the use of previous sampled information excels the efficiency of the proposed estimators for time-scaled surveys. [ABSTRACT FROM AUTHOR]

Quantifying ecosystem resilience to disturbance is important for understanding the effects of disturbances on ecosystems, especially in an era of rapid global change. However, there are few studies that have used standardized experimental disturbances to compare resilience patterns across abiotic gradients in real-world ecosystems. Theoretical studies have suggested that increased return times are associated with increasing variance during recovery from disturbance. However, this notion has rarely been explicitly tested in field, in part due to the challenges involved in obtaining long-term experimental data. In this study, we examined resilience to disturbance of 12 coastal marsh sites (five low-salinity and seven polyhaline [=salt] marshes) along a salinity gradient in Georgia, USA. We found that recovery times after experimental disturbance ranged from 7 to >127 months, and differed among response variables (vegetation height, cover and composition). Recovery rates decreased along the stress gradient of increasing salinity, presumably due to stress reducing plant vigor, but only when low-salinity and polyhaline sites were analyzed separately, indicating a strong role for traits of dominant plant species. The coefficient of variation of vegetation cover and height in control plots did not vary with salinity. In disturbed plots, however, the coefficient of variation (CV) was consistently elevated during the recovery period and increased with salinity. Moreover, higher CV values during recovery were correlated with slower recovery rates. Our results deepen our understanding of resilience to disturbance in natural ecosystems, and point to novel ways that variance can be used either to infer recent disturbance, or, if measured in areas with a known disturbance history, to predict recovery patterns. [ABSTRACT FROM AUTHOR]

BACKGROUND: Visual vertigo (VV) is a disease characterized by various visual signal-induced discomforts, including dizziness, unsteady balance, activity avoiding, and so forth. Distinguishing it from other kinds of dizziness is important because it needs the combination of visual training and vestibular rehabilitation together. However, there is no appropriate tool to diagnose VV in China, thus we would like to introduce an effective tool to China. OBJECTIVE: The aim of this study was to establish the reliability and validity of the Chinese version of visual vertigo analogue scale (VVAS-CH) and to achieve its cross-cultural adaptation in order to promote its further usage in China. METHODS: A total of 1681 patients complaining of vertigo or dizziness were enrolled and they were asked to complete the VVAS-CH. The cross-cultural adaptation, reliability and construct validity of the VVAS-CH were determined. RESULTS: Split-half reliability was 0.939, showing a good reliability. Factor analysis identified only one common factor for the nine items that explained 64.83% of the total variance. Most fit indices reached acceptable levels, proving the good fit of the VVAS-CH model. CONCLUSIONS: The VVAS-CH validated in this study can be used as an effective tool for diagnosing and evaluating VV in patients whose native language is Chinese. [ABSTRACT FROM AUTHOR]

Gestation length (GL) can potentially affect health and performance of both the dam and the newborn calf, and it is controlled by two genetic components, direct and maternal. This means that both the calf (direct effect) and the cow (maternal effect) genotypes contribute to determine GL and its variability. The aims of the present study were to estimate direct and maternal variance components of GL, develop a routine genetic evaluation of GL in Italian Holstein and evaluate potential (un)favourable associations with traits for which selection is undertaken in this population. A multiple‐trait repeatability linear animal model was employed for the estimation of variance components considering GL in first and later parities as different traits. The posterior mean (PM) of heritability of the direct effect was 0.43 for first parity and 0.35 for later parities. The PM of heritability of the maternal effect was lower, being 0.08 for primiparae and 0.06 for pluriparae. The posterior standard deviation (PSD) of the heritability estimates was small, ranging from 0.001 to 0.005. The relationship of direct and maternal effects with important traits such as milk yield and fertility indicated that selecting for extreme GL, longer or shorter, may have negative consequences on several traits, suggesting that GL has an intermediate optimum in dairy cattle. In conclusion, this study reveals that selecting an intermediate GL in the Italian Holstein population is advisable. Although scarcely variable compared to other conventional traits for which Italian Holstein is selected, GL is heritable and a deeper knowledge can be useful for decision‐making at the farm level. [ABSTRACT FROM AUTHOR]

The article presents the author's views on the dealer hedging strategy in Black-Scholes-Merton valuation for equity call options where dealer risk relative to hedge re-balance period Δt, confirming zero variance in Profit and Loss as Δt approaches zero, revealing substantial risk dependence on Δt for practical values. It mentions the creation of a simple model to test and portray risk-neutral derivative valuation, which was named "hedge strategy model."