Large Coefficient Of Variation Research Articles

A special Tweedie sub-family with application to loss reserving prediction error

The paper is concerned with a particular sub-family of the Tweedie family of distributions characterized by a constant mean-to-variance ratio (“CMVR”). The properties of the CMVR sub-family are explored. Some of these, concerned with addition of CMVR variates, are well adapted to the treatment of insurance losses and loss reserves. The tricky issue of parameter estimation within the CMVR Tweedie family is investigated. This family is applied to the estimation of the prediction error associated with a loss reserve, especially the model distribution error component of the prediction error. The model distribution error is the error in the loss reserve that arises from the wrong choice of distribution of observations. This is considered within the Tweedie family of distributions, examining the prediction error that occurs when one value of the Tweedie dispersion parameter p is correct, but a different one is assumed in the modelling a claim array. The study is carried out under the CMVR condition across all cells of the array, a condition that is found commonly compatible with real data sets. The main result of the paper is that, when cells have relatively large coefficients of variation under the CMVR condition, and the array can be modelled with a GLM, the MSEP of the loss reserve is relatively insensitive to the value of p. This implies that model distribution error can often be dismissed as small in many situations where MSEP of loss reserve is the measure of interest.

Reliability Analysis of Soil Liquefaction Considering Spatial Variability of Soil Property

The objective of this study was to investigate the liquefaction response of soil using the spatial variability of the shear modulus by considering different values of the coefficient of variation (COV) and the horizontal scale of fluctuation (SOF). For this purpose, a Monte Carlo simulation, combining the digital generation of a non-Gaussian random field with finite difference analyses, was utilized. Parametric studies were performed from the perspectives of the liquefaction area, excess pore water pressure (EPWP), and displacement at the ground surface. We found that a larger COV of the soil shear modulus was correlated with a slower reduction of liquefaction area and a lower EPWP ratio. To explain the influence from the perspective of the spatial distribution characteristics of the shear modulus, a deterministic model test was carried out. Additionally, it was found that the displacement history and the differential settlement at the end of shaking were regularly affected by the COV and the horizontal SOF, especially for large COV and horizontal SOF.

On ratio measures of heterogeneity for meta-analyses.

As a measure of heterogeneity in meta-analysis, the coefficient of variation (CV) has been recently considered, providing researchers with a complement to the very popular measure. While measures the proportion of total variance that is due to variance of the random effects, the CV is the ratio of the standard deviation of the random effects to the effect of interest. Consequently, the CV provides a different measure of the extent of heterogeneity in a meta-analysis relative to the effect being measured. However, very large CV values can occur when the effect is small making interpretation difficult. The purpose of this article is two-fold. First, we consider variants of the CV that exist in the interval which may be preferable for some researchers. Second, we provide interval estimators for the CV and its variants with excellent coverage properties. We perform simulation studies based on simulated and real data sets and draw comparisons between the methods. For both the CV and its transformations, we recommend confidence intervals using the propagating imprecision method or, as a simpler alternative but at the expense of slightly worse performance in terms of coverage, combining reduced-coverage confidence intervals for the two parameters. These interval estimators typically have better coverage properties for the CV measure than those previously considered.

Changes in intersegmental stability during gait in patients with spastic cerebral palsy.

Dysfunction in peripheral and neural structure with spastic cerebral palsy (CP) causes impaired performance and stability of various behaviors. Recent progress of quantification methods for the stability properties, which is based on the uncontrolled manifold hypothesis, has been applied to various neurological disorders. A prior study revealed that the ability for purposeful regulation of stability properties is weakened with CP during finger and hand actions. Successive regulation of stability properties is crucial for human locomotion; therefore, it is imperative to quantify the changes in the intersegmental coordination as to the stable performance in CP individuals during gait. We hypothesized that (1) Spastic CP group will show smaller step length and gait velocity with larger variability, and (2) Spastic CP group will show no changes in average stability indices for both the COM and head position stabilization, while the smaller difference between stable and unstable posture during the gait cycle. Whole-body kinematic data during walking were collected from CP and control subjects. Step length, velocity, and coefficient of variation (CV) were calculated as spatiotemporal parameters. We quantified the intersegmental stability index in time-series during gait for the stabilization of the whole-body COM and head position. The CP subjects showed smaller step length and velocity with larger CV than the controls. However, the CP group showed a significantly less difference in the stability indices between the single- and double-limb support phases as compared to the controls for both the COM and head position stabilization. Present study is the first to document the quantification of changing intersegmental stability in the spastic CP during locomotion. The dysfunction of intentional modulation of stability properties in CP individuals may be a more common problem, which is not limited to a specific body effector.

Should We Lose Sleep Over Sleep Disturbances After Sports-Related Concussion? A Scoping Review of the Literature.

A single, severe traumatic brain injury can result in chronic sleep disturbances that can persist several years after the incident. In contrast, it is unclear whether there are sleep disturbances after a sports-related concussion (SRC). Considering growing evidence of links between sleep disturbance and neurodegeneration, this review examined the potential links between diagnosed SRCs and sleep disturbances to provide guidance for future studies. The scoping review undertook a systematic search of key online databases (Scopus, MEDLINE, SportDiscus, and Web of Science) using predetermined search terms for any articles that examined sleep after concussion. A screening criterion using agreed inclusion and exclusion criteria was utilized to ensure inclusion of relevant articles. This scoping review is guided by the PRSIMA Scoping Review report. Ten studies met the inclusion criteria, reporting on 896 adults who had experienced an SRC. Comparison with 1327 non-SRC adults occurred in 8 studies. Nine studies subjectively examined sleep, of which all but one study reported sleep disturbances after an SRC. Three studies objectively measured sleep, with 2 studies indicating large coefficients of variation of sleep duration, suggesting a range of sleep responses after an SRC. The only study to examine overnight polysomnography showed no differences in sleep metrics between those with and without an SRC. No studies examined interventions to improve sleep outcomes in people with concussion. This scoping review indicates preliminary evidence of sleep disturbances following an SRC. The heterogeneity of methodology used in the included studies makes consensus on the results difficult. Given the mediating role of sleep in neurodegenerative disorders, further research is needed to identify physiological correlates and pathological mechanisms of sleep disturbances in SRC-related neurodegeneration and whether interventions for sleep problems improve recovery from concussion and reduce the risk of SRC-related neurodegeneration.

Reliability of 2D kinematics during landing of volleyball athletes after exhaustion

IntroductionIt is possible to quantify changes in movement patterns through kinematic analysis of landing, especially to quantify changes in pre and post exhaustion situations, however the reliability of this post exhaustion analysis is not known. ObjectiveTo verify the inter and intra-examiner reliability of two-dimensional kinematic analysis during the landing of a vertical jump of volleyball athletes, pre and post exhaustion protocol. ExperimentalThirty volleyball athletes were recruited, and kinematic analysis was performed during landing, pre and post exhaustion protocol. The angular measurements analyzed were: 1) frontal plane: knee valgus and 2) sagittal plane: anterior trunk inclination, knee flexion and tibiotarsal angle, performed by two examiners. The reliability calculation used the intraclass correlation coefficient (ICC), in addition to the error of measurement (SEM), the coefficient of variation (CV) and the minimum detectable difference (MDD). ResultsRegarding reliability: ICC = 0.95–0.98 (pre) and ICC = 0.83–0.98 (post exhaustion). The CV presented heterogeneous values for the knee valgus and the inclination of the trunk, both pre and post protocol. The SEM from all angles presented values that varied from 0.74°-2.33° and the MDD ranged from 2.55°-5.54° pre protocol and 2.05°-6.45° post protocol. Conclusion2D kinematic evaluation can be used during landing, before and after the application of an exhaustion protocol, but professionals should pay attention to the angles of the knee valgus and the inclination of the trunk, as they have a large CV.

New approach to determine the healthy immune variations by combining clustering methods

Immune-mediated inflammatory diseases are characterized by variability in disease presentation and severity but studying it is a challenging task. Defining the limits of a healthy immune system is therefore a prior step to capture variability in disease conditions. The goal of this study is to characterize the global immune cell composition along with their influencing factors. Blood samples were collected from 2 independent cohorts of respectively 389 (exploratory) and 208 (replication) healthy subjects. Twelve immune cells were measured in blood together with biological parameters. Three complementary clustering approaches were used to evaluate if variability related to the immune cells could be characterized as clusters or as a continuum. Large coefficients of variation confirmed the inter-individual variability of immune cells. Considering all subset variations in an overall analysis, it appeared that the immune makeup was organized as a continuum through the two cohorts. Some intrinsic and environmental factors affected the inter-individual variability of cells but without unveiling separable groups with similar features. This study provides a framework based on complementary clustering approach for analyzing inter-individual variability of immune cells. Our analyses support the absence of clusters in our two healthy cohorts. Also, our study reports some influence of age, gender, BMI, cortisol, season and CMV infection on immune variability.

GENES MEDIATING CELL GROWTH IN ALDOSTERONE-PRODUCING ADENOMAS

Objective: Aldosterone-producing adenomas (APA) are a major cause of primary aldosteronism. Somatic mutations explain the excess aldosterone production in the majority of patients with APA with mutations in KCNJ5 encoding a potassium channel the most prevalent in most reported populations. Mechanisms driving cell proliferation are largely undefined. Design and method: Quantitative transcriptome analysis using RNA-seq was used to identify differentially expressed genes between macro-APAs (n = 9, diameter >= 30 mm) and micro-APAs (n = 12, diameter <= 10 mm). Validation of RNA-seq data by TaqMan real-time PCR was performed for 14 genes in a broader cohort of APAs (NMD, no mutation detected, n = 28; KCNJ5-mutated, n = 43). Results: Hierarchical cluster analysis of the 500 genes with largest coefficient of variation indicated sample clustering based on genotype (KCNJ5 or NMD) and APA diameter. Differential expression of 155 and 348 genes was found between micro- and macro-APAs with KCNJ5 mutations and NMD, respectively. Among the top 5 overrepresented Gene Ontology terms (biological process), cell death was exclusively enriched in NMD micro- vs NMD macro-APAs. The expression levels of 10 genes were validated with a potential function related to cell growth. Expression of BEX1 (a reported tumour suppressor) was 2.8-fold down regulated in macro-APAs relative to micro-APAs (P < 0.001), and a linear negative correlation of BEX1 expression with APA diameter was observed in NMD APAs (r = -0.501, P = 0.007). Genes involved in beta-catenin signalling, SFRP2, DKK1 and TSPAN12 were 5.9-fold (P < 0.001), 1.8-fold (P = 0.007) and 8.3-fold (P < 0.0001) down regulated, respectively, in macro-APAs compared with micro-APAs. BAI1 and CCL21 were also down regulated in macro-APAs relative to micro-APAs (3.3-fold, P = 0.026; 2.6-fold, P = 0.145, respectively). Additionally, the expression of TMPRSS3 (r = 0.727, P < 0.001), BMP4 (r = 0.389, P = 0.041) and FBXL21 (r = 0.761, P < 0.001) showed a linear positive correlation with adenoma diameter in NMD subgroup. Conclusions: APA display distinct transcriptome profiles according to adenoma diameter which may help identify genes involved in APA tumour cell growth.

Experimental study for the establishment of a chemotherapy-induced ovarian insufficiency model in rats by using cyclophosphamide combined with busulfan

With an improvement in the survival rate of cancer patients, chemotherapy-induced premature ovarian insufficiency (POI) is increasingly affecting the quality of life of female patients. Currently, there are many relevant studies using mice as an animal model. However, a large coefficient of variation for weight in mice is not appropriate for endocrine-related studies, compared with rats; therefore, it is necessary to identify an appropriate experimental model in rats. In this study, cyclophosphamide combined with busulfan was used to establish an animal model. We compared several common modeling methods using chemotherapeutic drugs, cisplatin, cyclophosphamide, and 4-vinylcyclohexene diepoxide (VCD), and we found that the combination of cyclophosphamide and busulfan was more effective in establishing a POI model in rats with few side effects by analyzing general physical conditions, pathological tissue sections of heart, liver, lung, spleen, kidney, uterus, and ovary, serum hormone levels, and follicle counts; thus, providing a more reliable model basis for subsequent studies.

Pooled Versus Individualized Load-Velocity Profiling in the Free-Weight Back Squat and Power Clean.

This study compared pooled against individualized load-velocity profiles (LVPs) in the free-weight back squat and power clean. A total of 10 competitive weightlifters completed baseline 1-repetition maximum assessments in the back squat and power clean. Three incremental LVPs were completed, separated by 48 to 72 hours. Mean and peak velocity were measured via a linear-position transducer (GymAware). Linear and nonlinear (second-order polynomial) regression models were applied to all pooled and individualized LVP data. A combination of coefficient of variation (CV), intraclass correlation coefficient, typical error of measurement, and limits of agreement assessed between-subject variability and within-subject reliability. Acceptable reliability was defined a priori as intraclass correlation coefficient > .7 and CV < 10%. Very high to practically perfect inverse relationships were evident in the back squat (r = .83-.96) and power clean (r = .83-.89) for both regression models; however, stronger correlations were observed in the individualized LVPs for both exercises (r = .85-.99). Between-subject variability was moderate to large across all relative loads in the back squat (CV = 8.2%-27.8%) but smaller in the power clean (CV = 4.6%-8.5%). The power clean met our criteria for acceptable reliability across all relative loads; however, the back squat revealed large CVs in loads ≥90% of 1-repetition maximum (13.1%-20.5%). Evidently, load-velocity characteristics are highly individualized, with acceptable levels of reliability observed in the power clean but not in the back squat (≥90% of 1-repetition maximum). If practitioners want to adopt load-velocity profiling as part of their testing and monitoring procedures, an individualized LVP should be utilized over pooled LVPs.

Failure and reliability analysis of scarf-repaired CFRP: effect of hot–wet environment

Scarf repair method which can get uniform stress distributions and smooth surfaces has emerged as an adequate technique to repair damaged aerospace composite components. However, a prominent problem with the use of scarf-repaired structures is their susceptibility to environmental conditions. This research deals with the failure and reliability analysis of scarf-repaired carbon fiber-reinforced polymer composites (CFRP) before and after aged in hot–wet environment. Scarf-repaired CFRP with different laminate thicknesses was tested to investigate the failure strength and damage modes. The results indicate that the strength reduction of scarf-repaired CFRP varies with the laminate thickness (13.4–7.9%) because of different moisture contents. Fracture observations reveal that the decrease in load-bearing capacity of scarf-repaired CFRP is mainly due to the degradation of adhesive layer. Subsequently, theoretical models based on the distribution function of experimental results were established to predict the safe design strength at different reliability and confidence levels. It is shown that reliability has a greater effect on the safe design strength of both unaged and aged specimens than confidence level. A higher penalty paid to get high-reliability strength (R = 0.99, γ = 0.99) is observed for the unaged specimen, which has a larger coefficient of variation.

Polyphenolic Components and Composition Differences of Fruit Polyphenols in Apple Landraces Grown in Cold Regions

The composition and content of polyphenols in fruit pericarp and pulp &nbsp;of 12 Apple landraces grown &nbsp;of Heilongjiang Province were determined by ultra-high performance liquid chromatography (UPLC), and the differences in the composition and content characteristics of polyphenols in different varieties were studied, and the main factor analysis and cluster analysis were carried out. The results showed that 5 kinds of 20 kinds of polyphenols were detected in 12 Apple landraces , the main phenolic substances in pericarp were epicatechin and catechin, and the main phenolic substances in pulp were chlorogenic acid, catechin and procyanidin. There were significant differences in the composition and content of polyphenols among different varieties, the smallest coefficient of variation was quercetin 3-glucoside (37.48%), and the largest coefficient of variation was rutin (267.18%). It was found that the content of proanthocyanidins in pericarp and pulp was higher by principal component analysis. Based on the content of polyphenol components, it was found that the results of pulp clustering were more consistent with the field phenotypic identification results and kinship. The results provide data support and theoretical basis for processing and utilization of phenolic substances and breeding of local varieties in Heilongjiang province.

Research for Biochemical Components of Sun-dried Green Tea in Different Tea Areas of Yunnan by Using PCA and Cluster Analysis Methods

This paper was to study the biochemical components and groups differences among 28 tea samples from different tea regions in yunnan. The biochemical components of 28 tea samples were analyzed by conventional method and high performance liquid chromatography. Principal component analysis and cluster analysis were used to classify 28 tea samples.The results showed that the mainly biochemical components of 28 tea samples,which included catechinepicatechin and epigallocatechin had large variation coefficients,56.88%,36.41% and 49.52%,respectively. The diversity index was 1.91,1.91 and 1.97,respectively. All above explained the characteristics of the samples in biochemical components were more abundant in the composition and performance of non-galloylatedcatechins. The samples were divided into 6 groups by cluster analysis,there were some differences in the content of biochemical components between the groups.

Web-Based Software for Small Area Estimation under Unit Level Model

The purpose of this paper is to produce reasonably accurate direct estimators, not only for the characteristics of whole Population but also for a variety of Subpopulations or domains. Many policymakers and researchers also want to obtain statistics for small domains. These small domains are also called small areas, because the sample size in the area or domain from the Survey is small. Due to small sample size, domain-specific direct estimators provide an acceptably large coefficient of variation. Therefore, it becomes necessary to employ indirect small area estimators that make use of the sample data from related areas or domains through linking models, and this increases the effective sample size in the small areas. Such estimators can provide significantly smaller coefficient of variation than direct estimators, provided the linking models are valid. In this paper, a web-based software for small area estimation Under unit level model has been developed But this doesn’t include the Unit level effects in the model. This software will help the researchers, academicians, data analysts, Students and other domain groups who have been working in area of the SAE.

Urinary steroid profile in relation to the menstrual cycle.

The interpretation of the steroidal module of the Athlete Biological Passport (ABP) in female athletes is complex due to the large variation of the endogenous urinary steroids. The menstrual cycle seems to be one of the largest confounders of the steroid profile. The duration of the different phases in the menstrual cycle differs between women and is difficult to predict only by counting days after menstruation. Here, we have determined the follicle, ovulation, and luteal phases, by assessing the menstrual hormones in serum samples collected from 17 healthy women with regular menses. Urine samples were collected three times per week during two consecutive cycles to measure the urinary steroid concentrations used in the ABP.The metabolite that was mostly affected by the menstrual phases was epitestosterone (E), where the median concentration was 133% higher in the ovulation phase compared to the follicle phase (p < 0.0001). The women with a large coefficient of variation (CV) in their first cycle also had a large CV in their second cycle and vice versa. The inter‐individual difference was extensive with a range of 11%–230% difference between the lowest and the highest T/E ratio during a cycle.In conclusion, E and ratios with E as denominator are problematic biomarkers for doping in female athletes. The timing of the sample collection in the menstrual cycle will have a large influence on the steroid profile. The results of this study highlight the need to find additional biomarkers for T doping in females.

Contamination, Spatial Distribution and Source Analysis of Heavy Metals in Surface Soil of Anhui Chaohu Economic Development Zone, China

Anthropogenic activities may result in the accumulation of heavy metals in the soil, especially in economic development zones with frequent industrial activities. Therefore, the investigation and assessment of soil heavy metal pollution in economic development zones is one of the important measures for soil environmental management and sustainable development. This study used Nemero evaluation, Kriging interpolation, cluster analysis, and principal component analysis to investigate the contamination degree, spatial distribution, and origin of heavy metal in Anhui Chaohu Economic Development Zone (ACED), Anhui, East China. The result showed that different land use types can cause different levels and types of soil heavy metal pollution. The maximum concentrations of heavy metals in the study area all exceeded their background value but did not exceed the guide values. The highest average concentrations were found in Zn, followed by Cr and Ni. The concentrations of As in soils have the largest coefficient of variation (CV) at 38%. The concentration of heavy metals in different functional areas was varied, the areas with higher Ni, As, Cd, Zn, and Cr concentrations were mainly distributed in Hot Springs Resort (HSR), the relatively higher concentrations of Pb, Hg, and Cu were mainly distributed in Integrated Zone (IZ), while all heavy metal (except for Ni) have relatively higher content in the surface soil of Huashan Industrial Zone (HIZ). Origin analysis showed that soil As, Cd, and Zn in HSR surface soil were predominantly influenced by agricultural activities, while Ni and Cr were mainly controlled by parent material. Pb and Hg in IZ surface soil were predominantly originated from the vehicle and domestic exhaust, and Cu was mainly controlled by industrial pollutants. Industrial activity was the main source of soil heavy metals in HIZ. Although heavy metal in ACED surface soil did not reach pollution levels, the concentration of Cd, Hg, Pb, and Cu was significantly affected by anthropogenic activities, especially in HIZ, which the necessary attention of heavy metals needs to be given.

Comparison of the Meibomian Gland Openings by Optical Coherence Tomography in Obstructive Meibomian Gland Dysfunction and Normal Patients.

Purpose: The aim of this study was to use swept-source anterior segment optical coherence tomography (OCT) to explore imaging the meibomian gland openings and to identify their in vivo characteristics in patients with obstructive meibomian gland dysfunction (MGD) and healthy participants. Methods: We enrolled 49 patients with MGD and 54 health controls in this case-control study. Each participant underwent slit-lamp examination, meibography, and OCT scanning. Sixteen patients with MGD underwent a repeat OCT examination after eyelid massage. The outcome measures included determinations of meibomian gland openings (orifices and terminal ducts) from OCT images and comparisons of the meibomian openings between patients with MGD and normal controls before and after meibomian gland massage. Results: Using the same OCT scanning model, the number of visible orifices of the meibomian glands was similar between eyes with MGD and normal eyes (9.2 ± 2.3 vs. 9.7 ± 2.4). The mean diameter of the terminal ducts in patients with MGD was larger (120.22 ± 27.92 µm vs. 100.96 ± 20.30 µm) than in the normal controls, and had a larger coefficient of variation. Significant differences were observed in the mean diameter of the terminal ducts of patients with MGD before and after meibum gland massage (133.73 ± 27.81 μm vs. 102.26 ± 24.30 μm, p < 0.001). Conclusions: Patients with MGD have more diversified orifices and larger meibomian gland terminal duct diameters than normal subjects. In addition, meibomian gland terminal duct diameters seem to decrease in patients with MGD after meibum gland massage.

Confidence intervals for the common coefficient of variation of rainfall in Thailand.

The log-normal distribution is often used to analyze environmental data like daily rainfall amounts. The rainfall is of interest in Thailand because high variable climates can lead to periodic water stress and scarcity. The mean, standard deviation or coefficient of variation of the rainfall in the area is usually estimated. The climate moisture index is the ratio of plant water demand to precipitation. The climate moisture index should use the coefficient of variation instead of the standard deviation for comparison between areas with widely different means. The larger coefficient of variation indicates greater dispersion, whereas the lower coefficient of variation indicates the lower risk. The common coefficient of variation, is the weighted coefficients of variation based on k areas, presents the average daily rainfall. Therefore, the common coefficient of variation is used to describe overall water problems of k areas. In this paper, we propose four novel approaches for the confidence interval estimation of the common coefficient of variation of log-normal distributions based on the fiducial generalized confidence interval (FGCI), method of variance estimates recovery (MOVER), computational, and Bayesian approaches. A Monte Carlo simulation was used to evaluate the coverage probabilities and average lengths of the confidence intervals. In terms of coverage probability, the results show that the FGCI approach provided the best confidence interval estimates for most cases except for when the sample case was equal to six populations (k = 6) and the sample sizes were small (nI < 50), for which the MOVER confidence interval estimates were the best. The efficacies of the proposed approaches are illustrated with example using real-life daily rainfall datasets from regions of Thailand.

An nth high order perturbation-based stochastic isogeometric method and implementation for quantifying geometric uncertainty in shell structures

This paper presents an n-th high order perturbation-based stochastic isogeometric Kirchhoff–Love shell method, formulation and implementation for modeling and quantifying geometric (thickness) uncertainty in thin shell structures. Firstly, the Non-Uniform Rational B-Splines (NURBS) is used to describe the geometry and interpolate the variables in a deterministic aspect. Then, the shell structures with geometric (thickness) uncertainty are investigated by developing an nth order perturbation-based stochastic isogeometric method. Here, we develop the shell stochastic formulations in detail (particularly, expand the random input (thickness) and IGA Kirchhoff-Love shell element based state functions analytically around their expectations via n-th order Taylor series using a small perturbation parameterε), whilst freshly providing the Matlab core codes helpful for implementation. This work includes three key novelties: 1) by increasing/utilizing the high order of NURBS basis functions, we can exactly represent shell geometries and alleviate shear locking, as well as providing more accurate deterministic solution hence enhancing stochastic response accuracy. 2) Via increasing the nth order perturbation, we overcome the inherent drawbacks of first and second-order perturbation approaches, and hence can handle uncertainty problems with some large coefficients of variation. 3) The numerical examples, including two benchmarks and one engineering application (B-pillar in automobile), simulated by the proposed formulations and direct Monte Carlo simulations (MCS) verify that thickness randomness does strongly affect the response of shell structures, such as the displacement caused by uncertainty can increase up to 35%; Moreover, the proposed formulation is effective and significantly efficient. For example, compared to MCS, only 0.014% computational time is needed to obtain the stochastic response.

Genetic correlations for reproductive and growth traits in rabbits

The objective of this study was to obtain heritability estimates for reproductive (litter size at birth, number born alive, litter size at weaning) and growth traits (individual weaning weight, individual weight at the end of the fattening period), then determine the genetic correlation between them in a synthetic rabbit line. A total of 805 females, 3242 parities, and 18 472 growth records were measured from 2006 to 2017. A pentavariate animal model was used with reproductive and growth traits. Heritability ranged from 0.025 to 0.126 for reproductive traits and from 0.033 to 0.059 for growth traits. These traits showed a large coefficient of variation (from 32% to 56% for reproductive traits and from 21% to 28% for growth traits). The repeatability of reproductive traits was low and the common litter effect for growth traits was the most important component of total variance. The genetic and phenotypic correlations between reproductive and growth traits were high and negative, especially with weight at weaning (−0.848, −0.922, and −0.854 for litter size at birth, number born alive, and litter size at weaning, respectively). In conclusion, because of the high negative correlation between reproductive and growth traits, both reproductive and growth traits should be selected in independent lines and the response to selection should be due mainly to the high coefficient of variation of the traits.