Evaluation of vertical and multi-axial suspension seats for reducing vertical-dominant and multi-axial whole body vibration and associated neck and low back joint torque and muscle activity

The primary aim of this laboratory-based human subject study was to evaluate the biomechanical loading associated with mining vehicles' multi-axial whole body vibration (WBV) by comparing joint torque and muscle activity in the neck and low back during three vibration conditions: mining vehicles' multi-axial, on-road vehicles' vertical-dominant, and no vibration. Moreover, the secondary aim was to determine the efficacy of a vertical passive air suspension and a prototype multi-axial active suspension seat in reducing WBV exposures and associated biomechanical loading measures. The peak joint torque and muscle activity in the neck and low back were higher when exposed to multi-axial vibration compared to the vertical-dominant or no vibration condition. When comparing the two suspension seats, there were limited differences in WBV, joint torque, and muscle activity. These results indicate that there is a need to develop more effective engineering controls to lower exposures to multi-axial WBV and related biomechanical loading. Practitioner Summary: This study found that mining vehicles' multi-axial WBV can increase biomechanical loading in the neck and back more so than on-road vehicles' vertical-dominant WBV. While a newly-developed multi-axial active suspension seat slightly reduced the overall WBV exposures, the results indicate that more effective engineering controls should be developed. Abbreviation: APDF: amplitude probability density function; Aw: weighted average vibration; BMI: body mass index; C7: The 7th cervical vertebra; EMG: electromyography; ES: erector spinae; IRB: institutional review board; ISO: International Organization for Standardization; L5/S1: the fifth lumbar vertebra (L5)/the first sacral vertebra(S1); MSDs: musculoskeletal disorders; MVC: maximum voluntary contraction; PSD: power spectral density; RVC: reference voluntary contraction; SCM: sternocleidomastoid; SD: standard deviation; SPL: splenius capitis; TRAP: trapezius; VDV: vibration dose value; WBV: whole body vibration.

An efficient technique for Bayesian modeling of family data using the BUGS software

Linear mixed models have become a popular tool to analyze continuous data from family-based designs by using random effects that model the correlation of subjects from the same family. However, mixed models for family data are challenging to implement with the BUGS (Bayesian inference Using Gibbs Sampling) software because of the high-dimensional covariance matrix of the random effects. This paper describes an efficient parameterization that utilizes the singular value decomposition of the covariance matrix of random effects, includes the BUGS code for such implementation, and extends the parameterization to generalized linear mixed models. The implementation is evaluated using simulated data and an example from a large family-based study is presented with a comparison to other existing methods.

Genome-wide association study of personality traits in the long life family study

Personality traits have been shown to be associated with longevity and healthy aging. In order to discover novel genetic modifiers associated with personality traits as related with longevity, we performed a genome-wide association study (GWAS) on personality factors assessed by NEO-five-factor inventory in individuals enrolled in the Long Life Family Study (LLFS), a study of 583 families (N up to 4595) with clustering for longevity in the United States and Denmark. Three SNPs, in almost perfect LD, associated with agreeableness reached genome-wide significance (p < 10⁻⁸) and replicated in an additional sample of 1279 LLFS subjects, although one (rs9650241) failed to replicate and the other two were not available in two independent replication cohorts, the Baltimore Longitudinal Study of Aging and the New England Centenarian Study. Based on 10,000,000 permutations, the empirical p-value of 2 × 10⁻⁷ was observed for the genome-wide significant SNPs. Seventeen SNPs that reached marginal statistical significance in the two previous GWASs (p-value <10⁻⁴ and 10⁻⁵), were also marginally significantly associated in this study (p-value <0.05), although none of the associations passed the Bonferroni correction. In addition, we tested age-by-SNP interactions and found some significant associations. Since scores of personality traits in LLFS subjects change in the oldest ages, and genetic factors outweigh environmental factors to achieve extreme ages, these age-by-SNP interactions could be a proxy for complex gene–gene interactions affecting personality traits and longevity.