Just Another Gibbs Additive Modeller: Interfacing JAGS and mgcv

The BUGS language offers a very flexible way of specifying complex statistical models for the purposes of Gibbs sampling, while its JAGS variant offers very convenient R integration via the rjags package. However, including smoothers in JAGS models can involve some quite tedious coding, especially for multivariate or adaptive smoothers. Further, if an additive smooth structure is required then some care is needed, in order to centre smooths appropriately, and to find appropriate starting values. R package mgcv implements a wide range of smoothers, all in a manner appropriate for inclusion in JAGS code, and automates centring and other smooth setup tasks. The purpose of this note is to describe an interface between mgcv and JAGS, based around an R function, `jagam', which takes a generalized additive model (GAM) as specified in mgcv and automatically generates the JAGS model code and data required for inference about the model via Gibbs sampling. Although the auto-generated JAGS code can be run as is, the expectation is that the user would wish to modify it in order to add complex stochastic model components readily specified in JAGS. A simple interface is also provided for visualisation and further inference about the estimated smooth components using standard mgcv functionality. The methods described here will be un-necessarily inefficient if all that is required is fully Bayesian inference about a standard GAM, rather than the full flexibility of JAGS. In that case the BayesX package would be more efficient.Comment: Submitted to the Journal of Statistical Softwar

Modeling the angle-specific isokinetic hamstring to quadriceps ratio using multilevel generalized additive models

This study considered the use of a generalized additive multilevel model to describe the joint-angle-specific functional hamstring to quadriceps ratio (H:Q ratio) in the knee, using all of the available truly isokinetic data within the range. Materials and Methods: Thirty healthy male basketball players aged 15.0 (1.4) years (average stature = 180.0 cm, SD = 11.1 cm; average body mass = 71.2, SD = 14.9 kg) years were considered. All players considered had no history of lower extremity musculoskeletal injury at the time of testing or during the 6 months before testing, and had been engaged in formal basketball training and competition for 5.9 (2.4) years. Moments of force of the reciprocal concentric and eccentric muscular actions for the knee extensors and flexors assessed by isokinetic dynamometry at 60 degrees .s(-1) were used. Results: Maximum moments of force were attained at different angle positions for knee extension. For knee flexion, it was apparent that there was an ability to maintain high levels of moment of force between 30 degrees and 60 degrees in the concentric muscular action, corresponding to the concentric action of the hamstrings. However, for the eccentric knee flexion, corresponding to the quadriceps action, there was a marked peak of moment of force at about 55 degrees. The functional H:Q ratio for the knee extension was non-linear, remaining higher than 1.0 (i.e., point of equality) from the beginning of the extension until approximately 40 degrees of the knee extension, leveling off below the point of equality thereafter. On average, the functional H:Q ratio for the knee flexion did not attain 1.0 across the range of motion. The functional H:Q ratio for the knee in the present sample peaked at 20 degrees and 80 degrees, declining between these angle positions to below 0.50 at about 0.54. Conclusions: Estimating the form of the non-linear relationship on-the-fly using a generalized additive multilevel model provides joint-angle-specific curves and joint-angle-specific functional H:Q ratio patterns, allowing the identification and monitoring of strength development, with potential implications for injury and performance558COORDENAÇÃO DE APERFEIÇOAMENTO DE PESSOAL DE NÍVEL SUPERIOR - CAPESsem informaçã

Using density surface models to estimate spatio-temporal changes in population densities and trend

Funding – Centre for Research into Ecological and Environmental Modelling, University of St Andrews and U.S. Geological Survey provided funding for this analysis through a studentship to RJC.Precise measures of population abundance and trend are needed for species conservation; these are most difficult to obtain for rare and rapidly changing populations. We compare uncertainty in densities estimated from spatio–temporal models with that from standard design‐based methods. Spatio–temporal models allow us to target priority areas where, and at times when, a population may most benefit. Generalised additive models were fitted to a 31‐year time series of point‐transect surveys of an endangered Hawaiian forest bird, the Hawai'i ‘ākepa Loxops coccineus. This allowed us to estimate bird densities over space and time. We used two methods to quantify uncertainty in density estimates from the spatio–temporal model: the delta method (which assumes independence between detection and distribution parameters) and a variance propagation method. With the delta method we observed a 52% decrease in the width of the design‐based 95% confidence interval (CI), while we observed a 37% decrease in CI width when propagating the variance. We mapped bird densities as they changed across space and time, allowing managers to evaluate management actions. Integrating detection function modelling with spatio–temporal modelling exploits survey data more efficiently by producing finer‐grained abundance estimates than are possible with design‐based methods as well as producing more precise abundance estimates. Model‐based approaches require switching from making assumptions about the survey design to assumptions about bird distribution. Such a switch warrants carefully considered. In this case the model‐based approach benefits conservation planning through improved management efficiency and reduced costs by taking into account both spatial shifts and temporal changes in population abundance and distribution.Publisher PDFPeer reviewe

The potential of essential oils from active packaging to reduce ethylene biosynthesis in plant products. Part 2: fruits (Blueberries and blackberries)

Plant essential oils (EOs) have an important ability to inhibit ethylene biosynthesis. Nevertheless, the effects of EOs on the key components of ethylene biosynthesis (l-aminocyclopropane1-carboxylic (ACC) oxidase activity, ACC synthase activity, and ACC content) have not yet been thoroughly studied. Accordingly, this study focused on the effects of emitted EOs from active packaging (EO doses from 100 to 1000 mg m−2 ) on the key components of ethylene biosynthesis of blueberries and blackberries under several storage temperatures. Anise EO and lemon EO active packaging induced the greatest inhibitory effects (60–76%) on the ethylene production of blueberries and blackberries, respectively, even at high storage temperatures (22 ◦C). In terms of EO doses, active packaging with 1000 mg m−2 of anise EO or lemon EO led to the highest reduction of ethylene production, respectively. At 22 ◦C, the investigated EO active packing reduced the activities of ACC synthase and ACC oxidase up to 50%. In order to minimise ethylene biosynthesis in blueberries and blackberries when they are stored even under improper temperature scenarios at high temperatures, this EO active packaging is a natural and efficient technological solution.The authors are grateful to the SPANISH MINISTRY OF SCIENCE AND INNOVATION for the grant PID2020-119882RB-I00 funded by MCIN/AEI/10.13039/501100011033. Ginés Benito Martínez- Hernández was supported by a Beatriz Galindo scholarship (BG20-00069) from the SPANISH MINISTRY OF SCIENCE AND INNOVATION. Alberto Garre was supported by a Ramón y Cajal scholarship (RYC2021-034612-I) from the SPANISH MINISTRY OF SCIENCE AND INNOVATION. The authors are grateful to the company, Plus Berries, for facilitating the transport of blackberries to the facilities of the Universidad Politécnica de Cartagena