Manufacturers in a wide range of industries nowadays face the challenge of providing a rich product variety at a very low cost. This typically requires the implementation of cost efficient, flexible ...production systems. Often, so called mixed-model assembly lines are employed, where setup operations are reduced to such an extent that various models of a common base product can be manufactured in intermixed sequences. However, the observed diversity of mixed-model lines makes a thorough sequence planning essential for exploiting the benefits of assembly line production. This paper reviews and discusses the three major planning approaches presented in the literature, mixed-model sequencing, car sequencing and level scheduling, and provides a hierarchical classification scheme to systematically record the academic efforts in each field and to deduce future research issues.
Although several epidemiological studies have suggested that exposure to polycyclic aromatic hydrocarbons (PAHs) may induce brain atrophy, no longitudinal study has investigated the effect of PAH ...exposure on brain structural changes. This study examined the longitudinal associations between urinary PAH metabolites and brain cortical thickness. We obtained urinary concentrations of PAH metabolites and brain magnetic resonance images from 327 adults (≥50 years of age) without dementia at baseline and 3-year follow-up. We obtained whole-brain and regional cortical thicknesses, as well as an Alzheimer's disease (AD)-specific marker for cortical atrophy (a higher score indicated a greater similarity to patients with AD) at baseline and follow-up. We built a linear mixed-effect model including each of urinary PAH metabolites as the time-varying exposure variable of interest. We found that increases in urinary concentrations of 1-hydroxypyrene (β = −0.004; 95% CI, −0.008 to −0.001) and 2-hydroxyfluorene (β = −0.011; 95% CI, −0.015 to −0.006) were significantly associated with a reduced whole-brain cortical thickness. A urinary concentration of 2-hydroxyfluorene was significantly associated with an increased AD-specific cortical atrophy score (β = 2.031; 95% CI, 0.512 to 3.550). The specific brain regions showing the association of urinary concentrations of 1-hydroxypyrene, 2-naphthol, 1-hydroxyphenanthrene, or 2-hydroxyfluorene with cortical thinning were the frontal, parietal, temporal, and cingulate lobes. These findings suggested that exposure to PAHs may reduce brain cortical thickness and increase the similarity to AD-specific cortical atrophy patterns in adults.
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•Baseline and follow-up PAH metabolites and brain images were analyzed.•PAH exposure was associated with a reduced whole-brain cortical thickness.•The frontal, parietal, temporal, and cingulate lobes were affected by PAH exposure.•PAH exposure was associated with Alzheimer's disease-like brain shrinkage.
The connection between stress and sleep is well established in cross-sectional questionnaire studies and in a few prospective studies. Here, the intention was to study the link between stress and ...sleep on a day-to-day basis across 42days.
Fifty participants kept a sleep/wake diary across 42days and responded to daily questions on sleep and stress. The results were analyzed with a mixed model approach using stress during the prior day to predict morning ratings of sleep quality.
The results showed that bedtime stress and worries were the main predictors of sleep quality, but that, also, late awakening, short prior sleep, high quality of prior sleep, and good health the prior day predicted higher sleep quality.
Stress during the day predicts subsequent sleep quality on a day-to-day basis across 42 days. The observed range of variation in stress/worries was modest, which is why it is suggested that the present data underestimates the impact of stress on subsequent sleep quality.
•Site conditions exert larger influence over growth than competition.•Secondary growth in Pinus pinea is mainly controlled by water stress.•Effect of competition on growth is alleviated on extreme ...dry years.•Under future climate scenarios a significant decrease of production is expected.
Climate, competition and site conditions are the main drivers controlling annual secondary growth in tree species. These factors do no act independently on tree growth, but by means of interactions, resulting in mediated interactive effects. For example, the stress gradient hypothesis postulates alleviated interspecific competition under limiting spatial (site) or temporal (climate) resources. According to this, models predicting annual growth and yield for a given forest should consider these issues in their formulation. In this study, we present a modelling approach based on using data from permanent plots and dendrochronological analysis in order to describe annual tree growth in pure, even-aged stands of Pinus pinea L. in the Spanish Northern Plateau, a highly limiting environment due to its Mediterranean continental climate. Our method is based on identifying the different sources of variability by means of a multilevel linear mixed model, and thereby identifying the potential covariates explaining observed variability at the different spatiotemporal scales. Our results indicate that site related factors such as site index or dominant height exert a greater influence on annual secondary growth than size-symmetric competition. In addition, we found that the controlling influence of water stress is greater than that of temperatures on tree growth. Furthermore, our results allow evidence to be identified for the stress gradient hypothesis in temporal intraspecific interactions, since trees exposed to a higher degree of competition tend to grow more than expected in dry periods. In contrast, the effect of competition on growth, on average, tends to be aggravated at very poor sites. Finally, our modelling approach allows us to conduct growth and yield simulations under different climate scenarios at different spatial scales, providing results which point to significant decreases in timber and cone production under the more severe scenarios, which can be alleviated through more intensive silviculture.
In genome-wide association studies, ordinal categorical phenotypes are widely used to measure human behaviors, satisfaction, and preferences. However, because of the lack of analysis tools, methods ...designed for binary or quantitative traits are commonly used inappropriately to analyze categorical phenotypes. To accurately model the dependence of an ordinal categorical phenotype on covariates, we propose an efficient mixed model association test, proportional odds logistic mixed model (POLMM). POLMM is computationally efficient to analyze large datasets with hundreds of thousands of samples, can control type I error rates at a stringent significance level regardless of the phenotypic distribution, and is more powerful than alternative methods. In contrast, the standard linear mixed model approaches cannot control type I error rates for rare variants when the phenotypic distribution is unbalanced, although they performed well when testing common variants. We applied POLMM to 258 ordinal categorical phenotypes on array genotypes and imputed samples from 408,961 individuals in UK Biobank. In total, we identified 5,885 genome-wide significant variants, of which, 424 variants (7.2%) are rare variants with MAF < 0.01.
The industry of freight transport is recognized as one of the most important sectors for sustainable economic development, both on a regional and global scale. Although significant research has been ...produced for modeling demand for freight cargo, the incorporation of multimodality, connectivity, and proximity still needs to be further advanced supported by recent methodological advances. Concentrating on the close relationship of freight activity with the national economy, transport infrastructure, and the social context, a multi-dimensional approach should be considered for capturing and interpreting the dynamics of freight demand and services. Taking into account the spatial and temporal integration of regional characteristics into a coherent model may accurately reveal latent perspectives of freight demand that other approaches are not designed to capture. In the current paper, a robust model able to incorporate the multiple dimensions of freight demand at a regional scale, into one Spatio-temporal model form is developed and proposed for future spatio-temporal analyses. To achieve this, an extended form of the Spatial Autoregressive (SAR) model has been developed, estimated as the Linear Mixed Effect (LME) model, and named the Spatio-Temporal Linear Mixed Effect (STLME) model. The implementation has been applied to the European region for 5 years, providing valuable evidence on the factors that mostly affect freight demand. The results of this paper provide significant information on the spatial and temporal dynamics of the phenomenon.
Epidemiologic research often involves meta-analyses of proportions. Conventional two-step methods first transform each study's proportion and subsequently perform a meta-analysis on the transformed ...scale. They suffer from several important limitations: the log and logit transformations impractically treat within-study variances as fixed, known values and require ad hoc corrections for zero counts; the results from arcsine-based transformations may lack interpretability. Generalized linear mixed models (GLMMs) have been recommended in meta-analyses as a one-step approach to fully accounting for within-study uncertainties. However, they are seldom used in current practice to synthesize proportions. This article summarizes various methods for meta-analyses of proportions, illustrates their implementations, and explores their performance using real and simulated datasets. In general, GLMMs led to smaller biases and mean squared errors and higher coverage probabilities than two-step methods. Many software programs are readily available to implement these methods.
When testing for reduction of the mean value structure in linear mixed models, it is common to use an asymptotic ?2 test. Such tests can, however, be very poor for small and moderate sample sizes. ...The pbkrtest package implements two alternatives to such approximate ?2 tests: The package implements (1) a Kenward-Roger approximation for performing F tests for reduction of the mean structure and (2) parametric bootstrap methods for achieving the same goal. The implementation is focused on linear mixed models with independent residual errors. In addition to describing the methods and aspects of their implementation, the paper also contains several examples and a comparison of the various methods.
Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form. Markov chain ...Monte Carlo methods solve this problem by sampling from a series of simpler conditional distributions that can be evaluated. The R package MCMCglmm implements such an algorithm for a range of model fitting problems. More than one response variable can be analyzed simultaneously, and these variables are allowed to follow Gaussian, Poisson, multi(bi)nominal, exponential, zero-inflated and censored distributions. A range of variance structures are permitted for the random effects, including interactions with categorical or continuous variables (i.e., random regression), and more complicated variance structures that arise through shared ancestry, either through a pedigree or through a phylogeny. Missing values are permitted in the response variable(s) and data can be known up to some level of measurement error as in meta-analysis. All simu- lation is done in C/ C++ using the CSparse library for sparse linear systems.
Fusarium head blight (FHB) of wheat, caused by the fungus
, is associated with grain contamination with mycotoxins such as deoxynivalenol (DON). Although FHB is often positively correlated with DON, ...this relationship can break down under certain conditions. One possible explanation for this could be the conversion of DON to DON-3-glucoside (D3G), which is typically missed by common DON testing methods. The objective of this study was to quantify the effects of temperature, relative humidity (RH), and preharvest rainfall on DON, D3G, and the D3D/DON relationship. D3G levels were higher in grain from spikes exposed to 100% RH than to 70, 80, or 90% RH at 20 and 25°C across all tested levels of mean FHB index (percentage of diseased spikelets per spike). Mean D3G contamination was higher at 20°C than at 25 or 30°C. There were significantly positive linear relationships between DON and D3G. Rainfall treatments resulted in significantly higher mean D3G than the rain-free check and induced preharvest sprouting, as indicated by low falling numbers (FNs). There were significant positive relationships between the rate of increase in D3G per unit increase in DON (a measure of conversion) and sprouting. As FN decreased, the rate of D3G conversion increased, and this rate of conversion per unit decrease in FN was greater at relatively low than at high mean DON levels. These results provide strong evidence that moisture after FHB visual symptom development was associated with DON-to-D3G conversion and constitute valuable new information for understanding this complex disease-mycotoxin system.
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