BACKGROUND It is important to engage in regular physical activity in order to maintain a healthy lifestyle however a large portion of the population is insufficiently active. Understanding how different types of motivation contribute to exercise behavior is an important first step in identifying ways to increase exercise among individuals. The current study employs self-determination theory as ...

Drawing on novel survey data of Milwaukee renters, this study documents the prevalence of involuntary displacement from housing and estimates its consequences for neighborhood selection. More than one in eight Milwaukee renters experienced an eviction or other kind of forced move in the previous two years. Multivariate analyses suggest that renters who experienced a forced move relocate to poor...

Genotype by environment interactions (GEI) have attracted increasing attention in tropical breeding programs because of the variety of production systems involved. In this work, we assessed GEI in 450-day adjusted weight (W450) Nelore cattle from 366 Brazilian herds by comparing traditional univariate single-environment model analysis (UM) and random regression first order reaction norm models ...

A.1. Computation in ES Model. A particular ES model, describing an alternative hypothesis Ha, is fully specified by setting values for (φ, ω) and hyper-parameters (v1, . . . , vS , l1,m1, . . . , lS ,mS). Under the contrasting null model H0, we set φ = ω = 0 while keeping all other hyper-parameters the same. Let βs = (μs, βs), τs = σ −2 s and θ = (β1, . . . ,βs, τ1, . . . , τs, b̄), the marginal...

This study focuses on multi-step spatio-temporal wind speed forecasting for the Norwegian continental shelf. The aims to leverage spatial dependencies through relative physical location of different measurement stations improve local forecasts. Our models produce either 10-minute, 1- or 4-hour forecasts, with 10-minute resolution, meaning that more informative time series predicted future trend...

The increasing presence of intermittent renewables in modern power systems motivates the development methods for forecasting. More accurate forecasts may implicate less operational costs systems. In this context, paper proposes a family architectures based on fully convolutional neural networks wind speed prediction, ComPonentNet (CPNet) family. CPNet produces multi-site spatio-temporal forecas...