Due to the availability of good and reasonably priced auxiliary data, the use of model-based regression-synthetic estimators for small area estimation is popular in operational settings. Examples are forest management inventories, where a linking model is used in combination with airborne laser scanning data to estimate stand-level forest parameters where no or too few observations are collected within the stand. This paper focuses on different approaches to estimating the variances of those estimates. We compared a variance estimator which is based on the estimation of superpopulation parameters with variance estimators which are based on predictions of finite population values. One of the latter variance estimators considered the spatial autocorrelation of the residuals whereas the other one did not. The estimators were applied using timber volume on stand level as the variable of interest and photogrammetric image matching data as auxiliary information. Norwegian National Forest Inventory (NFI) data were used for model calibration and independent data clustered within stands were used for validation. The empirical coverage proportion (ECP) of confidence intervals (CIs) of the variance estimators which are based on predictions of finite population values was considerably higher than the ECP of the CI of the variance estimator which is based on the estimation of superpopulation parameters. The ECP further increased when considering the spatial autocorrelation of the residuals. The study also explores the link between confidence intervals that are based on variance estimates as well as the well-known confidence and prediction intervals of regression models. 2015 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license.

Increasing forest stress and tree mortality has been directly linked to combinations of drought and high temperatures. The climatic changes expected during the next decades - large increases in mean temperature, increased heat waves, and significant long-term regional drying in the western USA - will likely increase chronic forest stress and mortality. The aim of this research is to develop and apply a new forest vulnerability index (FVI) associated with drought and high temperatures across the Pacific Northwest region (PNW; Oregon and Washington) of the USA during the MODIS Aqua era (since 2003). Our technique incorporates the alterations to canopy water and energy exchange processes caused by drought and high temperatures with spatially continuous MODIS land surface temperature (LST) and evapotranspiration (ET), and with Parameter-elevation Relationships on Independent Slopes Model (PRISM) precipitation (P) data. With P and ET, we calculate a monthly water balance variable for each individual pixel normalized by forest type group (FTG), and then difference the water balance with the corresponding normalized monthly meanLST to calculate a monthly forest stress index (FSI). We then extract the pixel-specific (800-m resolution) statistically significant temporal trends of the FSI from 2003 to 2012 by month (April to October). The FVI is the slope of the monthly FSI across years, such that there is a FVI for each month. Statistically significant positive slopes indicate interannual increases in stress leading to expected forest vulnerability (positive FVI) for a given month. Positive FVI values were concentrated in the months of August and September, with peak vulnerability occurring at different times for different FTGs. Overall, increased vulnerability rates were the highest in drier FTGs such as Ponderosa Pine, Juniper, and Lodgepole Pine. Western Larch and Fir/Spruce/Mountain Hemlock groups occupy moister sites but also had relatively high proportion of positive FVI values. The Douglas-fir group had the second largest total area of increased vulnerability due to its large areal extent in the study area. Based on an analysis using imagery viewed in Google Earth, we confirm that areas with increased vulnerability are associated with greater amounts of stress and mortality. The FVI is a new way to conceptualize and monitor forest vulnerability based on first-order principles and has the potential to be generalized to other geographical areas. (C) 2015 Elsevier Inc. All rights reserved.

There is a large gap in our understanding of how top-down cognitive processes, such as memory, influence energy intake. Similarly, there is limited knowledge regarding how the brain controls the timing of meals and meal frequency. Understanding how cognition influences ingestive behavior and how the brain controls meal frequency will provide a more complete explanation of the neural mechanisms that regulate energy intake and may also increase our knowledge of the factors that contribute to diet-induced obesity. We hypothesize that dorsal hippocampal neurons, which are critical for memory of personal experiences (i.e., episodic memory), form a memory of a meal, inhibit meal onset during the period following a meal, and limit the amount ingested at the next meal. In support, we describe evidence from human research suggesting that episodic memory of a meal inhibits intake and review data from human and non-human animals showing that impaired hippocampal function is associated with increased intake. We then describe evidence from our laboratory showing that inactivation of dorsal hippocampal neurons decreases the interval between sucrose meals and increases intake at the next meal. We also describe our evidence suggesting that sweet orosensation is sufficient to induce synaptic plasticity in dorsal hippocampal neurons and raise the possibility that impaired dorsal hippocampal function and episodic memory deficits contribute to the development and/or maintenance of diet-induced obesity. Finally, we raise some critical questions that need to be addressed in future research. (C) 2016 Elsevier Inc. All rights reserved.

Delay discounting of financial rewards has been related to overeating and obesity. Neuropsychological evidence supports a dual-system account of both discounting and overeating behaviour where the degree of impulsive decision making is determined by the relative strength of reward desire and executive control. A dual-parameter model of discounting behaviour is consistent with this theory. In this study, the fit of the commonly used one-parameter model was compared to a new dual-parameter model for the first time in a sample of adults with wide ranging BMI. Delay discounting data from 79 males and females (males = 26) across a wide age (M = 28:44 years (SD = 8.81)) and BMI range (M = 25.42 (SD = 5.16)) was analysed. A dual-parameter model (saturating-hyperbolic; Doya, [Doya (2008)]) was applied to the data and compared on model fit indices to the single-parameter model. Discounting was significantly greater in the overweight/obese participants using both models, however, the two parameter model showed a superior fit to data (p < 0.0001). The two parameters were shown to be related yet distinct measures consistent with a dual-system account of inter-temporal choice behaviour. The dual-parameter model showed superior fit to data and the two parameters were shown to be related yet distinct indices, sensitive to differences between weight groups. Findings are discussed in terms of the impulsive reward and executive control systems that contribute to unhealthy food choice and within the context of obesity related research. (C) 2016 Elsevier Inc All rights reserved.

Background: Both portion size and energy density (ED) have substantial effects on intake; however, their combined effects on preschool children's intake have not been examined when multiple foods are varied at a meal. Objective: We tested the effects on intake of varying the portion size and ED of lunches served to children in their usual eating environment. Design: In a crossover design, lunch was served in 3 childcare centers once a week for 6 weeks to 120 children aged 3-5 y. Across the 6 meals, all items were served at 3 levels of portion size (100%, 150%, or 200%) and 2 levels of ED (100% or 142%). The lunch menu had either lower-ED or higher-ED versions of chicken, macaroni and cheese, vegetables, applesauce, ketchup, and milk. Children's ratings of the foods indicated that the lower-ED and higher-ED meals were similarly well liked. Results: The total weight of food and milk consumed at meals was increased by serving larger portions (P < 0.0001) but was unaffected by varying the ED (P = 0.22). Meal energy intake, however, was independently affected by portion size and ED (both P < 0.0001). Doubling the portions increased energy intake by 24% and increasing meal ED by 42% increased energy intake by 40%. These effects combined to increase intake by 175 12 kcal or 79% at the higher-ED meal with the largest portions compared to the lower-ED meal with the smallest portions. The foods contributing the most to this increase were chicken, macaroni and cheese, and applesauce. The effects of meal portion size and ED on intake were not influenced by child age or body size, but were significantly affected by parental ratings of child eating behavior. Conclusion: Strategically moderating the portion size and ED of foods typically consumed by children could substantially reduce their energy intake without affecting acceptability. (C) 2016 Elsevier Inc. All rights reserved.

Binary quadratic programming (BQP) is a typical integer programming problem widely applied in the field of signal processing, economy, management and engineering. However, it is NP-hard and lacks efficient algorithms. Due to this reason, in this paper, some novel polynomial algorithms are proposed to solve a class of unconstrained and linearly constrained binary quadratic programming problems. We first deduce the polynomial time solvable algorithms to the unconstrained binary quadratic programming problems with Q being a seven-diagonal matrix (UBQP7) and a five-diagonal matrix (UBQP5) respectively with two different approaches. Then, the algorithm to unconstrained problem is combined with the dynamic programming method to solve the linearly constrained binary quadratic programming problem with Q being a five-diagonal matrix (LCBQP5). In addition, the polynomial solvable feature of these algorithms is analyzed and some specific examples are presented to illustrate these new algorithms. Lastly, we demonstrate their polynomial feature as well as their high efficiency. (C) 2016 Elsevier B.V. All rights reserved.