Satiation attenuates BOLD activity in brain regions involved in reward and increases activity in dorsolateral prefrontal cortex: an fMRI study in healthy volunteers

BACKGROUND: Neural responses to rewarding food cues are significantly different in the fed vs. fasted (>8 h food-deprived) state. However, the effect of eating to satiety after a shorter (more natural) intermeal interval on neural responses to both rewarding and aversive cues has not been examined. OBJECTIVE: With the use of a novel functional magnetic resonance imaging (fMRI) task, we investigated the effect of satiation on neural responses to both rewarding and aversive food tastes and pictures. DESIGN: Sixteen healthy participants (8 men, 8 women) were scanned on 2 separate test days, before and after eating a meal to satiation or after not eating for 4 h (satiated vs. premeal). fMRI blood oxygen level-dependent (BOLD) signals to the sight and/or taste of the stimuli were recorded. RESULTS: A whole-brain cluster-corrected analysis (P < 0.05) showed that satiation attenuated the BOLD response to both stimulus types in the ventromedial prefrontal cortex (vmPFC), orbitofrontal cortex, nucleus accumbens, hypothalamus, and insula but increased BOLD activity in the dorsolateral prefrontal cortex (dlPFC; local maxima corrected to P ��� 0.001). A psychophysiological interaction analysis showed that the vmPFC was more highly connected to the dlPFC when individuals were exposed to food stimuli when satiated than when not satiated. CONCLUSIONS: These results suggest that natural satiation attenuates activity in reward-related brain regions and increases activity in the dlPFC, which may reflect a "top down" cognitive influence on satiation. This trial was registered at clinicaltrials.gov as NCT02298049.

The EU societal awareness of landscape indicator: a review of its meaning, utility and performance across different scales

There is increasing recognition that agricultural landscapes meet multiple societal needs and demands beyond provision of economic and environmental goods and services. Accordingly, there have been significant calls for the inclusion of societal, amenity and cultural values in agri-environmental landscape indicators to assist policy makers in monitoring the wider impacts of land-based policies. However, capturing the amenity and cultural values that rural agrarian areas provide, by use of such indicators, presents significant challenges. The EU social awareness of landscape indicator represents a new class of generalized social indicator using a top-down methodology to capture the social dimensions of landscape without reference to the specific structural and cultural characteristics of individual landscapes. This paper reviews this indicator in the context of existing agri-environmental indicators and their differing design concepts. Using a stakeholder consultation approach in five case study regions, the potential and limitations of the indicator are evaluated, with a particular focus on its perceived meaning, utility and performance in the context of different user groups and at different geographical scales. This analysis supplements previous EU-wide assessments, through regional scale assessment of the limitations and potentialities of the indicator and the need for further data collection. The evaluation finds that the perceived meaning of the indicator does not vary with scale, but in common with all mapped indicators, the usefulness of the indicator, to different user groups, does change with scale of presentation. This indicator is viewed as most useful when presented at the scale of governance at which end users operate. The relevance of the different sub-components of the indicator are also found to vary across regions.

Metabolic theory predicts whole-ecosystem properties

Understanding the effects of individual organisms on material cycles and energy fluxes within ecosystems is central to predicting the impacts of human-caused changes on climate, land use, and biodiversity. Here we present a theory that integrates metabolic (organism-based bottom-up) and systems (ecosystem-based top-down) approaches to characterize how the metabolism of individuals affects the flows and stores of materials and energy in ecosystems. The theory predicts how the average residence time of carbon molecules, total system throughflow (TST), and amount of recycling vary with the body size and temperature of the organisms and with trophic organization. We evaluate the theory by comparing theoretical predictions with outputs of numerical models designed to simulate diverse ecosystem types and with empirical data for real ecosystems. Although residence times within different ecosystems vary by orders of magnitude���from weeks in warm pelagic oceans with minute phytoplankton producers to centuries in cold forests with large tree producers���as predicted, all ecosystems fall along a single line: residence time increases linearly with slope = 1.0 with the ratio of whole-ecosystem biomass to primary productivity (B/P). TST was affected predominantly by primary productivity and recycling by the transfer of energy from microbial decomposers to animal consumers. The theory provides a robust basis for estimating the flux and storage of energy, carbon, and other materials in terrestrial, marine, and freshwater ecosystems and for quantifying the roles of different kinds of organisms and environments at scales from local ecosystems to the biosphere.

Nurturing bilingual learners: challenges and concerns in Singapore

Singapore���s bilingual policy legitimises English not only as the language of governmental administration and interethnic communication, but also as the medium of instruction in all schools on all levels and across all subjects except mother tongues (MTs). As a result of these politics of language recognition, a visible shift has occurred in all ethnic groups away from MTs towards English. To rectify the language shift situation, the government has emphasised that developing bilingualism and raising bilingual children should begin in preschools. In this paper, we examine two top-down official documents: Review of Mother Tongue Languages Report, issued in 2011, and Nurturing Early Learners Framework for Mother Tongue Languages, developed in 2013. Attempting to identify some of the complex factors that influence language shift, we present an intertextual analysis of the Report and the curriculum Framework. In doing so, we compare the consistencies and locate the implicit inconsistencies in the policy position on bilingual education in preschools. We conclude the article by outlining the implications for changing the current bilingual educational models and providing teacher training programmes that maximise the learning opportunities of young bilingual learners.

Eutrophication control in river-systems: an application of INCA-P to the River Lugg

The Integrated Catchments model of Phosphorus dynamics (INCA-P) was applied to the River Lugg to determine the key factors controlling delivery of phosphorus to the main channel and to quantify the relative contribution of diffuse and point sources to the in-stream phosphorus (P) load under varying hydrological conditions. The model is able to simulate the seasonal variations and inter-annual variations in the in-stream total-phosphorus concentrations. However, difficulties in simulating diffuse inputs arise due to equifinality in the model structure and parameters. The River Lugg is split into upper and lower reaches. The upper reaches are dominated by grassland and woodland, so the patterns in the stream-water total-phosphorus concentrations are typical of diffuse source inputs; application of the model leads to estimates of the relative contribution to the in-stream P load from diffuse and point sources as 9:1. In the lower reaches, which are more intensively cultivated and urbanised, the stream-water total-phosphorus concentration dynamics are influenced more by point-sources; the simulated relative diffuse/point contribution to the in-stream P load is 1: 1. The model set-up and simulations are used to identify the key source-areas of P in the catchment, the P contribution of the Lugg to the River Wye during years with contrasting precipitation inputs, and the uptake and release of P from within-reach sediment. In addition, model scenarios are run to identify the impacts of likely P reductions at sewage treatment works on the in-stream soluble-reactive P concentrations and the suitability of this as a management option is assessed for reducing eutrophication.

Modeling the mechanisms that control in-stream dissolved organic carbon dynamics in upland and forested catchments

[1] We present a new, process-based model of soil and stream water dissolved organic carbon (DOC): the Integrated Catchments Model for Carbon (INCA-C). INCA-C is the first model of DOC cycling to explicitly include effects of different land cover types, hydrological flow paths, in-soil carbon biogeochemistry, and surface water processes on in-stream DOC concentrations. It can be calibrated using only routinely available monitoring data. INCA-C simulates daily DOC concentrations over a period of years to decades. Sources, sinks, and transformation of solid and dissolved organic carbon in peat and forest soils, wetlands, and streams as well as organic carbon mineralization in stream waters are modeled. INCA-C is designed to be applied to natural and seminatural forested and peat-dominated catchments in boreal and temperate regions. Simulations at two forested catchments showed that seasonal and interannual patterns of DOC concentration could be modeled using climate-related parameters alone. A sensitivity analysis showed that model predictions were dependent on the mass of organic carbon in the soil and that in-soil process rates were dependent on soil moisture status. Sensitive rate coefficients in the model included those for organic carbon sorption and desorption and DOC mineralization in the soil. The model was also sensitive to the amount of litter fall. Our results show the importance of climate variability in controlling surface water DOC concentrations and suggest the need for further research on the mechanisms controlling production and consumption of DOC in soils.

Development and experimental identification of a biomechanical model of the trunk for functional electrical stimulation control in paraplegia

Objectives. Theoretic modeling and experimental studies suggest that functional electrical stimulation (FES) can improve trunk balance in spinal cord injured subjects. This can have a positive impact on daily life, increasing the volume of bimanual workspace, improving sitting posture, and wheelchair propulsion. A closed loop controller for the stimulation is desirable, as it can potentially decrease muscle fatigue and offer better rejection to disturbances. This paper proposes a biomechanical model of the human trunk, and a procedure for its identification, to be used for the future development of FES controllers. The advantage over previous models resides in the simplicity of the solution proposed, which makes it possible to identify the model just before a stimulation session ( taking into account the variability of the muscle response to the FES). Materials and Methods. The structure of the model is based on previous research on FES and muscle physiology. Some details could not be inferred from previous studies, and were determined from experimental data. Experiments with a paraplegic volunteer were conducted in order to measure the moments exerted by the trunk-passive tissues and artificially stimulated muscles. Data for model identification and validation also were collected. Results. Using the proposed structure and identification procedure, the model could adequately reproduce the moments exerted during the experiments. The study reveals that the stimulated trunk extensors can exert maximal moment when the trunk is in the upright position. In contrast, previous studies show that able-bodied subjects can exert maximal trunk extension when flexed forward. Conclusions. The proposed model and identification procedure are a successful first step toward the development of a model-based controller for trunk FES. The model also gives information on the trunk in unique conditions, normally not observable in able-bodied subjects (ie, subject only to extensor muscles contraction).

A new floating model level scheme for the assimilation of boundary layer top inversions: the univariate assimilation of temperature.

The assimilation of observations with a forecast is often heavily in���uenced by the description of the error covariances associated with the forecast. When a temperature inversion is present at the top of the boundary layer (BL), a signi���cant part of the forecast error may be described as a vertical positional error (as opposed to amplitude error normally dealt with in data assimilation). In these cases, failing to account for positional error explicitly is shown t o r esult in an analysis for which the inversion structure is erroneously weakened and degraded. In this article, a new assimilation scheme is proposed to explicitly include the positional error associated with an inversion. This is done through the introduction of an extra control variable to allow position errors in the a priori to be treated simultaneously with the usual amplitude errors. This new scheme, referred to as the ������oating BL scheme���, is applied to the one-dimensional (vertical) variational assimilation of temperature. The ���oating BL scheme is tested with a series of idealised experiments a nd with real data from radiosondes. For each idealised experiment, the ���oating BL scheme gives an analysis which has the inversion structure and position in agreement with the truth, and outperforms the a ssimilation which accounts only for forecast a mplitude error. When the ���oating BL scheme is used to assimilate a l arge sample of radiosonde data, its ability to give an analysis with an inversion height in better agreement with that observed is con���rmed. However, it is found that the use of Gaussian statistics is an inappropriate description o f t he error statistics o f t he extra c ontrol variable. This problem is alleviated by incorporating a non-Gaussian description of the new control variable in the new scheme. Anticipated challenges in implementing the scheme operationally are discussed towards the end of the article.

CASCADE: An Agent Based Framework For Modeling The Dynamics Of Smart Electricity Systems

The Complex Adaptive Systems, Cognitive Agents and Distributed Energy (CASCADE) project is developing a framework based on Agent Based Modelling (ABM). The CASCADE Framework can be used both to gain policy and industry relevant insights into the smart grid concept itself and as a platform to design and test distributed ICT solutions for smart grid based business entities. ABM is used to capture the behaviors of diff erent social, economic and technical actors, which may be defi ned at various levels of abstraction. It is applied to understanding their interactions and can be adapted to include learning processes and emergent patterns. CASCADE models ���prosumer��� agents (i.e., producers and/or consumers of energy) and ���aggregator��� agents (e.g., traders of energy in both wholesale and retail markets) at various scales, from large generators and Energy Service Companies down to individual people and devices. The CASCADE Framework is formed of three main subdivisions that link models of electricity supply and demand, the electricity market and power fl ow. It can also model the variability of renewable energy generation caused by the weather, which is an important issue for grid balancing and the profi tability of energy suppliers. The development of CASCADE has already yielded some interesting early fi ndings, demonstrating that it is possible for a mediating agent (aggregator) to achieve stable demandfl attening across groups of domestic households fi tted with smart energy control and communication devices, where direct wholesale price signals had previously been found to produce characteristic complex system instability. In another example, it has demonstrated how large changes in supply mix can be caused even by small changes in demand profi le. Ongoing and planned refi nements to the Framework will support investigation of demand response at various scales, the integration of the power sector with transport and heat sectors, novel technology adoption and diffusion work, evolution of new smart grid business models, and complex power grid engineering and market interactions.