Are food-related perceptions associated with meal portion size decisions? A cross-sectional study

The purpose of this study was to test a comprehensive model of meal portion size determinants consisting of sociodemographic, psychological and food-related variables, whilst controlling for hunger and thirst.
Using cross-sectional nationally representative data collected in 2075 participants from the Island of Ireland (IoI) and Denmark (DK), eight separate hierarchical multiple regression analyses were conducted to examine the association between food-related variables and meal portion size (i.e. pizza, vegetable soup, chicken salad and a pork meal) within each country. Stepwise regressions were run with physiological control measures (hunger and thirst) entered in the first step, sociodemographic variables (sex, age, body mass index (BMI)) in the second step; psychological variables (cognitive restraint, uncontrolled eating, emotional eating, general health interest (GHI)) in the third step and food-related variables (expected fillingness, liking, expected healthfulness, food familiarity) in the fourth step.
Sociodemographic variables accounted for 2-19% of the variance in meal portion sizes; psychological variables explained an additional 3-8%; and food-related variables explained an additional 2-12%. When all four variable groups were included in the regression models, liking and sometimes expected healthfulness was positively associated with meal portion size. The strongest association was for liking, which was statistically significant in both countries for all meal types. Whilst expected healthfulness was not associated with pizza portion size in either country, it was positively associated with meals that have a healthier image (vegetable soup; chicken salad and in IoI, the pork meal).
In conclusion, after considering sociodemographic and psychological variables, and the food-related variables of liking and expected healthfulness, there may be little merit in manipulating the satiating power, at least of these type of meals, to maintain or promote weight loss.
Keywords: Meal portion size; psychological variables; expected fillingness; expected healthfulness; food liking; food familiarity.

Runtime Support for Adaptive Power Capping on Heterogeneous SoCs

Power capping is a fundamental method for reducing the energy consumption of a wide range of modern computing environments, ranging from mobile embedded systems to datacentres. Unfortunately, maximising performance and system efficiency under static power caps remains challenging, while maximising performance under dynamic power caps has been largely unexplored. We present an adaptive power capping method that reduces the power consumption and maximizes the performance of heterogeneous SoCs for mobile and server platforms. Our technique combines power capping with coordinated DVFS, data partitioning and core allocations on a heterogeneous SoC with ARM processors and FPGA resources. We design our framework as a run-time system based on OpenMP and OpenCL to utilise the heterogeneous resources. We evaluate it through five data-parallel benchmarks on the Xilinx SoC which allows fully voltage and frequency control. Our experiments show a significant performance boost of 30% under dynamic power caps with concurrent execution on ARM and FPGA, compared to a naive separate approach.

Time series wind power forecasting based on variant Gaussian process and TLBO

Due to the variability and stochastic nature of wind power system, accurate wind power forecasting has an important role in developing reliable and economic power system operation and control strategies. As wind variability is stochastic, Gaussian Process regression has recently been introduced to capture the randomness of wind energy. However, the disadvantages of Gaussian Process regression include its computation complexity and incapability to adapt to time varying time-series systems. A variant Gaussian Process for time series forecasting is introduced in this study to address these issues. This new method is shown to be capable of reducing computational complexity and increasing prediction accuracy. It is further proved that the forecasting result converges as the number of available data approaches innite. Further, a teaching learning based optimization (TLBO) method is used to train the model and to accelerate
the learning rate. The proposed modelling and optimization method is applied to forecast both the wind power generation of Ireland and that from a single wind farm to show the eectiveness of the proposed method.

Video anomaly detection in real-time on a Power-Aware Heterogeneous Platform

FPGAs and GPUs are often used when real-time performance in video processing is required. An accelerated processor is chosen based on task-specific priorities (power consumption, processing time and detection accuracy), and this decision is normally made once at design time. All three characteristics are important, particularly in battery-powered systems. Here we propose a method for moving selection of processing platform from a single design-time choice to a continuous run time one.We implement Histogram of Oriented Gradients (HOG) detectors for cars and people and Mixture of Gaussians (MoG) motion detectors running across FPGA, GPU and CPU in a heterogeneous system. We use this to detect illegally parked vehicles in urban scenes. Power, time and accuracy information for each detector is characterised. An anomaly measure is assigned to each detected object based on its trajectory and location, when compared to learned contextual movement patterns. This drives processor and implementation selection, so that scenes with high behavioural anomalies are processed with faster but more power hungry implementations, but routine or static time periods are processed with power-optimised, less accurate, slower versions. Real-time performance is evaluated on video datasets including i-LIDS. Compared to power-optimised static selection, automatic dynamic implementation mapping is 10% more accurate but draws 12W extra power in our testbed desktop system.

Optimising power take-off of an oscillating wave surge converter using high fidelity numerical simulations

Oscillating wave surge converters are a promising technology to harvest ocean wave energy in the near shore region. Although research has been going on for many years, the characteristics of the wave action on the structure and especially the phase relation between the driving force and wave quantities like velocity or surface elevation have not been investigated in detail. The main reason for this is the lack of suitable methods. Experimental investigations using tank tests do not give direct access to overall hydrodynamic loads, only damping torque of a power take off system can be measured directly. Non-linear computational fluid dynamics methods have only recently been applied in the research of this type of devices. This paper presents a new metric named wave torque, which is the total hydrodynamic torque minus the still water pitch stiffness at any given angle of rotation. Changes in characteristics of that metric over a wave cycle and for different power take off settings are investigated using computational fluid dynamics methods. Firstly, it is shown that linearised methods cannot predict optimum damping in typical operating states of OWSCs. We then present phase relationships between main kinetic parameters for different damping levels. Although the flap seems to operate close to resonance, as predicted by linear theory, no obvious condition defining optimum damping is found.

Tyrosine kinase inhibitor insensitivity of non-cycling CD34+ human acute myeloid leukaemia cells with FMS-like tyrosine kinase 3 mutations.

The efficacy of tyrosine kinase (TK) inhibitors on non-cycling acute myeloid leukaemia (AML) cells, previously shown to have potent tumourigenic potential, is unknown. This pilot study describes the first attempt to characterize non-cycling cells from a small series of human FMS-like tyrosine kinase 3 (FLT3) mutation positive samples. CD34+ AML cells from patients with FLT3 mutation positive AML were cultured on murine stroma. In expansion cultures, non-cycling cells were found to retain CD34+ expression in contrast to dividing cells. Leukaemic gene rearrangements could be detected in non-cycling cells, indicating their leukaemic origin. Significantly, the FLT3-internal tandem duplication (ITD) mutation was found in the non-cycling fraction of four out of five cases. Exposure to the FLT3-directed inhibitor TKI258 clearly inhibited the growth of AML CD34+ cells in short-term cultures and colony-forming unit assays. Crucially, non-cycling cells were not eradicated, with the exception of one case, which exhibited exquisite sensitivity to the compound. Moreover, in longer-term cultures, TKI258-treated non-cycling cells showed no growth impairment compared to treatment-naive non-cycling cells. These findings suggest that non-cycling cells in AML may constitute a disease reservoir that is resistant to TK inhibition. Further studies with a larger sample size and other inhibitors are warranted.

Local Storage Meets Local Demand: A Technical Solution to Future Power Distribution System

Future power systems are expected to integrate large-scale stochastic and intermittent generation and load due to reduced use of fossil fuel resources, including renewable energy sources (RES) and electric vehicles (EV). Inclusion of such resources poses challenges for the dynamic stability of synchronous transmission and distribution networks, not least in terms of generation where system inertia may not be wholly governed by large-scale generation but displaced by small-scale and localised generation. Energy storage systems (ESS) can limit the impact of dispersed and distributed generation by offering supporting reserve while accommodating large-scale EV connection; the latter (load) also participating in storage provision. In this paper, a local energy storage system (LESS) is proposed. The structure, requirement and optimal sizing of the LESS are discussed. Three operating modes are detailed, including: 1) storage pack management; 2) normal operation; and 3) contingency operation. The proposed LESS scheme is evaluated using simulation studies based on data obtained from the Northern Ireland regional and residential network.

Sustainable solutions for the construction sector: integration of secondary raw materials in the production cycle of concrete

The construction industry is one of the largest consumers of raw materials and energy and one of the highest contributor to green-houses gases emissions. In order to become more sustainable it needs to reduce the use of both raw materials and energy, thus lim-iting its environmental impact. Developing novel technologies to integrate secondary raw materials (i.e. lightweight recycled aggre-gates and alkali activated “cementless” binders - geopolymers) in the production cycle of concrete is an all-inclusive solution to im-prove both sustainability and cost-efficiency of construction industry. SUS-CON “SUStainable, Innovative and Energy-Efficiency CONcrete, based on the integration of all-waste materials” is an European project (duration 2012-2015), which aim was the inte-gration of secondary raw materials in the production cycle of concrete, thus resulting in innovative, sustainable and cost-effective building solutions. This paper presents the main outcomes related to the successful scaling-up of SUS-CON concrete solutions in traditional production plants. Two European industrial concrete producers have been involved, to design and produce both pre-cast components (blocks and panels) and ready-mixed concrete. Recycled polyurethane foams and mixed plastics were used as aggre-gates, PFA (Pulverized Fuel Ash, a by-product of coal fuelled power plants) and GGBS (Ground Granulated Blast furnace Slag, a by-product of iron and steel industries) as binders. Eventually, the installation of SUS-CON concrete solutions on real buildings has been demonstrated, with the construction of three mock-ups located in Europe (Spain, Turkey and Romania)

A multi vector energy analysis for interconnected power and gas systems

This paper presents the first multi vector energy analysis for the interconnected energy systems of Great Britain (GB) and Ireland. Both systems share a common high penetration of wind power, but significantly different security of supply outlooks. Ireland is heavily dependent on gas imports from GB, giving significance to the interconnected aspect of the methodology in addition to the gas and power interactions analysed. A fully realistic unit commitment and economic dispatch model coupled to an energy flow model of the gas supply network is developed. Extreme weather events driving increased domestic gas demand and low wind power output were utilised to increase gas supply network stress. Decreased wind profiles had a larger impact on system security than high domestic gas demand. However, the GB energy system was resilient during high demand periods but gas network stress limited the ramping capability of localised generating units. Additionally, gas system entry node congestion in the Irish system was shown to deliver a 40% increase in short run costs for generators. Gas storage was shown to reduce the impact of high demand driven congestion delivering a reduction in total generation costs of 14% in the period studied and reducing electricity imports from GB, significantly contributing to security of supply.

Identifying the Impact of Incomplete Datasets on Process Cycle Time Prediction in an Aerospace Assembly Line

Supply Chain Simulation (SCS) is applied to acquire information to support outsourcing decisions but obtaining enough detail in key parameters can often be a barrier to making well informed decisions.
One aspect of SCS that has been relatively unexplored is the impact of inaccurate data around delays within the SC. The impact of the magnitude and variability of process cycle time on typical performance indicators in a SC context is studied.
System cycle time, WIP levels and throughput are more sensitive to the magnitude of deterministic deviations in process cycle time than variable deviations. Manufacturing costs are not very sensitive to these deviations.
Future opportunities include investigating the impact of process failure or product defects, including logistics and transportation between SC members and using alternative costing methodologies.

Cell cycle-coupled expansion of AR activity promotes cancer progression

The androgen receptor (AR) is required for prostate cancer (PCa) survival and progression, and ablation of AR activity is the first line of therapeutic intervention for disseminated disease. While initially effective, recurrent tumors ultimately arise for which there is no durable cure. Despite the dependence of PCa on AR activity throughout the course of disease, delineation of the AR-dependent transcriptional network that governs disease progression remains elusive, and the function of AR in mitotically active cells is not well understood. Analyzing AR activity as a function of cell cycle revealed an unexpected and highly expanded repertoire of AR-regulated gene networks in actively cycling cells. New AR functions segregated into two major clusters: those that are specific to cycling cells and retained throughout the mitotic cell cycle ('Cell Cycle Common'), versus those that were specifically enriched in a subset of cell cycle phases ('Phase Restricted'). Further analyses identified previously unrecognized AR functions in major pathways associated with clinical PCa progression. Illustrating the impact of these unmasked AR-driven pathways, dihydroceramide desaturase 1 was identified as an AR-regulated gene in mitotically active cells that promoted pro-metastatic phenotypes, and in advanced PCa proved to be highly associated with development of metastases, recurrence after therapeutic intervention and reduced overall survival. Taken together, these findings delineate AR function in mitotically active tumor cells, thus providing critical insight into the molecular basis by which AR promotes development of lethal PCa and nominate new avenues for therapeutic intervention.