Our understanding of the physiological systems that regulate food intake and body weight has increased immensely over the past decade. Brain centres, including the hypothalamus, brainstem and reward centres, signal via neuropeptides which regulate energy homeostasis. Insulin and hormones synthesized by adipose tissue reflect the long-term nutritional status of the body and are able to influence these circuits. Circulating gut hormones modulate these pathways acutely and result in appetite stimulation or satiety effects. This review discusses central neuronal networks and peripheral signals which contribute energy homeostasis, and how a loss of the homeostatic process may result in obesity. It also considers future therapeutic targets for the treatment of obesity.
This paper is an empirical study of the relationship between the energy performance rating of residential homes in the Dublin market between 2009 and 2014 and their market prices, controlling for building type, size, age and location. Initial results suggest that energy efficiency has a significant, positive relationship with list price. A 50-point improvement in the Energy Performance Indicator (kWh/m 2 /year) is associated with a 1.5 % higher list price. Alternatively, using the Building Energy Rating metric, a 1-point improvement in the 15-point scale from G to A1 yields a list price increase of 1 %. This mirrors findings for efficiency price premiums on a nationwide basis from Hyland et al. (2013). We also find that it is important to include controls for the age of the dwelling to avoid biased energy efficiency estimates in the hedonic model.
Driven by the large-scale adoption of cloud-based technologies, the past decade has experienced tremendous data centre growth around the globe. In addition to ongoing increases in energy consumption from the sector, the proliferation of data centres also induces a number of electrical network challenges.In this study, their potential to contribute to demand flexibility is analysed, exploring the trade-off between available flexibility and system energy costs, in a day-ahead electricity market. Data centre operation is modelled within a least cost energy mixed integer formulation for the 2030 Irish electricity sector, sourcing 70% of electrical demand from variable renewables. Subsequent impacts on generation and demand schedules, energy costs, renewable energy curtailment, emission levels, plant operational hours, etc. are evaluated, in order to demonstrate how largescale data centre growth can affect a system's ability to meet its renewable obligations.
Digital scholarship is an evolving area of librarianship. In this piece we propose 10 theses, statements about what this kind of work DOES, rather than trying to define with it IS. We believe that digitally-inflected research and learning, and the characteristics they employ, are essential to the recentering of our profession's position in/across the academy. We also believe that the "digital scholarship center" has served its time, and that the activities and models for digital scholarship work are core to librarianship. This manifesto is meant to serve as a starting point for a necessary discussion, not an end-all, be-all. We hope others will write and share counter-manifestos, passionate responses, or affirming statements.
Two obstacles are encountered in the probability analysis of ice jam floods: the first is the general lack of long-term hydrometric records in cold regions; the second, which compounds the first, is that the few records that are available for ice jam floods are difficult to transpose to even nearby sites. This means there must be heavy reliance placed on local historical data.A good illustration of the effort required and the rewards obtained in collecting and analyzing such data is provided by the situation at Hay River, N.W.T. The flood population at this site is completely dominated by ice jam floods for which there is no standard hydrometric data.This paper describes the approach used in the collection and analysis of the historical data at this site to define the flood probability distribution. A comparison of the resulting probability distribution with the previously designated flood zone, which was defined simply on the basis of the historical high water level, reveals the risk involved in designation based on the latter approach and demonstrates that even in the complex and apparently data-limited situation at Hay River, the systematic collection, collation, and probability analysis of historical data is well worthwhile. Key words: ice jams, historical flood analysis, probability analysis, hydrology, river floods, river ice.
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