989 resultados para spin-symmetry energy
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Prevalence of protein-energy malnutrition (PEM), food intake inadequacy and associated health-related outcomes in morbidly obese (Body Mass Index ≥ 40 kg/m2) acute care patients are unknown. This study reports findings in morbidly obese participants from the Australasian Nutrition Care Day Survey (ANCDS) conducted in 2010. The ANCDS was a cross-sectional survey involving acute care patients from 56 Australian and New Zealand hospitals. Hospital-based dietitians evaluated participants’ nutritional status (defined by Subjective Global Assessment, SGA) and 24-hour food intake (as 0%, 25%, 50%, 75%, and 100% of the offered food). Three months later, outcome data, including length of stay (LOS) and 90-day in-hospital mortality, were collected. Of the 3122 participants, 4% (n = 136) were morbidly obese (67% females, 55 ± 14 years, BMI: 48 ± 8 kg/m2). Eleven percent (n = 15) of the morbidly obese patients were malnourished, and most (n = 11/15, 73%)received standard hospital diets without additional nutritional support. Malnourished morbidly obese patients had significantly longer LOS and greater 90-day in-hospital mortality than well-nourished counterparts (23 days vs. 9 days, p = 0.036; 14% vs. 0% mortality, p = 0.011 respectively). Thirteen morbidly obese patients (10%) consumed only 25% of the offered meals with a significantly greater proportion of malnourished (n = 4, 27%) versus well-nourished (n = 9, 7%) (p = 0.018). These results provide new knowledge on the prevalence of PEM and poor food intake in morbidly obese patients in Australian and New Zealand hospitals. For the first time internationally, the study establishes that PEM is significantly associated with negative outcomes in morbidly obese patients and warrants timely nutritional support during hospitalisation.
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Background To determine whether changes in appetite and energy intake (EI) can be detected and play a role in the effectiveness of interventions, it is necessary to identify their variability under normal conditions. We assessed the reproducibility of subjective appetite ratings and ad libitum test meal EI after a standardised pre-load in overweight and obese males. Methods Fifteen overweight and obese males (BMI 30.3 ± 4.9 kg/m2, aged 34.9 ± 10.6 years) completed two identical test days, 7 days apart. Participants were provided with a standardised fixed breakfast (1676 kJ) and 5 h later an ad libitum pasta lunch. An electronic appetite rating system was used to assess subjective ratings before and after the fixed breakfast, and periodically during the postprandial period. EI was assessed at the ad libitum lunch meal. Sample size estimates for paired design studies were calculated. Results Appetite ratings demonstrated a consistent oscillating pattern between test days, and were more reproducible for mean postprandial than fasting ratings. The correlation between ad libitum EI on the two test days was r = 0.78 (P < 0.01). Using a paired design and a power of 0.8, a minimum of 12 participants would be needed to detect a 10 mm change in 5 h postprandial mean ratings and 17 to detect a 500 kJ difference in ad libitum EI. Conclusion Intra-individual variability of appetite and ad libitum test meal EI in overweight and obese males is comparable to previous reports in normal weight adults. Sample size requirements for studies vary depending on the parameter of interest and sensitivity needed.
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As governments seek to transition to more efficient vehicle fleets, one strategy has been to incentivize ‘green’ vehicle choice by exempting some of these vehicles from road user charges. As an example, to stimulate sales of Energy-Efficient Vehicles (EEVs) in Sweden, some of these automobiles were exempted from Stockholm’s congestion tax. In this paper the effect this policy had on the demand for new, privately-owned, exempt EEVs is assessed by first estimating a model of vehicle choice and then by applying this model to simulate vehicle alternative market shares under different policy scenarios. The database used to calibrate the model includes owner-specific demographics merged with vehicle registry data for all new private vehicles registered in Stockholm County during 2008. Characteristics of individuals with a higher propensity to purchase an exempt EEV were identified. The most significant factors included intra-cordon residency (positive), distance from home to the CBD (negative), and commuting across the cordon (positive). By calculating vehicle shares from the vehicle choice model and then comparing these estimates to a simulated scenario where the congestion tax exemption was inactive, the exemption was estimated to have substantially increased the share of newly purchased, private, exempt EEVs in Stockholm by 1.8% (+/- 0.3%; 95% C.I.) to a total share of 18.8%. This amounts to an estimated 10.7% increase in private, exempt EEV purchases during 2008 i.e. 519 privately owned, exempt EEVs.
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The aims of the project were to scope and develop sustainable energy curriculum frameworks for Australian higher education Institutions that meet the needs of Australian and international student graduates and employers, both now and into the near future. The focus was on student centred learning and outcomes and to support graduates with the knowledge, skills and generic attributes required to work in the rapidly expanding sustainable energy industry in Australia and globally. The outputs of the project are designed to be relevant to specialist Sustainable Engineering and Energy Studies programs, as well as conventional engineering, science and humanities and social science programs that have a sustainable energy focus or major.
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This guide is to support institutions in developing and teaching tertiary level programmes for sustainable energy professionals. Ongoing curriculum renewal is more difficult but vital for multidisciplinary courses preparing graduates to work in a specialised rapidly changing field. After more than 15 years of offering tertiary level “sustainable energy” qualifications in Australian Universities there was a clear need to assess how these courses are taught and develop curriculum frameworks to guide Universities designing/redesigning programs and courses to provide graduates with the relevant skills, knowledge and attributes (capabilities) seen by graduates and employers as required to work in this rapidly changing field. This guide presents the sustainable energy curriculum frameworks developed by the “Renewing the sustainable energy curriculum – providing internationally relevant skills for a carbon constrained economy” project, which was conducted over a two-and-a-quarter year period.
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Cool roof coatings are identified by their solar reflectance index. They have been reported to have multiple benefits, the extent of which are strongly dependent on the peculiarities of the local climate, building stock and electricity network. This paper presents measured and simulated data from residential, educational and commercial buildings involved in recent field trials in Australia. The purpose of the field trials was to evaluate the impact of such coatings on electricity demand and load and to assess their potential application to improve comfort whilst avoiding the need for air conditioners. Measured reductions in temperature, power (kW) and energy (kWh) were used to develop a predictive model that correlates ambient temperature distribution profiles, building demand reduction profiles and electricity network peak demand times. Combined with simulated data, the study indicates the types of buildings that could be targeted in Demand Management programs for the mutual benefit of electricity networks and building occupants.
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Housing affordability and sustainable development are not polarised ideologies as both are necessary with increasing urbanisation. We must bridge the gap between current median house pricing and target affordable house pricing whilst pursuing sustainability. This paper examines the potential of initial construction cost and ongoing utilities and transport cost reduction through the integration of sustainable housing design and transit oriented development principles in a Commuter Energy and Building Utilities System (CEBUS). It also introduces current research on the development of a Dynamic Simulation Model for CEBUS applications in the Australian property development and construction industry.
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Energy usage in general, and electricity usage in particular, are major concerns internationally due to the increased cost of providing energy supplies and the environmental impacts of electricity generation using carbon-based fuels. If a "systems" approach is taken to understanding energy issues then both supply and demand need to be considered holistically. This paper examines two research projects in the energy area with IT tools as key deliverables, one examining supply issues and the other studying demand side issues. The supply side project used hard engineering methods to build the models and software, while the demand side project used a social science approach. While the projects are distinct, there was an overlap in personnel. Comparing the knowledge extraction, model building, implementation and interface issues of these two deliverables identifies both interesting contrasts and commonalities.
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Integrating Photovoltaic (PV) systems with battery energy storage in the distribution network will be essential to allow for continued uptake of domestic PV system installations. With increasing concerns regarding environmental and climate change issues, incorporating sources of renewable energy into power networks across the world will be key for a sustainable future. Australia is well placed to utilise solar energy as a significant component of its future energy generation and within the last 5 years there has been a rapid growth in the penetration levels seen by the grid. This growth of PV systems is causing a number of issues including intermittency of supply, negative power flow and voltage rises. Using the simulator tool GridLAB-D with a model of a typical South-East Queensland (SEQ) 11 kV distribution feeder, the effect of various configurations of PV systems have been offset with Battery Energy Storage Systems (BESS). From this, combinations of PV and storage that are most effective at mitigating the issues were explored.
Resumo:
With the recent development of advanced metering infrastructure, real-time pricing (RTP) scheme is anticipated to be introduced in future retail electricity market. This paper proposes an algorithm for a home energy management scheduler (HEMS) to reduce the cost of energy consumption using RTP. The proposed algorithm works in three subsequent phases namely real-time monitoring (RTM), stochastic scheduling (STS) and real-time control (RTC). In RTM phase, characteristics of available controllable appliances are monitored in real-time and stored in HEMS. In STS phase, HEMS computes an optimal policy using stochastic dynamic programming (SDP) to select a set of appliances to be controlled with an objective of the total cost of energy consumption in a house. Finally, in RTC phase, HEMS initiates the control of the selected appliances. The proposed HEMS is unique as it intrinsically considers uncertainties in RTP and power consumption pattern of various appliances. In RTM phase, appliances are categorized according to their characteristics to ease the control process, thereby minimizing the number of control commands issued by HEMS. Simulation results validate the proposed method for HEMS.
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Social marketers and governments have often targeted hard to reach or vulnerable groups (Gordon et al., 2006) such as young adults and low income earners. Past research has shown that low-income earners are often at risk of poor health outcomes and diminished lifestyle (Hampson et al., 2009; Scott et al., 2012). Young adults (aged 18 to 35) are in a transition phase of their life where lifestyle preferences are still being formed and are thus a useful target for long-term sustainable change. An area of focus for all levels of government is the use of energy with an aim to reduce consumption. There is little research to date that combines both of these groups and in particular in the context of household energy usage. Research into financially disadvantaged consumers is challenging the notion that that low income consumer purchasing and usage of products and services is based upon economic status (Sharma et al., 2012). Prior research shows higher income earners view items such as televisions and computers as necessities rather than non-essential (Karlsson et al., 2004). Consistent with this is growing evidence that low income earners purchase non-essential, energy intensive electronic appliances such as multiple big screen TV sets and additional refrigerators. With this in mind, there is a need for knowledge about how psychological and economic factors influence the energy consumption habits (e.g. appliances on standby power, leaving appliances turned on, running multiple devices at one time) of low income earners. Thus, our study sought to address the research question of: What are the factors that influence young adult low-income earners energy habits?
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This study evaluated the energy cost of walking (Cw) with knee flexion contractures (FC) simulated with a knee brace, in total knee arthroplasty (TKA) recipients (n=16) and normal controls (n=15), and compared it to baseline (no brace). There was no significant difference in Cw between the groups at baseline but TKA recipients walked slower (P=0.048) and with greater knee flexion in this condition (P=0.003). Simulated FC significantly increased Cw in both groups (TKA P=0.020, control P=0.002) and this occurred when FC exceeded 20° in the TKA group and 15° in the controls. Reported perceived exertion was only significantly increased by FC in the control group (control P<0.001, TKA P=0.058). Simulated knee FCs less than 20° do not increase Cw or perceived exertion in TKA recipients.
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This paper examines how ideas and practices of accounting come together in turning the abstract concept of climate change into a new non-financial performance measure in a large energy company in the UK. It develops the notion of ‘governmental management’ to explain how the firm’s carbon dioxide emissions were transformed into a new organisational object that could be made quantifiable, measureable and ultimately manageable because of the modern power of accounting in tying disciplinary subjectivities and objectivities together whilst operating simultaneously at the level of individual and the organisation. Examining these interrelations highlights the constitutive nature of accounting in creating not just new categories for accounting’s attention, but in turn new organisational knowledge and knowledge experts in the making up accounting for climate change. Significantly, it appears these new knowledge experts are no longer accountants: which may help explain accounting’s evolution into evermore spheres of influence as we increasingly choose to manage our world ‘by the numbers’.
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A new era of visible and sharable electricity information is emerging. Where eco-feedback is installed, households can now visualise many aspects of their energy consumption and share this information with others through Internet platforms such as social media. Despite providing users with many affordances, eco-feedback information can make public previously private actions from within the intimate setting of the family home. This paper represents a study focussing specifically on the privacy aspects of nascent ways for viewing and sharing this new stream of personal information. It explores the nuances of privacy related to eco-feedback both within and beyond the family home. While electricity consumption information may not be considered private itself, the household practices which eco-feedback systems makes visible may be private. We show that breaches of privacy can occur in unexpected ways and have the potential to cause distress. The paper concludes with some suggestions for how to realise the benefits of sharing energy consumption information whist effectively maintaining individuals’ conceptions of adequate privacy.
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This paper presents an efficient algorithm for optimizing the operation of battery storage in a low voltage distribution network with a high penetration of PV generation. A predictive control solution is presented that uses wavelet neural networks to predict the load and PV generation at hourly intervals for twelve hours into the future. The load and generation forecast, and the previous twelve hours of load and generation history, is used to assemble load profile. A diurnal charging profile can be compactly represented by a vector of Fourier coefficients allowing a direct search optimization algorithm to be applied. The optimal profile is updated hourly allowing the state of charge profile to respond to changing forecasts in load.