862 resultados para peak demand
Resumo:
This research investigated strategies for motorway congestion management from a different angle: that is, how to quickly recover motorway from congestion at the end of peak hours, given congestion cannot be eliminated due to excessive demand during the long peak hours nowadays. The project developed a zone recovery strategy using ramp metering for rapid congestion recovery, and a serious of traffic simulation investigations were included to evaluate the developed strategy. The results, from both microscopic and macroscopic simulation, demonstrated the effectiveness of the zone recovery strategy.
Resumo:
A pilot experiment was performed using the WOMBAT powder diffraction instrument at ANSTO in which the first neutron diffraction peak (Q0) was measured for D2O flowing in a 2 mm internal diameter aluminium tube. Measurements of Q0 were made at -9, 4.3, 6.9, 12, 18.2 and 21.5 °C. The D2O was circulated using a siphon with water in the lower reservoir returned to the upper reservoir using a small pump. This enabled stable flow to be maintained for several hours. For example, if the pump flow increased slightly, the upper reservoir level rose, increasing the siphon flow until it matched the return flow. A neutron wavelength of 2.4 Å was used and data integrated over 60 minutes for each temperature. A jet of nitrogen from a liquid N2 Dewar was directed over the aluminium tube to vary water temperature. After collection of the data, the d spacing of the aluminium peaks was used to calculate the temperature of the aluminium within the neutron beam and therefore was considered to be an accurate measure of water temperature within the beam. Sigmaplot version 12.3 was used to fit a Weibull five parameter peak fit to the first neutron diffraction peak. The values of Q0 obtained in this experiment showed an increase with temperature consistent with data in the literature [1] but were consistently higher than published values for bulk D20. For example at 21.5 °C we obtained a value of 2.008 Å-1 for Q0 compared to a literature value of 1.988 Å-1 for bulk D2O at 20 °C, a difference of 1%. Further experiments are required to see if this difference is real or artifactual.
Resumo:
X-ray diffraction structure functions for water flowing in a 1.5 mm diameter siphon in the temperature range 4 – 63 °C were obtained using a 20 keV beam at the Australian Synchrotron. These functions were compared with structure functions obtained at the Advanced Light Source for a 0.5 mm thick sample of water in the temperature range 1 – 77 °C irradiated with an 11 keV beam. The two sets of structure functions are similar, but there are subtle differences in the shape and relative position of the two functions suggesting a possible differences between the structure of bulk and siphon water. In addition, the first structural peak (Q0) for water in a siphon, showed evidence of a step-wise increase in Q0 with increasing temperature rather than a smoothly varying increase. More experiments are required to investigate this apparent difference.
Resumo:
This work presents a demand side response model (DSR) which assists small electricity consumers, through an aggregator, exposed to the market price to proactively mitigate price and peak impact on the electrical system. The proposed model allows consumers to manage air-conditioning when as a function of possible price spikes. The main contribution of this research is to demonstrate how consumers can minimise the total expected cost by optimising air-conditioning to account for occurrences of a price spike in the electricity market. This model investigates how pre-cooling method can be used to minimise energy costs when there is a substantial risk of an electricity price spike. The model was tested with Queensland electricity market data from the Australian Energy Market Operator and Brisbane temperature data from the Bureau of Statistics during hot days on weekdays in the period 2011 to 2012.
Resumo:
Numerous initiatives have been employed around the world in order to address rising greenhouse gas (GHG) emissions originating from the transport sector. These measures include: travel demand management (congestion‐charging), increased fuel taxes, alternative fuel subsidies and low‐emission vehicle (LEV) rebates. Incentivizing the purchase of LEVs has been one of the more prevalent approaches in attempting to tackle this global issue. LEVs, whilst having the advantage of lower emissions and, in some cases, more efficient fuel consumption, also bring the downsides of increased purchase cost, reduced convenience of vehicle fuelling, and operational uncertainty. To stimulate demand in the face of these challenges, various incentive‐based policies, such as toll exemptions, have been used by national and local governments to encourage the purchase of these types of vehicles. In order to address rising GHG emissions in Stockholm, and in line with the Swedish Government’s ambition to operate a fossil free fleet by 2030, a number of policies were implemented targeting the transport sector. Foremost amongst these was the combination of a congestion charge – initiated to discourage emissions‐intensive travel – and an exemption from this charge for some LEVs, established to encourage a transition towards a ‘green’ vehicle fleet. Although both policies shared the aim of reducing GHG emissions, the exemption for LEVs carried the risk of diminishing the effectiveness of the congestion charging scheme. As the number of vehicle owners choosing to transition to an eligible LEV increased, the congestion‐reduction effectiveness of the charging scheme weakened. In fact, policy makers quickly recognized this potential issue and consequently phased out the LEV exemption less than 18 months after its introduction (1). Several studies have investigated the demand for LEVs through stated‐preference (SP) surveys across multiple countries, including: Denmark (2), Germany (3, 4), UK (5), Canada (6), USA (7, 8) and Australia (9). Although each of these studies differed in approach, all involved SP surveys where differing characteristics between various types of vehicles, including LEVs, were presented to respondents and these respondents in turn made hypothetical decisions about which vehicle they would be most likely to purchase. Although these studies revealed a number of interesting findings in regards to the potential demand for LEVs, they relied on SP data. In contrast, this paper employs an approach where LEV choice is modelled by taking a retrospective view and by using revealed preference (RP) data. By examining the revealed preferences of vehicle owners in Stockholm, this study overcomes one of the principal limitations of SP data, namely that stated preferences may not in fact reflect individuals’ actual choices, such as when cost, time, and inconvenience factors are real rather than hypothetical. This paper’s RP approach involves modelling the characteristics of individuals who purchased new LEVs, whilst estimating the effect of the congestion charging exemption upon choice probabilities and subsequent aggregate demand. The paper contributes to the current literature by examining the effectiveness of a toll exemption under revealed preference conditions, and by assessing the total effect of the policy based on key indicators for policy makers, including: vehicle owner home location, commuting patterns, number of children, age, gender and income. Extended Abstract Submission for Kuhmo Nectar Conference 2014 2 The two main research questions motivating this study were: Which individuals chose to purchase a new LEV in Stockholm in 2008?; and, How did the congestion charging exemption affect the aggregate demand for new LEVs in Stockholm in 2008? In order to answer these research questions the analysis was split into two stages. Firstly, a multinomial logit (MNL) model was used to identify which demographic characteristics were most significantly related to the purchase of an LEV over a conventional vehicle. The three most significant variables were found to be: intra‐cordon residency (positive); commuting across the cordon (positive); and distance of residence from the cordon (negative). In order to estimate the effect of the exemption policy on vehicle purchase choice, the model included variables to control for geographic differences in preferences, based on the location of the vehicle owners’ homes and workplaces in relation to the congestion‐charging cordon boundary. These variables included one indicator representing commutes across the cordon and another indicator representing intra‐cordon residency. The effect of the exemption policy on the probability of purchasing LEVs was estimated in the second stage of the analysis by focusing on the groups of vehicle owners that were most likely to have been affected by the policy i.e. those commuting across the cordon boundary (in both directions). Given the inclusion of the indicator variable representing commutes across the cordon, it is assumed that the estimated coefficient of this variable captures the effect of the exemption policy on the utility of choosing to purchase an exempt LEV for these two groups of vehicle owners. The intra‐cordon residency indicator variable also controls for differences between the two groups, based upon direction of travel across the cordon boundary. A counter‐hypothesis to this assumption is that the coefficient of the variable representing commuting across the cordon boundary instead only captures geo‐demographic differences that lead to variations in LEV ownership across the different groups of vehicle owners in relation to the cordon boundary. In order to address this counter‐hypothesis, an additional analysis was performed on data from a city with a similar geodemographic pattern to Stockholm, Gothenburg ‐ Sweden’s second largest city. The results of this analysis provided evidence to support the argument that the coefficient of the variable representing commutes across the cordon was capturing the effect of the exemption policy. Based upon this framework, the predicted vehicle type shares were calculated using the estimated coefficients of the MNL model and compared with predicted vehicle type shares from a simulated scenario where the exemption policy was inactive. This simulated scenario was constructed by setting the coefficient for the variable representing commutes across the cordon boundary to zero for all observations to remove the utility benefit of the exemption policy. Overall, the procedure of this second stage of the analysis led to results showing that the exemption had a substantial effect upon the probability of purchasing and aggregate demand for exempt LEVs in Stockholm during 2008. By making use of unique evidence of revealed preferences of LEV owners, this study identifies the common characteristics of new LEV owners and estimates the effect of Stockholm's congestion charging exemption upon the demand for new LEVs during 2008. It was found that the variables that had the greatest effect upon the choice of purchasing an exempt LEV included intra‐cordon residency (positive), distance of home from the cordon (negative), and commuting across the cordon (positive). It was also determined that owners under the age of 30 years preferred non‐exempt LEVs (low CO2 LEVs), whilst those over the age of 30 years preferred electric vehicles. In terms of electric vehicles, it was apparent that those individuals living within the city had the highest propensity towards purchasing this vehicle type. A negative relationship between choosing an electric vehicle and the distance of an individuals’ residency from the cordon was also evident. Overall, the congestion charging exemption was found to have increased the share of exempt LEVs in Stockholm by 1.9%, with, as expected, a much stronger effect on those commuting across the boundary, with those living inside the cordon having a 13.1% increase, and those owners living outside the cordon having a 5.0% increase. This increase in demand corresponded to an additional 538 (+/‐ 93; 95% C.I.) new exempt LEVs purchased in Stockholm during 2008 (out of a total of 5 427; 9.9%). Policy makers can take note that an incentive‐based policy can increase the demand for LEVs and appears to be an appropriate approach to adopt when attempting to reduce transport emissions through encouraging a transition towards a ‘green’ vehicle fleet.
Resumo:
The endoplasmic reticulum (ER) is the central organelle in the eukaryotic secretory pathway. The ER functions in protein synthesis and maturation and is crucial for proper maintenance of cellular homeostasis and adaptation to adverse environments. Acting as a cellular sentinel, the ER is exquisitely sensitive to changing environments principally via the ER quality control machinery. When perturbed, ER-stress triggers a tightly regulated and highly conserved, signal transduction pathway known as the unfolded protein response (UPR) that prevents the dangerous accumulation of unfolded/misfolded proteins. In situations where excessive UPR activity surpasses threshold levels, cells deteriorate and eventually trigger programmed cell death (PCD) as a way for the organism to cope with dysfunctional or toxic signals. The programmed cell death that results from excessive ER stress in mammalian systems contributes to several important diseases including hypoxia, neurodegeneration, and diabetes. Importantly, hallmark features and markers of cell death that are associated with ER stress in mammals are also found in plants. In particular, there is a common, conserved set of chaperones that modulate ER cell death signaling. Here we review the elements of plant cell death responses to ER stress and note that an increasing number of plant-pathogen interactions are being identified in which the host ER is targeted by plant pathogens to establish compatibility.
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In C & E Pty Ltd v Corrigan [2006] QCA 47, the Queensland Court of Appeal considered whether r103 of the Uniform Civil Procedure Rules applied to the service of an application to set aside a statutory demand under s459G of the Corporations Act 2001 (Cth). The decision provides analysis and clarification of an issue that has clearly been one of some uncertainty.
Resumo:
Background & Objectives Emergency health services (EHS) throughout the world are increasingly congested. As more people use EHS, factors such as population growth and aging cannot fully explain this increase. Also, focus on patients’ clinical characteristics ignores the role that attitudinal and perceptual factors and motivations play in directing their decisions and actions. The aim of this study is to review and synthesize an integrated conceptual framework for understanding social psychological factors underpinning demand for EHS. Methodology A comprehensive search and review of empirical and theoretical studies about the utilization of EHS was conducted using major medical, health, social and behavioral sciences databases. Results A small number of studies used a relevant conceptual framework (e.g. Health Services Utilization Model or Health Belief Model) or their components to analyze patients’ decision to use EHS. The studies evidenced that demand was affected by perceived severity of the condition; perceived costs and benefits (e.g. availability, accessibility and affordability of alternative services); experience, preference and knowledge; perceived and actual social support; and demographic characteristics (e.g. age, sex, socioeconomic status, ethnicity, marital and living circumstances, place of residence). Conclusions Conceptual models that are commonly used in areas like social and behavioral sciences have rarely been applied in the EHS utilization field. Understanding patients’ decision-making and associated factors will lay the groundwork for identification of the evidence to inform improved policy responses and the development of demand management strategies. An integrated conceptual framework will be introduced as part of this study.
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Sensing the mental, physical and emotional demand of a driving task is of primary importance in road safety research and for effectively designing in-vehicle information systems (IVIS). Particularly, the need of cars capable of sensing and reacting to the emotional state of the driver has been repeatedly advocated in the literature. Algorithms and sensors to identify patterns of human behavior, such as gestures, speech, eye gaze and facial expression, are becoming available by using low cost hardware: This paper presents a new system which uses surrogate measures such as facial expression (emotion) and head pose and movements (intention) to infer task difficulty in a driving situation. 11 drivers were recruited and observed in a simulated driving task that involved several pre-programmed events aimed at eliciting emotive reactions, such as being stuck behind slower vehicles, intersections and roundabouts, and potentially dangerous situations. The resulting system, combining face expressions and head pose classification, is capable of recognizing dangerous events (such as crashes and near misses) and stressful situations (e.g. intersections and way giving) that occur during the simulated drive.
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This paper estimates the demand for transportation systems that are used primarily by disabled individuals. These systems are known as paratransit systems and have experienced large increases in number and average size over the past 15 years. We first use a national database and standard time series techniques to model aggregate demand. We then use a unique data set of administrative records from a paratransit system in central Virginia to estimate standard and nonstandard count models of individual demand. We conclude that most of the demand growth is from new passengers, but that predicting the growth of new passengers is very difficult. Our results also highlight the importance of incorporating autocorrelation and possible sample attrition into standard count models.
Resumo:
We describe a passenger education program to encourage responsible use of paratransit by people with disabilities. We use state-of-the-art econometric techniques to evaluate its success. We find that it has moderate effects on demand for transportation but large effects on how passengers use the transportation. In particular, passengers are more responsible about meeting the transportation at the curb rather than waiting for help inside their home. Cost-benefit analysis of the program suggests that it is a long-term worthwhile activity.
Resumo:
This paper uses a correlated multinomial logit model and a Poisson regression model to measure the factors affecting demand for different types of transportation by elderly and disabled people in rural Virginia. The major results are: (a) A paratransit system providing door-to-door service is highly valued by transportation-handicapped people; (b) Taxis are probably a potential but inferior alternative even when subsidized; (c) Buses are a poor alternative, especially in rural areas where distances to bus stops may be long; (d) Making buses handicap-accessible would have a statistically significant but small effect on mode choice; (e) Demand is price inelastic; and (f) The total number of trips taken is insensitive to mode availability and characteristics. These results suggest that transportation-handicapped people take a limited number of trips. Those they do take are in some sense necessary (given the low elasticity with respect to mode price or availability). People will substitute away from relying upon others when appropriate transportation is available, at least to some degree. But such transportation needs to be flexible enough to meet the needs of the people involved.
Semiparametric estimates of the supply and demand effects of disability on labor force participation
Resumo:
This paper modifies and uses the semiparametric methods of Ichimura and Lee (1991) on standard cross-section data to decompose the effect of disability on labor force participation into a demand and a supply effect. It shows that straightforward use of Ichimura and Lee leads to meaningless results while imposing monotonicity on the unknown function leads to substantial results. The paper finds that supply effects dominate the demand effects of disability.
Resumo:
This study determined the current trends in supply, demand, and equilibrium (ie, the level of employment where supply equals demand) in the market for Certified Registered Nurse Anesthetists (CRNAs). It also forecasts future needs for CRNAs given different possible scenarios. The impact of the current availability of CRNAs, projected retirements, and changes in the demand for surgeries are considered in relation to CRNAs needed for the future. The study used data from many sources to estimate models associated with the supply and demand for CRNAs and the relationship to relevant community and policy characteristics such as per capita income of the community and managed care. These models were used to forecast changes in surgeries and in the supply of CRNAs in the future. The supply of CRNAs has increased in recent years, stimulated by shortages of CRNAs and subsequent increases in the number of CRNAs trained. However, the increases have not offset the number of retiring CRNAs to maintain a constant age in the CRNA population. The average age will continue to increase for CRNAs in the near future despite increases in CRNAs trained. The supply of CRNAs in relation to surgeries will increase in the near future.
Resumo:
Recurrent congestion caused by high commuter traffic is an irritation to motorway users. Ramp metering (RM) is the most effective motorway control means (M Papageorgiou & Kotsialos, 2002) for significantly reducing motorway congestion. However, given field constraints (e.g. limited ramp space and maximum ramp waiting time), RM cannot eliminate recurrent congestion during the increased long peak hours. This paper, therefore, focuses on rapid congestion recovery to further improve RM systems: that is, to quickly clear congestion in recovery periods. The feasibility of using RM for recovery is analyzed, and a zone recovery strategy (ZRS) for RM is proposed. Note that this study assumes no incident and demand management involved, i.e. no re-routing behavior and strategy considered. This strategy is modeled, calibrated and tested in the northbound model of the Pacific Motorway, Brisbane, Australia in a micro-simulation environment for recurrent congestion scenario, and evaluation results have justified its effectiveness.