Robust Unit Commitment Considering Uncertain Demand Response
Liu, Guodong; Tomsovic, Kevin
2014-09-28
Although price responsive demand response has been widely accepted as playing an important role in the reliable and economic operation of power system, the real response from demand side can be highly uncertain due to limited understanding of consumers' response to pricing signals. To model the behavior of consumers, the price elasticity of demand has been explored and utilized in both research and real practice. However, the price elasticity of demand is not precisely known and may vary greatly with operating conditions and types of customers. To accommodate the uncertainty of demand response, alternative unit commitment methods robust to themore » uncertainty of the demand response require investigation. In this paper, a robust unit commitment model to minimize the generalized social cost is proposed for the optimal unit commitment decision taking into account uncertainty of the price elasticity of demand. By optimizing the worst case under proper robust level, the unit commitment solution of the proposed model is robust against all possible realizations of the modeled uncertain demand response. Numerical simulations on the IEEE Reliability Test System show the e ectiveness of the method. Finally, compared to unit commitment with deterministic price elasticity of demand, the proposed robust model can reduce the average Locational Marginal Prices (LMPs) as well as the price volatility.« less
Aggregate modeling of fast-acting demand response and control under real-time pricing
Chassin, David P.; Rondeau, Daniel
2016-08-24
This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less
Aggregate modeling of fast-acting demand response and control under real-time pricing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chassin, David P.; Rondeau, Daniel
This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. Finally, the results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less
Aggregate modeling of fast-acting demand response and control under real-time pricing
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chassin, David P.; Rondeau, Daniel
This paper develops and assesses the performance of a short-term demand response (DR) model for utility load control with applications to resource planning and control design. Long term response models tend to underestimate short-term demand response when induced by prices. This has two important consequences. First, planning studies tend to undervalue DR and often overlook its benefits in utility demand management program development. Second, when DR is not overlooked, the open-loop DR control gain estimate may be too low. This can result in overuse of load resources, control instability and excessive price volatility. Our objective is therefore to develop amore » more accurate and better performing short-term demand response model. We construct the model from first principles about the nature of thermostatic load control and show that the resulting formulation corresponds exactly to the Random Utility Model employed in economics to study consumer choice. The model is tested against empirical data collected from field demonstration projects and is shown to perform better than alternative models commonly used to forecast demand in normal operating conditions. The results suggest that (1) existing utility tariffs appear to be inadequate to incentivize demand response, particularly in the presence of high renewables, and (2) existing load control systems run the risk of becoming unstable if utilities close the loop on real-time prices.« less
NASA Astrophysics Data System (ADS)
Huang, Y.; Liu, B. Z.; Wang, K. Y.; Ai, X.
2017-12-01
In response to the new requirements of the operation mode of wind-storage combined system and demand side response for transmission network planning, this paper presents a joint planning of energy storage and transmission considering wind-storage combined system and demand side response. Firstly, the charge-discharge strategy of energy storage system equipped at the outlet of wind farm and demand side response strategy are analysed to achieve the best comprehensive benefits through the coordination of the two. Secondly, in the general transmission network planning model with wind power, both energy storage cost and demand side response cost are added to the objective function. Not only energy storage operation constraints and but also demand side response constraints are introduced into the constraint condition. Based on the classical formulation of TEP, a new formulation is developed considering the simultaneous addition of the charge-discharge strategy of energy storage system equipped at the outlet of the wind farm and demand side response strategy, which belongs to a typical mixed integer linear programming model that can be solved by mature optimization software. The case study based on the Garver-6 bus system shows that the validity of the proposed model is verified by comparison with general transmission network planning model. Furthermore, the results demonstrate that the joint planning model can gain more economic benefits through setting up different cases.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Joyce Jihyun; Yin, Rongxin; Kiliccote, Sila
Open Automated Demand Response (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demand response participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demand response programs in New York and discuss OpenADR communication, prioritization of demand response signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demand response capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate bothmore » demand response participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.« less
Michigan's Statewide Travel Demand Model
DOT National Transportation Integrated Search
1999-09-01
The Travel Demand and Intermodal Services Section of Michigan's Department of Transportation is responsible for the development, maintenance and application of the Statewide Travel Demand Model. Michigan's Statewide and Urban Travel Demand Models are...
Renewable Energy Resources Portfolio Optimization in the Presence of Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Behboodi, Sahand; Chassin, David P.; Crawford, Curran
In this paper we introduce a simple cost model of renewable integration and demand response that can be used to determine the optimal mix of generation and demand response resources. The model includes production cost, demand elasticity, uncertainty costs, capacity expansion costs, retirement and mothballing costs, and wind variability impacts to determine the hourly cost and revenue of electricity delivery. The model is tested on the 2024 planning case for British Columbia and we find that cost is minimized with about 31% renewable generation. We also find that demand responsive does not have a significant impact on cost at themore » hourly level. The results suggest that the optimal level of renewable resource is not sensitive to a carbon tax or demand elasticity, but it is highly sensitive to the renewable resource installation cost.« less
DOT National Transportation Integrated Search
2016-08-01
The objective of this study is to develop a model for estimating demand for rural demand-response transit services for the general public. Lack of data for demand-response service characteristics and geographic coverage has limited the development of...
Design of demand side response model in energy internet demonstration park
NASA Astrophysics Data System (ADS)
Zhang, Q.; Liu, D. N.
2017-08-01
The implementation of demand side response can bring a lot of benefits to the power system, users and society, but there are still many problems in the actual operation. Firstly, this paper analyses the current situation and problems of demand side response. On this basis, this paper analyses the advantages of implementing demand side response in the energy Internet demonstration park. Finally, the paper designs three kinds of feasible demand side response modes in the energy Internet demonstration park.
Modeling demand for public transit services in rural areas
DOE Office of Scientific and Technical Information (OSTI.GOV)
Attaluri, P.; Seneviratne, P.N.; Javid, M.
1997-05-01
Accurate estimates of demand are critical for planning, designing, and operating public transit systems. Previous research has demonstrated that the expected demand in rural areas is a function of both demographic and transit system variables. Numerous models have been proposed to describe the relationship between the aforementioned variables. However, most of them are site specific and their validity over time and space is not reported or perhaps has not been tested. Moreover, input variables in some cases are extremely difficult to quantify. In this article, the estimation of demand using the generalized linear modeling technique is discussed. Two separate models,more » one for fixed-route and another for demand-responsive services, are presented. These models, calibrated with data from systems in nine different states, are used to demonstrate the appropriateness and validity of generalized linear models compared to the regression models. They explain over 70% of the variation in expected demand for fixed-route services and 60% of the variation in expected demand for demand-responsive services. It was found that the models are spatially transferable and that data for calibration are easily obtainable.« less
Demand Response Resource Quantification with Detailed Building Energy Models
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hale, Elaine; Horsey, Henry; Merket, Noel
Demand response is a broad suite of technologies that enables changes in electrical load operations in support of power system reliability and efficiency. Although demand response is not a new concept, there is new appetite for comprehensively evaluating its technical potential in the context of renewable energy integration. The complexity of demand response makes this task difficult -- we present new methods for capturing the heterogeneity of potential responses from buildings, their time-varying nature, and metrics such as thermal comfort that help quantify likely acceptability of specific demand response actions. Computed with an automated software framework, the methods are scalable.
The Role of Demand Response in Reducing Water-Related Power Plant Vulnerabilities
NASA Astrophysics Data System (ADS)
Macknick, J.; Brinkman, G.; Zhou, E.; O'Connell, M.; Newmark, R. L.; Miara, A.; Cohen, S. M.
2015-12-01
The electric sector depends on readily available water supplies for reliable and efficient operation. Elevated water temperatures or low water levels can trigger regulatory or plant-level decisions to curtail power generation, which can affect system cost and reliability. In the past decade, dozens of power plants in the U.S. have curtailed generation due to water temperatures and water shortages. Curtailments occur during the summer, when temperatures are highest and there is greatest demand for electricity. Climate change could alter the availability and temperature of water resources, exacerbating these issues. Constructing alternative cooling systems to address vulnerabilities can be capital intensive and can also affect power plant efficiencies. Demand response programs are being implemented by electric system planners and operators to reduce and shift electricity demands from peak usage periods to other times of the day. Demand response programs can also play a role in reducing water-related power sector vulnerabilities during summer months. Traditionally, production cost modeling and demand response analyses do not include water resources. In this effort, we integrate an electricity production cost modeling framework with water-related impacts on power plants in a test system to evaluate the impacts of demand response measures on power system costs and reliability. Specifically, we i) quantify the cost and reliability implications of incorporating water resources into production cost modeling, ii) evaluate the impacts of demand response measures on reducing system costs and vulnerabilities, and iii) consider sensitivity analyses with cooling systems to highlight a range of potential benefits of demand response measures. Impacts from climate change on power plant performance and water resources are discussed. Results provide key insights to policymakers and practitioners for reducing water-related power plant vulnerabilities via lower cost methods.
Electric Water Heater Modeling and Control Strategies for Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.
2012-07-22
Abstract— Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency supportmore » following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms— Centralized control, decentralized control, demand response, electrical water heater, smart grid« less
NASA Astrophysics Data System (ADS)
Schmidt, R. D.; Taylor, R. G.; Stodick, L. D.; Contor, B. A.
2009-12-01
A recent federal interagency report on climate change and water management (Brekke et. al., 2009) describes several possible management responses to the impacts of climate change on water supply and demand. Management alternatives include changes to water supply infrastructure, reservoir system operations, and water demand policies. Water users in the Bureau of Reclamation’s Boise Project (located in the Lower Boise River basin in southwestern Idaho) would be among those impacted both hydrologically and economically by climate change. Climate change and management responses to climate change are expected to cause shifts in water supply and demand. Supply shifts would result from changes in basin precipitation patterns, and demand shifts would result from higher evapotranspiration rates and a longer growing season. The impacts would also extend to non-Project water users in the basin, since most non-Project groundwater pumpers and drain water diverters rely on hydrologic externalities created by seepage losses from Boise Project water deliveries. An integrated hydrologic-economic model was developed for the Boise basin to aid Reclamation in evaluating the hydrologic and economic impacts of various management responses to climate change. A spatial, partial-equilibrium, economic optimization model calculates spatially-distinct equilibrium water prices and quantities, and maximizes a social welfare function (the sum of consumer and producers surpluses) for all agricultural and municipal water suppliers and demanders (both Project and non-Project) in the basin. Supply-price functions and demand-price functions are exogenous inputs to the economic optimization model. On the supply side, groundwater and river/reservoir models are used to generate hydrologic responses to various management alternatives. The response data is then used to develop water supply-price functions for Project and non-Project water users. On the demand side, crop production functions incorporating crop distribution, evapotranspiration rates, irrigation efficiencies, and crop prices are used to develop water demand-price functions for agricultural water users. Demand functions for municipal and industrial water users are also developed. Recent applications of the integrated model have focused on the hydrologic and economic impacts of demand management alternatives, including large-scale canal lining conservation measures, and market-based water trading between canal diverters and groundwater pumpers. A supply management alternative being investigated involves revising reservoir rule curves to compensate for climate change impacts on timing of reservoir filling.
Teaching Aggregate Demand and Supply Models
ERIC Educational Resources Information Center
Wells, Graeme
2010-01-01
The author analyzes the inflation-targeting model that underlies recent textbook expositions of the aggregate demand-aggregate supply approach used in introductory courses in macroeconomics. He shows how numerical simulations of a model with inflation inertia can be used as a tool to help students understand adjustments in response to demand and…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Broeer, Torsten; Fuller, Jason C.; Tuffner, Francis K.
2014-01-31
Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generatormore » and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demand response to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of Demand Response (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.« less
Modelling Per Capita Water Demand Change to Support System Planning
NASA Astrophysics Data System (ADS)
Garcia, M. E.; Islam, S.
2016-12-01
Water utilities have a number of levers to influence customer water usage. These include levers to proactively slow demand growth over time such as building and landscape codes as well as levers to decrease demands quickly in response to water stress including price increases, education campaigns, water restrictions, and incentive programs. Even actions aimed at short term reductions can result in long term water usage declines when substantial changes are made in water efficiency, as in incentives for fixture replacement or turf removal, or usage patterns such as permanent lawn watering restrictions. Demand change is therefore linked to hydrological conditions and to the effects of past management decisions - both typically included in water supply planning models. Yet, demand is typically incorporated exogenously using scenarios or endogenously using only price, though utilities also use rules and incentives issued in response to water stress and codes specifying standards for new construction to influence water usage. Explicitly including these policy levers in planning models enables concurrent testing of infrastructure and policy strategies and illuminates interactions between the two. The City of Las Vegas is used as a case study to develop and demonstrate this modeling approach. First, a statistical analysis of system data was employed to rule out alternate hypotheses of per capita demand decrease such as changes in population density and economic structure. Next, four demand sub-models were developed including one baseline model in which demand is a function of only price. The sub-models were then calibrated and tested using monthly data from 1997 to 2012. Finally, the best performing sub-model was integrated with a full supply and demand model. The results highlight the importance of both modeling water demand dynamics endogenously and taking a broader view of the variables influencing demand change.
Price Responsiveness in the AEO2003 NEMS Residential and Commercial Buildings Sector Models
2003-01-01
This paper describes the demand responses to changes in energy prices in the Annual Energy Outlook 2003 versions of the Residential and Commercial Demand Modules of the National Energy Modeling System (NEMS). It updates a similar paper completed for the Annual Energy Outlook 1999 version of the NEMS.
Auto-DR and Pre-cooling of Buildings at Tri-City Corporate Center
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yin, Rongxin; Xu, Peng; Kiliccote, Sila
2008-11-01
Over the several past years, Lawrence Berkeley National Laboratory (LBNL) has conducted field tests for different pre-cooling strategies in different commercial buildings within California. The test results indicated that pre-cooling strategies were effective in reducing electric demand in these buildings during peak periods. This project studied how to optimize pre-cooling strategies for eleven buildings in the Tri-City Corporate Center, San Bernardino, California with the assistance of a building energy simulation tool -- the Demand Response Quick Assessment Tool (DRQAT) developed by LBNL's Demand Response Research Center funded by the California Energy Commission's Public Interest Energy Research (PIER) Program. From themore » simulation results of these eleven buildings, optimal pre-cooling and temperature reset strategies were developed. The study shows that after refining and calibrating initial models with measured data, the accuracy of the models can be greatly improved and the models can be used to predict load reductions for automated demand response (Auto-DR) events. This study summarizes the optimization experience of the procedure to develop and calibrate building models in DRQAT. In order to confirm the actual effect of demand response strategies, the simulation results were compared to the field test data. The results indicated that the optimal demand response strategies worked well for all buildings in the Tri-City Corporate Center. This study also compares DRQAT with other building energy simulation tools (eQUEST and BEST). The comparison indicate that eQUEST and BEST underestimate the actual demand shed of the pre-cooling strategies due to a flaw in DOE2's simulation engine for treating wall thermal mass. DRQAT is a more accurate tool in predicting thermal mass effects of DR events.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Macknick, Jordan; Zhou, Ella; O'Connell, Matthew
The U.S. electricity sector is highly dependent upon water resources; changes in water temperatures and water availability can affect operational costs and the reliability of power systems. Despite the importance of water for power system operations, the effects of changes in water characteristics on multiple generators in a system are generally not modeled. Moreover, demand response measures, which can change the magnitude and timing of loads and can have beneficial impacts on power system operations, have not yet been evaluated in the context of water-related power vulnerabilities. This effort provides a first comprehensive vulnerability and cost analysis of water-related impactsmore » on a modeled power system and the potential for demand response measures to address vulnerability and cost concerns. This study uniquely combines outputs and inputs of a water and power plant system model, production cost, model, and relative capacity value model to look at variations in cooling systems, policy-related thermal curtailments, and demand response measures to characterize costs and vulnerability for a test system. Twenty-five scenarios over the course of one year are considered: a baseline scenario as well as a suite of scenarios to evaluate six cooling system combinations, the inclusion or exclusion of policy-related thermal curtailments, and the inclusion or exclusion of demand response measures. A water and power plant system model is utilized to identify changes in power plant efficiencies resulting from ambient conditions, a production cost model operating at an hourly scale is used to calculate generation technology dispatch and costs, and a relative capacity value model is used to evaluate expected loss of carrying capacity for the test system.« less
Taxonomy for Modeling Demand Response Resources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olsen, Daniel; Kiliccote, Sila; Sohn, Michael
2014-08-01
Demand response resources are an important component of modern grid management strategies. Accurate characterizations of DR resources are needed to develop systems of optimally managed grid operations and to plan future investments in generation, transmission, and distribution. The DOE Demand Response and Energy Storage Integration Study (DRESIS) project researched the degree to which demand response (DR) and energy storage can provide grid flexibility and stability in the Western Interconnection. In this work, DR resources were integrated with traditional generators in grid forecasting tools, specifically a production cost model of the Western Interconnection. As part of this study, LBNL developed amore » modeling framework for characterizing resource availability and response attributes of DR resources consistent with the governing architecture of the simulation modeling platform. In this report, we identify and describe the following response attributes required to accurately characterize DR resources: allowable response frequency, maximum response duration, minimum time needed to achieve load changes, necessary pre- or re-charging of integrated energy storage, costs of enablement, magnitude of controlled resources, and alignment of availability. We describe a framework for modeling these response attributes, and apply this framework to characterize 13 DR resources including residential, commercial, and industrial end-uses. We group these end-uses into three broad categories based on their response capabilities, and define a taxonomy for classifying DR resources within these categories. The three categories of resources exhibit different capabilities and differ in value to the grid. Results from the production cost model of the Western Interconnection illustrate that minor differences in resource attributes can have significant impact on grid utilization of DR resources. The implications of these findings will be explored in future DR valuation studies.« less
ERIC Educational Resources Information Center
Bakker, Arnold B.; ten Brummelhuis, Lieke L.; Prins, Jelle T.; van der Heijden, Frank M. M. A.
2011-01-01
Work-home interference (WHI) is a prevalent problem because most employees have substantial family responsibilities on top of their work demands. The present study hypothesized that high job demands in combination with low job resources contribute to WHI. The job demands-resources (JD-R) model was used as a theoretical framework. Using a sample of…
Calibrating Physical Parameters in House Models Using Aggregate AC Power Demand
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Yannan; Stevens, Andrew J.; Lian, Jianming
For residential houses, the air conditioning (AC) units are one of the major resources that can provide significant flexibility in energy use for the purpose of demand response. To quantify the flexibility, the characteristics of all the houses need to be accurately estimated, so that certain house models can be used to predict the dynamics of the house temperatures in order to adjust the setpoints accordingly to provide demand response while maintaining the same comfort levels. In this paper, we propose an approach using the Reverse Monte Carlo modeling method and aggregate house models to calibrate the distribution parameters ofmore » the house models for a population of residential houses. Given the aggregate AC power demand for the population, the approach can successfully estimate the distribution parameters for the sensitive physical parameters based on our previous uncertainty quantification study, such as the mean of the floor areas of the houses.« less
Cyber Physical System Modelling of Distribution Power Systems for Dynamic Demand Response
NASA Astrophysics Data System (ADS)
Chu, Xiaodong; Zhang, Rongxiang; Tang, Maosen; Huang, Haoyi; Zhang, Lei
2018-01-01
Dynamic demand response (DDR) is a package of control methods to enhance power system security. A CPS modelling and simulation platform for DDR in distribution power systems is presented in this paper. CPS modelling requirements of distribution power systems are analyzed. A coupled CPS modelling platform is built for assessing DDR in the distribution power system, which combines seamlessly modelling tools of physical power networks and cyber communication networks. Simulations results of IEEE 13-node test system demonstrate the effectiveness of the modelling and simulation platform.
Modeling Demand-Responsive Feeder Systems in the UTPS Framework
DOT National Transportation Integrated Search
1978-07-01
For the transit planner considering alternative future transit designs, there has been little in the way of analytical tools available to assess the impact of demand-responsive transportation (DRT) systems. The intent of this report is to provide the...
Tracing regulatory routes in metabolism using generalised supply-demand analysis.
Christensen, Carl D; Hofmeyr, Jan-Hendrik S; Rohwer, Johann M
2015-12-03
Generalised supply-demand analysis is a conceptual framework that views metabolism as a molecular economy. Metabolic pathways are partitioned into so-called supply and demand blocks that produce and consume a particular intermediate metabolite. By studying the response of these reaction blocks to perturbations in the concentration of the linking metabolite, different regulatory routes of interaction between the metabolite and its supply and demand blocks can be identified and their contribution quantified. These responses are mediated not only through direct substrate/product interactions, but also through allosteric effects. Here we subject previously published kinetic models of pyruvate metabolism in Lactococcus lactis and aspartate-derived amino acid synthesis in Arabidopsis thaliana to generalised supply-demand analysis. Multiple routes of regulation are brought about by different mechanisms in each model, leading to behavioural and regulatory patterns that are generally difficult to predict from simple inspection of the reaction networks depicting the models. In the pyruvate model the moiety-conserved cycles of ATP/ADP and NADH/NAD(+) allow otherwise independent metabolic branches to communicate. This causes the flux of one ATP-producing reaction block to increase in response to an increasing ATP/ADP ratio, while an NADH-consuming block flux decreases in response to an increasing NADH/NAD(+) ratio for certain ratio value ranges. In the aspartate model, aspartate semialdehyde can inhibit its supply block directly or by increasing the concentration of two amino acids (Lys and Thr) that occur as intermediates in demand blocks and act as allosteric inhibitors of isoenzymes in the supply block. These different routes of interaction from aspartate semialdehyde are each seen to contribute differently to the regulation of the aspartate semialdehyde supply block. Indirect routes of regulation between a metabolic intermediate and a reaction block that either produces or consumes this intermediate can play a much larger regulatory role than routes mediated through direct interactions. These indirect routes of regulation can also result in counter-intuitive metabolic behaviour. Performing generalised supply-demand analysis on two previously published models demonstrated the utility of this method as an entry point in the analysis of metabolic behaviour and the potential for obtaining novel results from previously analysed models by using new approaches.
History-Based Response Threshold Model for Division of Labor in Multi-Agent Systems
Lee, Wonki; Kim, DaeEun
2017-01-01
Dynamic task allocation is a necessity in a group of robots. Each member should decide its own task such that it is most commensurate with its current state in the overall system. In this work, the response threshold model is applied to a dynamic foraging task. Each robot employs a task switching function based on the local task demand obtained from the surrounding environment, and no communication occurs between the robots. Each individual member has a constant-sized task demand history that reflects the global demand. In addition, it has response threshold values for all of the tasks and manages the task switching process depending on the stimuli of the task demands. The robot then determines the task to be executed to regulate the overall division of labor. This task selection induces a specialized tendency for performing a specific task and regulates the division of labor. In particular, maintaining a history of the task demands is very effective for the dynamic foraging task. Various experiments are performed using a simulation with multiple robots, and the results show that the proposed algorithm is more effective as compared to the conventional model. PMID:28555031
The impact of changing technology on the demand for air transportation
NASA Technical Reports Server (NTRS)
Kneafsey, J. T.; Taneja, N. K.
1978-01-01
Demand models for air transportation that are sensitive to the impact of changing technology were developed. The models are responsive to potential changes in technology, and to changing economic, social, and political factors as well. In addition to anticipating the wide differences in the factors influencing the demand for long haul and short haul air travel, the models were designed to clearly distinguish among the unique features of these markets.
Dynamic management of integrated residential energy systems
NASA Astrophysics Data System (ADS)
Muratori, Matteo
This study combines principles of energy systems engineering and statistics to develop integrated models of residential energy use in the United States, to include residential recharging of electric vehicles. These models can be used by government, policymakers, and the utility industry to provide answers and guidance regarding the future of the U.S. energy system. Currently, electric power generation must match the total demand at each instant, following seasonal patterns and instantaneous fluctuations. Thus, one of the biggest drivers of costs and capacity requirement is the electricity demand that occurs during peak periods. These peak periods require utility companies to maintain operational capacity that often is underutilized, outdated, expensive, and inefficient. In light of this, flattening the demand curve has long been recognized as an effective way of cutting the cost of producing electricity and increasing overall efficiency. The problem is exacerbated by expected widespread adoption of non-dispatchable renewable power generation. The intermittent nature of renewable resources and their non-dispatchability substantially limit the ability of electric power generation of adapting to the fluctuating demand. Smart grid technologies and demand response programs are proposed as a technical solution to make the electric power demand more flexible and able to adapt to power generation. Residential demand response programs offer different incentives and benefits to consumers in response to their flexibility in the timing of their electricity consumption. Understanding interactions between new and existing energy technologies, and policy impacts therein, is key to driving sustainable energy use and economic growth. Comprehensive and accurate models of the next-generation power system allow for understanding the effects of new energy technologies on the power system infrastructure, and can be used to guide policy, technology, and economic decisions. This dissertation presents a bottom-up highly resolved model of a generic residential energy eco-system in the United States. The model is able to capture the entire energy footprint of an individual household, to include all appliances, space conditioning systems, in-home charging of plug-in electric vehicles, and any other energy needs, viewing residential and transportation energy needs as an integrated continuum. The residential energy eco-system model is based on a novel bottom-up approach that quantifies consumer energy use behavior. The incorporation of stochastic consumer behaviors allows capturing the electricity consumption of each residential specific end-use, providing an accurate estimation of the actual amount of available controllable resources, and for a better understanding of the potential of residential demand response programs. A dynamic energy management framework is then proposed to manage electricity consumption inside each residential energy eco-system. Objective of the dynamic energy management framework is to optimize the scheduling of all the controllable appliances and in-home charging of plug-in electric vehicles to minimize cost. Such an automated energy management framework is used to simulate residential demand response programs, and evaluate their impact on the electric power infrastructure. For instance, time-varying electricity pricing might lead to synchronization of the individual residential demands, creating pronounced rebound peaks in the aggregate demand that are higher and steeper than the original demand peaks that the time-varying electricity pricing structure intended to eliminate. The modeling tools developed in this study can serve as a virtual laboratory for investigating fundamental economic and policy-related questions regarding the interplay of individual consumers with energy use. The models developed allow for evaluating the impact of different energy policies, technology adoption, and electricity price structures on the total residential electricity demand. In particular, two case studies are reported in this dissertation to illustrate application of the tools developed. The first considers the impact of market penetration of plug-in electric vehicles on the electric power infrastructure. The second provides a quantitative comparison of the impact of different electricity price structures on residential demand response. Simulation results and an electricity price structure, called Multi-TOU, aimed at solving the rebound peak issue, are presented.
A Hybrid Demand Response Simulator Version 1.0
DOE Office of Scientific and Technical Information (OSTI.GOV)
2012-05-02
A hybrid demand response simulator is developed to test different control algorithms for centralized and distributed demand response (DR) programs in a small distribution power grid. The HDRS is designed to model a wide variety of DR services such as peak having, load shifting, arbitrage, spinning reserves, load following, regulation, emergency load shedding, etc. The HDRS does not model the dynamic behaviors of the loads, rather, it simulates the load scheduling and dispatch process. The load models include TCAs (water heaters, air conditioners, refrigerators, freezers, etc) and non-TCAs (lighting, washer, dishwasher, etc.) The ambient temperature changes, thermal resistance, capacitance, andmore » the unit control logics can be modeled for TCA loads. The use patterns of the non-TCA can be modeled by probability of use and probabilistic durations. Some of the communication network characteristics, such as delays and errors, can also be modeled. Most importantly, because the simulator is modular and greatly simplified the thermal models for TCA loads, it is very easy and fast to be used to test and validate different control algorithms in a simulated environment.« less
The value of demand response in Florida
DOE Office of Scientific and Technical Information (OSTI.GOV)
Stoll, Brady; Buechler, Elizabeth; Hale, Elaine
Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.
The value of demand response in Florida
Stoll, Brady; Buechler, Elizabeth; Hale, Elaine
2017-11-10
Many electrical loads may be operated flexibly to provide grid services, including peaking capacity, reserves, and load shifting. The authors model 14 demand end uses in Florida and analyze their operational impacts and overall value for a wide range of solar penetrations and grid flexibility options. They find demand response is able to reduce production costs, reduce the number of low-load hours for traditional generators, reduce starting of gas generators, and reduce curtailment.
The Impact of Uncertain Physical Parameters on HVAC Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sun, Yannan; Elizondo, Marcelo A.; Lu, Shuai
HVAC units are currently one of the major resources providing demand response (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units.more » These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demand response.« less
Fournier, Lisa R; Herbert, Rhonda J; Farris, Carrie
2004-10-01
This study examined how response mapping of features within single- and multiple-feature targets affects decision-based processing and attentional capacity demands. Observers judged the presence or absence of 1 or 2 target features within an object either presented alone or with distractors. Judging the presence of 2 features relative to the less discriminable of these features alone was faster (conjunction benefits) when the task-relevant features differed in discriminability and were consistently mapped to responses. Conjunction benefits were attributed to asynchronous decision priming across attended, task-relevant dimensions. A failure to find conjunction benefits for disjunctive conjunctions was attributed to increased memory demands and variable feature-response mapping for 2- versus single-feature targets. Further, attentional demands were similar between single- and 2-feature targets when response mapping, memory demands, and discriminability of the task-relevant features were equated between targets. Implications of the findings for recent attention models are discussed. (c) 2004 APA, all rights reserved
Wu, Ching-Han; Hwang, Kevin P
2009-12-01
To improve ambulance response time, matching ambulance availability with the emergency demand is crucial. To maintain the standard of 90% of response times within 9 minutes, the authors introduce a discrete-event simulation method to estimate the threshold for expanding the ambulance fleet when demand increases and to find the optimal dispatching strategies when provisional events create temporary decreases in ambulance availability. The simulation model was developed with information from the literature. Although the development was theoretical, the model was validated on the emergency medical services (EMS) system of Tainan City. The data are divided: one part is for model development, and the other for validation. For increasing demand, the effect was modeled on response time when call arrival rates increased. For temporary availability decreases, the authors simulated all possible alternatives of ambulance deployment in accordance with the number of out-of-routine-duty ambulances and the durations of three types of mass gatherings: marathon races (06:00-10:00 hr), rock concerts (18:00-22:00 hr), and New Year's Eve parties (20:00-01:00 hr). Statistical analysis confirmed that the model reasonably represented the actual Tainan EMS system. The response-time standard could not be reached when the incremental ratio of call arrivals exceeded 56%, which is the threshold for the Tainan EMS system to expand its ambulance fleet. When provisional events created temporary availability decreases, the Tainan EMS system could spare at most two ambulances from the standard configuration, except between 20:00 and 01:00, when it could spare three. The model also demonstrated that the current Tainan EMS has two excess ambulances that could be dropped. The authors suggest dispatching strategies to minimize the response times in routine daily emergencies. Strategies of capacity management based on this model improved response times. The more ambulances that are out of routine duty, the better the performance of the optimal strategies that are based on this model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chen, Qifang; Wang, Fei; Hodge, Bri-Mathias
A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and uppermore » bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.« less
Centralized and Decentralized Control for Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng
2011-04-29
Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity,more » and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.« less
Pupillary Response to Cognitive Demand in Parkinson’s Disease: A Pilot Study
Kahya, Melike; Moon, Sanghee; Lyons, Kelly E.; Pahwa, Rajesh; Akinwuntan, Abiodun E.; Devos, Hannes
2018-01-01
Previous studies have shown that pupillary response, a physiological measure of cognitive workload, reflects cognitive demand in healthy younger and older adults. However, the relationship between cognitive workload and cognitive demand in Parkinson’s disease (PD) remains unclear. The aim of this pilot study was to examine the pupillary response to cognitive demand in a letter-number sequencing (LNS) task between 16 non-demented individuals with PD (age, median (Q1–Q3): 68 (62–72); 10 males) and 10 control participants (age: 63 (59–67); 2 males), matched for age, education, and Montreal Cognitive Assessment (MOCA) scores. A mixed model analysis was employed to investigate cognitive workload changes as a result of incremental cognitive demand for both groups. As expected, no differences were found in cognitive scores on the LNS between groups. Cognitive workload, exemplified by greater pupil dilation, increased with incremental cognitive demand in both groups (p = 0.003). No significant between-group (p = 0.23) or interaction effects were found (p = 0.45). In addition, individuals who achieved to complete the task at higher letter-number (LN) load responded differently to increased cognitive demand compared with those who completed at lower LN load (p < 0.001), regardless of disease status. Overall, the findings indicated that pupillary response reflects incremental cognitive demand in non-demented people with PD and healthy controls. Further research is needed to investigate the pupillary response to incremental cognitive demand of PD patients with dementia compared to non-demented PD and healthy controls. Highlights -Pupillary response reflects cognitive demand in both non-demented people with PD and healthy controls-Although not significant due to insufficient power, non-demented individuals with PD had increased cognitive workload compared to the healthy controls throughout the testing-Pupillary response may be a valid measure of cognitive demand in non-demented individuals with PD-In future, pupillary response might be used to detect cognitive impairment in individuals with PD PMID:29692720
Demand Response Availability Profiles for California in the Year 2020
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olsen, Daniel; Sohn, Michael; Piette, Mary Ann
2014-11-01
Demand response (DR) is being considered as a valuable resource for keeping the electrical grid stable and efficient, and deferring upgrades to generation, transmission, and distribution systems. However, simulations to determine how much infrastructure upgrades can be deferred are necessary in order to plan optimally. Production cost modeling is a technique, which simulates the dispatch of generators to meet demand and reserves in each hour of the year, at minimal cost. By integrating demand response resources into a production cost model (PCM), their value to the grid can be estimated and used to inform operations and infrastructure planning. DR availabilitymore » profiles and constraints for 13 end-uses in California for the year 2020 were developed by Lawrence Berkeley National Laboratory (LBNL), and integrated into a production cost model by Lawrence Livermore National Laboratory (LLNL), for the California Energy Commission’s Value of Energy Storage and Demand Response for Renewable Integration in California Study. This report summarizes the process for developing the DR availability profiles for California, and their aggregate capabilities. While LBNL provided potential DR hourly profiles for regulation product in the ancillary services market and five-minute load following product in the energy market for LLNL’s study, additional results in contingency reserves and an assumed flexible product are also defined. These additional products are included in the analysis for managing high ramps associated with renewable generation and capacity products and they are also presented in this report.« less
Essays on Mathematical Optimization for Residential Demand Response in the Energy Sector
NASA Astrophysics Data System (ADS)
Palaparambil Dinesh, Lakshmi
In the electric utility industry, it could be challenging to adjust supply to match demand due to large generator ramp up times, high generation costs and insufficient in-house generation capacity. Demand response (DR) is a technique for adjusting the demand for electric power instead of the supply. Direct Load Control (DLC) is one of the ways to implement DR. DLC program participants sign up for power interruption contracts and are given financial incentives for curtailing electricity usage during peak demand time periods. This dissertation studies a DLC program for residential air conditioners using mathematical optimization models. First, we develop a model that determines what contract parameters to use in designing contracts between the provider and residential customers, when to turn which power unit on or off and how much power to cut during peak demand hours. The model uses information on customer preferences for choice of contract parameters such as DLC financial incentives and energy usage curtailment. In numerical experiments, the proposed model leads to projected cost savings of the order of 20%, compared to a current benchmark model used in practice. We also quantify the impact of factors leading to cost savings and study characteristics of customers picked by different contracts. Second, we study a DLC program in a macro economic environment using a Computable General Equilibrium (CGE) model. A CGE model is used to study the impact of external factors such as policy and technology changes on different economic sectors. Here we differentiate customers based on their preference for DLC programs by using different values for price elasticity of demand for electricity commodity. Consequently, DLC program customers could substitute demand for electricity commodity with other commodities such as transportation sector. Price elasticity of demand is calculated using a novel methodology that incorporates customer preferences for DLC contracts from the first model. The calculation of elasticity based on our methodology is useful since the prices of commodities are not only determined by aggregate demand and supply but also by customers' relative preferences for commodities. In addition to this we quantify the indirect substitution and rebound effects on sectoral activity levels, incomes and prices based on customer differences, when DLC is implemented.
Federal Register 2010, 2011, 2012, 2013, 2014
2011-06-28
... performance measurement of demand response in PJM's capacity market, the Reliability Pricing Model (RPM). \\1...'s April 7, 2011 filing, which proposes to modify the reference point of capacity demand response... less than the customer's Peak Load Contribution (PLC).\\2\\ \\2\\ PJM describes the PLC as the average of...
Future Climate Impacts on Crop Water Demand and Groundwater Longevity in Agricultural Regions
NASA Astrophysics Data System (ADS)
Russo, T. A.; Sahoo, S.; Elliott, J. W.; Foster, I.
2016-12-01
Improving groundwater management practices under future drought conditions in agricultural regions requires three steps: 1) estimating the impacts of climate and drought on crop water demand, 2) projecting groundwater availability given climate and demand forcing, and 3) using this information to develop climate-smart policy and water use practices. We present an innovative combination of models to address the first two steps, and inform the third. Crop water demand was simulated using biophysical crop models forced by multiple climate models and climate scenarios, with one case simulating climate adaptation (e.g. modify planting or harvest time) and another without adaptation. These scenarios were intended to represent a range of drought projections and farm management responses. Nexty, we used projected climate conditions and simulated water demand across the United States as inputs to a novel machine learning-based groundwater model. The model was applied to major agricultural regions relying on the High Plains and Mississippi Alluvial aquifer systems in the US. The groundwater model integrates input data preprocessed using single spectrum analysis, mutual information, and a genetic algorithm, with an artificial neural network model. Model calibration and test results indicate low errors over the 33 year model run, and strong correlations to groundwater levels in hundreds of wells across each aquifer. Model results include a range of projected groundwater level changes from the present to 2050, and in some regions, identification and timeframe of aquifer depletion. These results quantify aquifer longevity under climate and crop scenarios, and provide decision makers with the data needed to compare scenarios of crop water demand, crop yield, and groundwater response, as they aim to balance water sustainability with food security.
The IT Advantage Assessment Model: Applying an Expanded Value Chain Model to Academia
ERIC Educational Resources Information Center
Turner, Walter L.; Stylianou, Antonis C.
2004-01-01
Academia faces an uncertain future as the 21st century unfolds. New demands, discerning students, increased competition from non-traditional competitors are just a few of the forces demanding a response. The use of information technology (IT) in academia has not kept pace with its use in industry. What has been lacking is a model for the strategic…
de Croon, E M; Blonk, R; de Zwart, B C H; Frings-Dresen, M; Broersen, J
2002-01-01
Objectives: Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. Methods: From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. Results: The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Conclusions: Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work. PMID:12040108
de Croon, E M; Blonk, R W B; de Zwart, B C H; Frings-Dresen, M H W; Broersen, J P J
2002-06-01
Building on Karasek's model of job demands and control (JD-C model), this study examined the effects of job control, quantitative workload, and two occupation specific job demands (physical demands and supervisor demands) on fatigue and job dissatisfaction in Dutch lorry drivers. From 1181 lorry drivers (adjusted response 63%) self reported information was gathered by questionnaire on the independent variables (job control, quantitative workload, physical demands, and supervisor demands) and the dependent variables (fatigue and job dissatisfaction). Stepwise multiple regression analyses were performed to examine the main effects of job demands and job control and the interaction effect between job control and job demands on fatigue and job dissatisfaction. The inclusion of physical and supervisor demands in the JD-C model explained a significant amount of variance in fatigue (3%) and job dissatisfaction (7%) over and above job control and quantitative workload. Moreover, in accordance with Karasek's interaction hypothesis, job control buffered the positive relation between quantitative workload and job dissatisfaction. Despite methodological limitations, the results suggest that the inclusion of (occupation) specific job control and job demand measures is a fruitful elaboration of the JD-C model. The occupation specific JD-C model gives occupational stress researchers better insight into the relation between the psychosocial work environment and wellbeing. Moreover, the occupation specific JD-C model may give practitioners more concrete and useful information about risk factors in the psychosocial work environment. Therefore, this model may provide points of departure for effective stress reducing interventions at work.
Price impact on urban residential water demand: A dynamic panel data approach
NASA Astrophysics Data System (ADS)
ArbuéS, Fernando; BarberáN, Ramón; Villanúa, Inmaculada
2004-11-01
In this paper, we formulate and estimate a model of residential water demand with the aim of evaluating the potential of pricing policies as a mechanism for managing residential water. The proposed econometric model offers a new perspective on urban water demand analysis by combining microlevel data with a dynamic panel data estimation procedure. The empirical application suggests that residential users are more responsive to a lagged average price specification. Another result of the estimated model is that price is a moderately effective tool in reducing residential water demand within the present range of prices, with the estimated values for income elasticity and "elasticity of consumption with respect to family size" reinforcing this conclusion.
Reliability evaluation of microgrid considering incentive-based demand response
NASA Astrophysics Data System (ADS)
Huang, Ting-Cheng; Zhang, Yong-Jun
2017-07-01
Incentive-based demand response (IBDR) can guide customers to adjust their behaviour of electricity and curtail load actively. Meanwhile, distributed generation (DG) and energy storage system (ESS) can provide time for the implementation of IBDR. The paper focus on the reliability evaluation of microgrid considering IBDR. Firstly, the mechanism of IBDR and its impact on power supply reliability are analysed. Secondly, the IBDR dispatch model considering customer’s comprehensive assessment and the customer response model are developed. Thirdly, the reliability evaluation method considering IBDR based on Monte Carlo simulation is proposed. Finally, the validity of the above models and method is studied through numerical tests on modified RBTS Bus6 test system. Simulation results demonstrated that IBDR can improve the reliability of microgrid.
Price elasticity matrix of demand in power system considering demand response programs
NASA Astrophysics Data System (ADS)
Qu, Xinyao; Hui, Hongxun; Yang, Shengchun; Li, Yaping; Ding, Yi
2018-02-01
The increasing renewable energy power generations have brought more intermittency and volatility to the electric power system. Demand-side resources can improve the consumption of renewable energy by demand response (DR), which becomes one of the important means to improve the reliability of power system. In price-based DR, the sensitivity analysis of customer’s power demand to the changing electricity prices is pivotal for setting reasonable prices and forecasting loads of power system. This paper studies the price elasticity matrix of demand (PEMD). An improved PEMD model is proposed based on elasticity effect weight, which can unify the rigid loads and flexible loads. Moreover, the structure of PEMD, which is decided by price policies and load types, and the calculation method of PEMD are also proposed. Several cases are studied to prove the effectiveness of this method.
Interpersonal interactions, job demands and work-related outcomes in pharmacy.
Gaither, Caroline A; Nadkarni, Anagha
2012-04-01
Objectives The objective of this study was to examine the interaction between job demands of pharmacists and resources in the form of interpersonal interactions and its association with work-related outcomes such as organizational and professional commitment, job burnout, professional identity and job satisfaction. The job demands-resources (JD-R) model served as the theoretical framework. Methods Subjects for the study were drawn from the Pharmacy Manpower Project Database (n = 1874). A 14-page mail-in survey measured hospital pharmacists' responses on the frequency of occurrence of various job-related scenarios as well as work-related outcomes. The study design was a 2 × 2 factorial design. Responses were collected on a Likert scale. Descriptive statistics, reliability analyses and correlational and multiple regression analyses were conducted using SPSS version 17 (SPSS, Chicago, IL, USA). Key findings The 566 pharmacists (30% response rate) who responded to the survey indicated that high-demand/pleasant encounters and low-demand/pleasant encounters occurred more frequently in the workplace. The strongest correlations were found between high-demand/unpleasant encounters and frequency and intensity of emotional exhaustion. Multiple regression analyses indicated that when controlling for demographic factors high-demand/unpleasant encounters were negatively related to affective organizational commitment and positively related to frequency and intensity of emotional exhaustion. Low-demand/pleasant encounters were positively related to frequency and intensity of personal accomplishment. Low-demand/unpleasant encounters were significantly and negatively related to professional commitment, job satisfaction and frequency and intensity of emotional exhaustion, while high-demand/pleasant encounters were also related to frequency and intensity of emotional exhaustion Conclusion Support was found for the JD-R model and the proposed interaction effects. Study results suggest that adequate attention must be paid to the interplay between demands on the job and interactions with healthcare professionals to improve the quality of the pharmacist's work life. Future research should examine other types of job demands and resources. © 2011 The Authors. IJPP © 2011 Royal Pharmaceutical Society.
Chetcuti, Lacey; Hudry, Kristelle; Grant, Megan; Vivanti, Giacomo
2017-11-01
We examined the role of social motivation and motor execution factors in object-directed imitation difficulties in autism spectrum disorder. A series of to-be-imitated actions was presented to 35 children with autism spectrum disorder and 20 typically developing children on an Apple ® iPad ® by a socially responsive or aloof model, under conditions of low and high motor demand. There were no differences in imitation performance (i.e. the number of actions reproduced within a fixed sequence), for either group, in response to a model who acted socially responsive or aloof. Children with autism spectrum disorder imitated the high motor demand task more poorly than the low motor demand task, while imitation performance for typically developing children was equivalent across the low and high motor demand conditions. Furthermore, imitative performance in the autism spectrum disorder group was unrelated to social reciprocity, though positively associated with fine motor coordination. These results suggest that difficulties in object-directed imitation in autism spectrum disorder are the result of motor execution difficulties, not reduced social motivation.
Task Decomposition Model for Dispatchers in Dynamic Scheduling of Demand Responsive Transit Systems
DOT National Transportation Integrated Search
2000-06-01
Since the passage of ADA, the demand for paratransit service is steadily increasing. Paratransit companies are relying on computer automation to streamline dispatch operations, increase productivity and reduce operator stress and error. Little resear...
Drought, water conservation, and water demand rebound in California
NASA Astrophysics Data System (ADS)
Gonzales, P.; Ajami, N.
2017-12-01
There is growing recognition that dynamic community values, preferences, and water use behaviors are important drivers of water demand in addition to external factors such as temperature and precipitation. Water demand drivers have been extensively studied, yet they have traditionally been applied to models that assume static conditions and usually do not account for potential societal changes in response to increased scarcity awareness. For example, following a period of sustained low demand such as during a drought, communities often increase water use during a hydrologically wet period, a phenomenon known as "rebounding" water use. Yet previous experiences show the extent of this rebound is not a straightforward function of policy and efficiency improvements, but may also reflect short-term or long-lasting change in community behavior, which are not easily captured by models that assume stationarity. In this study we explore cycles of decreased water demand during drought and subsequent water use rebound observed in California in recent decades. We have developed a novel dynamic system model for water demand in three diverse but interconnected service areas in the San Francisco Bay Area, exposing local trends of changing water use behaviors and long-term impacts on water demand since 1980 to the present. In this model, we apply the concept of social memory, defined as a community's inherited knowledge about hazardous events or degraded environmental conditions from past experiences. While this concept has been applied to further conceptual understanding of socio-hydrologic systems in response to hydrological extremes, to the best of our knowledge this the first study to incorporate social memory to model the water demand rebound phenomenon and to use such a model in the examination of changing dynamics validated by historical data. In addition, we take a closer look at water demand during the recent historic drought in California from 2012-16, and relate our long-term insights to recent events and statewide trends. This comparative modeling exercise shows that increased public awareness during droughts can be related to systematic changes in the way diverse communities respond to near- and long-term conservation incentives.
Configurable product design considering the transition of multi-hierarchical models
NASA Astrophysics Data System (ADS)
Ren, Bin; Qiu, Lemiao; Zhang, Shuyou; Tan, Jianrong; Cheng, Jin
2013-03-01
The current research of configurable product design mainly focuses on how to convert a predefined set of components into a valid set of product structures. With the scale and complexity of configurable products increasing, the interdependencies between customer demands and product structures grow up as well. The result is that existing product structures fails to satisfy the individual customer requirements and hence product variants are needed. This paper is aimed to build a bridge between customer demands and product structures in order to make demand-driven fast response design feasible. First of all, multi-hierarchical models of configurable product design are established with customer demand model, technical requirement model and product structure model. Then, the transition of multi-hierarchical models among customer demand model, technical requirement model and product structure model is solved with fuzzy analytic hierarchy process (FAHP) and the algorithm of multi-level matching. Finally, optimal structure according to the customer demands is obtained with the calculation of Euclidean distance and similarity of some cases. In practice, the configuration design of a clamping unit of injection molding machine successfully performs an optimal search strategy for the product variants with reasonable satisfaction to individual customer demands. The proposed method can automatically generate a configuration design with better alternatives for each product structures, and shorten the time of finding the configuration of a product.
Su, Zheng; Meng, Tianguang
2016-09-01
The widespread use of information and communication technology (ICT) has reshaped the public sphere in the digital era, making online forums a new channel for political participation. Using big data analytics of full records of citizen-government interactions from 2008 to early 2014 on a nationwide political forum, we find that authoritarian China is considerably responsive to citizens' demands with a rapid growth of response rate; however, government responsiveness is highly selective, conditioning on actors' social identities and the policy domains of their online demands. Results from logistic and duration models suggest that requests which made by local citizens, expressed collectively, focused on the single task issue, and are closely related to economic growth are more likely to be responded to. These strategies adopted by Chinese provincial leaders reveal the scope and selectivity of authoritarian responsiveness. Copyright © 2016 Elsevier Inc. All rights reserved.
Effect of Response Reduction Factor on Peak Floor Acceleration Demand in Mid-Rise RC Buildings
NASA Astrophysics Data System (ADS)
Surana, Mitesh; Singh, Yogendra; Lang, Dominik H.
2017-06-01
Estimation of Peak Floor Acceleration (PFA) demand along the height of a building is crucial for the seismic safety of nonstructural components. The effect of the level of inelasticity, controlled by the response reduction factor (strength ratio), is studied using incremental dynamic analysis. A total of 1120 nonlinear dynamic analyses, using a suite of 30 recorded ground motion time histories, are performed on mid-rise reinforced-concrete (RC) moment-resisting frame buildings covering a wide range in terms of their periods of vibration. The obtained PFA demands are compared with some of the major national seismic design and retrofit codes (IS 1893 draft version, ASCE 41, EN 1998, and NZS 1170.4). It is observed that the PFA demand at the building's roof level decreases with increasing period of vibration as well as with strength ratio. However, current seismic building codes do not account for these effects thereby producing very conservative estimates of PFA demands. Based on the identified parameters affecting the PFA demand, a model to obtain the PFA distribution along the height of a building is proposed. The proposed model is validated with spectrum-compatible time history analyses of the considered buildings with different strength ratios.
An econometric model of the U.S. pallet market
Albert T. Schuler; Walter B. Wallin
1979-01-01
A need for quantitative information on demand and price has been expressed by the pallet industry. In response to this, an econometric model of the aggregate U.S. pallet market was developed. Demand was found to be affected by real pallet price, industrial and food production levels, and slipsheet prices. Supply was affected by real price, housing starts lagged 1 year...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Starke, Michael R; Kirby, Brendan J; Kueck, John D
2009-02-01
Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower greenmore » house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.« less
Prediction Models for Dynamic Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aman, Saima; Frincu, Marc; Chelmis, Charalampos
2015-11-02
As Smart Grids move closer to dynamic curtailment programs, Demand Response (DR) events will become necessary not only on fixed time intervals and weekdays predetermined by static policies, but also during changing decision periods and weekends to react to real-time demand signals. Unique challenges arise in this context vis-a-vis demand prediction and curtailment estimation and the transformation of such tasks into an automated, efficient dynamic demand response (D 2R) process. While existing work has concentrated on increasing the accuracy of prediction models for DR, there is a lack of studies for prediction models for D 2R, which we address inmore » this paper. Our first contribution is the formal definition of D 2R, and the description of its challenges and requirements. Our second contribution is a feasibility analysis of very-short-term prediction of electricity consumption for D 2R over a diverse, large-scale dataset that includes both small residential customers and large buildings. Our third, and major contribution is a set of insights into the predictability of electricity consumption in the context of D 2R. Specifically, we focus on prediction models that can operate at a very small data granularity (here 15-min intervals), for both weekdays and weekends - all conditions that characterize scenarios for D 2R. We find that short-term time series and simple averaging models used by Independent Service Operators and utilities achieve superior prediction accuracy. We also observe that workdays are more predictable than weekends and holiday. Also, smaller customers have large variation in consumption and are less predictable than larger buildings. Key implications of our findings are that better models are required for small customers and for non-workdays, both of which are critical for D 2R. Also, prediction models require just few days’ worth of data indicating that small amounts of historical training data can be used to make reliable predictions, simplifying the complexity of big data challenge associated with D 2R.« less
How Often Is the Misfit of Item Response Theory Models Practically Significant?
ERIC Educational Resources Information Center
Sinharay, Sandip; Haberman, Shelby J.
2014-01-01
Standard 3.9 of the Standards for Educational and Psychological Testing ([, 1999]) demands evidence of model fit when item response theory (IRT) models are employed to data from tests. Hambleton and Han ([Hambleton, R. K., 2005]) and Sinharay ([Sinharay, S., 2005]) recommended the assessment of practical significance of misfit of IRT models, but…
A Review of Player Monitoring Approaches in Basketball: Current Trends and Future Directions.
Fox, Jordan L; Scanlan, Aaron T; Stanton, Robert
2017-07-01
Fox, JL, Scanlan, AT, and Stanton, R. A review of player monitoring approaches in basketball: current trends and future directions. J Strength Cond Res 31(7): 2021-2029, 2017-Effective monitoring of players in team sports such as basketball requires an understanding of the external demands and internal responses, as they relate to training phases and competition. Monitoring of external demands and internal responses allows coaching staff to determine the dose-response associated with the imposed training load (TL), and subsequently, if players are adequately prepared for competition. This review discusses measures reported in the literature for monitoring the external demands and internal responses of basketball players during training and competition. The external demands of training and competition were primarily monitored using time-motion analysis, with limited use of microtechnology being reported. Internal responses during training were typically measured using hematological markers, heart rate, various TL models, and perceptual responses such as rating of perceived exertion (RPE). Heart rate was the most commonly reported indicator of internal responses during competition with limited reporting of hematological markers or RPE. These findings show a large discrepancy between the reporting of external and internal measures and training and competition demands. Microsensors, however, may be a practical and convenient method of player monitoring in basketball to overcome the limitations associated with current approaches while allowing for external demands and internal responses to be recorded simultaneously. The triaxial accelerometers of microsensors seem well suited for basketball and warrant validation to definitively determine their place in the monitoring of basketball players. Coaching staff should make use of this technology by tracking individual player responses across the annual plan and using real-time monitoring to minimize factors such as fatigue and injury risk.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Herter, Karen; Rasin, Josh; Perry, Tim
2009-11-30
The goal of this study was to demonstrate a demand response system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated Demand Response (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricingmore » information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.« less
Jagtap, Pranav; Diwadkar, Vaibhav A.
2016-01-01
Frontal-thalamic interactions are crucial for bottom-up gating and top-down control, yet have not been well studied from brain network perspectives. We applied network modeling of fMRI signals (Dynamic Causal Modeling; DCM) to investigate frontal-thalamic interactions during an attention task with parametrically varying levels of demand. fMRI was collected while subjects participated in a sustained continuous performance task with low and high attention demands. 162 competing model architectures were employed in DCM to evaluate hypotheses on bilateral frontal-thalamic connections and their modulation by attention demand, selected at a second level using Bayesian Model Selection. The model architecture evinced significant contextual modulation by attention of ascending (thalamus → dPFC) and descending (dPFC → thalamus) pathways. However, modulation of these pathways was asymmetric: While positive modulation of the ascending pathway was comparable across attention demand, modulation of the descending pathway was significantly greater when attention demands were increased. Increased modulation of the (dPFC → thalamus) pathway in response to increased attention demand constitutes novel evidence of attention-related gain in the connectivity of the descending attention pathway. By comparison demand-independent modulation of the ascending (thalamus → dPFC) pathway suggests unbiased thalamic inputs to the cortex in the context of the paradigm. PMID:27145923
Pragmatic hydraulic theory predicts stomatal responses to climatic water deficits.
Sperry, John S; Wang, Yujie; Wolfe, Brett T; Mackay, D Scott; Anderegg, William R L; McDowell, Nate G; Pockman, William T
2016-11-01
Ecosystem models have difficulty predicting plant drought responses, partially from uncertainty in the stomatal response to water deficits in soil and atmosphere. We evaluate a 'supply-demand' theory for water-limited stomatal behavior that avoids the typical scaffold of empirical response functions. The premise is that canopy water demand is regulated in proportion to threat to supply posed by xylem cavitation and soil drying. The theory was implemented in a trait-based soil-plant-atmosphere model. The model predicted canopy transpiration (E), canopy diffusive conductance (G), and canopy xylem pressure (P canopy ) from soil water potential (P soil ) and vapor pressure deficit (D). Modeled responses to D and P soil were consistent with empirical response functions, but controlling parameters were hydraulic traits rather than coefficients. Maximum hydraulic and diffusive conductances and vulnerability to loss in hydraulic conductance dictated stomatal sensitivity and hence the iso- to anisohydric spectrum of regulation. The model matched wide fluctuations in G and P canopy across nine data sets from seasonally dry tropical forest and piñon-juniper woodland with < 26% mean error. Promising initial performance suggests the theory could be useful in improving ecosystem models. Better understanding of the variation in hydraulic properties along the root-stem-leaf continuum will simplify parameterization. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
Price elasticity and medication use: cost sharing across multiple clinical conditions.
Gatwood, Justin; Gibson, Teresa B; Chernew, Michael E; Farr, Amanda M; Vogtmann, Emily; Fendrick, A Mark
2014-11-01
To address the impact that out-of-pocket prices may have on medication use, it is vital to understand how the demand for medications may be affected when patients are faced with changes in the price to acquire treatment and how price responsiveness differs across medication classes. To examine the impact of cost-sharing changes on the demand for 8 classes of prescription medications. This was a retrospective database analysis of 11,550,363 commercially insured enrollees within the 2005-2009 MarketScan Database. Patient cost sharing, expressed as a price index for each medication class, was the main explanatory variable to examine the price elasticity of demand. Negative binomial fixed effect models were estimated to examine medication fills. The elasticity estimates reflect how use changes over time as a function of changes in copayments. Model estimates revealed that price elasticity of demand ranged from -0.015 to -0.157 within the 8 categories of medications (P less than 0.01 for 7 of 8 categories). The price elasticity of demand for smoking deterrents was largest (-0.157, P less than 0.0001), while demand for antiplatelet agents was not responsive to price (P greater than 0.05). The price elasticity of demand varied considerably by medication class, suggesting that the influence of cost sharing on medication use may be related to characteristics inherent to each medication class or underlying condition.
Impact of warmer weather on electricity sector emissions due to building energy use
NASA Astrophysics Data System (ADS)
Meier, Paul; Holloway, Tracey; Patz, Jonathan; Harkey, Monica; Ahl, Doug; Abel, David; Schuetter, Scott; Hackel, Scott
2017-06-01
Most US energy consumption occurs in buildings, with cooling demands anticipated to increase net building electricity use under warmer conditions. The electricity generation units that respond to this demand are major contributors to sulfur dioxide (SO2) and nitrogen oxides (NOx), both of which have direct impacts on public health, and contribute to the formation of secondary pollutants including ozone and fine particulate matter. This study quantifies temperature-driven changes in power plant emissions due to increased use of building air conditioning. We compare an ambient temperature baseline for the Eastern US to a model-calculated mid-century scenario with summer-average temperature increases ranging from 1 C to 5 C across the domain. We find a 7% increase in summer electricity demand and a 32% increase in non-coincident peak demand. Power sector modeling, assuming only limited changes to current generation resources, calculated a 16% increase in emissions of NOx and an 18% increase in emissions of SO2. There is a high level of regional variance in the response of building energy use to climate, and the response of emissions to associated demand. The East North Central census region exhibited the greatest sensitivity of energy demand and associated emissions to climate.
Accurate Estimation of Target amounts Using Expanded BASS Model for Demand-Side Management
NASA Astrophysics Data System (ADS)
Kim, Hyun-Woong; Park, Jong-Jin; Kim, Jin-O.
2008-10-01
The electricity demand in Korea has rapidly increased along with a steady economic growth since 1970s. Therefore Korea has positively propelled not only SSM (Supply-Side Management) but also DSM (Demand-Side Management) activities to reduce investment cost of generating units and to save supply costs of electricity through the enhancement of whole national energy utilization efficiency. However study for rebate, which have influence on success or failure on DSM program, is not sufficient. This paper executed to modeling mathematically expanded Bass model considering rebates, which have influence on penetration amounts for DSM program. To reflect rebate effect more preciously, the pricing function using in expanded Bass model directly reflects response of potential participants for rebate level.
NASA Astrophysics Data System (ADS)
Cui, Gaoying; Fan, Jie; Qin, Yuchen; Wang, Dong; Chen, Guangyan
2017-05-01
In order to promote the effective use of demand response load side resources, promote the interaction between supply and demand, enhance the level of customer service and achieve the overall utilization of energy, this paper briefly explain the background significance of design demand response information platform and current situation of domestic and foreign development; Analyse the new demand of electricity demand response combined with the application of Internet and big data technology; Design demand response information platform architecture, construct demand responsive system, analyse process of demand response strategy formulate and intelligent execution implement; study application which combined with the big data, Internet and demand response technology; Finally, from information interaction architecture, control architecture and function design perspective design implementation of demand response information platform, illustrate the feasibility of the proposed platform design scheme implemented in a certain extent.
Understanding and Modeling Freight Stakeholder Behavior
DOT National Transportation Integrated Search
2012-04-01
This project developed a conceptual model of private-sector freight stakeholder decisions and interactions for : forecasting freight demands in response to key policy variables. Using East Central Wisconsin as a study area, empirical : models were de...
Freight model improvement project for ECWRPC.
DOT National Transportation Integrated Search
2011-08-01
In early 2009 WisDOT, HNTB and ECWRPC completed the first phase of the Northeast Region Travel Demand Model. : While the model includes a truck trip generation based on the quick response freight manual, the model lacks enough : truck classification ...
He, Xinhua; Hu, Wenfa
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model.
The Oak Ridge Competitive Electricity Dispatch (ORCED) Model Version 9
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hadley, Stanton W.; Baek, Young Sun
The Oak Ridge Competitive Electricity Dispatch (ORCED) model dispatches power plants in a region to meet the electricity demands for any single given year up to 2030. It uses publicly available sources of data describing electric power units such as the National Energy Modeling System and hourly demands from utility submittals to the Federal Energy Regulatory Commission that are projected to a future year. The model simulates a single region of the country for a given year, matching generation to demands and predefined net exports from the region, assuming no transmission constraints within the region. ORCED can calculate a numbermore » of key financial and operating parameters for generating units and regional market outputs including average and marginal prices, air emissions, and generation adequacy. By running the model with and without changes such as generation plants, fuel prices, emission costs, plug-in hybrid electric vehicles, distributed generation, or demand response, the marginal impact of these changes can be found.« less
He, Xinhua
2014-01-01
This paper presents a multiple-rescue model for an emergency supply chain system under uncertainties in large-scale affected area of disasters. The proposed methodology takes into consideration that the rescue demands caused by a large-scale disaster are scattered in several locations; the servers are arranged in multiple echelons (resource depots, distribution centers, and rescue center sites) located in different places but are coordinated within one emergency supply chain system; depending on the types of rescue demands, one or more distinct servers dispatch emergency resources in different vehicle routes, and emergency rescue services queue in multiple rescue-demand locations. This emergency system is modeled as a minimal queuing response time model of location and allocation. A solution to this complex mathematical problem is developed based on genetic algorithm. Finally, a case study of an emergency supply chain system operating in Shanghai is discussed. The results demonstrate the robustness and applicability of the proposed model. PMID:24688367
Transactive Control of Commercial Buildings for Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hao, He; Corbin, Charles D.; Kalsi, Karanjit
Transactive control is a type of distributed control strategy that uses market mechanism to engage self-interested responsive loads to achieve power balance in the electrical power grid. In this paper, we propose a transactive control approach of commercial building Heating, Ventilation, and Air- Conditioning (HVAC) systems for demand response. We first describe the system models, and identify their model parameters using data collected from Systems Engineering Building (SEB) located on our Pacific Northwest National Laboratory (PNNL) campus. We next present a transactive control market structure for commercial building HVAC system, and describe its agent bidding and market clearing strategies. Severalmore » case studies are performed in a simulation environment using Building Control Virtual Test Bed (BCVTB) and calibrated SEB EnergyPlus model. We show that the proposed transactive control approach is very effective at peak clipping, load shifting, and strategic conservation for commercial building HVAC systems.« less
ERIC Educational Resources Information Center
Sinharay, Sandip; Haberman, Shelby J.; Jia, Helena
2011-01-01
Standard 3.9 of the "Standards for Educational and Psychological Testing" (American Educational Research Association, American Psychological Association, & National Council for Measurement in Education, 1999) demands evidence of model fit when an item response theory (IRT) model is used to make inferences from a data set. We applied two recently…
Schechter, J; Green, L W; Olsen, L; Kruse, K; Cargo, M
1997-01-01
To apply Karasek's Job Content Model to an analysis of the relationships between job type and perceived stress and stress behaviors in a large company during a period of reorganization and downsizing. Cross-sectional mail-out, mail-back survey. A large Canadian telephone/telecommunications company. Stratified random sample (stratified by job category) of 2200 out of 13,000 employees with a response rate of 48.8%. Responses to 25 of Karasek's core questions were utilized to define four job types: low-demand and high control = "relaxed"; high demand and high control = "active"; low demand and low control = "passive", and high demand and low control = "high strain." These job types were compared against self-reported stress levels, perceived general level of health, absenteeism, alcohol use, exercise level, and use of medications and drugs. Similar analyses were performed to assess the influence of shift work. Employees with "passive" or "high strain" job types reported higher levels of stress (trend test p < .0001); poorer health (trend test P = .006); and higher levels of absenteeism (trend test p < .0001). More shift workers reported themselves in poor or fair health (chi-square p = .018) and reported high levels of stress at home (chi-square p = .002) than nonshift workers. The relationships between job type and levels of stress, health and absenteeism, however, held for nonshift workers as well. Job types with high demand and low control were associated with increased stress, increased absenteeism, and poorer self-concept of health. The demand/control model of Karasek and Theorell was validated in this setting with respect to stress and some stress-associated attitudes and behaviors.
Measuring Technical Vocational Education and Training (TVET) Efficiency: Developing a Framework
ERIC Educational Resources Information Center
Liu, Guimei; Clayton, John
2016-01-01
The growing demand for an increasingly skilled competitive workforce and the associated demand for change and responsiveness in the provision of technical vocational education and training (TVET) has led to the development of stronger links between New Zealand and the People's Republic of China. A collaborative model programme project aims to…
Modeling water demand when households have multiple sources of water
NASA Astrophysics Data System (ADS)
Coulibaly, Lassina; Jakus, Paul M.; Keith, John E.
2014-07-01
A significant portion of the world's population lives in areas where public water delivery systems are unreliable and/or deliver poor quality water. In response, people have developed important alternatives to publicly supplied water. To date, most water demand research has been based on single-equation models for a single source of water, with very few studies that have examined water demand from two sources of water (where all nonpublic system water sources have been aggregated into a single demand). This modeling approach leads to two outcomes. First, the demand models do not capture the full range of alternatives, so the true economic relationship among the alternatives is obscured. Second, and more seriously, economic theory predicts that demand for a good becomes more price-elastic as the number of close substitutes increases. If researchers artificially limit the number of alternatives studied to something less than the true number, the price elasticity estimate may be biased downward. This paper examines water demand in a region with near universal access to piped water, but where system reliability and quality is such that many alternative sources of water exist. In extending the demand analysis to four sources of water, we are able to (i) demonstrate why households choose the water sources they do, (ii) provide a richer description of the demand relationships among sources, and (iii) calculate own-price elasticity estimates that are more elastic than those generally found in the literature.
Opportunities for Automated Demand Response in California’s Dairy Processing Industry
DOE Office of Scientific and Technical Information (OSTI.GOV)
Homan, Gregory K.; Aghajanzadeh, Arian; McKane, Aimee
During periods of peak electrical demand on the energy grid or when there is a shortage of supply, the stability of the grid may be compromised or the cost of supplying electricity may rise dramatically, respectively. Demand response programs are designed to mitigate the severity of these problems and improve reliability by reducing the demand on the grid during such critical times. In 2010, the Demand Response Research Center convened a group of industry experts to suggest potential industries that would be good demand response program candidates for further review. The dairy industry was suggested due to the perception thatmore » the industry had suitable flexibility and automatic controls in place. The purpose of this report is to provide an initial description of the industry with regard to demand response potential, specifically automated demand response. This report qualitatively describes the potential for participation in demand response and automated demand response by dairy processing facilities in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use. Typical process equipment and controls are discussed, as well as common impediments to participation in demand response and automated demand response programs. Two case studies of demand response at dairy facilities in California and across the country are reviewed. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.« less
NASA Astrophysics Data System (ADS)
Kanta, L.
2016-12-01
Outdoor water use for landscape and irrigation constitutes a significant end use in residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water use restrictions. Because utilities do not typically record outdoor and indoor water uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density or lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, records of outdoor conservation programs, frequency and type of mandatory water use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden irrigation parameters to determine the most significant factors that should be considered by water utilities to reduce outdoor demand. Data from multiple sources and the agent-based modeling methodology are integrated using a holistic approach to assist utilities in efficiently and sustainably managing outdoor demand.
NASA Astrophysics Data System (ADS)
Kanta, L.; Berglund, E. Z.; Soh, M. H.
2017-12-01
Outdoor water-use for landscape and irrigation constitutes a significant end-use in total residential water demand. In periods of water shortages, utilities may reduce garden demands by implementing irrigation system audits, rebate programs, local ordinances, and voluntary or mandatory water-use restrictions. Because utilities do not typically record outdoor and indoor water-uses separately, the effects of policies for reducing garden demands cannot be readily calculated. The volume of water required to meet garden demands depends on the housing density, lawn size, type of vegetation, climatic conditions, efficiency of garden irrigation systems, and consumer water-use behaviors. Many existing outdoor demand estimation methods are deterministic and do not include consumer responses to conservation campaigns. In addition, mandatory restrictions may have a substantial impact on reducing outdoor demands, but the effectiveness of mandatory restrictions depends on the timing and the frequency of restrictions, in addition to the distribution of housing density and consumer types within a community. This research investigates a garden end-use model by coupling an agent-based modeling approach and a mechanistic-stochastic water demand model to create a methodology for estimating garden demand and evaluating demand reduction policies. The garden demand model is developed for two water utilities, using a diverse data sets, including residential customer billing records, outdoor conservation programs, frequency and type of mandatory water-use restrictions, lot size distribution, population growth, and climatic data. A set of garden irrigation parameter values, which are based on the efficiency of irrigation systems and irrigation habits of consumers, are determined for a set of conservation ordinances and restrictions. The model parameters are then validated using customer water usage data from the participating water utilities. A sensitivity analysis is conducted for garden irrigation parameters to determine the most significant factors that should be considered by water utilities to reduce outdoor demand. Data from multiple sources and the agent-based modeling methodology are integrated using a holistic approach to assist utilities in efficiently and sustainably managing outdoor demand.
A model of the demand for Islamic banks debt-based financing instrument
NASA Astrophysics Data System (ADS)
Jusoh, Mansor; Khalid, Norlin
2013-04-01
This paper presents a theoretical analysis of the demand for debt-based financing instruments of the Islamic banks. Debt-based financing, such as through baibithamanajil and al-murabahah, is by far the most prominent of the Islamic bank financing and yet it has been largely ignored in Islamic economics literature. Most studies instead have been focusing on equity-based financing of al-mudharabah and al-musyarakah. Islamic bank offers debt-based financing through various instruments derived under the principle of exchange (ukud al-mu'awadhat) or more specifically, the contract of deferred sale. Under such arrangement, Islamic debt is created when goods are purchased and the payments are deferred. Thus, unlike debt of the conventional bank which is a form of financial loan contract to facilitate demand for liquid assets, this Islamic debt is created in response to the demand to purchase goods by deferred payment. In this paper we set an analytical framework that is based on an infinitely lived representative agent model (ILRA model) to analyze the demand for goods to be purchased by deferred payment. The resulting demand will then be used to derive the demand for Islamic debt. We also investigate theoretically, factors that may have an impact on the demand for Islamic debt.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hale, Elaine
Demand response may be a valuable flexible resource for low-carbon electric power grids. However, there are as many types of possible demand response as there are ways to use electricity, making demand response difficult to study at scale in realistic settings. This talk reviews our state of knowledge regarding the potential value of demand response in several example systems as a function of increasing levels of wind and solar power, sometimes drawing on the analogy between demand response and storage. Overall, we find demand response to be promising, but its potential value is very system dependent. Furthermore, demand response, likemore » storage, can easily saturate ancillary service markets.« less
Rummel, Jan; Wesslein, Ann-Katrin; Meiser, Thorsten
2017-05-01
Event-based prospective memory (PM) is the ability to remember to perform an intention in response to an environmental cue. Recent microstructure models postulate four distinguishable stages of successful event-based PM fulfillment. That is, (a) the event must be noticed, (b) the intention must be retrieved, (c) the context must be verified, and (d) the intended action must be coordinated with the demands of any currently ongoing task (e.g., Marsh, Hicks, & Watson, 2002b). Whereas the cognitive processes of Stages 1, 2, and 3 have been studied more or less extensively, little is known about the processes of Stage 4 so far. To fill this gap, the authors manipulated the magnitude of response overlap between the ongoing task and the PM task to isolate Stage-4 processes. Results demonstrate that PM performance improves in the presence versus absence of a response overlap, independent of cue saliency (Experiment 1) and of demands from currently ongoing tasks (Experiment 2). Furthermore, working-memory capacity is associated with PM performance, especially when there is little response overlap (Experiments 2 and 3). Finally, PM performance benefits only from strong response overlap, that is, only when the appropriate ongoing-task and PM response keys were identical (Experiment 4). They conclude that coordinating ongoing-task and PM actions puts cognitive demands on the individual which are distinguishable from the demands imposed by cue-detection and intention-retrieval processes. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Bilgic, Abdulbaki; Florkowski, Wojciech J
2007-06-01
This paper identifies factors that influence the demand for a bass fishing trip taken in the southeastern United States using a hurdle negative binomial count data model. The probability of fishing for a bass is estimated in the first stage and the fishing trip frequency is estimated in the second stage for individuals reporting bass fishing trips in the Southeast. The applied approach allows the decomposition of the effects of factors responsible for the decision to take a trip and the trip number. Calculated partial and total elasticities indicate a highly inelastic demand for the number of fishing trips as trip costs increase. However, the demand can be expected to increase if anglers experience a success measured by the number of caught fish or their size. Benefit estimates based on alternative estimation methods differ substantially, suggesting the need for testing each modeling approach applied in empirical studies.
Opportunities for Automated Demand Response in California Agricultural Irrigation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Olsen, Daniel; Aghajanzadeh, Arian; McKane, Aimee
Pumping water for agricultural irrigation represents a significant share of California’s annual electricity use and peak demand. It also represents a large source of potential flexibility, as farms possess a form of storage in their wetted soil. By carefully modifying their irrigation schedules, growers can participate in demand response without adverse effects on their crops. This report describes the potential for participation in demand response and automated demand response by agricultural irrigators in California, as well as barriers to widespread participation. The report first describes the magnitude, timing, location, purpose, and manner of energy use in California. Typical on-farm controlsmore » are discussed, as well as common impediments to participation in demand response and automated demand response programs. Case studies of demand response programs in California and across the country are reviewed, and their results along with overall California demand estimates are used to estimate statewide demand response potential. Finally, recommendations are made for future research that can enhance the understanding of demand response potential in this industry.« less
Comparison of Two Buyer-Vendor Coordination Models
NASA Astrophysics Data System (ADS)
Diar Astanti, Ririn; Ai, The Jin; Gong, Dah-Chuan; Luong, Hunyh Trung
2018-03-01
This paper develops and compares two mathematical models for describing situation in coordination of buyer and vendor. In this case the vendor which is an Original Equipment Manufacturers (OEMS) of automotive parts, are supplying different type of buyers, i.e. automotive industry, repair shop and automotive dealers. It is well known that automotive industries are operated in Just in Time (JIT) Production Environment, so that the demand behaviour from this buyer has different characteristics than the demand behaviour from other buyers. Two mathematical models are developed in order to depict two different manufacturing strategies as the vendor response dealing with different type of buyers. These strategies are dividing production lot size for each type of buyer and consolidating all buyer’s demand in to single production lot size.
Rasmussen, Erin B; Reilly, William; Buckley, Jessica; Boomhower, Steven R
2012-02-01
Research on free-food intake suggests that cannabinoids are implicated in the regulation of feeding. Few studies, however, have characterized how environmental factors that affect food procurement interact with cannabinoid drugs that reduce food intake. Demand analysis provides a framework to understand how cannabinoid blockers, such as rimonabant, interact with effort in reducing demand for food. The present study examined the effects rimonabant had on demand for sucrose in obese Zucker rats when effort to obtain food varied and characterized the data using the exponential ("essential value") model of demand. Twenty-nine male (15 lean, 14 obese) Zucker rats lever-pressed under eight fixed ratio (FR) schedules of sucrose reinforcement, in which the number of lever-presses to gain access to a single sucrose pellet varied between 1 and 300. After behavior stabilized under each FR schedule, acute doses of rimonabant (1-10mg/kg) were administered prior to some sessions. The number of food reinforcers and responses in each condition was averaged and the exponential and linear demand equations were fit to the data. These demand equations quantify the value of a reinforcer by its sensitivity to price (FR) increases. Under vehicle conditions, obese Zucker rats consumed more sucrose pellets than leans at smaller fixed ratios; however, they were equally sensitive to price increases with both models of demand. Rimonabant dose-dependently reduced reinforcers and responses for lean and obese rats across all FR schedules. Data from the exponential analysis suggest that rimonabant dose-dependently increased elasticity, i.e., reduced the essential value of sucrose, a finding that is consistent with graphical depictions of normalized demand curves. Copyright © 2011 Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Pourmousavi Kani, Seyyed Ali
Future power systems (known as smart grid) will experience a high penetration level of variable distributed energy resources to bring abundant, affordable, clean, efficient, and reliable electric power to all consumers. However, it might suffer from the uncertain and variable nature of these generations in terms of reliability and especially providing required balancing reserves. In the current power system structure, balancing reserves (provided by spinning and non-spinning power generation units) usually are provided by conventional fossil-fueled power plants. However, such power plants are not the favorite option for the smart grid because of their low efficiency, high amount of emissions, and expensive capital investments on transmission and distribution facilities, to name a few. Providing regulation services in the presence of variable distributed energy resources would be even more difficult for islanded microgrids. The impact and effectiveness of demand response are still not clear at the distribution and transmission levels. In other words, there is no solid research reported in the literature on the evaluation of the impact of DR on power system dynamic performance. In order to address these issues, a real-time demand response approach along with real-time power management (specifically for microgrids) is proposed in this research. The real-time demand response solution is utilized at the transmission (through load-frequency control model) and distribution level (both in the islanded and grid-tied modes) to provide effective and fast regulation services for the stable operation of the power system. Then, multiple real-time power management algorithms for grid-tied and islanded microgrids are proposed to economically and effectively operate microgrids. Extensive dynamic modeling of generation, storage, and load as well as different controller design are considered and developed throughout this research to provide appropriate models and simulation environment to evaluate the effectiveness of the proposed methodologies. Simulation results revealed the effectiveness of the proposed methods in providing balancing reserves and microgrids' economic and stable operation. The proposed tools and approaches can significantly enhance the application of microgrids and demand response in the smart grid era. They will also help to increase the penetration level of variable distributed generation resources in the smart grid.
Prices and E-Cigarette Demand: Evidence From the European Union.
Stoklosa, Michal; Drope, Jeffrey; Chaloupka, Frank J
2016-10-01
Many European Union (EU) Member States have expressed the need for EU legislation to clarify the issue of e-cigarette taxation, but the economic evidence to inform creation of such policies has been lacking. To date, only one study-on the United States only-has examined responsiveness of e-cigarette demand to price changes. We used 2011-2014 pooled time-series data on e-cigarette sales, as well as e-cigarette and cigarette prices for six EU markets (Estonia, Ireland, Latvia, Lithuania, Sweden, and the United Kingdom). We utilized static and dynamic fixed-effects models to estimate the own and cross-price elasticity of demand for e-cigarettes. In a separate model for Sweden, we examined the effects of snus prices on e-cigarette sales. Based on static models, every 10% increase in e-cigarette prices is associated with a drop in e-cigarettes sales of approximately 8.2%, while based on dynamic models, the drop is 2.7% in the short run and 11.5% in the long run. Combustible cigarette prices are positively associated with sales of e-cigarettes. Snus prices are positively associated with sales of e-cigarettes in Sweden. Our results indicate that the sales of e-cigarettes are responsive to price changes, which suggests that excise taxes can help governments to mitigate an increase in e-cigarette use. E-cigarettes and regular cigarettes are substitutes, with higher cigarette prices being associated with increased e-cigarette sales. Making combustible cigarettes more expensive compared to e-cigarettes could be effective in moving current combustible smokers to e-cigarettes, which might have positive health effects. This study is an exploratory analysis of the issues around e-cigarette taxation in Europe. Our results suggest that taxation is a measure that could potentially address the concerns of both opponents and proponents of e-cigarettes: taxes on e-cigarettes could be used to raise prices so as to deter e-cigarette initiation by never users, while concomitant greater tax increases on regular cigarettes could incentivize switching from combustible products to e-cigarettes. The estimates from our models suggest that e-cigarette demand is possibly more responsive to price than cigarette demand. Policymakers who consider implementing excise taxes on e-cigarettes should take this difference in price responsiveness of demand for these two products under consideration. © The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Optimal crop selection and water allocation under limited water supply in irrigation
NASA Astrophysics Data System (ADS)
Stange, Peter; Grießbach, Ulrike; Schütze, Niels
2015-04-01
Due to climate change, extreme weather conditions such as droughts may have an increasing impact on irrigated agriculture. To cope with limited water resources in irrigation systems, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand at the same time. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from optimized agronomic response on farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF). These functions take into account different soil types, crops and stochastically generated climate scenarios. The SCWPF's are used to compute the water demand considering different conditions, e.g., variable and fixed costs. This generic approach enables the consideration of both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance IRrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies.
Estimating the Market Demand and Elasticity for Enrollment at an Institution
ERIC Educational Resources Information Center
Wohlgemuth, Darin
2013-01-01
This article presents an applied research framework that can be helpful in tuition and net price policy discussions. It is the classic microeconomic concept of market demand applied to enrollment management in higher education. The policy relevance includes measuring a response to price. For example, the results of this model will allow the…
Energy Efficiency and Demand Response for Residential Applications
NASA Astrophysics Data System (ADS)
Wellons, Christopher J., II
The purpose of this thesis is to analyze the costs, feasibility and benefits of implementing energy efficient devices and demand response programs to a residential consumer environment. Energy efficiency and demand response are important for many reasons, including grid stabilization. With energy demand increasing, as the years' pass, the drain on the grid is going up. There are two key solutions to this problem, increasing supply by building more power plants and decreasing demand during peak periods, by increasing participation in demand response programs and by upgrading residential and commercial customers to energy efficient devices, to lower demand throughout the day. This thesis focuses on utilizing demand response methods and energy efficient device to reduce demand. Four simulations were created to analyze these methods. These simulations show the importance of energy efficiency and demand response participation to help stabilize the grid, integrate more alternative energy resources, and reduce emissions from fossil fuel generating facilities. The results of these numerical analyses show that demand response and energy efficiency can be beneficial to consumers and utilities. With demand response being the most beneficial to the utility and energy efficiency, specifically LED lighting, providing the most benefits to the consumer.
Jagtap, Pranav; Diwadkar, Vaibhav A
2016-07-01
Frontal-thalamic interactions are crucial for bottom-up gating and top-down control, yet have not been well studied from brain network perspectives. We applied network modeling of fMRI signals [dynamic causal modeling (DCM)] to investigate frontal-thalamic interactions during an attention task with parametrically varying levels of demand. fMRI was collected while subjects participated in a sustained continuous performance task with low and high attention demands. 162 competing model architectures were employed in DCM to evaluate hypotheses on bilateral frontal-thalamic connections and their modulation by attention demand, selected at a second level using Bayesian model selection. The model architecture evinced significant contextual modulation by attention of ascending (thalamus → dPFC) and descending (dPFC → thalamus) pathways. However, modulation of these pathways was asymmetric: while positive modulation of the ascending pathway was comparable across attention demand, modulation of the descending pathway was significantly greater when attention demands were increased. Increased modulation of the (dPFC → thalamus) pathway in response to increased attention demand constitutes novel evidence of attention-related gain in the connectivity of the descending attention pathway. By comparison demand-independent modulation of the ascending (thalamus → dPFC) pathway suggests unbiased thalamic inputs to the cortex in the context of the paradigm. Hum Brain Mapp 37:2557-2570, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Lako, Christiaan J; Rosenau, Pauline
2009-03-01
In the Netherlands, current policy opinion emphasizes demand-driven health care. Central to this model is the view, advocated by some Dutch health policy makers, that patients should be encouraged to be aware of and make use of health quality and health outcomes information in making personal health care provider choices. The success of the new health care system in the Netherlands is premised on this being the case. After a literature review and description of the new Dutch health care system, the adequacy of this demand-driven health policy is tested. The data from a July 2005, self-administered questionnaire survey of 409 patients (response rate of 94%) as to how they choose a hospital are presented. Results indicate that most patients did not choose by actively employing available quality and outcome information. They were, rather, referred by their general practitioner. Hospital choice is highly related to the importance a patient attaches to his or her physician's opinion about a hospital. Some patients indicated that their hospital choice was affected by the reputation of the hospital, by the distance they lived from the hospital, etc. but physician's advice was, by far, the most important factor. Policy consequences are important; the assumptions underlying the demand-driven model of patient health provider choice are inadequate to explain the pattern of observed responses. An alternative, more adequate model is required, one that takes into account the patient's confidence in physician referral and advice.
NASA Astrophysics Data System (ADS)
Pleban, J. R.; Mackay, D. S.; Ewers, B. E.; Weinig, C.; Guadagno, C. L.
2016-12-01
Human society has modified agriculture management practices and utilized a variety of breeding approaches to adapt to changing environments. Presently a dual pronged challenge has emerged as environmental change is occurring more rapidly while the demand of population growth on food supply is rising. Knowledge of how current agricultural practices will respond to these challenges can be informed through crafted prognostic modeling approaches. Amongst the uncertainties associated with forecasting agricultural production in a changing environment is evaluation of the responses across the existing genotypic diversity of crop species. Mechanistic models of plant productivity provide a means of genotype level parameterization allowing for a prognostic evaluation of varietal performance under changing climate. Brassica rapa represents an excellent species for this type of investigation because of its wide cultivation as well as large morphological and physiological diversity. We incorporated genotypic parameterization of B. rapa genotypes based on unique CO2 assimilation strategies, vulnerabilities to cavitation, and root to leaf area relationships into the TREES model. Three climate drivers, following the "business-as-usual" greenhouse gas emissions scenario (RCP 8.5) from Coupled Model Intercomparison Project, Phase 5 (CMIP5) were considered: temperature (T) along with associated changes in vapor pressure deficit (VPD), increasing CO2, as well as alternatives in irrigation regime across a temporal scale of present day to 2100. Genotypic responses to these drivers were evaluated using net primary productivity (NPP) and percent loss hydraulic conductance (PLC) as a measure of tolerance for a particular watering regime. Genotypic responses to T were witnessed as water demand driven by increases in VPD at 2050 and 2100 drove some genotypes to greater PLC and in a subset of these saw periodic decreases in NPP during a growing season. Genotypes able to withstand the greater water demand showed lower NPP yields relative to hydraulically aggressive genotypes but saw limited PLC. Expansion of this analysis to large recombinant inbred populations may inform breeders in identification of trait combinations needed to meet the coupled challenge of rapid environmental change and increase food demand.
Race, Elizabeth A; Shanker, Shanti; Wagner, Anthony D
2009-09-01
Past experience is hypothesized to reduce computational demands in PFC by providing bottom-up predictive information that informs subsequent stimulus-action mapping. The present fMRI study measured cortical activity reductions ("neural priming"/"repetition suppression") during repeated stimulus classification to investigate the mechanisms through which learning from the past decreases demands on the prefrontal executive system. Manipulation of learning at three levels of representation-stimulus, decision, and response-revealed dissociable neural priming effects in distinct frontotemporal regions, supporting a multiprocess model of neural priming. Critically, three distinct patterns of neural priming were identified in lateral frontal cortex, indicating that frontal computational demands are reduced by three forms of learning: (a) cortical tuning of stimulus-specific representations, (b) retrieval of learned stimulus-decision mappings, and (c) retrieval of learned stimulus-response mappings. The topographic distribution of these neural priming effects suggests a rostrocaudal organization of executive function in lateral frontal cortex.
New York State energy-analytic information system: first-stage implementation
DOE Office of Scientific and Technical Information (OSTI.GOV)
Allentuck, J.; Carroll, O.; Fiore, L.
1979-09-01
So that energy policy by state government may be formulated within the constraints imposed by policy determined at the national level - yet reflect the diverse interests of its citizens - large quantities of data and sophisticated analytic capabilities are required. This report presents the design of an energy-information/analytic system for New York State, the data for a base year, 1976, and projections of these data. At the county level, 1976 energy-supply demand data and electric generating plant data are provided as well. Data-base management is based on System 2000. Three computerized models provide the system's basic analytic capacity. Themore » Brookhaven Energy System Network Simulator provides an integrating framework while a price-response model and a weather sensitive energy demand model furnished a short-term energy response estimation capability. The operation of these computerized models is described. 62 references, 25 figures, 39 tables.« less
NASA Astrophysics Data System (ADS)
Abdel Raheem, Shehata E.; Ahmed, Mohamed M.; Alazrak, Tarek M. A.
2015-03-01
Soil conditions have a great deal to do with damage to structures during earthquakes. Hence the investigation on the energy transfer mechanism from soils to buildings during earthquakes is critical for the seismic design of multi-story buildings and for upgrading existing structures. Thus, the need for research into soil-structure interaction (SSI) problems is greater than ever. Moreover, recent studies show that the effects of SSI may be detrimental to the seismic response of structure and neglecting SSI in analysis may lead to un-conservative design. Despite this, the conventional design procedure usually involves assumption of fixity at the base of foundation neglecting the flexibility of the foundation, the compressibility of the underneath soil and, consequently, the effect of foundation settlement on further redistribution of bending moment and shear force demands. Hence the SSI analysis of multi-story buildings is the main focus of this research; the effects of SSI are analyzed for typical multi-story building resting on raft foundation. Three methods of analysis are used for seismic demands evaluation of the target moment-resistant frame buildings: equivalent static load; response spectrum methods and nonlinear time history analysis with suit of nine time history records. Three-dimensional FE model is constructed to investigate the effects of different soil conditions and number of stories on the vibration characteristics and seismic response demands of building structures. Numerical results obtained using SSI model with different soil conditions are compared to those corresponding to fixed-base support modeling assumption. The peak responses of story shear, story moment, story displacement, story drift, moments at beam ends, as well as force of inner columns are analyzed. The results of different analysis approaches are used to evaluate the advantages, limitations, and ease of application of each approach for seismic analysis.
Monetary incentive moderates the effect of implicit fear on effort-related cardiovascular response.
Chatelain, Mathieu; Gendolla, Guido H E
2016-05-01
Integrating the implicit-affect-primes-effort model (Gendolla, 2012, 2015) with the principles of motivational intensity theory (Brehm & Self, 1989) we investigated if the effort mobilization deficit observed in people exposed to fear primes (vs. anger primes) in a difficult short-term memory task could be compensated by high monetary incentive. Effort was operationalized as cardiac response. We expected that fear primes should lead to the strongest cardiac pre-ejection period (PEP) reactivity when incentive was high (high subjective demand and high justified effort) and to the weakest response when incentive was low (high subjective demand but only low justified effort). PEP reactivity in the anger-prime conditions should fall in between (high but feasible demand). We obtained the predicted pattern on responses of PEP and systolic blood pressure. The present findings show for the first time that the effort mobilization deficit of participants exposed to fear primes in a difficult cognitive task could be compensated by a high incentive. Copyright © 2016 Elsevier B.V. All rights reserved.
Krishnakumar, Ambika; Narine, Lutchmie; Soonthorndhada, Amara; Thianlai, Kanchana
2015-03-01
To examine gender variations in the linkages among family stressors, home demands and responsibilities, coping resources, social connectedness, and older adult health problems. Data were collected from 3,800 elderly participants (1,654 men and 2,146 women) residing in Kanchanaburi province, Thailand. Findings indicated gender variations in the levels of these constructs and in the mediational pathways. Thai women indicated greater health problems than men. Emotional empathy was the central variable that linked financial strain, home demands and responsibilities, and older adult health problems through social connectedness. Financial strain (and negative life events for women) was associated with lowered coping self-efficacy and increased health problems. The model indicated greater strength in predicting female health problems. Findings support gender variations in the relationships between ecological factors and older adult health problems. © The Author(s) 2014.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique
Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospectivemore » for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.« less
Light responsive hybrid nanofibres for on-demand therapeutic drug and cell delivery.
Li, Yan-Fang; Slemming-Adamsen, Peter; Wang, Jing; Song, Jie; Wang, Xueqin; Yu, Ying; Dong, Mingdong; Chen, Chunying; Besenbacher, Flemming; Chen, Menglin
2017-08-01
Smart materials for on-demand delivery of therapeutically active agents are challenging in pharmaceutical and biomaterials science. In the present study, we report hybrid nanofibres capable of being reversibly controlled to pulsatile deliver both therapeutic drugs and cells on-demand of near-infrared (NIR) light. The nanofibres, fabricated by co-electrospinning of poly (N-isopropylacrylamide), silica-coated gold nanorods and polyhedral oligomeric silsesquinoxanes have, for the first time, demonstrated rapid, reversible large-volume changes of 83% on-demand with NIR stimulation, with retained nanofibrous morphology. Combining with the extracellular matrix-mimicking fibrillary properties, the nanofibres achieved accelerated release of model drug or cells on demand with NIR triggering. The release of the model drug doxorubicin demonstrated normal anti-cancer efficacy by reducing the viability of human cervical cancer HeLa cells by 97% in 48 h. In parallel, the fibres allowed model cell NIH3T3 fibroblast entrapment, adhesion, proliferation, differentiation and, upon NIR irradiation, cell release with undisturbed cellular function. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Sasaki, Satoshi; Comber, Alexis J; Suzuki, Hiroshi; Brunsdon, Chris
2010-01-28
Ambulance response time is a crucial factor in patient survival. The number of emergency cases (EMS cases) requiring an ambulance is increasing due to changes in population demographics. This is decreasing ambulance response times to the emergency scene. This paper predicts EMS cases for 5-year intervals from 2020, to 2050 by correlating current EMS cases with demographic factors at the level of the census area and predicted population changes. It then applies a modified grouping genetic algorithm to compare current and future optimal locations and numbers of ambulances. Sets of potential locations were evaluated in terms of the (current and predicted) EMS case distances to those locations. Future EMS demands were predicted to increase by 2030 using the model (R2 = 0.71). The optimal locations of ambulances based on future EMS cases were compared with current locations and with optimal locations modelled on current EMS case data. Optimising the location of ambulance stations locations reduced the average response times by 57 seconds. Current and predicted future EMS demand at modelled locations were calculated and compared. The reallocation of ambulances to optimal locations improved response times and could contribute to higher survival rates from life-threatening medical events. Modelling EMS case 'demand' over census areas allows the data to be correlated to population characteristics and optimal 'supply' locations to be identified. Comparing current and future optimal scenarios allows more nuanced planning decisions to be made. This is a generic methodology that could be used to provide evidence in support of public health planning and decision making.
The role of storage dynamics in annual wheat prices
NASA Astrophysics Data System (ADS)
Schewe, Jacob; Otto, Christian; Frieler, Katja
2017-05-01
Identifying the drivers of global crop price fluctuations is essential for estimating the risks of unexpected weather-induced production shortfalls and for designing optimal response measures. Here we show that with a consistent representation of storage dynamics, a simple supply-demand model can explain most of the observed variations in wheat prices over the last 40 yr solely based on time series of annual production and long term demand trends. Even the most recent price peaks in 2007/08 and 2010/11 can be explained by additionally accounting for documented changes in countries’ trade policies and storage strategies, without the need for external drivers such as oil prices or speculation across different commodity or stock markets. This underlines the critical sensitivity of global prices to fluctuations in production. The consistent inclusion of storage into a dynamic supply-demand model closes an important gap when it comes to exploring potential responses to future crop yield variability under climate and land-use change.
Are College Graduates More Responsive to Distant Labor Market Opportunities?
ERIC Educational Resources Information Center
Wozniak, Abigail
2010-01-01
Are highly educated workers better at locating in areas with high labor demand? To answer this question, I use three decades of U.S. Census data to estimate a McFadden-style model of residential location choice. I test for education differentials in the likelihood that young workers reside in states experiencing positive labor demand shocks at the…
Theory and Techniques for Assessing the Demand and Supply of Outdoor Recreation in the United States
H. Ken Cordell; John C. Bergstrom
1989-01-01
As the central analysis for the 1989 Renewable Resources planning Act Assessment, a household market model covering 37 recreational activities was computed for the United States. Equilibrium consumption and costs were estimated, as were likely future changes in consumption and costs in response to expected demand growth and alternative development and access policies...
Impact of Climate Change on Energy Demand in the Midwestern USA
NASA Astrophysics Data System (ADS)
Yan, M. B.; Zhang, F.; Franklin, M.; Kotamarthi, V. R.
2008-12-01
The impact of climate change on energy demand and use is a significant issue for developing future GHG emission scenarios and developing adaptation and mitigation strategies. A number of studies have evaluated the increase in GHG emissions as a result of changes in energy production from fossil fuels, but the consequences of climate change on energy consumption have not been the focus of many studies. Here we focus on the impacts of climate change on energy use at a regional scale using the Midwestern USA as a test. The paper presents results of analyzing energy use in response to ambient temperature changes in a 17-year period from 1989 to 2006 and projection of energy use under future climate scenarios (2010-2061). This study consisted of a two-step procedure. In the first step, sensitivity of historic energy demand, specifically electricity and natural gas in residential and commercial sectors (42% of end-use energy), with respect to many climatic and non-climatic variables was examined. State-specific regression models were developed to quantify the relationship between energy use and climatic variables using degree days. We found that model parameters and base temperatures for estimating heating and cooling days varied by state and energy sector, mainly depending on climate conditions, infrastructure, economic factors, and seasonal change in energy use. In the second step, we applied these models to predict future energy demand using output data generated by the Community Climate System Model (CCSM) for the SRES A1B scenario used in the IPCC AR-4. The annual demands of electricity and natural gas were predicted for each state from 2010 to 2061. The model results indicate that the average annual electricity demand will increase 3%-5% for the southern states and 1%-3% for the northern states in the region by 2061 and that the demand for natural gas is expected to be reduced in all states. A seasonal analysis of energy distribution in response to climate variables identifies a significant peak in demand in July-August (11%-16% in southern states and 6%-10% in the northern states). These findings suggest that the energy sector is vulnerable to climate change even in the northern Midwest region of the US. Furthermore, we demonstrate that a state-level assessment can help to better identify adaptation strategies for future regional energy sector changes.
Real-time pricing strategy of micro-grid energy centre considering price-based demand response
NASA Astrophysics Data System (ADS)
Xu, Zhiheng; Zhang, Yongjun; Wang, Gan
2017-07-01
With the development of energy conversion technology such as power to gas (P2G), fuel cell and so on, the coupling between energy sources becomes more and more closely. Centralized dispatch among electricity, natural gas and heat will become a trend. With the goal of maximizing the system revenue, this paper establishes the model of micro-grid energy centre based on energy hub. According to the proposed model, the real-time pricing strategy taking into account price-based demand response of load is developed. And the influence of real-time pricing strategy on the peak load shifting is discussed. In addition, the impact of wind power predicted inaccuracy on real-time pricing strategy is analysed.
Integrating Demand-Side Resources into the Electric Grid: Economic and Environmental Considerations
NASA Astrophysics Data System (ADS)
Fisher, Michael J.
Demand-side resources are taking an increasingly prominent role in providing essential grid services once provided by thermal power plants. This thesis considers the economic feasibility and environmental effects of integrating demand-side resources into the electric grid with consideration given to the diversity of market and environmental conditions that can affect their behavior. Chapter 2 explores the private economics and system-level carbon dioxide reduction when using demand response for spinning reserve. Steady end uses like lighting are more than twice as profitable as seasonal end uses because spinning reserve is needed year-round. Avoided carbon emission damages from using demand response instead of fossil fuel generation for spinning reserve are sufficient to justify incentives for demand response resources. Chapter 3 quantifies the system-level net emissions rate and private economics of behind-the-meter energy storage. Net emission rates are lower than marginal emission rates for power plants and in-line with estimates of net emission rates from grid-level storage. The economics are favorable for many buildings in regions with high demand charges like California and New York, even without subsidies. Future penetration into regions with average charges like Pennsylvania will depend greatly on installation cost reductions and wholesale prices for ancillary services. Chapter 4 outlines a novel econometric model to quantify potential revenues from energy storage that reduces demand charges. The model is based on a novel predictive metric that is derived from the building's load profile. Normalized revenue estimates are independent of the power capacity of the battery holding other performance characteristics equal, which can be used to calculate the profit-maximizing storage size. Chapter 5 analyzes the economic feasibility of flow batteries in the commercial and industrial market. Flow batteries at a 4-hour duration must be less expensive on a dollar per installed kWh basis, often by 20-30%, to break even with shorter duration li-ion or lead-acid despite allowing for deeper depth of discharge and superior cycle life. These results are robust to assumptions of tariff rates, battery round-trip efficiencies, amount of solar generation and whether the battery can participate in the wholesale energy and ancillary services markets.
An Exploration of Principal Instructional Technology Leadership
ERIC Educational Resources Information Center
Townsend, LaTricia Walker
2013-01-01
Nationwide the demand for schools to incorporate technology into their educational programs is great. In response, North Carolina developed the IMPACT model in 2003 to provide a comprehensive model for technology integration in the state. The model is aligned to national educational technology standards for teachers, students, and principals.…
Demand Side Management: An approach to peak load smoothing
NASA Astrophysics Data System (ADS)
Gupta, Prachi
A preliminary national-level analysis was conducted to determine whether Demand Side Management (DSM) programs introduced by electric utilities since 1992 have made any progress towards their stated goal of reducing peak load demand. Estimates implied that DSM has a very small effect on peak load reduction and there is substantial regional and end-user variability. A limited scholarly literature on DSM also provides evidence in support of a positive effect of demand response programs. Yet, none of these studies examine the question of how DSM affects peak load at the micro-level by influencing end-users' response to prices. After nearly three decades of experience with DSM, controversy remains over how effective these programs have been. This dissertation considers regional analyses that explore both demand-side solutions and supply-side interventions. On the demand side, models are estimated to provide in-depth evidence of end-user consumption patterns for each North American Electric Reliability Corporation (NERC) region, helping to identify sectors in regions that have made a substantial contribution to peak load reduction. The empirical evidence supports the initial hypothesis that there is substantial regional and end-user variability of reductions in peak demand. These results are quite robust in rapidly-urbanizing regions, where air conditioning and lighting load is substantially higher, and regions where the summer peak is more pronounced than the winter peak. It is also evident from the regional experiences that active government involvement, as shaped by state regulations in the last few years, has been successful in promoting DSM programs, and perhaps for the same reason we witness an uptick in peak load reductions in the years 2008 and 2009. On the supply side, we estimate the effectiveness of DSM programs by analyzing the growth of capacity margin with the introduction of DSM programs. The results indicate that DSM has been successful in offsetting the need for additional production capacity by the means of demand response measures, but the success is limited to only a few regions. The rate of progress in the future will depend on a wide range of improved technologies and a continuous government monitoring for successful adoption of demand response programs to manage growing energy demand.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Christensen, Craig
Opportunities for combining energy efficiency, demand response, and energy storage with PV are often missed, because the required knowledge and expertise for these different technologies exist in separate organizations or individuals. Furthermore, there is a lack of quantitative tools to optimize energy efficiency, demand response and energy storage with PV, especially for existing buildings. Our goal is to develop a modeling tool, BEopt-CA (Ex), with capabilities to facilitate identification and implementation of a balanced integration of energy efficiency (EE), demand response (DR), and energy storage (ES) with photovoltaics (PV) within the residential retrofit market. To achieve this goal, we willmore » adapt and extend an existing tool -- BEopt -- that is designed to identify optimal combinations of efficiency and PV in new home designs. In addition, we will develop multifamily residential modeling capabilities for use in California, to facilitate integration of distributed solar power into the grid in order to maximize its value to California ratepayers. The project is follow-on research that leverages previous California Solar Initiative RD&D investment in the BEopt software. BEopt facilitates finding the least cost combination of energy efficiency and renewables to support integrated DSM (iDSM) and Zero Net Energy (ZNE) in California residential buildings. However, BEopt is currently focused on modeling single-family houses and does not include satisfactory capabilities for modeling multifamily homes. The project brings BEopt's existing modeling and optimization capabilities to multifamily buildings, including duplexes, triplexes, townhouses, flats, and low-rise apartment buildings.« less
Photosynthetic capacity regulation is uncoupled from nutrient limitation
NASA Astrophysics Data System (ADS)
Smith, N. G.; Keenan, T. F.; Prentice, I. C.; Wang, H.
2017-12-01
Ecosystem and Earth system models need information on leaf-level photosynthetic capacity, but to date typically rely on empirical estimates and an assumed dependence on nitrogen supply. Recent evidence suggests that leaf nitrogen is actively controlled though plant responses to photosynthetic demand. Here, we propose and test a theory of demand-driven coordination of photosynthetic processes, and use it to assess the relative roles of nutrient supply and photosynthetic demand. The theory captured 63% of observed variability in a global dataset of Rubisco carboxylation capacity (Vcmax; 3,939 values at 219 sites), suggesting that environmentally regulated biophysical costs and light availability are the first-order drivers of photosynthetic capacity. Leaf nitrogen, on the other hand, was a weak secondary driver of Vcmax, explaining less than 6% of additional observed variability. We conclude that leaf nutrient allocation is primarily driven by demand. Our theory offers a simple, robust strategy for dynamically predicting leaf-level photosynthetic capacity in global models.
Residential water demand with endogenous pricing: The Canadian Case
NASA Astrophysics Data System (ADS)
Reynaud, Arnaud; Renzetti, Steven; Villeneuve, Michel
2005-11-01
In this paper, we show that the rate structure endogeneity may result in a misspecification of the residential water demand function. We propose to solve this endogeneity problem by estimating a probabilistic model describing how water rates are chosen by local communities. This model is estimated on a sample of Canadian local communities. We first show that the pricing structure choice reflects efficiency considerations, equity concerns, and, in some cases, a strategy of price discrimination across consumers by Canadian communities. Hence estimating the residential water demand without taking into account the pricing structures' endogeneity leads to a biased estimation of price and income elasticities. We also demonstrate that the pricing structure per se plays a significant role in influencing price responsiveness of Canadian residential consumers.
Impacts of demand response and renewable generation in electricity power market
NASA Astrophysics Data System (ADS)
Zhao, Zhechong
This thesis presents the objective of the research which is to analyze the impacts of uncertain wind power and demand response on power systems operation and power market clearing. First, in order to effectively utilize available wind generation, it is usually given the highest priority by assigning zero or negative energy bidding prices when clearing the day-ahead electric power market. However, when congestion occurs, negative wind bidding prices would aggravate locational marginal prices (LMPs) to be negative in certain locations. A load shifting model is explored to alleviate possible congestions and enhance the utilization of wind generation, by shifting proper amount of load from peak hours to off peaks. The problem is to determine proper amount of load to be shifted, for enhancing the utilization of wind generation, alleviating transmission congestions, and making LMPs to be non-negative values. The second piece of work considered the price-based demand response (DR) program which is a mechanism for electricity consumers to dynamically manage their energy consumption in response to time-varying electricity prices. It encourages consumers to reduce their energy consumption when electricity prices are high, and thereby reduce the peak electricity demand and alleviate the pressure to power systems. However, it brings additional dynamics and new challenges on the real-time supply and demand balance. Specifically, price-sensitive DR load levels are constantly changing in response to dynamic real-time electricity prices, which will impact the economic dispatch (ED) schedule and in turn affect electricity market clearing prices. This thesis adopts two methods for examining the impacts of different DR price elasticity characteristics on the stability performance: a closed-loop iterative simulation method and a non-iterative method based on the contraction mapping theorem. This thesis also analyzes the financial stability of DR load consumers, by incorporating explicit LMP formulations and consumer payment requirements into the network-constrained unit commitment (NCUC) problem. The proposed model determines the proper amount of DR loads to be shifted from peak hours to off-peaks under ISO's direct load control, for reducing the operation cost and ensuring that consumer payments of DR loads will not deteriorate significantly after load shifting. Both MINLP and MILP models are discussed, and improved formulation strategies are presented.
Efficient Kill-Save Ratios Ease Up the Cognitive Demands on Counterintuitive Moral Utilitarianism.
Trémolière, Bastien; Bonnefon, Jean-François
2014-07-01
The dual-process model of moral judgment postulates that utilitarian responses to moral dilemmas (e.g., accepting to kill one to save five) are demanding of cognitive resources. Here we show that utilitarian responses can become effortless, even when they involve to kill someone, as long as the kill-save ratio is efficient (e.g., 1 is killed to save 500). In Experiment 1, participants responded to moral dilemmas featuring different kill-save ratios under high or low cognitive load. In Experiments 2 and 3, participants responded at their own pace or under time pressure. Efficient kill-save ratios promoted utilitarian responding and neutered the effect of load or time pressure. We discuss whether this effect is more easily explained by a parallel-activation model or by a default-interventionist model. © 2014 by the Society for Personality and Social Psychology, Inc.
The behavioral economics of driving after drinking among college drinkers.
Teeters, Jenni B; Murphy, James G
2015-05-01
Driving after drinking (DAD) among college students is a significant public health concern, yet little is known about specific theoretical risk factors for DAD, beyond drinking level, among college student drinkers. This study had the following aims: (i) to examine the associations between elevated alcohol demand and DAD, (ii) to determine whether demand decreases in response to a hypothetical driving scenario, (iii) to determine whether drivers who report DAD in the past 3 months would show less of a reduction in demand in response to the hypothetical driving scenario, and (iv) to determine whether delayed reward discounting (DRD) is associated with DAD. Participants were 419 college students who reported at least 1 day of past-month alcohol use. Participants completed 2 alcohol purchase tasks (APTs) that assessed hypothetical alcohol consumption across 17 drink prices with and without a driving scenario, a delay-discounting task, and a series of questions regarding DAD. In logistic regression models that controlled for drinking level, demographics, and sensation seeking, participants reporting higher demand intensity (95% confidence interval [95% CI] [1.04, 2.34]), breakpoint (95% CI [1.23, 2.28]), Omax (95% CI [1.03, 1.53]), and lower elasticity (95% CI [0.15, 1.02]) were more likely to report DAD. Additionally, in analyses of covariance, DAD(+) participants exhibited significantly less of a reduction in demand between the standard and the driving APT (intensity, p < 0.01, breakpoint, p = 0.05, and Omax , p < 0.01). A binary logistic regression model with identical covariates revealed that DRD is not associated with DAD. DAD is associated with elevated/inelastic demand and less sensitivity to a hypothetical driving scenario. Drinkers with elevated demand should be prioritized for DAD intervention efforts. Copyright © 2015 by the Research Society on Alcoholism.
Stressful working conditions and poor self-rated health among financial services employees.
Silva, Luiz Sérgio; Barreto, Sandhi Maria
2012-06-01
To assess the association between exposure to adverse psychosocial working conditions and poor self-rated health among bank employees. A cross-sectional study including a sample of 2,054 employees of a government bank was conducted in 2008. Self-rated health was assessed by a single question: "In general, would you say your health is (...)." Exposure to adverse psychosocial working conditions was evaluated by the effort-reward imbalance model and the demand-control model. Information on other independent variables was obtained through a self-administered semi-structured questionnaire. A multiple logistic regression analysis was performed and odds ratio calculated to assess independent associations between adverse psychosocial working conditions and poor self-rated health. The overall prevalence of poor self-rated health was 9%, with no significant gender difference. Exposure to high demand and low control environment at work was associated with poor self-rated health. Employees with high effort-reward imbalance and overcommitment also reported poor self-rated health, with a dose-response relationship. Social support at work was inversely related to poor self-rated health, with a dose-response relationship. Exposure to adverse psychosocial work factors assessed based on the effort-reward imbalance model and the demand-control model is independently associated with poor self-rated health among the workers studied.
Advances In High Temperature (Viscoelastoplastic) Material Modeling for Thermal Structural Analysis
NASA Technical Reports Server (NTRS)
Arnold, Steven M.; Saleeb, Atef F.
2005-01-01
Typical High Temperature Applications High Temperature Applications Demand High Performance Materials: 1) Complex Thermomechanical Loading; 2) Complex Material response requires Time-Dependent/Hereditary Models: Viscoelastic/Viscoplastic; and 3) Comprehensive Characterization (Tensile, Creep, Relaxation) for a variety of material systems.
Predictors of new graduate nurses' workplace well-being: testing the job demands-resources model.
Spence Laschinger, Heather K; Grau, Ashley L; Finegan, Joan; Wilk, Piotr
2012-01-01
New graduate nurses currently experience a stressful transition into the workforce, resulting in high levels of burnout and job turnover in their first year of practice. This study tested a theoretical model of new graduate nurses' worklife derived from the job demands-resources model to better understand how job demands (workload and bullying), job resources (job control and supportive professional practice environments), and a personal resource (psychological capital) combine to influence new graduate experiences of burnout and work engagement and, ultimately, health and job outcomes. A descriptive correlational design was used to test the hypothesized model in a sample of newly graduated nurses (N = 420) working in acute care hospitals in Ontario, Canada. Data were collected from July to November 2009. Participants were mailed questionnaires to their home address using the Total Design Method to improve response rates. All variables were measured using standardized questionnaires, and structural equation modeling was used to test the model. The final model fit statistics partially supported the original hypothesized model. In the final model, job demands (workload and bullying) predicted burnout and, subsequently, poor mental health. Job resources (supportive practice environment and control) predicted work engagement and, subsequently, lower turnover intentions. Burnout also was a significant predictor of turnover intent (a crossover effect). Furthermore, personal resources (psychological capital) significantly influenced both burnout and work engagement. The model suggests that managerial strategies targeted at specific job demands and resources can create workplace environments that promote work engagement and prevent burnout to support the retention and well-being of the new graduate nurse population.
Demand driven decision support for efficient water resources allocation in irrigated agriculture
NASA Astrophysics Data System (ADS)
Schuetze, Niels; Grießbach, Ulrike Ulrike; Röhm, Patric; Stange, Peter; Wagner, Michael; Seidel, Sabine; Werisch, Stefan; Barfus, Klemens
2014-05-01
Due to climate change, extreme weather conditions, such as longer dry spells in the summer months, may have an increasing impact on the agriculture in Saxony (Eastern Germany). For this reason, and, additionally, declining amounts of rainfall during the growing season the use of irrigation will be more important in future in Eastern Germany. To cope with this higher demand of water, a new decision support framework is developed which focuses on an integrated management of both irrigation water supply and demand. For modeling the regional water demand, local (and site-specific) water demand functions are used which are derived from the optimized agronomic response at farms scale. To account for climate variability the agronomic response is represented by stochastic crop water production functions (SCWPF) which provide the estimated yield subject to the minimum amount of irrigation water. These functions take into account the different soil types, crops and stochastically generated climate scenarios. By applying mathematical interpolation and optimization techniques, the SCWPF's are used to compute the water demand considering different constraints, for instance variable and fix costs or the producer price. This generic approach enables the computation for both multiple crops at farm scale as well as of the aggregated response to water pricing at a regional scale for full and deficit irrigation systems. Within the SAPHIR (SAxonian Platform for High Performance Irrigation) project a prototype of a decision support system is developed which helps to evaluate combined water supply and demand management policies for an effective and efficient utilization of water in order to meet future demands. The prototype is implemented as a web-based decision support system and it is based on a service-oriented geo-database architecture.
Uncertainty and operational considerations in mass prophylaxis workforce planning.
Hupert, Nathaniel; Xiong, Wei; King, Kathleen; Castorena, Michelle; Hawkins, Caitlin; Wu, Cindie; Muckstadt, John A
2009-12-01
The public health response to an influenza pandemic or other large-scale health emergency may include mass prophylaxis using multiple points of dispensing (PODs) to deliver countermeasures rapidly to affected populations. Computer models created to date to determine "optimal" staffing levels at PODs typically assume stable patient demand for service. The authors investigated POD function under dynamic and uncertain operational environments. The authors constructed a Monte Carlo simulation model of mass prophylaxis (the Dynamic POD Simulator, or D-PODS) to assess the consequences of nonstationary patient arrival patterns on POD function under a variety of POD layouts and staffing plans. Compared are the performance of a standard POD layout under steady-state and variable patient arrival rates that may mimic real-life variation in patient demand. To achieve similar performance, PODs functioning under nonstationary patient arrival rates require higher staffing levels than would be predicted using the assumption of stationary arrival rates. Furthermore, PODs may develop severe bottlenecks unless staffing levels vary over time to meet changing patient arrival patterns. Efficient POD networks therefore require command and control systems capable of dynamically adjusting intra- and inter-POD staff levels to meet demand. In addition, under real-world operating conditions of heightened uncertainty, fewer large PODs will require a smaller total staff than many small PODs to achieve comparable performance. Modeling environments that capture the effects of fundamental uncertainties in public health disasters are essential for the realistic evaluation of response mechanisms and policies. D-PODS quantifies POD operational efficiency under more realistic conditions than have been modeled previously. The authors' experiments demonstrate that effective POD staffing plans must be responsive to variation and uncertainty in POD arrival patterns. These experiments highlight the need for command and control systems to be created to manage emergency response successfully.
Understanding Heterogeneity in Price Elasticities in the Demand for Alcohol for Older Individuals
Ayyagari, Padmaja; Deb, Partha; Fletcher, Jason; Gallo, William; Sindelar, Jody L.
2013-01-01
This paper estimates the price elasticity of demand for alcohol using Health and Retirement Study data. To account for unobserved heterogeneity in price responsiveness, we use finite mixture models. We recover two latent groups, one is significantly responsive to price, but the other is unresponsive. The group with greater responsiveness is disadvantaged in multiple domains, including health, financial resources, education and perhaps even planning abilities. These results have policy implications. The unresponsive group drinks more heavily, suggesting that a higher tax would fail to curb the negative alcohol-related externalities. In contrast, the more disadvantaged group is more responsive to price, thus suffering greater deadweight loss, yet this group consumes fewer drinks per day and might be less likely to impose negative externalities. PMID:22162113
Understanding heterogeneity in price elasticities in the demand for alcohol for older individuals.
Ayyagari, Padmaja; Deb, Partha; Fletcher, Jason; Gallo, William; Sindelar, Jody L
2013-01-01
This paper estimates the price elasticity of demand for alcohol using Health and Retirement Study data. To account for unobserved heterogeneity in price responsiveness, we use finite mixture models. We recover two latent groups, one is significantly responsive to price, but the other is unresponsive. The group with greater responsiveness is disadvantaged in multiple domains, including health, financial resources, education and perhaps even planning abilities. These results have policy implications. The unresponsive group drinks more heavily, suggesting that a higher tax would fail to curb the negative alcohol-related externalities. In contrast, the more disadvantaged group is more responsive to price, thus suffering greater deadweight loss, yet this group consumes fewer drinks per day and might be less likely to impose negative externalities. Copyright © 2011 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Rajagopalan, K.; Chinnayakanahalli, K. J.; Stockle, C. O.; Nelson, R. L.; Kruger, C. E.; Brady, M. P.; Malek, K.; Dinesh, S. T.; Barber, M. E.; Hamlet, A. F.; Yorgey, G. G.; Adam, J. C.
2018-03-01
Adaptation to a changing climate is critical to address future global food and water security challenges. While these challenges are global, successful adaptation strategies are often generated at regional scales; therefore, regional-scale studies are critical to inform adaptation decision making. While climate change affects both water supply and demand, water demand is relatively understudied, especially at regional scales. The goal of this work is to address this gap, and characterize the direct impacts of near-term (for the 2030s) climate change and elevated CO2 levels on regional-scale crop yields and irrigation demands for the Columbia River basin (CRB). This question is addressed through a coupled crop-hydrology model that accounts for site-specific and crop-specific characteristics that control regional-scale response to climate change. The overall near-term outlook for agricultural production in the CRB is largely positive, with yield increases for most crops and small overall increases in irrigation demand. However, there are crop-specific and location-specific negative impacts as well, and the aggregate regional response of irrigation demands to climate change is highly sensitive to the spatial crop mix. Low-value pasture/hay varieties of crops—typically not considered in climate change assessments—play a significant role in determining the regional response of irrigation demands to climate change, and thus cannot be overlooked. While, the overall near-term outlook for agriculture in the region is largely positive, there may be potential for a negative outlook further into the future, and it is important to consider this in long-term planning.
Forest gradient response in Sierran landscapes: the physical template
Urban, Dean L.; Miller, Carol; Halpin, Patrick N.; Stephenson, Nathan L.
2000-01-01
Vegetation pattern on landscapes is the manifestation of physical gradients, biotic response to these gradients, and disturbances. Here we focus on the physical template as it governs the distribution of mixed-conifer forests in California's Sierra Nevada. We extended a forest simulation model to examine montane environmental gradients, emphasizing factors affecting the water balance in these summer-dry landscapes. The model simulates the soil moisture regime in terms of the interaction of water supply and demand: supply depends on precipitation and water storage, while evapotranspirational demand varies with solar radiation and temperature. The forest cover itself can affect the water balance via canopy interception and evapotranspiration. We simulated Sierran forests as slope facets, defined as gridded stands of homogeneous topographic exposure, and verified simulated gradient response against sample quadrats distributed across Sequoia National Park. We then performed a modified sensitivity analysis of abiotic factors governing the physical gradient. Importantly, the model's sensitivity to temperature, precipitation, and soil depth varies considerably over the physical template, particularly relative to elevation. The physical drivers of the water balance have characteristic spatial scales that differ by orders of magnitude. Across large spatial extents, temperature and precipitation as defined by elevation primarily govern the location of the mixed conifer zone. If the analysis is constrained to elevations within the mixed-conifer zone, local topography comes into play as it influences drainage. Soil depth varies considerably at all measured scales, and is especially dominant at fine (within-stand) scales. Physical site variables can influence soil moisture deficit either by affecting water supply or water demand; these effects have qualitatively different implications for forest response. These results have clear implications about purely inferential approaches to gradient analysis, and bear strongly on our ability to use correlative approaches in assessing the potential responses of montane forests to anthropogenic climatic change.
NASA Astrophysics Data System (ADS)
Javadi, Maryam; Shahrabi, Jamal
2014-03-01
The problems of facility location and the allocation of demand points to facilities are crucial research issues in spatial data analysis and urban planning. It is very important for an organization or governments to best locate its resources and facilities and efficiently manage resources to ensure that all demand points are covered and all the needs are met. Most of the recent studies, which focused on solving facility location problems by performing spatial clustering, have used the Euclidean distance between two points as the dissimilarity function. Natural obstacles, such as mountains and rivers, can have drastic impacts on the distance that needs to be traveled between two geographical locations. While calculating the distance between various supply chain entities (including facilities and demand points), it is necessary to take such obstacles into account to obtain better and more realistic results regarding location-allocation. In this article, new models were presented for location of urban facilities while considering geographical obstacles at the same time. In these models, three new distance functions were proposed. The first function was based on the analysis of shortest path in linear network, which was called SPD function. The other two functions, namely PD and P2D, were based on the algorithms that deal with robot geometry and route-based robot navigation in the presence of obstacles. The models were implemented in ArcGIS Desktop 9.2 software using the visual basic programming language. These models were evaluated using synthetic and real data sets. The overall performance was evaluated based on the sum of distance from demand points to their corresponding facilities. Because of the distance between the demand points and facilities becoming more realistic in the proposed functions, results indicated desired quality of the proposed models in terms of quality of allocating points to centers and logistic cost. Obtained results show promising improvements of the allocation, the logistics costs and the response time. It can also be inferred from this study that the P2D-based model and the SPD-based model yield similar results in terms of the facility location and the demand allocation. It is noted that the P2D-based model showed better execution time than the SPD-based model. Considering logistic costs, facility location and response time, the P2D-based model was appropriate choice for urban facility location problem considering the geographical obstacles.
Optimizing the location of ambulances in Tijuana, Mexico.
Dibene, Juan Carlos; Maldonado, Yazmin; Vera, Carlos; de Oliveira, Mauricio; Trujillo, Leonardo; Schütze, Oliver
2017-01-01
In this work we report on modeling the demand for Emergency Medical Services (EMS) in Tijuana, Baja California, Mexico, followed by the optimization of the location of the ambulances for the Red Cross of Tijuana (RCT), which is by far the largest provider of EMS services in the region. We used data from more than 10,000 emergency calls surveyed during the year 2013 to model and classify the demand for EMS in different scenarios that provide different perspectives on the demand throughout the city, considering such factors as the time of day, work and off-days. A modification of the Double Standard Model (DSM) is proposed and solved to determine a common robust solution to the ambulance location problem that simultaneously satisfies all specified constraints in all demand scenarios selecting from a set of almost 1000 possible base locations. The resulting optimization problems are solved using integer linear programming and the solutions are compared with the locations currently used by the Red Cross. Results show that demand coverage and response times can be substantially improved by relocating the current bases without the need for additional resources. Copyright © 2016 Elsevier Ltd. All rights reserved.
Johannessen, Håkon A; Tynes, Tore; Sterud, Tom
2013-06-01
To examine the impact of occupational role conflict and emotional demands on subsequent psychological distress. A randomly drawn cohort from the general Norwegian working-age population was followed up for 3 years (n = 12,550; response rate = 67%). Eligible respondents were in paid work during the reference week in 2006 and 2009 or temporarily absent from such work (n = 6,745; response rate = 68%). In the fully adjusted model, both high role conflict (odds ratios = 1.53; 95% CI = 1.15 to 2.03) and high emotional demands (odds ratios = 1.38; 95% CI = 1.13 to 1.69) were significant predictors of psychological distress. Additional significant predictors were low job control, bullying/harassment, and job insecurity (P < 0.05). Considering all of the evaluated work-related factors, role conflict and emotional demands contributed the most to the population risk of developing psychological distress.
Yabalak, Erdal
2018-05-18
This study was performed to investigate the mineralization of ticarcillin in the artificially prepared aqueous solution presenting ticarcillin contaminated waters, which constitute a serious problem for human health. 81.99% of total organic carbon removal, 79.65% of chemical oxygen demand removal, and 94.35% of ticarcillin removal were achieved by using eco-friendly, time-saving, powerful and easy-applying, subcritical water oxidation method in the presence of a safe-to-use oxidizing agent, hydrogen peroxide. Central composite design, which belongs to the response surface methodology, was applied to design the degradation experiments, to optimize the methods, to evaluate the effects of the system variables, namely, temperature, hydrogen peroxide concentration, and treatment time, on the responses. In addition, theoretical equations were proposed in each removal processes. ANOVA tests were utilized to evaluate the reliability of the performed models. F values of 245.79, 88.74, and 48.22 were found for total organic carbon removal, chemical oxygen demand removal, and ticarcillin removal, respectively. Moreover, artificial neural network modeling was applied to estimate the response in each case and its prediction and optimizing performance was statistically examined and compared to the performance of central composite design.
Code of Federal Regulations, 2014 CFR
2014-10-01
... public entities operating a demand responsive system for the general public. 37.77 Section 37.77...-rail vehicles by public entities operating a demand responsive system for the general public. (a) Except as provided in this section, a public entity operating a demand responsive system for the general...
Code of Federal Regulations, 2010 CFR
2010-10-01
... public entities operating a demand responsive system for the general public. 37.77 Section 37.77...-rail vehicles by public entities operating a demand responsive system for the general public. (a) Except as provided in this section, a public entity operating a demand responsive system for the general...
Code of Federal Regulations, 2011 CFR
2011-10-01
... public entities operating a demand responsive system for the general public. 37.77 Section 37.77...-rail vehicles by public entities operating a demand responsive system for the general public. (a) Except as provided in this section, a public entity operating a demand responsive system for the general...
Code of Federal Regulations, 2012 CFR
2012-10-01
... public entities operating a demand responsive system for the general public. 37.77 Section 37.77...-rail vehicles by public entities operating a demand responsive system for the general public. (a) Except as provided in this section, a public entity operating a demand responsive system for the general...
NASA Astrophysics Data System (ADS)
Giri, B. C.; Maiti, T.
2013-05-01
This article develops a single-manufacturer and single-retailer supply chain model under two-level permissible delay in payments when the manufacturer follows a lot-for-lot policy in response to the retailer's demand. The manufacturer offers a trade credit period to the retailer with the contract that the retailer must share a fraction of the profit earned during the trade credit period. On the other hand, the retailer provides his customer a partial trade credit which is less than that of the manufacturer. The demand at the retailer is assumed to be dependent on the selling price and the trade credit period offered to the customers. The average net profit of the supply chain is derived and an algorithm for finding the optimal solution is developed. Numerical examples are given to demonstrate the coordination policy of the supply chain and examine the sensitivity of key model-parameters.
Nurse-Performed Endoscopy: Implications for the Nursing Profession in Australia.
Duffield, Christine; Chapman, Susan; Rowbotham, Samantha; Blay, Nicole
2017-02-01
Increasing demands for health care globally often lead to discussions about expanding the involvement of nurses in a range of nontraditional roles. Several countries have introduced nurse endoscopists as a means of easing the burden of demand for a range of endoscopic procedures. A shortage of medical staff in Australia combined with increasing demand for endoscopy led to the implementation of nurse endoscopists as a pilot program in the state of Queensland, where a nurse practitioner model was implemented, and Victoria, where an advanced practice model was used. This article will discuss the implementation of and responses from the nursing, medical, and policy community to nurse-performed endoscopy in this country. Regarding health policy, access to cancer screening may be improved by providing nurses with advanced training to safely perform endoscopy procedures. Moreover, issues of nurse credentialing and payment need to be considered appropriate to each country's health system model.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Piette, Mary Ann
California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the usemore » of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.« less
Saving Power at Peak Hours (LBNL Science at the Theater)
Piette, Mary Ann [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
2018-05-23
California needs new, responsive, demand-side energy technologies to ensure that periods of tight electricity supply on the grid don't turn into power outages. Led by Berkeley Lab's Mary Ann Piette, the California Energy Commission (through its Public Interest Energy Research Program) has established a Demand Response Research Center that addresses two motivations for adopting demand responsiveness: reducing average electricity prices and preventing future electricity crises. The research seeks to understand factors that influence "what works" in Demand Response. Piette's team is investigating the two types of demand response, load response and price response, that may influence and reduce the use of peak electric power through automated controls, peak pricing, advanced communications, and other strategies.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lekov, Alex; Thompson, Lisa; McKane, Aimee
2009-05-11
This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demand response opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demand response opportunities and provides analysis results from three demand response studies. In addition, several energy efficiency, load management, and demand response case studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demand response and that facilities which have implemented energy efficiencymore » measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demand response (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.« less
NASA Astrophysics Data System (ADS)
Condon, Laura E.; Maxwell, Reed M.
2014-03-01
Groundwater-fed irrigation has been shown to deplete groundwater storage, decrease surface water runoff, and increase evapotranspiration. Here we simulate soil moisture-dependent groundwater-fed irrigation with an integrated hydrologic model. This allows for direct consideration of feedbacks between irrigation demand and groundwater depth. Special attention is paid to system dynamics in order to characterized spatial variability in irrigation demand and response to increased irrigation stress. A total of 80 years of simulation are completed for the Little Washita Basin in Southwestern Oklahoma, USA spanning a range of agricultural development scenarios and management practices. Results show regionally aggregated irrigation impacts consistent with other studies. However, here a spectral analysis reveals that groundwater-fed irrigation also amplifies the annual streamflow cycle while dampening longer-term cyclical behavior with increased irrigation during climatological dry periods. Feedbacks between the managed and natural system are clearly observed with respect to both irrigation demand and utilization when water table depths are within a critical range. Although the model domain is heterogeneous with respect to both surface and subsurface parameters, relationships between irrigation demand, water table depth, and irrigation utilization are consistent across space and between scenarios. Still, significant local heterogeneities are observed both with respect to transient behavior and response to stress. Spatial analysis of transient behavior shows that farms with groundwater depths within a critical depth range are most sensitive to management changes. Differences in behavior highlight the importance of groundwater's role in system dynamics in addition to water availability.
Demand for pneumococcal vaccination under subsidy program for the elderly in Japan.
Kondo, Masahide; Yamamura, Mariko; Hoshi, Shu-Ling; Okubo, Ichiro
2012-09-12
Vaccination programs often organize subsidies and public relations in order to obtain high uptake rates and coverage. However, effects of subsidies and public relations have not been studied well in the literature. In this study, the demand function of pneumococcal vaccination among the elderly in Japan is estimated, incorporating effects of public relations and subsidy. Using a data from a questionnaire survey sent to municipalities, the varying and constant elasticity models were applied to estimate the demand function. The response variable is the uptake rate. Explanatory variables are: subsidy supported shot price, operating years of the program, target population size for vaccination, shot location intensity, income and various public relations tools. The best model is selected by c-AIC, and varying and constant price elasticities are calculated from estimation results. The vaccine uptake rate and the shot price have a negative relation. From the results of varying price elasticity, the demand for vaccination is elastic at municipalities with a shot price higher than 3,708 JPY (35.7 USD). Effects of public relations on the uptake rate are not found. It can be suggested that municipalities with a shot price higher than 3,708 JPY (35.7 USD) could subsidize more and reduce price to increase the demand for vaccination. Effects of public relations are not confirmed in this study, probably due to measurement errors of variables used for public relations, and studies at micro level exploring individual's response to public relations would be required.
29 CFR 20.55 - Second and subsequent notifications.
Code of Federal Regulations, 2010 CFR
2010-07-01
... second and subsequent demands for payment, if payment or other appropriate response is not received within the time specified by the initial demand. Unless a response to the first or second demand indicates that a further demand would be futile or the debtor's response does not require rebuttal, the...
NASA Astrophysics Data System (ADS)
Rajagopalan, K.; Chinnayakanahalli, K.; Adam, J. C.; Malek, K.; Nelson, R.; Stockle, C.; Brady, M.; Dinesh, S.; Barber, M. E.; Yorgey, G.; Kruger, C.
2012-12-01
The objective of this work is to assess the impacts of climate change and socio economics on agriculture in the Columbia River basin (CRB) in the Pacific Northwest region of the U.S. and a portion of Southwestern Canada. The water resources of the CRB are managed to satisfy multiple objectives including agricultural withdrawal, which is the largest consumptive user of CRB water with 14,000 square kilometers of irrigated area. Agriculture is an important component of the region's economy, with an annual value over 5 billion in Washington State alone. Therefore, the region is relevant for applying a modeling framework that can aid agriculture decision making in the context of a changing climate. To do this, we created an integrated biophysical and socio-economic regional modeling framework that includes human and natural systems. The modeling framework captures the interactions between climate, hydrology, crop growth dynamics, water management and socio economics. The biophysical framework includes a coupled macro-scale physically-based hydrology model (the Variable Infiltration Capacity, VIC model), and crop growth model (CropSyst), as well as a reservoir operations simulation model. Water rights data and instream flow target requirements are also incorporated in the model to simulate the process of curtailment during water shortage. The economics model informs the biophysical model of the short term agricultural producer response to water shortage as well as the long term agricultural producer response to domestic growth and international trade in terms of an altered cropping pattern. The modeling framework was applied over the CRB for the historical period 1976-2006 and compared to a future 30-year period centered on the 2030s. Impacts of climate change on irrigation water availability, crop irrigation demand, frequency of curtailment, and crop yields are quantified and presented. Sensitivity associated with estimates of water availability, irrigation demand, crop yields, unmet demand and available instream flows due to climate inputs, hydrology and crop model parameterization, water management assumptions, model integration assumptions, as well as multiple socio economic alternatives are also presented. Compared to historical conditions, for the 2030s time period, our results show an average additional irrigation water demand requirement of 370 million cubic meters in the CRB, an increased frequency of curtailment and a revenue impact between 70 and $150 million resulting from adverse crop yield impacts due to curtailment in the state of Washington. The impacts vary spatially and some of the CRB tributary watersheds are impacted more than others, e.g., unmet demand in the Yakima River basin is expected to increase by 50%. Increased irrigation demand, coupled with decreased seasonal supply poses difficult water resources management questions in the region.
Cui, Borui; Gao, Dian-ce; Xiao, Fu; ...
2016-12-23
This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning capital cost associated with storage capacity as well as incentives from both fast DR and PLM. Inmore » the method, the active CTES operates under a fast DR control strategy during DR events while under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Cui, Borui; Gao, Dian-ce; Xiao, Fu
This article provides a method in comprehensive evaluation of cost-saving potential of active cool thermal energy storage (CTES) integrated with HVAC system for demand management in non-residential building. The active storage is beneficial by shifting peak demand for peak load management (PLM) as well as providing longer duration and larger capacity of demand response (DR). In this research, a model-based optimal design method using genetic algorithm is developed to optimize the capacity of active CTES aiming for maximizing the life-cycle cost saving concerning capital cost associated with storage capacity as well as incentives from both fast DR and PLM. Inmore » the method, the active CTES operates under a fast DR control strategy during DR events while under the storage-priority operation mode to shift peak demand during normal days. The optimal storage capacities, maximum annual net cost saving and corresponding power reduction set-points during DR event are obtained by using the proposed optimal design method. Lastly, this research provides guidance in comprehensive evaluation of cost-saving potential of CTES integrated with HVAC system for building demand management including both fast DR and PLM.« less
Opportunities for Automated Demand Response in California Wastewater Treatment Facilities
DOE Office of Scientific and Technical Information (OSTI.GOV)
Aghajanzadeh, Arian; Wray, Craig; McKane, Aimee
Previous research over a period of six years has identified wastewater treatment facilities as good candidates for demand response (DR), automated demand response (Auto-DR), and Energy Efficiency (EE) measures. This report summarizes that work, including the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy used and demand, as well as details of the wastewater treatment process. It also discusses control systems and automated demand response opportunities. Furthermore, this report summarizes the DR potential of three wastewater treatment facilities. In particular, Lawrence Berkeley National Laboratory (LBNL) has collected data at these facilities from control systems, submetered processmore » equipment, utility electricity demand records, and governmental weather stations. The collected data were then used to generate a summary of wastewater power demand, factors affecting that demand, and demand response capabilities. These case studies show that facilities that have implemented energy efficiency measures and that have centralized control systems are well suited to shed or shift electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. In summary, municipal wastewater treatment energy demand in California is large, and energy-intensive equipment offers significant potential for automated demand response. In particular, large load reductions were achieved by targeting effluent pumps and centrifuges. One of the limiting factors to implementing demand response is the reaction of effluent turbidity to reduced aeration at an earlier stage of the process. Another limiting factor is that cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities, limit a facility’s potential to participate in other DR activities.« less
ERIC Educational Resources Information Center
Vargas, Joel
2014-01-01
In order to prepare the large number of postsecondary-educated youth our economy demands, high schools and higher education must break through the boundaries that have traditionally separated them and assume joint responsibility for student success. This brief describes an unusual school district partnership with colleges that has achieved…
Firing Costs and Flexibility: Evidence from Firms’ Employment Responses to Shocks in India*
Adhvaryu, Achyuta; Chari, A. V.; Sharma, Siddharth
2013-01-01
A key prediction of dynamic labor demand models is that firing restrictions attenuate firms’ employment responses to economic fluctuations. We provide the first direct test of this prediction using data from India. We exploit the fact that rainfall fluctuations, through their effects on agricultural productivity, generate variation in local demand within districts over time. Consistent with the theory, we find that industrial employment is more sensitive to shocks where labor regulation is less restrictive. Our results are robust to controlling for endogenous firm placement and vary across factory size in a pattern consistent with institutional features of Indian labor law. PMID:24357882
Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load.
Holper, L; Van Brussel, L D; Schmidt, L; Schulthess, S; Burke, C J; Louie, K; Seifritz, E; Tobler, P N
2017-01-01
Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain's capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations.
NASA Astrophysics Data System (ADS)
Koutiva, Ifigeneia; Makropoulos, Christos
2015-04-01
The urban water system's sustainable evolution requires tools that can analyse and simulate the complete cycle including both physical and cultural environments. One of the main challenges, in this regard, is the design and development of tools that are able to simulate the society's water demand behaviour and the way policy measures affect it. The effects of these policy measures are a function of personal opinions that subsequently lead to the formation of people's attitudes. These attitudes will eventually form behaviours. This work presents the design of an ABM tool for addressing the social dimension of the urban water system. The created tool, called Urban Water Agents' Behaviour (UWAB) model, was implemented, using the NetLogo agent programming language. The main aim of the UWAB model is to capture the effects of policies and environmental pressures to water conservation behaviour of urban households. The model consists of agents representing urban households that are linked to each other creating a social network that influences the water conservation behaviour of its members. Household agents are influenced as well by policies and environmental pressures, such as drought. The UWAB model simulates behaviour resulting in the evolution of water conservation within an urban population. The final outcome of the model is the evolution of the distribution of different conservation levels (no, low, high) to the selected urban population. In addition, UWAB is implemented in combination with an existing urban water management simulation tool, the Urban Water Optioneering Tool (UWOT) in order to create a modelling platform aiming to facilitate an adaptive approach of water resources management. For the purposes of this proposed modelling platform, UWOT is used in a twofold manner: (1) to simulate domestic water demand evolution and (2) to simulate the response of the water system to the domestic water demand evolution. The main advantage of the UWAB - UWOT model integration is that it allows the investigation of the effects of different water demand management strategies to an urban population's water demand behaviour and ultimately the effects of these policies to the volume of domestic water demand and the water resources system. The proposed modelling platform is optimised to simulate the effects of water policies during the Athens drought period of 1988-1994. The calibrated modelling platform is then applied to evaluate scenarios of water supply, water demand and water demand management strategies.
12 CFR 602.23 - Responses to demands served on FCA employees.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Responses to demands served on FCA employees. 602.23 Section 602.23 Banks and Banking FARM CREDIT ADMINISTRATION ADMINISTRATIVE PROVISIONS RELEASING....23 Responses to demands served on FCA employees. (a) An employee served with a demand or a subpoena...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Behboodi, Sahand; Chassin, David P.; Djilali, Ned
This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less
Behboodi, Sahand; Chassin, David P.; Djilali, Ned; ...
2016-12-23
This study describes a new approach for solving the multi-area electricity resource allocation problem when considering both intermittent renewables and demand response. The method determines the hourly inter-area export/import set that maximizes the interconnection (global) surplus satisfying transmission, generation and load constraints. The optimal inter-area transfer set effectively makes the electricity price uniform over the interconnection apart from constrained areas, which overall increases the consumer surplus more than it decreases the producer surplus. The method is computationally efficient and suitable for use in simulations that depend on optimal scheduling models. The method is demonstrated on a system that represents Northmore » America Western Interconnection for the planning year of 2024. Simulation results indicate that effective use of interties reduces the system operation cost substantially. Excluding demand response, both the unconstrained and the constrained scheduling solutions decrease the global production cost (and equivalently increase the global economic surplus) by 12.30B and 10.67B per year, respectively, when compared to the standalone case in which each control area relies only on its local supply resources. This cost saving is equal to 25% and 22% of the annual production cost. Including 5% demand response, the constrained solution decreases the annual production cost by 10.70B, while increases the annual surplus by 9.32B in comparison to the standalone case.« less
Guided Comprehension in the Primary Grades.
ERIC Educational Resources Information Center
McLaughlin, Maureen
Intended as a response to recent developments in reading research and a demand by primary-grade teachers for a comprehension-based instructional framework, this book adapts the Guided Comprehension Model introduced in the author/educator's book "Guided Comprehension: A Teaching Model for Grades 3-8." According to the book, the Guided…
Space-time modeling of timber prices
Mo Zhou; Joseph Buongriorno
2006-01-01
A space-time econometric model was developed for pine sawtimber timber prices of 21 geographically contiguous regions in the southern United States. The correlations between prices in neighboring regions helped predict future prices. The impulse response analysis showed that although southern pine sawtimber markets were not globally integrated, local supply and demand...
Joint Real-Time Energy and Demand-Response Management using a Hybrid Coalitional-Noncooperative Game
DOE Office of Scientific and Technical Information (OSTI.GOV)
He, Fulin; Gu, Yi; Hao, Jun
In order to model the interactions among utility companies, building demands and renewable energy generators (REGs), a hybrid coalitional-noncooperative game framework has been proposed. We formulate a dynamic non-cooperative game to study the energy dispatch within multiple utility companies, while we take a coalitional perspective on REGs and buildings demands through a hedonic coalition formation game approach. In this case, building demands request different power supply from REGs, then the building demands can be organized into an ultimate coalition structure through a distributed hedonic shift algorithm. At the same time, utility companies can also obtain a stable power generation profile.more » In addition, the interactive progress among the utility companies and building demands which cannot be supplied by REGs is implemented by distributed game theoretic algorithms. Numerical results illustrate that the proposed hybrid coalitional-noncooperative game scheme reduces the cost of both building demands and utility companies compared with the initial scene.« less
Co-optimization of Energy and Demand-Side Reserves in Day-Ahead Electricity Markets
NASA Astrophysics Data System (ADS)
Surender Reddy, S.; Abhyankar, A. R.; Bijwe, P. R.
2015-04-01
This paper presents a new multi-objective day-ahead market clearing (DAMC) mechanism with demand-side reserves/demand response (DR) offers, considering realistic voltage-dependent load modeling. The paper proposes objectives such as social welfare maximization (SWM) including demand-side reserves, and load served error (LSE) minimization. In this paper, energy and demand-side reserves are cleared simultaneously through co-optimization process. The paper clearly brings out the unsuitability of conventional SWM for DAMC in the presence of voltage-dependent loads, due to reduction of load served (LS). Under such circumstances multi-objective DAMC with DR offers is essential. Multi-objective Strength Pareto Evolutionary Algorithm 2+ (SPEA 2+) has been used to solve the optimization problem. The effectiveness of the proposed scheme is confirmed with results obtained from IEEE 30 bus system.
NASA Astrophysics Data System (ADS)
Ribeiro Neto, A.; Scott, C. A.; Lima, E. A.; Montenegro, S. M. G. L.; Cirilo, J. A.
2014-09-01
Water availability for a range of human uses will increasingly be affected by climate change, especially in the arid and semiarid tropics. The main objective of this study is to evaluate the infrastructure sufficiency in meeting water demand under climate-induced socio-hydrological transition in the Capibaribe River basin (CRB). The basin has experienced spatial and sectoral (agriculture-to-urban) reconfiguration of water demands. Human settlements that were once dispersed, relying on intermittent sources of surface water, are now larger and more spatially concentrated, which increases water-scarcity effects. Based on the application of linked hydrologic and water-resources models using precipitation and temperature projections of the IPCC SRES (Special Report: Emissions Scenarios) A1B scenario, a reduction in rainfall of 26.0% translated to streamflow reduction of 60.0%. We used simulations from four members of the HadCM3 (UK Met Office Hadley Centre) perturbed physics ensemble, in which a single model structure is used and perturbations are introduced to the physical parameterization schemes in the model (Chou et al., 2012). We considered that the change of the water availability in the basin in the future scenarios must drive the water management and the development of adaptation strategies that will manage the water demand. Several adaptive responses are considered, including water-loss reductions, wastewater collection and reuse, and rainwater collection cisterns, which together have potential to reduce future water demand by 23.0%. This study demonstrates the vulnerabilities of the infrastructure system during socio-hydrological transition in response to hydroclimatic and demand variabilities in the CRB and also indicates the differential spatial impacts and vulnerability of multiple uses of water to changes over time. The simulations showed that the measures proposed and the water from interbasin transfer project of the São Francisco River had a positive impact over the water supply in the basin, mainly for human use. Industry and irrigation will suffer impact unless other measures are implemented for demand control.
Winter weather demand considerations.
DOT National Transportation Integrated Search
2015-04-01
Winter weather has varied effects on travel behavior. Using 418 survey responses from the Northern Virginia : commuting area of Washington, D.C. and binary logit models, this study examines travel related changes under : different types of winter wea...
Social and Structural Patterns of Drought-Related Water Conservation and Rebound
NASA Astrophysics Data System (ADS)
Gonzales, Patricia; Ajami, Newsha
2017-12-01
Water use practices and conservation are the result of complex sociotechnical interactions of political, economic, hydroclimatic, and social factors. While the drivers of water demand have been extensively studied, they have traditionally been applied to models that assume stationary relationships between these various factors, and usually do not account for potential societal changes in response to increased scarcity awareness. For example, following a period of sustained low demand such as during a drought, communities often increase water use during a hydrologically wet period, a phenomenon known as "rebounding" water use. Previous experiences show the extent of this rebound is not a straightforward function of policy and efficiency improvements, but may also reflect short-term or long-lasting change in community behavior, which are not easily captured by models that assume stationarity. In this work, we develop a system dynamics model to represent water demand as a function of both structural and social factors. We apply this model to the analysis of three diverse water utilities in the San Francisco Bay Area between 1980 and 2017, identifying drought response trends and drivers over time. Our model is consistent with empirical patterns and historical context of water use in California, and provides important insights on the rebound phenomenon that can be extended to other locations. This comparative assessment indicates that policies, public outreach, and better data availability have played a key role in raising public awareness of water scarcity, especially with the raise of the internet era in recent years.
Weng, Shuo-Chun; Chen, Yu-Chi; Chen, Ching-Yu; Cheng, Yuan-Yang; Tang, Yih-Jing; Yang, Shu-Hui; Lin, Jwu-Rong
2017-04-01
The effect of health depreciation in older people on medical care demand is not well understood. We tried to assess the medical care demand with length of hospitalization and their impact on profits as a result of health depreciation. All participants who underwent comprehensive geriatric assessment were from a prospective cohort study at a tertiary hospital. A total of 1191 cases between September 2008 to October 2012 were investigated. Three sets of qualitative response models were constructed to estimate the impact of older adults' health depreciation on multidisciplinary geriatric care services. Furthermore, we analyzed the factors affecting the composite end-point of rehospitalization within 14 days, re-admission to the emergency department within 3 days and patient death. Greater health depreciation in elderly patients was positively correlated with greater medical care demand. Three major components were defined as health depreciation: elderly adaptation function, geriatric syndromes and multiple chronic diseases. On admission, the better the basic living functions, the shorter the length of hospitalization (coefficient = -0.35, P < 0.001 in Poisson regression; coefficient = -0.33, P < 0.001 in order choice profit model; coefficient = -0.29, P < 0.001 in binary choice profit model). The major determinants for poor outcome were male sex, middle old age and length of hospitalization. However, factors that correlated with relatively good outcome were functional improvement after medical care services and level of disease education. An optimal allocation system for selection of cases into multidisciplinary geriatric care is required because of limited resources. Outcomes will improve with health promotion and preventive care services. Geriatr Gerontol Int 2017; 17: 645-652. © 2016 Japan Geriatrics Society.
Lam, Sean Shao Wei; Zhang, Ji; Zhang, Zhong Cheng; Oh, Hong Choon; Overton, Jerry; Ng, Yih Yng; Ong, Marcus Eng Hock
2015-02-01
Dynamically reassigning ambulance deployment locations throughout a day to balance ambulance availability and demands can be effective in reducing response times. The objectives of this study were to model dynamic ambulance allocation plans in Singapore based on the system status management (SSM) strategy and to evaluate the dynamic deployment plans using a discrete event simulation (DES) model. The geographical information system-based analysis and mathematical programming were used to develop the dynamic ambulance deployment plans for SSM based on ambulance calls data from January 1, 2011, to June 30, 2011. A DES model that incorporated these plans was used to compare the performance of the dynamic SSM strategy against static reallocation policies under various demands and travel time uncertainties. When the deployment plans based on the SSM strategy were followed strictly, the DES model showed that the geographical information system-based plans resulted in approximately 13-second reduction in the median response times compared to the static reallocation policy, whereas the mathematical programming-based plans resulted in approximately a 44-second reduction. The response times and coverage performances were still better than the static policy when reallocations happened for only 60% of all the recommended moves. Dynamically reassigning ambulance deployment locations based on the SSM strategy can result in superior response times and coverage performance compared to static reallocation policies even when the dynamic plans were not followed strictly. Copyright © 2014 Elsevier Inc. All rights reserved.
Strategies for Improved Hospital Response to Mass Casualty Incidents.
TariVerdi, Mersedeh; Miller-Hooks, Elise; Kirsch, Thomas
2018-03-19
Mass casualty incidents are a concern in many urban areas. A community's ability to cope with such events depends on the capacities and capabilities of its hospitals for handling a sudden surge in demand of patients with resource-intensive and specialized medical needs. This paper uses a whole-hospital simulation model to replicate medical staff, resources, and space for the purpose of investigating hospital responsiveness to mass casualty incidents. It provides details of probable demand patterns of different mass casualty incident types in terms of patient categories and arrival patterns, and accounts for related transient system behavior over the response period. Using the layout of a typical urban hospital, it investigates a hospital's capacity and capability to handle mass casualty incidents of various sizes with various characteristics, and assesses the effectiveness of designed demand management and capacity-expansion strategies. Average performance improvements gained through capacity-expansion strategies are quantified and best response actions are identified. Capacity-expansion strategies were found to have superadditive benefits when combined. In fact, an acceptable service level could be achieved by implementing only 2 to 3 of the 9 studied enhancement strategies. (Disaster Med Public Health Preparedness. 2018;page 1 of 13).
NASA Astrophysics Data System (ADS)
Meng, M.; Macknick, J.; Tidwell, V. C.; Zagona, E. A.; Magee, T. M.; Bennett, K.; Middleton, R. S.
2017-12-01
The U.S. electricity sector depends on large amounts of water for hydropower generation and cooling thermoelectric power plants. Variability in water quantity and temperature due to climate change could reduce the performance and reliability of individual power plants and of the electric grid as a system. While studies have modeled water usage in power systems planning, few have linked grid operations with physical water constraints or with climate-induced changes in water resources to capture the role of the energy-water nexus in power systems flexibility and adequacy. In addition, many hydrologic and hydropower models have a limited representation of power sector water demands and grid interaction opportunities of demand response and ancillary services. A multi-model framework was developed to integrate and harmonize electricity, water, and climate models, allowing for high-resolution simulation of the spatial, temporal, and physical dynamics of these interacting systems. The San Juan River basin in the Southwestern U.S., which contains thermoelectric power plants, hydropower facilities, and multiple non-energy water demands, was chosen as a case study. Downscaled data from three global climate models and predicted regional water demand changes were implemented in the simulations. The Variable Infiltration Capacity hydrologic model was used to project inflows, ambient air temperature, and humidity in the San Juan River Basin. Resulting river operations, water deliveries, water shortage sharing agreements, new water demands, and hydroelectricity generation at the basin-scale were estimated with RiverWare. The impacts of water availability and temperature on electric grid dispatch, curtailment, cooling water usage, and electricity generation cost were modeled in PLEXOS. Lack of water availability resulting from climate, new water demands, and shortage sharing agreements will require thermoelectric generators to drastically decrease power production, as much as 50% during intensifying drought scenarios, which can have broader electricity sector system implications. Results relevant to stakeholder and power provider interests highlight the vulnerabilities in grid operations driven by water shortage agreements and changes in the climate.
Systems and methods for energy cost optimization in a building system
Turney, Robert D.; Wenzel, Michael J.
2016-09-06
Methods and systems to minimize energy cost in response to time-varying energy prices are presented for a variety of different pricing scenarios. A cascaded model predictive control system is disclosed comprising an inner controller and an outer controller. The inner controller controls power use using a derivative of a temperature setpoint and the outer controller controls temperature via a power setpoint or power deferral. An optimization procedure is used to minimize a cost function within a time horizon subject to temperature constraints, equality constraints, and demand charge constraints. Equality constraints are formulated using system model information and system state information whereas demand charge constraints are formulated using system state information and pricing information. A masking procedure is used to invalidate demand charge constraints for inactive pricing periods including peak, partial-peak, off-peak, critical-peak, and real-time.
Epstein, Tamir; Xu, Liping; Gillies, Robert J; Gatenby, Robert A
2014-01-01
Cancer cells, and a variety of normal cells, exhibit aerobic glycolysis, high rates of glucose fermentation in the presence of normal oxygen concentrations, also known as the Warburg effect. This metabolism is considered abnormal because it violates the standard model of cellular energy production that assumes glucose metabolism is predominantly governed by oxygen concentrations and, therefore, fermentative glycolysis is an emergency back-up for periods of hypoxia. Though several hypotheses have been proposed for the origin of aerobic glycolysis, its biological basis in cancer and normal cells is still not well understood. We examined changes in glucose metabolism following perturbations in membrane activity in different normal and tumor cell lines and found that inhibition or activation of pumps on the cell membrane led to reduction or increase in glycolysis, respectively, while oxidative phosphorylation remained unchanged. Computational simulations demonstrated that these findings are consistent with a new model of normal physiological cellular metabolism in which efficient mitochondrial oxidative phosphorylation supplies chronic energy demand primarily for macromolecule synthesis and glycolysis is necessary to supply rapid energy demands primarily to support membrane pumps. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. The predictions were confirmed experimentally. Our results show that glycolytic metabolism serves a critical physiological function under normoxic conditions by responding to rapid energetic demand, mainly from membrane transport activities, even in the presence of oxygen. This supports a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Cells use efficient but slow-responding aerobic metabolism to meet baseline, steady energy demand and glycolytic metabolism, which is inefficient but can rapidly increase adenosine triphosphate (ATP) production, to meet short-timescale energy demands, mainly from membrane transport activities. In this model, the origin of the Warburg effect in cancer cells and aerobic glycolysis in general represents a normal physiological function due to enhanced energy demand for membrane transporters activity required for cell division, growth, and migration.
Bus operators' responses to job strain: An experimental test of the job demand-control model.
Cendales-Ayala, Boris; Useche, Sergio Alejandro; Gómez-Ortiz, Viviola; Bocarejo, Juan Pablo
2017-10-01
The research aim was to test the Job Demand-Control (JDC) Model demands × Control interaction (or buffering) hypothesis in a simulated bus driving experiment. The buffering hypothesis was tested using a 2 (low and high demands) × 2 (low and high decision latitude) design with repeated measures on the second factor. A sample of 80 bus operators were randomly assigned to the low (n = 40) and high demands (n = 40) conditions. Demands were manipulated by increasing or reducing the number of stops to pick up passengers, and decision latitude by imposing or removing restrictions on the Rapid Transit Bus (BRT) operators' pace of work. Outcome variables include physiological markers (heart rate [HR], heart rate variability [HRV], breathing rate [BR], electromyography [EMG], and skin conductance [SC]), objective driving performance and self-report measurements of psychological wellbeing (psychological distress, interest/enjoyment [I/E], perceived competence, effort/importance [E/I], and pressure/tension [P/T]). It was found that job decision latitude moderates the effect of job demands on both physiological arousal (BR: F(1, 74) = 4.680, p = .034, SC: F(1, 75) = 6.769, p = .011, and EMG: F(1, 75) = 6.550, p = .013) and psychological well-being (P/T: F(1, 75) = 4.289, p = .042 and I/E: F(1, 74) = 4.548, p = .036). Consistently with the JDC model buffering hypothesis, the experimental findings suggest that increasing job decision latitude can moderate the negative effect of job demands on different psychophysiological outcomes. This finding is useful for designing organizational and clinical interventions in an occupational group at high risk of work stress-related disease. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Demand for pneumococcal vaccination under subsidy program for the elderly in Japan
2012-01-01
Background Vaccination programs often organize subsidies and public relations in order to obtain high uptake rates and coverage. However, effects of subsidies and public relations have not been studied well in the literature. In this study, the demand function of pneumococcal vaccination among the elderly in Japan is estimated, incorporating effects of public relations and subsidy. Methods Using a data from a questionnaire survey sent to municipalities, the varying and constant elasticity models were applied to estimate the demand function. The response variable is the uptake rate. Explanatory variables are: subsidy supported shot price, operating years of the program, target population size for vaccination, shot location intensity, income and various public relations tools. The best model is selected by c-AIC, and varying and constant price elasticities are calculated from estimation results. Results The vaccine uptake rate and the shot price have a negative relation. From the results of varying price elasticity, the demand for vaccination is elastic at municipalities with a shot price higher than 3,708 JPY (35.7 USD). Effects of public relations on the uptake rate are not found. Conclusions It can be suggested that municipalities with a shot price higher than 3,708 JPY (35.7 USD) could subsidize more and reduce price to increase the demand for vaccination. Effects of public relations are not confirmed in this study, probably due to measurement errors of variables used for public relations, and studies at micro level exploring individual’s response to public relations would be required. PMID:22970727
Economic demand and essential value.
Hursh, Steven R; Silberberg, Alan
2008-01-01
The strength of a rat's eating reflex correlates with hunger level when strength is measured by the response frequency that precedes eating (B. F. Skinner, 1932a, 1932b). On the basis of this finding, Skinner argued response frequency could index reflex strength. Subsequent work documented difficulties with this notion because responding was affected not only by the strengthening properties of the reinforcer but also by the rate-shaping effects of the schedule. This article obviates this problem by measuring strength via methods from behavioral economics. This approach uses demand curves to map how reinforcer consumption changes with changes in the "price" different ratio schedules impose. An exponential equation is used to model these demand curves. The value of this exponential's rate constant is used to scale the strength or essential value of a reinforcer, independent of the scalar dimensions of the reinforcer. Essential value determines the consumption level to be expected at particular prices and the response level that will occur to support that consumption. This approach permits comparing reinforcers that differ in kind, contributing toward the goal of scaling reinforcer value. (c) 2008 APA, all rights reserved
75 FR 15362 - Demand Response Compensation in Organized Wholesale Energy Markets
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-29
... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission 18 CFR Part 35 [Docket No. RM10-17-000... FERC ] 61,213, PJM Interconnection, LLC, Docket No. EL09-68-000 Notice of Proposed Rulemaking Table of... Emergency Demand Response; NYISO's Emergency Demand Response Program; PJM's Emergency Load Response; and ISO...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zhu, Xiangqi; Wang, Jiyu; Mulcahy, David
This paper presents a voltage-load sensitivity matrix (VLSM) based voltage control method to deploy demand response resources for controlling voltage in high solar penetration distribution feeders. The IEEE 123-bus system in OpenDSS is used for testing the performance of the preliminary VLSM-based voltage control approach. A load disaggregation process is applied to disaggregate the total load profile at the feeder head to each load nodes along the feeder so that loads are modeled at residential house level. Measured solar generation profiles are used in the simulation to model the impact of solar power on distribution feeder voltage profiles. Different casemore » studies involving various PV penetration levels and installation locations have been performed. Simulation results show that the VLSM algorithm performance meets the voltage control requirements and is an effective voltage control strategy.« less
More physicians: improved availability or induced demand?
Carlsen, F; Grytten, J
1998-09-01
A number of empirical studies have shown that there is a negative association between population:physician ratio and utilization of medical services. However, it is not clear whether this relationship reflects supplier-inducement, the effect of lower prices on patient demand, a supply response to variation in health status, or improved availability. In Norway, patient fees and state reimbursement fees are set centrally. Therefore, the correlation between utilization and population:physician ratio either reflects supplier-inducement, a supply response or an availability effect. We applied a theoretical model which distinguished between an inducement and an availability effect. The model was implemented on a cross-sectional data set which contained information about patient visits and laboratory tests for all fee-for-service primary care physicians in Norway. Since population:physician ratio is potentially endogenous, an instrumental variable approach is used. We found no evidence for inducement either for number of visits or for provision of laboratory services.
Individual Differences in Response to Automation: The Five Factor Model of Personality
ERIC Educational Resources Information Center
Szalma, James L.; Taylor, Grant S.
2011-01-01
This study examined the relationship of operator personality (Five Factor Model) and characteristics of the task and of adaptive automation (reliability and adaptiveness--whether the automation was well-matched to changes in task demand) to operator performance, workload, stress, and coping. This represents the first investigation of how the Five…
ERIC Educational Resources Information Center
Blau, Judith R.; And Others
Traditional theoretical explanations for the rate of expansion of educational institutions have included the "organizational ecology" model of new foundings as a function of population density, the "institutional theory" argument that foundings are responsive to societal/consumer demand, and theories of political economy which describe foundings…
A Sustainable Model for Training Teachers to Use Pivotal Response Training
ERIC Educational Resources Information Center
Suhrheinrich, Jessica
2015-01-01
The increase in the rate of autism diagnoses has created a growing demand for teachers who are trained to use effective interventions. The train-the-trainer model, which involves training supervisors to train others, may be ideal for providing cost-effective training and ongoing support to teachers. Although research supports interventions, such…
NASA Astrophysics Data System (ADS)
Yilmaz, Zeynep
Typically, the vertical component of the ground motion is not considered explicitly in seismic design of bridges, but in some cases the vertical component can have a significant effect on the structural response. The key question of when the vertical component should be incorporated in design is answered by the probabilistic seismic hazard assessment study incorporating the probabilistic seismic demand models and ground motion models. Nonlinear simulation models with varying configurations of an existing bridge in California were considered in the analytical study. The simulation models were subjected to the set of selected ground motions in two stages: at first, only horizontal components of the motion were applied; while in the second stage the structures were subjected to both horizontal and vertical components applied simultaneously and the ground motions that produced the largest adverse effects on the bridge system were identified. Moment demand in the mid-span and at the support of the longitudinal girder and the axial force demand in the column are found to be significantly affected by the vertical excitations. These response parameters can be modeled using simple ground motion parameters such as horizontal spectral acceleration and vertical spectral acceleration within 5% to 30% error margin depending on the type of the parameter and the period of the structure. For a complete hazard assessment, both of these ground motion parameters explaining the structural behavior should also be modeled. For the horizontal spectral acceleration, Abrahamson and Silva (2008) model was used within many available standard model. A new NGA vertical ground motion model consistent with the horizontal model was constructed. These models are combined in a vector probabilistic seismic hazard analyses. Series of hazard curves developed and presented for different locations in Bay Area for soil site conditions to provide a roadmap for the prediction of these features for future earthquakes. Findings from this study will contribute to the development of revised guidelines to address vertical ground motion effects, particularly in the near fault regions, in the seismic design of highway bridges.
Iguchi, Aya
2016-01-01
Objectives The purpose of this study was to investigate the job demands and job resources of public health nurses based on the Job Demands-Resources (JD-R) model, and to build a model that can estimate turnover intention based on job demands and job resources.Method By adding 12 items to the existing questionnaire, the author created a questionnaire consisting of 10 factors and 167 items, and used statistical analysis to examine job demands and job resources in relation to turnover intention.Results Out of 2,668 questionnaires sent, 1993 (72.5%) were returned. Considering sex-based differences in occupational stress, I analyzed women's answers in 1766 (66.2%) mails among the 1798 valid responses. The average age of respondents was 41.0±9.8 years, and the mean service duration was 17.0±10.0 years. For public health nurses, there was a turnover intention of 9.2%. The "job demands" section consisted of 29 items and 10 factors, while the "job resources" section consisted of 54 items and 22 factors. The result of examining the structure of job demands and job resources, leading to turnover intention was supported by the JD-R model. Turnover intention was strong and the Mental Component Summary (MCS) is low in those who had many job demands and few job resources (experiencing 'burn-out'). Enhancement of work engagement and turnover intention was weak in those who had many job resources. This explained approximately 60% of the dispersion to "burn-out", and approximately 40% to "work engagement", with four factors: work suitability, work significance, positive work self-balance, and growth opportunity of job resources.Conclusion This study revealed that turnover intention is strong in those who are burned out because of many job demands. Enhancement of work engagement and turnover intention is weak in those with many job resources. This suggests that suitable staffing and organized efforts to raise awareness of job significance are effective in reducing turnover intention.
Mass casualty events: blood transfusion emergency preparedness across the continuum of care.
Doughty, Heidi; Glasgow, Simon; Kristoffersen, Einar
2016-04-01
Transfusion support is a key enabler to the response to mass casualty events (MCEs). Transfusion demand and capability planning should be an integrated part of the medical planning process for emergency system preparedness. Historical reviews have recently supported demand planning for MCEs and mass gatherings; however, computer modeling offers greater insights for resource management. The challenge remains balancing demand and supply especially the demand for universal components such as group O red blood cells. The current prehospital and hospital capability has benefited from investment in the management of massive hemorrhage. The management of massive hemorrhage should address both hemorrhage control and hemostatic support. Labile blood components cannot be stockpiled and a large surge in demand is a challenge for transfusion providers. The use of blood components may need to be triaged and demand managed. Two contrasting models of transfusion planning for MCEs are described. Both illustrate an integrated approach to preparedness where blood transfusion services work closely with health care providers and the donor community. Preparedness includes appropriate stock management and resupply from other centers. However, the introduction of alternative transfusion products, transfusion triage, and the greater use of an emergency donor panel to provide whole blood may permit greater resilience. © 2016 AABB.
Burnout in medical residents: a study based on the job demands-resources model.
Zis, Panagiotis; Anagnostopoulos, Fotios; Sykioti, Panagiota
2014-01-01
Burnout is a prolonged response to chronic emotional and interpersonal stressors on the job. The purpose of our cross-sectional study was to estimate the burnout rates among medical residents in the largest Greek hospital in 2012 and identify factors associated with it, based on the job demands-resources model (JD-R). Job demands were examined via a 17-item questionnaire assessing 4 characteristics (emotional demands, intellectual demands, workload, and home-work demands' interface) and job resources were measured via a 14-item questionnaire assessing 4 characteristics (autonomy, opportunities for professional development, support from colleagues, and supervisor's support). The Maslach Burnout Inventory (MBI) was used to measure burnout. Of the 290 eligible residents, 90.7% responded. In total 14.4% of the residents were found to experience burnout. Multiple logistic regression analysis revealed that each increased point in the JD-R questionnaire score regarding home-work interface was associated with an increase in the odds of burnout by 25.5%. Conversely, each increased point for autonomy, opportunities in professional development, and each extra resident per specialist were associated with a decrease in the odds of burnout by 37.1%, 39.4%, and 59.0%, respectively. Burnout among medical residents is associated with home-work interface, autonomy, professional development, and resident to specialist ratio.
A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, Lindsay; Zéphyr, Luckny; Cardell, Judith B.
The evolution of the power system to the reliable, efficient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of renewable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distribution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for cooptimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this framework, microgrids encompass consumers, distributed renewables and storage. The energy managementmore » system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the development of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic optimization, including decomposition and stochastic dual dynamic programming.« less
A Vision for Co-optimized T&D System Interaction with Renewables and Demand Response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Anderson, C. Lindsay; Zéphyr, Luckny; Liu, Jialin
The evolution of the power system to the reliable, effi- cient and sustainable system of the future will involve development of both demand- and supply-side technology and operations. The use of demand response to counterbalance the intermittency of re- newable generation brings the consumer into the spotlight. Though individual consumers are interconnected at the low-voltage distri- bution system, these resources are typically modeled as variables at the transmission network level. In this paper, a vision for co- optimized interaction of distribution systems, or microgrids, with the high-voltage transmission system is described. In this frame- work, microgrids encompass consumers, distributed renewablesmore » and storage. The energy management system of the microgrid can also sell (buy) excess (necessary) energy from the transmission system. Preliminary work explores price mechanisms to manage the microgrid and its interactions with the transmission system. Wholesale market operations are addressed through the devel- opment of scalable stochastic optimization methods that provide the ability to co-optimize interactions between the transmission and distribution systems. Modeling challenges of the co-optimization are addressed via solution methods for large-scale stochastic op- timization, including decomposition and stochastic dual dynamic programming.« less
NASA Astrophysics Data System (ADS)
Dong, Dai; Li, Xiaoning
2015-03-01
High-pressure solenoid valve with high flow rate and high speed is a key component in an underwater driving system. However, traditional single spool pilot operated valve cannot meet the demands of both high flow rate and high speed simultaneously. A new structure for a high pressure solenoid valve is needed to meet the demand of the underwater driving system. A novel parallel-spool pilot operated high-pressure solenoid valve is proposed to overcome the drawback of the current single spool design. Mathematical models of the opening process and flow rate of the valve are established. Opening response time of the valve is subdivided into 4 parts to analyze the properties of the opening response. Corresponding formulas to solve 4 parts of the response time are derived. Key factors that influence the opening response time are analyzed. According to the mathematical model of the valve, a simulation of the opening process is carried out by MATLAB. Parameters are chosen based on theoretical analysis to design the test prototype of the new type of valve. Opening response time of the designed valve is tested by verifying response of the current in the coil and displacement of the main valve spool. The experimental results are in agreement with the simulated results, therefore the validity of the theoretical analysis is verified. Experimental opening response time of the valve is 48.3 ms at working pressure of 10 MPa. The flow capacity test shows that the largest effective area is 126 mm2 and the largest air flow rate is 2320 L/s. According to the result of the load driving test, the valve can meet the demands of the driving system. The proposed valve with parallel spools provides a new method for the design of a high-pressure valve with fast response and large flow rate.
Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models
NASA Astrophysics Data System (ADS)
Sun, Yan; Peng, Shushi; Goll, Daniel S.; Ciais, Philippe; Guenet, Bertrand; Guimberteau, Matthieu; Hinsinger, Philippe; Janssens, Ivan A.; Peñuelas, Josep; Piao, Shilong; Poulter, Benjamin; Violette, Aurélie; Yang, Xiaojuan; Yin, Yi; Zeng, Hui
2017-07-01
Most of the Earth System Models (ESMs) project increases in net primary productivity (NPP) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO2, none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from (1) changes in C stocks and (2) changes in NPP. The C stock-based additional P demand was estimated to range between -31 and 193 Tg P and between -89 and 262 Tg P for Representative Concentration Pathway (RCP) 2.6 and RCP8.5, respectively, with negative values indicating a P surplus. The NPP-based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648-1606 Tg P for RCP2.6 and 924-2110 Tg P for RCP8.5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP-based demand and C stock-based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Overall, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.
Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models.
Sun, Yan; Peng, Shushi; Goll, Daniel S; Ciais, Philippe; Guenet, Bertrand; Guimberteau, Matthieu; Hinsinger, Philippe; Janssens, Ivan A; Peñuelas, Josep; Piao, Shilong; Poulter, Benjamin; Violette, Aurélie; Yang, Xiaojuan; Yin, Yi; Zeng, Hui
2017-07-01
Most of the Earth System Models (ESMs) project increases in net primary productivity (NPP) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO 2 , none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from (1) changes in C stocks and (2) changes in NPP. The C stock-based additional P demand was estimated to range between -31 and 193 Tg P and between -89 and 262 Tg P for Representative Concentration Pathway (RCP) 2.6 and RCP8.5, respectively, with negative values indicating a P surplus. The NPP-based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648-1606 Tg P for RCP2.6 and 924-2110 Tg P for RCP8.5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP-based demand and C stock-based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Overall, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.
Demand Response and Energy Storage Integration Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ma, Ookie; Cheung, Kerry; Olsen, Daniel J.
2016-03-01
Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational valuemore » in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.« less
Demand Response and Energy Storage Integration Study
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ma, Ookie; Cheung, Kerry
Demand response and energy storage resources present potentially important sources of bulk power system services that can aid in integrating variable renewable generation. While renewable integration studies have evaluated many of the challenges associated with deploying large amounts of variable wind and solar generation technologies, integration analyses have not yet fully incorporated demand response and energy storage resources. This report represents an initial effort in analyzing the potential integration value of demand response and energy storage, focusing on the western United States. It evaluates two major aspects of increased deployment of demand response and energy storage: (1) Their operational valuemore » in providing bulk power system services and (2) Market and regulatory issues, including potential barriers to deployment.« less
Chenu, Karine; Chapman, Scott C; Hammer, Graeme L; McLean, Greg; Salah, Halim Ben Haj; Tardieu, François
2008-03-01
Physiological and genetic studies of leaf growth often focus on short-term responses, leaving a gap to whole-plant models that predict biomass accumulation, transpiration and yield at crop scale. To bridge this gap, we developed a model that combines an existing model of leaf 6 expansion in response to short-term environmental variations with a model coordinating the development of all leaves of a plant. The latter was based on: (1) rates of leaf initiation, appearance and end of elongation measured in field experiments; and (2) the hypothesis of an independence of the growth between leaves. The resulting whole-plant leaf model was integrated into the generic crop model APSIM which provided dynamic feedback of environmental conditions to the leaf model and allowed simulation of crop growth at canopy level. The model was tested in 12 field situations with contrasting temperature, evaporative demand and soil water status. In observed and simulated data, high evaporative demand reduced leaf area at the whole-plant level, and short water deficits affected only leaves developing during the stress, either visible or still hidden in the whorl. The model adequately simulated whole-plant profiles of leaf area with a single set of parameters that applied to the same hybrid in all experiments. It was also suitable to predict biomass accumulation and yield of a similar hybrid grown in different conditions. This model extends to field conditions existing knowledge of the environmental controls of leaf elongation, and can be used to simulate how their genetic controls flow through to yield.
Adaptive Value Normalization in the Prefrontal Cortex Is Reduced by Memory Load
Burke, C. J.; Seifritz, E.; Tobler, P. N.
2017-01-01
Abstract Adaptation facilitates neural representation of a wide range of diverse inputs, including reward values. Adaptive value coding typically relies on contextual information either obtained from the environment or retrieved from and maintained in memory. However, it is unknown whether having to retrieve and maintain context information modulates the brain’s capacity for value adaptation. To address this issue, we measured hemodynamic responses of the prefrontal cortex (PFC) in two studies on risky decision-making. In each trial, healthy human subjects chose between a risky and a safe alternative; half of the participants had to remember the risky alternatives, whereas for the other half they were presented visually. The value of safe alternatives varied across trials. PFC responses adapted to contextual risk information, with steeper coding of safe alternative value in lower-risk contexts. Importantly, this adaptation depended on working memory load, such that response functions relating PFC activity to safe values were steeper with presented versus remembered risk. An independent second study replicated the findings of the first study and showed that similar slope reductions also arose when memory maintenance demands were increased with a secondary working memory task. Formal model comparison showed that a divisive normalization model fitted effects of both risk context and working memory demands on PFC activity better than alternative models of value adaptation, and revealed that reduced suppression of background activity was the critical parameter impairing normalization with increased memory maintenance demand. Our findings suggest that mnemonic processes can constrain normalization of neural value representations. PMID:28462394
Price Elasticity of Alcohol Demand in India.
Kumar, Santosh
2017-05-01
Using a household survey conducted in 2014, this study estimates price elasticity of demand (PED) for beer, country liquor and spirits in India. Ordinary least-square models were used to estimate the responsiveness in alcohol demand due to price change. A large number of control variables were included to adjust for potential confounding in the model. Inter-district variation in alcohol consumption is adjusted for by including district fixed effects. Alcohol prices are negatively associated with demand for alcoholic beverages. The PED ranged from -0.14 for spirits to -0.46 for country liquor. Low level of education was positively associated with spirits consumption. The magnitude of elasticity varied by rural-urban, education and gender. Results indicate that a policy mix of price controls and awareness campaigns would be most effective in tackling the adverse effects of harmful drinking in India. The demand for beer, country liquor and spirits is negatively associated with its own price. The elasticity estimates ranged from -0.14 for spirits to -0.44 for country liquor. The elasticity estimates varied by rural-urban, gender and by education levels of the drinkers. © The Author 2017. Medical Council on Alcohol and Oxford University Press. All rights reserved
The dissociation of subjective measures of mental workload and performance
NASA Technical Reports Server (NTRS)
Yeh, Y. H.; Wickens, C. D.
1984-01-01
Dissociation between performance and subjective workload measures was investigated in the theoretical framework of the multiple resources model. Subjective measures do not preserve the vector characteristics in the multidimensional space described by the model. A theory of dissociation was proposed to locate the sources that may produce dissociation between the two workload measures. According to the theory, performance is affected by every aspect of processing whereas subjective workload is sensitive to the amount of aggregate resource investment and is dominated by the demands on the perceptual/central resources. The proposed theory was tested in three experiments. Results showed that performance improved but subjective workload was elevated with an increasing amount of resource investment. Furthermore, subjective workload was not as sensitive as was performance to differences in the amount of resource competition between two tasks. The demand on perceptual/central resources was found to be the most salient component of subjective workload. Dissociation occurred when the demand on this component was increased by the number of concurrent tasks or by the number of display elements. However, demands on response resources were weighted in subjective introspection as much as demands on perceptual/central resources. The implications of these results for workload practitioners are described.
A Game Theoretical Model for Location of Terror Response Facilities under Capacitated Resources
Kang, Qi; Xu, Weisheng; Wu, Qidi
2013-01-01
This paper is concerned with the effect of capacity constraints on the locations of terror response facilities. We assume that the state has limited resources, and multiple facilities may be involved in the response until the demand is satisfied consequently. We formulate a leader-follower game model between the state and the terrorist and prove the existence and uniqueness of the Nash equilibrium. An integer linear programming is proposed to obtain the equilibrium results when the facility number is fixed. The problem is demonstrated by a case study of the 19 districts of Shanghai, China. PMID:24459446
Smoktunowicz, Ewelina; Cieslak, Roman; Demerouti, Evangelia
2017-09-01
This study derives from Work-Home Resources model (ten Brummelhuis, L. L., & Bakker, A. B. (2012). A resource perspective on the work-home interface: The work-home resources model. American Psychologist, 67(7), 545-556. doi: 10.1037/a0027974 ) and Social Cognitive Theory (Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Englewood Cliffs, NJ, US: Prentice-Hall, Inc.) to investigate mechanisms responsible for the effect of job and family demands on work- and family-related perceived stress. We hypothesized that interrole conflict and self-efficacy to manage work and family demands operate either independently or sequentially transmitting the effects of demands on perceived stress. A sample of 100 employees of various occupations participated in the study conducted online in two waves: Time 1 (T1) and Time 2 (T2) with a three-month interval. Regression analysis with bootstrapping was applied. Interrole conflict (T1) did not mediate the relationships between demands (T1) and perceived stress (T2), whereas self-efficacy (T1) mediated only those between family demands (T1) and stress (T2). However, data supported the sequential mediation hypotheses: Demands (T1) were associated with increased interrole conflict (T1) which in turn decreased self-efficacy (T1) and ultimately resulted in the elevated perceived stress at work and in the family (T2). Demands originating in one domain can impact stress both in the same and other life areas through the sequence of interrole conflict and context-specific self-efficacy.
An analysis of at-home demand for ice cream in the United States.
Davis, C G; Blayney, D P; Yen, S T; Cooper, J
2009-12-01
Ice cream has been manufactured commercially in the United States since the middle of the 19th century. Ice cream and frozen dessert products comprise an important and relatively stable component of the United States dairy industry. As with many other dairy products, ice cream is differentiated in several dimensions. A censored translog demand system model was employed to analyze purchases of 3 ice cream product categories. The objective of this study was to determine the effect that changes in retail prices and consumer income have on at-home ice cream consumption. The analysis was based on Nielsen 2005 home scan retail data and used marital status, age, race, education, female employment status, and location in the estimations of aggregate demand elasticities. Results revealed that price and consumer income were the main determinants of demand for ice cream products. Calculated own-price elasticities indicated relatively elastic responses by consumers for all categories except for compensated bulk ice cream. All expenditure elasticities were inelastic except for bulk ice cream, and most of the ice cream categories were substitutes. Ongoing efforts to examine consumer demand for these products will assist milk producers, dairy processors and manufacturers, and dairy marketers as they face changing consumer responses to food and diet issues.
NASA Astrophysics Data System (ADS)
Abdulaal, Ahmed
The work in this study addresses the current limitations of the price-driven demand response (DR) approach. Mainly, the dependability on consumers to respond in an energy aware conduct, the response timeliness, the difficulty of applying DR in a busy industrial environment, and the problem of load synchronization are of utmost concern. In order to conduct a simulation study, realistic price simulation model and consumers' building load models are created using real data. DR action is optimized using an autonomous control method, which eliminates the dependency on frequent consumer engagement. Since load scheduling and long-term planning approaches are infeasible in the industrial environment, the proposed method utilizes instantaneous DR in response to hour-ahead price signals (RTP-HA). Preliminary simulation results concluded savings at the consumer-side at the cost of increased supplier-side burden due to the aggregate effect of the universal DR policies. Therefore, a consumer disaggregation strategy is briefly discussed. Finally, a refined discrete-continuous control system is presented, which utilizes multi-objective Pareto optimization, evolutionary programming, utility functions, and bidirectional loads. Demonstrated through a virtual testbed fit with real data, the new system achieves momentary optimized DR in real-time while maximizing the consumer's wellbeing.
The Community Water Model (CWATM) / Development of a community driven global water model
NASA Astrophysics Data System (ADS)
Burek, Peter; Satoh, Yusuke; Greve, Peter; Kahil, Taher; Wada, Yoshihide
2017-04-01
With a growing population and economic development, it is expected that water demands will increase significantly in the future, especially in developing regions. At the same time, climate change is expected to alter spatial patterns of hydrological cycle and will have global, regional and local impacts on water availability. Thus, it is important to assess water supply, water demand and environmental needs over time to identify the populations and locations that will be most affected by these changes linked to water scarcity, droughts and floods. The Community Water Model (CWATM) will be designed for this purpose in that it includes an accounting of how future water demands will evolve in response to socioeconomic change and how water availability will change in response to climate. CWATM represents one of the new key elements of IIASA's Water program. It has been developed to work flexibly at both global and regional level at different spatial resolutions. The model is open source and community-driven to promote our work amongst the wider water community worldwide and is flexible enough linking to further planned developments such as water quality and hydro-economic modules. CWATM will be a basis to develop a next-generation global hydro-economic modeling framework that represents the economic trade-offs among different water management options over a basin looking at water supply infrastructure and demand managements. The integrated modeling framework will consider water demand from agriculture, domestic, energy, industry and environment, investment needs to alleviate future water scarcity, and will provide a portfolio of economically optimal solutions for achieving future water management options under the Sustainable Development Goals (SDG) for example. In addition, it will be able to track the energy requirements associated with the water supply system e.g., pumping, desalination and interbasin transfer to realize the linkage with the water-energy economy. In a bigger framework of nexus - water, energy, food, ecosystem - CWATM will be coupled to the existing IIASA models including the Integrated Assessment Model MESSAGE and the global land and ecosystem model GLOBIOM in order to realize an improved assessments of water-energy-food-ecosystem nexus and associated feedback. Our vision for the short to medium term work is to introduce water quality (e.g., salinization in deltas and eutrophication associated with mega cities) into CWATM and to consider qualitative and quantitative measures of transboundary river and groundwater governance into an integrated modelling framework.
Distributed computing feasibility in a non-dedicated homogeneous distributed system
NASA Technical Reports Server (NTRS)
Leutenegger, Scott T.; Sun, Xian-He
1993-01-01
The low cost and availability of clusters of workstations have lead researchers to re-explore distributed computing using independent workstations. This approach may provide better cost/performance than tightly coupled multiprocessors. In practice, this approach often utilizes wasted cycles to run parallel jobs. The feasibility of such a non-dedicated parallel processing environment assuming workstation processes have preemptive priority over parallel tasks is addressed. An analytical model is developed to predict parallel job response times. Our model provides insight into how significantly workstation owner interference degrades parallel program performance. A new term task ratio, which relates the parallel task demand to the mean service demand of nonparallel workstation processes, is introduced. It was proposed that task ratio is a useful metric for determining how large the demand of a parallel applications must be in order to make efficient use of a non-dedicated distributed system.
General practitioner workforce planning: assessment of four policy directions.
Teljeur, Conor; Thomas, Stephen; O'Kelly, Fergus D; O'Dowd, Tom
2010-06-02
Estimating the supply of GPs into the future is important in forecasting shortages. The lengthy training process for medicine means that adjusting supply to meet demand in a timely fashion is problematic. This study uses Ireland as a case study to determine the future demand and supply of GPs and to assess the potential impact of several possible interventions to address future shortages. Demand was estimated by applying GP visit rates by age and sex to national population projections. Supply was modelled using a range of parameters derived from two national surveys of GPs. A stochastic modelling approach was adopted to determine the probable future supply of GPs. Four policy interventions were tested: increasing vocational training places; recruiting GPs from abroad; incentivising later retirement; increasing nurse substitution to enable practice nurses to deliver more services. Relative to most other European countries, Ireland has few GPs per capita. Ireland has an ageing population and demand is estimated to increase by 19% by 2021. Without intervention, the supply of GPs will be 5.7% less than required in 2021. Increasing training places will enable supply to meet demand but only after 2019. Recruiting GPs from overseas will enable supply to meet demand continuously if the number recruited is approximately 0.8 per cent of the current workforce per annum. Later retirement has only a short-term impact. Nurse substitution can enable supply to meet demand but only if large numbers of practice nurses are recruited and allowed to deliver a wide range of GP services. A significant shortfall in GP supply is predicted for Ireland unless recruitment is increased. The shortfall will have numerous knock-on effects including price increases, longer waiting lists and an increased burden on hospitals. Increasing training places will not provide an adequate response to future shortages. Foreign recruitment has ethical considerations but may provide a rapid and effective response. Increased nurse substitution appears to offer the best long-term prospects of addressing GP shortages and presents the opportunity to reshape general practice to meet the demands of the future.
Interoperability of Demand Response Resources Demonstration in NY
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wellington, Andre
2014-03-31
The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lekov, Alex; Thompson, Lisa; McKane, Aimee
This report summarizes the Lawrence Berkeley National Laboratory?s research to date in characterizing energy efficiency and automated demand response opportunities for wastewater treatment facilities in California. The report describes the characteristics of wastewater treatment facilities, the nature of the wastewater stream, energy use and demand, as well as details of the wastewater treatment process. It also discusses control systems and energy efficiency and automated demand response opportunities. In addition, several energy efficiency and load management case studies are provided for wastewater treatment facilities.This study shows that wastewater treatment facilities can be excellent candidates for open automated demand response and thatmore » facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for automated demand response at little additional cost. These improved controls may prepare facilities to be more receptive to open automated demand response due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.« less
Code of Federal Regulations, 2011 CFR
2011-07-01
... designee) of the creditor Labor Department agency shall send appropriate written demands to the debtor in... written demands at not more than 30-day intervals will normally be made unless a response to the first or second demand indicates that a further demand would be futile and the debtor's response does not require...
Code of Federal Regulations, 2010 CFR
2010-07-01
... designee) of the creditor Labor Department agency shall send appropriate written demands to the debtor in... written demands at not more than 30-day intervals will normally be made unless a response to the first or second demand indicates that a further demand would be futile and the debtor's response does not require...
van Woerkom, Marianne; Bakker, Arnold B; Nishii, Lisa H
2016-01-01
Absenteeism associated with accumulated job demands is a ubiquitous problem. We build on prior research on the benefits of counteracting job demands with resources by focusing on a still untapped resource for buffering job demands-that of strengths use. We test the idea that employees who are actively encouraged to utilize their personal strengths on the job are better positioned to cope with job demands. Based on conservation of resources (COR) theory, we hypothesized that job demands can accumulate and together have an exacerbating effect on company registered absenteeism. In addition, using job demands-resources theory, we hypothesized that perceived organizational support for strengths use can buffer the impact of separate and combined job demands (workload and emotional demands) on absenteeism. Our sample consisted of 832 employees from 96 departments (response rate = 40.3%) of a Dutch mental health care organization. Results of multilevel analyses indicated that high levels of workload strengthen the positive relationship between emotional demands and absenteeism and that support for strength use interacted with workload and emotional job demands in the predicted way. Moreover, workload, emotional job demands, and strengths use interacted to predict absenteeism. Strengths use support reduced the level of absenteeism of employees who experienced both high workload and high emotional demands. We conclude that providing strengths use support to employees offers organizations a tool to reduce absenteeism, even when it is difficult to redesign job demands. (c) 2016 APA, all rights reserved).
Kimber, S; Gardner, D H
2016-07-01
To use a job demands-resources model to examine the associations among perceived job demands, job resources, family-to-work enrichment, positive team relationships, work engagement, emotional exhaustion, cynicism and intention to leave, in a sample of New Zealand veterinary nurses. Data were collected by means of a self-reported online survey, with the help of eight New Zealand tertiary education providers and the New Zealand Veterinary Nurses' Association. Nine measures or variables were assessed using questions or statements with responses categorised on a linear scale. Measurement models for each of the variables in the study were assessed to establish whether the variables represented the respective item-level data. Structural equation modelling was then used to test the hypothesised interrelationships among study variables. There were 253 respondents; 17.1% of individuals who classified themselves as veterinary nurses in the 2013 New Zealand census. In the final structural model job demands were associated with emotional exhaustion (standardised regression coefficient β=0.57), which was related to cynicism (β=0.52) and intention to leave (β=0.56). Job resources were negatively related to emotional exhaustion (β=-0.32). Higher work engagement was associated with lower emotional exhaustion (β=-0.29) and lower intention to leave (β=-0.30). Job resources were associated with work-to-family enrichment (β=0.69), which was related to work engagement (β=0.57); and job resources were associated with positive team relationships (β=0.79). It is important that job resources are available to help deal with demanding work. Without resources, demanding work is associated with exhaustion, cynicism and increased intention to leave, while positive spill over between work and family life are related to higher work engagement.
Poole, KM; Nelson, CE; Joshi, RV; Martin, JR; Gupta, MK; Haws, SC; Kavanaugh, TE; Skala, MC; Duvall, CL
2014-01-01
A new microparticle-based delivery system was synthesized from reactive oxygen species (ROS)-responsive poly(propylene sulfide) (PPS) and tested for “on demand” antioxidant therapy. PPS is hydrophobic but undergoes a phase change to become hydrophilic upon oxidation and thus provides a useful platform for ROS-demanded drug release. This platform was tested for delivery of the promising anti-inflammatory and antioxidant therapeutic molecule curcumin, which is currently limited in use in its free form due to poor pharmacokinetic properties. PPS microspheres efficiently encapsulated curcumin through oil-in-water emulsion and provided sustained, on demand release that was modulated in vitro by hydrogen peroxide concentration. The cytocompatible, curcumin-loaded microspheres preferentially targeted and scavenged intracellular ROS in activated macrophages, reduced in vitro cell death in the presence of cytotoxic levels of ROS, and decreased tissue-level ROS in vivo in the diabetic mouse hind limb ischemia model of peripheral arterial disease. Interestingly, due to the ROS scavenging behavior of PPS, the blank microparticles also showed inherent therapeutic properties that were synergistic with the effects of curcumin in these assays. Functionally, local delivery of curcumin-PPS microspheres accelerated recovery from hind limb ischemia in diabetic mice, as demonstrated using non-invasive imaging techniques. This work demonstrates the potential for PPS microspheres as a generalizable vehicle for ROS-demanded drug release and establishes the utility of this platform for improving local curcumin bioavailability for treatment of chronic inflammatory diseases. PMID:25522975
Focus Group Study Exploring Factors Related to Frequent Sickness Absence.
Notenbomer, Annette; Roelen, Corné A M; van Rhenen, Willem; Groothoff, Johan W
2016-01-01
Research investigating frequent sickness absence (3 or more episodes per year) is scarce and qualitative research from the perspective of frequent absentees themselves is lacking. The aim of the current study is to explore awareness, determinants of and solutions to frequent sickness absence from the perspective of frequent absentees themselves. We performed a qualitative study of 3 focus group discussions involving a total of 15 frequent absentees. Focus group discussions were audiotaped and transcribed verbatim. Results were analyzed with the Graneheim method using the Job Demands Resources (JD-R) model as theoretical framework. Many participants were not aware of their frequent sickness absence and the risk of future long-term sickness absence. As determinants, participants mentioned job demands, job resources, home demands, poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Managing these factors and improving communication (skills) were regarded as solutions to reduce frequent sickness absence. The JD-R model provided a framework for determinants of and solutions to frequent sickness absence. Additional determinants were poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Frequent sickness absence should be regarded as a signal that something is wrong. Managers, supervisors, and occupational health care providers should advise and support frequent absentees to accommodate job demands, increase both job and personal resources, and improve health rather than express disapproval of frequent sickness absence and apply pressure regarding work attendance.
Multivariate analysis of sludge disintegration by microwave-hydrogen peroxide pretreatment process.
Ya-Wei, Wang; Cheng-Min, Gui; Xiao-Tang, Ni; Mei-Xue, Chen; Yuan-Song, Wei
2015-01-01
Microwave irradiation (with H2O2) has been shown to offer considerable advantages owing to its flexible control, low overall cost, and resulting higher soluble chemical oxygen demand (SCOD); accordingly, the method has been proposed recently as a means of improving sludge disintegration. However, the key factor controlling this sludge pretreatment process, pH, has received insufficient attention to date. To address this, the response surface approach (central composite design) was applied to evaluate the effects of total suspended solids (TSS, 2-20 g/L), pH (4-10), and H2O2 dosage (0-2 w/w) and their interactions on 16 response variables (e.g., SCODreleased, pH, H2O2remaining). The results demonstrated that all three factors affect sludge disintegration significantly, and no pronounced interactions between response variables were observed during disintegration, except for three variables (TCOD, TSSremaining, and H2O2 remaining). Quadratic predictive models were constructed for all 16 response variables (R(2): 0.871-0.991). Taking soluble chemical oxygen demand (SCOD) as an example, the model and coefficients derived above were able to predict the performance of microwave pretreatment (enhanced by H2O2 and pH adjustment) from previously published studies. The predictive models developed were able to optimize the treatment process for multiple disintegration objectives. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Technical Reports Server (NTRS)
Wickens, C.; Gill, R.; Kramer, A.; Ross, W.; Donchin, E.
1981-01-01
Three experiments are described in which tracking difficulty is varied in the presence of a covert tone discrimination task. Event related brain potentials (ERPs) elicited by the tones are employed as an index of the resource demands of tracking. The ERP measure reflected the control order variation, and this variable was thereby assumed to compete for perceptual/central processing resources. A fine-grained analysis of the results suggested that the primary demands of second order tracking involve the central processing operations of maintaining a more complex internal model of the dynamic system, rather than the perceptual demands of higher derivative perception. Experiment 3 varied tracking bandwidth in random input tracking, and the ERP was unaffected. Bandwidth was then inferred to compete for response-related processing resources that are independent of the ERP.
Correlates of parental antibiotic knowledge, demand, and reported use.
Kuzujanakis, Marianne; Kleinman, Ken; Rifas-Shiman, Sheryl; Finkelstein, Jonathan A
2003-01-01
Clinicians cite parental misconceptions and requests for antibiotics as reasons for inappropriate prescribing. To identify misconceptions regarding antibiotics and predictors of parental demand for antibiotics and to determine if parental knowledge and attitudes are associated with use. Survey of parents in 16 Massachusetts communities. Domains included antibiotic-related knowledge, attitudes about antibiotics, antibiotic use during a 12-month period, demographics, and access to health information. Bivariate and multivariate analyses evaluated predictors of knowledge and proclivity to demand antibiotics. A multivariate model evaluated the associations of knowledge, demand, and demographic factors with parent-reported antibiotic use. A total of 1106 surveys were returned (response rates: 54% and 32% for commercially-insured and Medicaid-insured families). Misconceptions were common regarding bronchitis (92%) and green nasal discharge (78%). Two hundred sixty-five (24%) gave responses suggesting a proclivity to demand antibiotics. Antibiotic knowledge was associated with increased parental age and education, having more than 1 child, white race, and receipt of media information on resistance. Factors associated with a proclivity to demand antibiotics included decreased knowledge, pressure from day-care settings, lack of alternatives offered by clinicians, and lack of access to media information. Among all respondents, reported antibiotic use was associated with younger child age and day-care attendance. Among Medicaid-insured children only, less antibiotic knowledge and tendency to demand antibiotics were associated with higher rates of antibiotic use. Misconceptions regarding antibiotic use are widespread and potentially modifiable by clinicians and media sources. Particular attention should be paid to Medicaid-insured patients in whom such misconceptions may contribute to inappropriate prescribing.
Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma.
Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E; Bollinger, Kathryn; Devos, Hannes
2017-01-01
Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal-Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups ( p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1-Q3) 3 (2-6.50) vs. 2 (0.50-2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2-6) vs. 1 (0.50-2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls ( p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma.
Automated Demand Response for Energy Sustainability
2015-05-01
project’s stated performance objectives. Emerging opportunities to participate in wholesale electricity markets can provide important economic, energy, and...Response in Wholesale Electricity Markets ..................................................... 7 Figure 5. Demand Bidding Communication and Control...resource in response to market or reliability conditions Demand Bidding Program DR programs that encourage customers to bid into an electricity market
Industrial Scale Energy Systems Integration; NREL (National Renewable Energy Laboratory)
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ruth, Mark
2015-07-28
The industrial sector consumes 25% of the total energy in the U.S. and produces 18% of the greenhouse gas (GHG) emissions. Energy Systems Integration (ESI) opportunities can reduce those values and increase the profitability of that sector. This presentation outlines several options. Combined heat and power (CHP) is an option that is available today for many applications. In some cases, it can be extended to trigeneration by adding absorbtion cooling. Demand response is another option in use by the industrial sector - in 2012, industry provided 47% of demand response capacity. A longer term option that combines the benefits ofmore » CHP with those of demand response is hybrid energy systems (HESs). Two possible HESs are described and development implications discussed. extended to trigeneration by adding absorbtion cooling. Demand response is another option in use by the industrial sector - in 2012, industry provided 47% of demand response capacity. A longer term option that combines the benefits of CHP with those of demand response is hybrid energy systems (HESs). Two possible HESs are described and development implications discussed.« less
Photovoltaic venture analysis. Final report. Volume I. Executive summary
DOE Office of Scientific and Technical Information (OSTI.GOV)
Costello, D.; Posner, D.; Schiffel, D.
1978-07-01
The objective of the study, government programs under investigation, and a brief review of the approach are presented. Potential markets for photovoltaic systems relevant to the study are described. The response of the photovoltaic supply industry is then considered. A model which integrates the supply and demand characteristics of photovoltaics over time was developed. This model also calculates the economic benefits associated with various government subsidy programs. Results are derived under alternative possible supply, demand, and macroeconomic conditions. A probabilistic analysis of the costs and benefits of a $380 million federal photovoltaic procurement initiative, as well as certain alternative strategies,more » is summarized. Conclusions and recommendations based on the analysis are presented.« less
Diagnosing phosphorus limitations in natural terrestrial ecosystems in carbon cycle models
Sun, Yan; Peng, Shushi; Goll, Daniel S.; ...
2017-04-28
Most of the Earth System Models (ESMs) project increases in net primary productivity (NPP) and terrestrial carbon (C) storage during the 21st century. Despite empirical evidence that limited availability of phosphorus (P) may limit the response of NPP to increasing atmospheric CO 2, none of the ESMs used in the previous Intergovernmental Panel on Climate Change assessment accounted for P limitation. We diagnosed from ESM simulations the amount of P need to support increases in carbon uptake by natural ecosystems using two approaches: the demand derived from changes in C stocks and changes in NPP. The C stock-based additional Pmore » demand was estimated to range between -31 and 193 Tg P and between -89 and 262 Tg P for Representative Concentration Pathway (RCP) 2.6 and RCP8.5, respectively, with negative values indicating a P surplus. The NPP-based demand, which takes ecosystem P recycling into account, results in a significantly higher P demand of 648–1606 Tg P for RCP2.6 and 924–2110 Tg P for RCP8.5. We found that the P demand is sensitive to the turnover of P in decomposing plant material, explaining the large differences between the NPP-based demand and C stock-based demand. The discrepancy between diagnosed P demand and actual P availability (potential P deficit) depends mainly on the assumptions about availability of the different soil P forms. Altogether, future P limitation strongly depends on both soil P availability and P recycling on ecosystem scale.« less
School Leadership Lessons from England
ERIC Educational Resources Information Center
Supovitz, Jonathan
2015-01-01
The flat structure of American schools is ill-suited to meeting today's demands for education improvement. Historically, American schools have addressed this instructional support deficit with a patchwork of poorly defined roles and responsibilities--underused department chairs, fitful coaching models, and informal teacher leaders who generally…
On the Effect of Preferential Sampling in Spatial Prediction
The choice of the sampling locations in a spatial network is often guided by practical demands. In particular, typically, locations are preferentially chosen to capture high values of a response, for example, air pollution levels in environmental monitoring. Then, model estimatio...
MAG traffic generator study : survey data from Arizona State University
DOT National Transportation Integrated Search
1994-12-01
The Maricopa Association of Governments (MAG) is responsible for the travel demand models used to forecast multi-modal travel behavior in the Phoenix metropolitan area. The main campus of Arizona State University (ASU), located in Tempe, is one of th...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Xin; Baker, Kyri A.; Christensen, Dane T.
This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Xin; Baker, Kyri A; Isley, Steven C
This paper presents a user-preference-driven home energy management system (HEMS) for demand response (DR) with residential building loads and battery storage. The HEMS is based on a multi-objective model predictive control algorithm, where the objectives include energy cost, thermal comfort, and carbon emission. A multi-criterion decision making method originating from social science is used to quickly determine user preferences based on a brief survey and derive the weights of different objectives used in the optimization process. Besides the residential appliances used in the traditional DR programs, a home battery system is integrated into the HEMS to improve the flexibility andmore » reliability of the DR resources. Simulation studies have been performed on field data from a residential building stock data set. Appliance models and usage patterns were learned from the data to predict the DR resource availability. Results indicate the HEMS was able to provide a significant amount of load reduction with less than 20% prediction error in both heating and cooling cases.« less
Smart material platforms for miniaturized devices: implications in disease models and diagnostics.
Verma, Ritika; Adhikary, Rishi Rajat; Banerjee, Rinti
2016-05-24
Smart materials are responsive to multiple stimuli like light, temperature, pH and redox reactions with specific changes in state. Various functionalities in miniaturised devices can be achieved through the application of "smart materials" that respond to changes in their surroundings. The change in state of the materials in the presence of a stimulus may be used for on demand alteration of flow patterns in devices, acting as microvalves, as scaffolds for cellular aggregation or as modalities for signal amplification. In this review, we discuss the concepts of smart trigger responsive materials and their applications in miniaturized devices both for organ-on-a-chip disease models and for point-of-care diagnostics. The emphasis is on leveraging the smartness of these materials for example, to allow on demand sample actuation, ion dependent spheroid models for cancer or light dependent contractility of muscle films for organ-on-a-chip applications. The review throws light on the current status, scope for technological enhancements, challenges for translation and future prospects of increased incorporation of smart materials as integral parts of miniaturized devices.
Deep-Learning-Enabled On-Demand Design of Chiral Metamaterials.
Ma, Wei; Cheng, Feng; Liu, Yongmin
2018-06-11
Deep-learning framework has significantly impelled the development of modern machine learning technology by continuously pushing the limit of traditional recognition and processing of images, speech, and videos. In the meantime, it starts to penetrate other disciplines, such as biology, genetics, materials science, and physics. Here, we report a deep-learning-based model, comprising two bidirectional neural networks assembled by a partial stacking strategy, to automatically design and optimize three-dimensional chiral metamaterials with strong chiroptical responses at predesignated wavelengths. The model can help to discover the intricate, nonintuitive relationship between a metamaterial structure and its optical responses from a number of training examples, which circumvents the time-consuming, case-by-case numerical simulations in conventional metamaterial designs. This approach not only realizes the forward prediction of optical performance much more accurately and efficiently but also enables one to inversely retrieve designs from given requirements. Our results demonstrate that such a data-driven model can be applied as a very powerful tool in studying complicated light-matter interactions and accelerating the on-demand design of nanophotonic devices, systems, and architectures for real world applications.
Burnout in Medical Residents: A Study Based on the Job Demands-Resources Model
2014-01-01
Purpose. Burnout is a prolonged response to chronic emotional and interpersonal stressors on the job. The purpose of our cross-sectional study was to estimate the burnout rates among medical residents in the largest Greek hospital in 2012 and identify factors associated with it, based on the job demands-resources model (JD-R). Method. Job demands were examined via a 17-item questionnaire assessing 4 characteristics (emotional demands, intellectual demands, workload, and home-work demands' interface) and job resources were measured via a 14-item questionnaire assessing 4 characteristics (autonomy, opportunities for professional development, support from colleagues, and supervisor's support). The Maslach Burnout Inventory (MBI) was used to measure burnout. Results. Of the 290 eligible residents, 90.7% responded. In total 14.4% of the residents were found to experience burnout. Multiple logistic regression analysis revealed that each increased point in the JD-R questionnaire score regarding home-work interface was associated with an increase in the odds of burnout by 25.5%. Conversely, each increased point for autonomy, opportunities in professional development, and each extra resident per specialist were associated with a decrease in the odds of burnout by 37.1%, 39.4%, and 59.0%, respectively. Conclusions. Burnout among medical residents is associated with home-work interface, autonomy, professional development, and resident to specialist ratio. PMID:25531003
Modeling irrigation behavior in groundwater systems
NASA Astrophysics Data System (ADS)
Foster, Timothy; Brozović, Nicholas; Butler, Adrian P.
2014-08-01
Integrated hydro-economic models have been widely applied to water management problems in regions of intensive groundwater-fed irrigation. However, policy interpretations may be limited as most existing models do not explicitly consider two important aspects of observed irrigation decision making, namely the limits on instantaneous irrigation rates imposed by well yield and the intraseasonal structure of irrigation planning. We develop a new modeling approach for determining irrigation demand that is based on observed farmer behavior and captures the impacts on production and water use of both well yield and climate. Through a case study of irrigated corn production in the Texas High Plains region of the United States we predict optimal irrigation strategies under variable levels of groundwater supply, and assess the limits of existing models for predicting land and groundwater use decisions by farmers. Our results show that irrigation behavior exhibits complex nonlinear responses to changes in groundwater availability. Declining well yields induce large reductions in the optimal size of irrigated area and irrigation use as constraints on instantaneous application rates limit the ability to maintain sufficient soil moisture to avoid negative impacts on crop yield. We demonstrate that this important behavioral response to limited groundwater availability is not captured by existing modeling approaches, which therefore may be unreliable predictors of irrigation demand, agricultural profitability, and resilience to climate change and aquifer depletion.
Demand curves for hypothetical cocaine in cocaine-dependent individuals.
Bruner, Natalie R; Johnson, Matthew W
2014-03-01
Drug purchasing tasks have been successfully used to examine demand for hypothetical consumption of abused drugs including heroin, nicotine, and alcohol. In these tasks, drug users make hypothetical choices whether to buy drugs, and if so, at what quantity, at various potential prices. These tasks allow for behavioral economic assessment of that drug's intensity of demand (preferred level of consumption at extremely low prices) and demand elasticity (sensitivity of consumption to price), among other metrics. However, a purchasing task for cocaine in cocaine-dependent individuals has not been investigated. This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data. Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use. Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and O max (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, P max, were significantly correlated with real-world cocaine use. Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use.
78 FR 21928 - Demand Response Coalition v. PJM Interconnection, L.L.C.; Notice of Complaint
Federal Register 2010, 2011, 2012, 2013, 2014
2013-04-12
... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL13-57-000] Demand Response Coalition v. PJM Interconnection, L.L.C.; Notice of Complaint Take notice that on April 3, 2013, pursuant to... Demand Response Coalition \\1\\ (Complainant) filed a formal complaint against the PJM Interconnection, L.L...
ERIC Educational Resources Information Center
Kwok, Percy Lai Yin
2010-01-01
Based on some longitudinal studies of private tutoring in twelve cities, towns, municipalities and provinces of China, the paper endeavours to depict demand intensity, articulate market parameters and reflect on policy responses towards the demand-supply mechanism of the vast shadowy educational phenomena at primary and secondary levels. Such…
Integrated Platform for Automated Sustainable Demand Response in Smart Grids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zois, Vassilis; Frincu, Marc; Prasanna, Viktor K.
2014-10-08
Demand Response(DR) is a common practice used by utility providers to regulate energy demand. It is used at periods of high demand to minimize the peak to average consumption ratio. Several methods have been Demand Response(DR) is a common praon using information about the baseline consumption and the consumption during DR. Our goal is to provide a sustainable reduction to ensure the elimination of peaks in demand. The proposed system includes an adaptation mechanism for when the provided solution does not meet the DR requirements. We conducted a series of experiments using consumption data from a real life micro gridmore » to evaluate the efficiency as well as the robustness of our solution.« less
Noren, Shawn R.; Udevitz, Mark S.; Jay, Chadwick V.
2014-01-01
Decreases in sea ice have altered habitat use and activity patterns of female Pacific walruses Odobenus rosmarus divergens and could affect their energetic demands, reproductive success, and population status. However, a lack of physiological data from walruses has hampered efforts to develop the bioenergetics models required for fully understanding potential population-level impacts. We analyzed long-term longitudinal data sets of caloric consumption and body mass from nine female Pacific walruses housed at six aquaria using a hierarchical Bayesian approach to quantify relative energetic demands for maintenance, growth, pregnancy, and lactation. By examining body mass fluctuations in response to food consumption, the model explicitly uncoupled caloric demand from caloric intake. This is important for pinnipeds because they sequester and deplete large quantities of lipids throughout their lifetimes. Model outputs were scaled to account for activity levels typical of free-ranging Pacific walruses, averaging 83% of the time active in water and 17% of the time hauled-out resting. Estimated caloric requirements ranged from 26,900 kcal d−1 for 2-yr-olds to 93,370 kcal d−1 for simultaneously lactating and pregnant walruses. Daily consumption requirements were higher for pregnancy than lactation, reflecting energetic demands of increasing body size and lipid deposition during pregnancy. Although walruses forage during lactation, fat sequestered during pregnancy sustained 27% of caloric requirements during the first month of lactation, suggesting that walruses use a mixed strategy of capital and income breeding. Ultimately, this model will aid in our understanding of the energetic and population consequences of sea ice loss.
NASA Astrophysics Data System (ADS)
Wang, Qiming; Gossweiler, Gregory R.; Craig, Stephen L.; Zhao, Xuanhe
2014-09-01
Cephalopods can display dazzling patterns of colours by selectively contracting muscles to reversibly activate chromatophores - pigment-containing cells under their skins. Inspired by this novel colouring strategy found in nature, we design an electro-mechano-chemically responsive elastomer system that can exhibit a wide variety of fluorescent patterns under the control of electric fields. We covalently couple a stretchable elastomer with mechanochromic molecules, which emit strong fluorescent signals if sufficiently deformed. We then use electric fields to induce various patterns of large deformation on the elastomer surface, which displays versatile fluorescent patterns including lines, circles and letters on demand. Theoretical models are further constructed to predict the electrically induced fluorescent patterns and to guide the design of this class of elastomers and devices. The material and method open promising avenues for creating flexible devices in soft/wet environments that combine deformation, colorimetric and fluorescent response with topological and chemical changes in response to a single remote signal.
NASA Astrophysics Data System (ADS)
Brookshire, D. S.; Coursey, D.; Dimint, A.; Tidwell, V.
2004-12-01
Since 1950, the demand for water has more than doubled in the United States. Historically, growing demands have been met by increasing reservoir capacity and through groundwater mining, often at the expense of environmental and cultural concerns. The future is expected to hold much the same. Demand for water will continue to increase particularly in response to the expanding urban sector, while growing concerns over the environment are prompting interest in allocating more water for in-stream uses. So, where will this water come from? Virtually all water supplies are allocated. Providing for new uses requires a reduction in the amount of water dedicated to existing uses. The water banking/leasing model is formulated within a system dynamics context using the object oriented commercial software package, Powersimä Studio 2003. System dynamics provides a unique mathematical framework for integrating the natural and social processes important to managing natural resources and can provide an interactive interface for engaging the public in the decision process. These system level models focus on capturing the broad structure of the system, specifically the feedback and time delays between interacting subsystems. The spatially aggregated models are computationally efficient allowing simulations to be conducted on a PC in a matter of seconds to minutes. By employing interactive interfaces, these models can be taken directly to the public or decision maker. To demonstrate the water banking/leasing model, application has been made to potential markets on the Rio Grande. Specifically, the model spans the reach between Elephant Butte Reservoir (central New Mexico) and the New Mexico/Texas state line. Primary sectors in the model include climate, surface and groundwater, riparian and aquatic habitat, watershed processes, water quality, water demand (residential, commercial, industrial, institution, and agricultural), economics, policy, and legal institutions. Within the model the basin is divided into four distinct but interacting reaches and a monthly time-step is employed. River operations and water demand trends have been calibrated to historical data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Marks, Gary; Wilcox, Edmund; Olsen, Daniel
California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agriculturalmore » irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as conducting a more comprehensive survey of California growers.« less
McVicar, Andrew
2016-03-01
To identify core antecedents of job stress and job satisfaction, and to explore the potential of stress interventions to improve job satisfaction. Decreased job satisfaction for nurses is strongly associated with increased job stress. Stress management strategies might have the potential to improve job satisfaction. Comparative scoping review of studies (2000-2013) and location of their outcomes within the 'job demands-job resources' (JD-R) model of stress to identify commonalities and trends. Many, but not all, antecedents of both phenomena appeared consistently suggesting they are common mediators. Others were more variable but the appearance of 'emotional demands' as a common antecedent in later studies suggests an evolving influence of the changing work environment. The occurrence of 'shift work' as a common issue in later studies points to further implications for nurses' psychosocial well-being. Job satisfaction problems in nursing might be co-responsive to stress management intervention. Improving the buffering effectiveness of increased resilience and of prominent perceived job resource issues are urgently required. Participatory, psychosocial methods have the potential to raise job resources but will require high-level collaboration by stakeholders, and participative leadership and facilitation by managers to enable better decision-latitude, support for action planning and responsive changes. © 2015 John Wiley & Sons Ltd.
Community health centers at the crossroads: growth and staffing needs.
Proser, Michelle; Bysshe, Tyler; Weaver, Donald; Yee, Ronald
2015-04-01
In response to increased demand for primary care services under the Affordable Care Act, the national network of community health centers (CHCs) will play an increasingly prominent role. CHCs have a broad staffing model that includes extensive use of physician assistants (PAs), nurse practitioners (NPs), and certified nurse midwives (CNMs). Between 2007 and 2012, the number of PAs, NPs, and CNMs at CHCs increased by 61%, compared with 31% for physicians. However, several policy and payment issues jeopardize CHCs' ability to expand their workforce and meet the current and rising demand for care.
Smart Grid Development: Multinational Demo Project Analysis
NASA Astrophysics Data System (ADS)
Oleinikova, I.; Mutule, A.; Obushevs, A.; Antoskovs, N.
2016-12-01
This paper analyses demand side management (DSM) projects and stakeholders' experience with the aim to develop, promote and adapt smart grid tehnologies in Latvia. The research aims at identifying possible system service posibilites, including demand response (DR) and determining the appropriate market design for such type of services to be implemented at the Baltic power system level, with the cooperation of distribution system operator (DSO) and transmission system operator (TSO). This paper is prepared as an extract from the global smart grid best practices, smart solutions and business models.
Novick, Gina; Womack, Julie A.; Lewis, Jessica; Stasko, Emily C.; Rising, Sharon S.; Sadler, Lois S.; Cunningham, Shayna C.; Tobin, Jonathan N.; Ickovics, Jeannette R.
2016-01-01
Group prenatal care improves perinatal outcomes, but implementing this complex model places substantial demands on settings designed for individual care. To describe perceived barriers and facilitators to implementing and sustaining Centering Pregnancy Plus (CP+) group prenatal care, 24 in-depth interviews were conducted with 22 clinicians, staff, administrators, and study personnel in six of the 14 sites of a randomized trial of the model. All sites served low-income, minority women. Sites for the present evaluation were selected for variation in location, study arm, and initial implementation response. Implementing CP+ was challenging in all sites, requiring substantial adaptations of clinical systems. All sites had barriers to meeting the model’s demands, but how sites responded to these barriers affected whether implementation thrived or struggled. Thriving sites had organizational cultures that supported innovation, champions who advocated for CP+, and staff who viewed logistical demands as manageable hurdles. Struggling sites had bureaucratic organizational structures and lacked buy-in and financial resources, and staff were overwhelmed by the model’s challenges. Findings suggested that implementing and sustaining health care innovation requires new practices and different ways of thinking, and health systems may not fully recognize the magnitude of change required. Consequently, evidence-based practices are modified or discontinued, and outcomes may differ from those in the original controlled studies. Before implementing new models of care, clinical settings should anticipate model demands and assess capacity for adapting to the disruptions of innovation. PMID:26340483
Learn More | Energy Analysis | NREL
flexibility. Value of Demand Response: Quantities from Production Cost Modeling (Presentation) (2014 adding variable renewable generation to the grid. Market Design Evolution of Wholesale Electricity Market Design with Increasing Levels of Renewable Generation (2014) Reviewed market design approaches focused on
Dynamics of assembly production flow
NASA Astrophysics Data System (ADS)
Ezaki, Takahiro; Yanagisawa, Daichi; Nishinari, Katsuhiro
2015-06-01
Despite recent developments in management theory, maintaining a manufacturing schedule remains difficult because of production delays and fluctuations in demand and supply of materials. The response of manufacturing systems to such disruptions to dynamic behavior has been rarely studied. To capture these responses, we investigate a process that models the assembly of parts into end products. The complete assembly process is represented by a directed tree, where the smallest parts are injected at leaves and the end products are removed at the root. A discrete assembly process, represented by a node on the network, integrates parts, which are then sent to the next downstream node as a single part. The model exhibits some intriguing phenomena, including overstock cascade, phase transition in terms of demand and supply fluctuations, nonmonotonic distribution of stockout in the network, and the formation of a stockout path and stockout chains. Surprisingly, these rich phenomena result from only the nature of distributed assembly processes. From a physical perspective, these phenomena provide insight into delay dynamics and inventory distributions in large-scale manufacturing systems.
12 CFR 602.24 - Responses to demands served on non-FCA employees or entities.
Code of Federal Regulations, 2010 CFR
2010-01-01
... 12 Banks and Banking 6 2010-01-01 2010-01-01 false Responses to demands served on non-FCA employees or entities. 602.24 Section 602.24 Banks and Banking FARM CREDIT ADMINISTRATION ADMINISTRATIVE... Not a Named Party § 602.24 Responses to demands served on non-FCA employees or entities. If you are...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Epstein, T; Xu, L; Gillies, R
2014-06-01
Purpose: To study a new model of glucose metabolism which is primarily governed by the timescale of the energetic demand and not by the oxygen level, and its implication on cancer metabolism (Warburg effect) Methods: 1) Metabolic profiling of membrane transporters activity in several cell lines, which represent the spectrum from normal breast epithelium to aggressive, metastatic cancer, using Seahorse XF reader.2) Spatial localization of oxidative and non-oxidative metabolic components using immunocytochemical imaging of the glycolytic ATP-producing enzyme, pyruvate kinase and mitochondria. 3) Finite element simulations of coupled partial differential equations using COMSOL and MATLAB. Results: Inhibition or activation ofmore » pumps on the cell membrane led to reduction or increase in aerobic glycolysis, respectively, while oxidative phosphorylation remained unchanged. These results were consistent with computational simulations of changes in short-timescale demand for energy by cell membrane processes. A specific model prediction was that the spatial distribution of ATP-producing enzymes in the glycolytic pathway must be primarily localized adjacent to the cell membrane, while mitochondria should be predominantly peri-nuclear. These predictions were confirmed experimentally. Conclusion: The results in this work support a new model for glucose metabolism in which glycolysis and oxidative phosphorylation supply different types of energy demand. Similar to power grid economics, optimal metabolic control requires the two pathways, even in normoxic conditions, to match two different types of energy demands. Cells use aerobic metabolism to meet baseline, steady energy demand and glycolytic metabolism to meet short-timescale energy demands, mainly from membrane transport activities, even in the presence of oxygen. This model provides a mechanism for the origin of the Warburg effect in cancer cells. Here, the Warburg effect emerges during carcinogenesis is a physiological response to an increase in energy demands from membrane transporters, required for cell division, growth, and migration. This work is supported by the NIH Physical Sciences in Oncology Center grant 1U54CA143970-03 and NIH R01 CA077575-10.« less
Tiered co-payments, pricing, and demand in reference price markets for pharmaceuticals.
Herr, Annika; Suppliet, Moritz
2017-12-01
Health insurance companies curb price-insensitive behavior and the moral hazard of insureds by means of cost-sharing, such as tiered co-payments or reference pricing in drug markets. This paper evaluates the effect of price limits - below which drugs are exempt from co-payments - on prices and on demand. First, using a difference-in-differences estimation strategy, we find that the new policy decreases prices by 5 percent for generics and increases prices by 4 percent for brand-name drugs in the German reference price market. Second, estimating a nested-logit demand model, we show that consumers appreciate co-payment exempt drugs and calculate lower price elasticities for brand-name drugs than for generics. This explains the different price responses of brand-name and generic drugs and shows that price-related co-payment tiers are an effective tool to steer demand to low-priced drugs. Copyright © 2017 Elsevier B.V. All rights reserved.
Sweis, Nadia J; Cherukupalli, Rajeev
2016-11-01
To estimate the price elasticity of cigarette demand for university students aged 18-24 years in Jordan. Questions from the Global Adult Tobacco Survey were adapted and administered to students from 10 public universities in Jordan in 2014. A two-part econometric model of cigarette demand was estimated. Nearly one-third of university students in Jordan smoke, purchasing 33.2 packs per month and paying 1.70 Jordanian dinars on average (US$2.40) for a pack of 20 cigarettes. The price elasticity of cigarette demand was estimated to be -1.15. Higher taxes may be particularly effective in reducing smoking among University students in Jordan. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.
Zhou, Shaoqi; Feng, Xinbin
2017-01-01
In this paper, a statistically-based experimental design with response surface methodology (RSM) was employed to examine the effects of functional conditions on the photoelectrocatalytic oxidation of landfill leachate using a Cu/N co-doped TiO2 (Ti) electrode. The experimental design method was applied to response surface modeling and the optimization of the operational parameters of the photoelectro-catalytic degradation of landfill leachate using TiO2 as a photo-anode. The variables considered were the initial chemical oxygen demand (COD) concentration, pH and the potential bias. Two dependent parameters were either directly measured or calculated as responses: chemical oxygen demand (COD) removal and total organic carbon (TOC) removal. The results of this investigation reveal that the optimum conditions are an initial pH of 10.0, 4377.98mgL-1 initial COD concentration and 25.0 V of potential bias. The model predictions and the test data were in satisfactory agreement. COD and TOC removals of 67% and 82.5%, respectively, were demonstrated. Under the optimal conditions, GC/MS showed 73 organic micro-pollutants in the raw landfill leachate which included hydrocarbons, aromatic compounds and esters. After the landfill leachate treatment processes, 38 organic micro-pollutants disappeared completely in the photoelectrocatalytic process. PMID:28671943
NASA Astrophysics Data System (ADS)
Klassert, C. J. A.; Yoon, J.; Gawel, E.; Klauer, B.; Sigel, K.; Talozi, S.; Lachaut, T.; Selby, P. D.; Knox, S.; Gorelick, S.; Tilmant, A.; Harou, J. J.; Mustafa, D.; Medellin-Azuara, J.; Rajsekhar, D.; Avisse, N.; Zhang, H.
2016-12-01
In arid countries around the world, markets of private small-scale water providers, mostly delivering water via tanker trucks, have emerged to balance the shortcomings of public water supply systems. While these markets can provide substantial contributions to meeting customers' water demands, they often partially rely on illegal water abstractions, thus imposing an unregulated and unmonitored strain on ground and surface water resources. Despite their important impacts on water users' welfare and resource sustainability, these markets are still poorly understood. We use a multi-agent, hydroeconomic simulation model, developed as part of the Jordan Water Project, to investigate the role of these markets in a country-wide case-study of Jordan. Jordan's water sector is characterized by a severe and growing scarcity of water resources, high intermittency in the public water network, and a strongly increasing demand due to an unprecedented refugee crisis. The tanker water market serves an important role in providing water from rural wells to households and commercial enterprises, especially during supply interruptions. In order to overcome the lack of direct data about this partially illegal market, we simulate demand and supply for tanker water. The demand for tanker water is conceptualized as a residual demand, remaining after a water user has depleted all available cheap and qualitatively reliable piped water. It is derived from residential and commercial demand functions on the basis of survey data. Tanker water supply is determined by farm simulation models calculating the groundwater pumping cost and the agricultural opportunity cost of tanker water. A market algorithm is then used to match rural supplies with users' demands, accounting for survey data on tanker operators' transport costs and profit expectations. The model is used to gain insights into the size of the tanker markets in all 89 subdistricts of Jordan and their responsiveness to various policy interventions. A dynamic coupling of the model with a country-wide groundwater model allows for projections of the spatial development of the tanker market over time. Accounting for this important supply source will be essential for the formulation of any policy aiming to reconcile the interests of water users with resource sustainability.
Dispatch Control with PEV Charging and Renewables for Multiplayer Game Application
DOE Office of Scientific and Technical Information (OSTI.GOV)
Davis, Nathan; Johnson, Brian; McJunkin, Timothy
This paper presents a demand response model for a hypothetical microgrid that integrates renewable resources and plug-in electric vehicle (PEV) charging systems. It is assumed that the microgrid has black start capability and that external generation is available for purchase while grid connected to satisfy additional demand. The microgrid is developed such that in addition to renewable, non-dispatchable generation from solar, wind and run of the river hydroelectric resources, local dispatchable generation is available in the form of small hydroelectric and moderately sized gas and coal fired facilities. To accurately model demand, the load model is separated into independent residential,more » commercial, industrial, and PEV charging systems. These are dispatched and committed based on a mixed integer linear program developed to minimize the cost of generation and load shedding while satisfying constraints associated with line limits, conservation of energy, and ramp rates of the generation units. The model extends a research tool to longer time frames intended for policy setting and educational environments and provides a realistic and intuitive understanding of beneficial and challenging aspects of electrification of vehicles combined with integration of green electricity production.« less
Research on electricity market operation mechanism and its benefit of demand side participation
NASA Astrophysics Data System (ADS)
Han, Shuai; Yan, Xu; Qin, Li-juan; Lin, Xi-qiao; Zeng, Bo
2017-08-01
Demand response plays an important role in maintaining the economic stability of the system, and has the characteristics of high efficiency, low cost, fast response, good environmental benefits and so on. Demand side resource is an important part of electricity market. The research of demand side resources in our country is still in the initial stage, but the opening of the electricity sales side provides a broad prospect for the development of electricity market. This paper summarizes the main types of demand side resources in our country, analyzes the economic principle of demand response from the micro perspective, puts forward some suggestions on the operation mechanism of China’s demand side resources participating in the electricity market under the condition of electricity sales side opening, analyzes the current situation of pricing in the electricity wholesale market and sets up the pricing strategy of the centralized wholesale market with the demand side power supply participating in quotation, which makes the social and economic benefits reach the maximum.
NASA Astrophysics Data System (ADS)
Lim, C. H.; Choi, Y.; Jeon, S. W.; Lee, W. K.
2017-12-01
Given their complexity and the number of stakeholders involved, it is difficult to solve social issues or problems based on an analysis that focuses on a single dimension. In particular, research surrounding climate change is inherently multidisciplinary and there is a need for highly pluralistic nexuses that can be used as a framework for policy decisions. Here, we suggest to water-centric nexus on agriculture and forest sector to improve response to climate change. The nexus is composed agricultural water demand and forest water supply to enhancing water-related adaptation to climate change in the Korean Peninsula. Agricultural productivity and water use related variables was estimating by EPIC crop model, and InVEST model applied for estimation of forest water supply. Results under two climate change scenarios (RCP4.5 and 8.5) and time period (2050s and 2070s), the forest water supply for the all future climate scenarios will increase significantly. In case of agriculture, irrigated crops experienced only the benefits of climate change, but rainfed crops were negatively impacted. It was also found that crop irrigation demand in the future is expected to be around twice as high as baseline levels, thus making irrigation more difficult to successfully implement. These hydrological threats have the potential to greatly reduce food security. In the nexus perspectives, the drop in the productivity of rainfed crops and the increase in irrigation demand in the agriculture sector can be resolved through interconnections with the forest sector. Appropriate management of the water supply in future climatic conditions characterized by increasing precipitation can maintain and expand agricultural areas through irrigation. To achieve this, a time-series water supply versus demand analysis must be performed so that an accurate balance between supply and demand can be established. Water-centric interactions of the agriculture and forest are the basis of nexus-based adaptation and they can suggest effective climate change responses for the Korean peninsula. In particular, this approach will be effective in transforming sectors that experience trade-offs into ones that promote synergies.
Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma
Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E.; Bollinger, Kathryn; Devos, Hannes
2017-01-01
Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal–Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups (p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1–Q3) 3 (2–6.50) vs. controls: 2 (0.50–2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2–6) vs. controls: 1 (0.50–2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls (p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma. PMID:28912712
Automated Dynamic Demand Response Implementation on a Micro-grid
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kuppannagari, Sanmukh R.; Kannan, Rajgopal; Chelmis, Charalampos
In this paper, we describe a system for real-time automated Dynamic and Sustainable Demand Response with sparse data consumption prediction implemented on the University of Southern California campus microgrid. Supply side approaches to resolving energy supply-load imbalance do not work at high levels of renewable energy penetration. Dynamic Demand Response (D 2R) is a widely used demand-side technique to dynamically adjust electricity consumption during peak load periods. Our D 2R system consists of accurate machine learning based energy consumption forecasting models that work with sparse data coupled with fast and sustainable load curtailment optimization algorithms that provide the ability tomore » dynamically adapt to changing supply-load imbalances in near real-time. Our Sustainable DR (SDR) algorithms attempt to distribute customer curtailment evenly across sub-intervals during a DR event and avoid expensive demand peaks during a few sub-intervals. It also ensures that each customer is penalized fairly in order to achieve the targeted curtailment. We develop near linear-time constant-factor approximation algorithms along with Polynomial Time Approximation Schemes (PTAS) for SDR curtailment that minimizes the curtailment error defined as the difference between the target and achieved curtailment values. Our SDR curtailment problem is formulated as an Integer Linear Program that optimally matches customers to curtailment strategies during a DR event while also explicitly accounting for customer strategy switching overhead as a constraint. We demonstrate the results of our D 2R system using real data from experiments performed on the USC smartgrid and show that 1) our prediction algorithms can very accurately predict energy consumption even with noisy or missing data and 2) our curtailment algorithms deliver DR with extremely low curtailment errors in the 0.01-0.05 kWh range.« less
Calatayud, Joaquin; Jakobsen, Markus D; Sundstrup, Emil; Casaña, Jose; Andersen, Lars L
2015-12-01
Regular physical activity is important for longevity and health, but knowledge about the optimal dose of physical activity for maintaining good work ability is unknown. This study investigates the association between intensity and duration of physical activity during leisure time and work ability in relation to physical demands of the job. From the 2010 round of the Danish Work Environment Cohort Study, currently employed wage earners with physically demanding work (n = 2952) replied to questions about work, lifestyle and health. Excellent (100 points), very good (75 points), good (50 points), fair (25 points) and poor (0 points) work ability in relation to the physical demands of the job was experienced by 18%, 40%, 30%, 10% and 2% of the respondents, respectively. General linear models that controlled for gender, age, physical and psychosocial work factors, lifestyle and chronic disease showed that the duration of high-intensity physical activity during leisure was positively associated with work ability, in a dose-response fashion (p < 0.001). Those performing ⩾ 5 hours of high-intensity physical activity per week had on average 8 points higher work ability than those not performing such activities. The duration of low-intensity leisure-time physical activity was not associated with work ability (p = 0.5668). The duration of high-intensity physical activity during leisure time is associated in a dose-response fashion with work ability, in workers with physically demanding jobs. © 2015 the Nordic Societies of Public Health.
NASA Astrophysics Data System (ADS)
Kumar, Santosh; Raychowdhury, Prishati; Gundlapalli, Prabhakar
2015-06-01
Design of critical facilities such as nuclear power plant requires an accurate and precise evaluation of seismic demands, as any failure of these facilities poses immense threat to the community. Design complexity of these structures reinforces the necessity of a robust 3D modeling and analysis of the structure and the soil-foundation interface. Moreover, it is important to consider the multiple components of ground motion during time history analysis for a realistic simulation. Present study is focused on investigating the seismic response of a nuclear containment structure considering nonlinear Winkler-based approach to model the soil-foundation interface using a distributed array of inelastic springs, dashpots and gap elements. It is observed from this study that the natural period of the structure increases about 10 %, whereas the force demands decreases up to 24 % by considering the soil-structure interaction. Further, it is observed that foundation deformations, such as rotation and sliding are affected by the embedment ratio, indicating an increase of up to 56 % in these responses for a reduction of embedment from 0.5 to 0.05× the width of the footing.
Poor impulse control predicts inelastic demand for nicotine but not alcohol in rats.
Diergaarde, Leontien; van Mourik, Yvar; Pattij, Tommy; Schoffelmeer, Anton N M; De Vries, Taco J
2012-05-01
Tobacco and alcohol dependence are characterized by continued use despite deleterious health, social and occupational consequences, implying that addicted individuals pay a high price for their use. In behavioral economic terms, such persistent consumption despite increased costs can be conceptualized as inelastic demand. Recent animal studies demonstrated that high-impulsive individuals are more willing to work for nicotine or cocaine infusions than their low-impulsive counterparts, indicating that this trait might be causally related to inelastic drug demand. By employing progressive ratio schedules of reinforcement combined with a behavioral economics approach of analysis, we determined whether trait impulsivity is associated with an insensitivity of nicotine or alcohol consumption to price increments. Rats were trained on a delayed discounting task, measuring impulsive choice. Hereafter, high- and low-impulsive rats were selected and trained to nose poke for intravenous nicotine or oral alcohol. Upon stable self-administration on a continuous reinforcement schedule, the price (i.e. response requirement) was increased. Demand curves, depicting the relationship between price and consumption, were produced using Hursh's exponential demand equation. Similar to human observations, nicotine and alcohol consumption in rats fitted this equation, thereby demonstrating the validity of our model. Moreover, high-impulsive rats displayed inelastic nicotine demand, as their nicotine consumption was less sensitive to price increments as compared with that in low-impulsive rats. Impulsive choice was not related to differences in alcohol demand elasticity. Our model seems well suited for studying nicotine and alcohol demand in rats and, as such, might contribute to our understanding of tobacco and alcohol dependence. © 2011 The Authors, Addiction Biology © 2011 Society for the Study of Addiction.
Price responsiveness of demand for cigarettes: does rationality matter?
Laporte, Audrey
2006-01-01
Meta-analysis is applied to aggregate-level studies that model the demand for cigarettes using static, myopic, or rational addiction frameworks in an attempt to synthesize key findings in the literature and to identify determinants of the variation in reported price elasticity estimates across studies. The results suggest that the rational addiction framework produces statistically similar estimates to the static framework but that studies that use the myopic framework tend to report more elastic price effects. Studies that applied panel data techniques or controlled for cross-border smuggling reported more elastic price elasticity estimates, whereas the use of instrumental variable techniques and time trends or time dummy variables produced less elastic estimates. The finding that myopic models produce different estimates than either of the other two model frameworks underscores that careful attention must be given to time series properties of the data.
Household social characteristics of the demand for alcoholic beverages among Spanish students.
Gil-Lacruz, Ana Isabel; Gil-Lacruz, Marta
2013-03-01
This paper studies how household social capital affects adolescents' demand for alcoholic drinks. To that end, we focus on a theoretical framework that combines elements from the Model of Rational Addiction and the Model of Social Economics. For the empirical framework, we use a simultaneous Type II Tobit model, with data drawn from the Spanish National Survey on Drug Use in the School Population (2000, 2002, and 2004). The sample is comprised of 12,627 students aged 17 years old. Our results confirm that parents' decisions about drinking are even more decisive in their children's behavior than socioeconomic variables, such as parents' educative levels or working status. Parental responsibilities go beyond the endowment of health and educational goods and services; so, these results suggest the importance of designing family-drug use prevention programs. The study's limitations are noted.
Focus Group Study Exploring Factors Related to Frequent Sickness Absence
van Rhenen, Willem
2016-01-01
Introduction Research investigating frequent sickness absence (3 or more episodes per year) is scarce and qualitative research from the perspective of frequent absentees themselves is lacking. The aim of the current study is to explore awareness, determinants of and solutions to frequent sickness absence from the perspective of frequent absentees themselves. Methods We performed a qualitative study of 3 focus group discussions involving a total of 15 frequent absentees. Focus group discussions were audiotaped and transcribed verbatim. Results were analyzed with the Graneheim method using the Job Demands Resources (JD–R) model as theoretical framework. Results Many participants were not aware of their frequent sickness absence and the risk of future long-term sickness absence. As determinants, participants mentioned job demands, job resources, home demands, poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Managing these factors and improving communication (skills) were regarded as solutions to reduce frequent sickness absence. Conclusions The JD–R model provided a framework for determinants of and solutions to frequent sickness absence. Additional determinants were poor health, chronic illness, unhealthy lifestyles, and diminished feeling of responsibility to attend work in cases of low job resources. Frequent sickness absence should be regarded as a signal that something is wrong. Managers, supervisors, and occupational health care providers should advise and support frequent absentees to accommodate job demands, increase both job and personal resources, and improve health rather than express disapproval of frequent sickness absence and apply pressure regarding work attendance. PMID:26872050
Barron J. Orr; Wolfgang Grunberg; Amanda B. Cockerham; Anne Y. Thwaits; Heather S. Severson; Noah M. D. Lerman; Rachel M. Miller; Michael Haseltine; Barbara J. Morehouse; Jonathan T. Overpeck; Stephen R. Yool; Thomas W. Swetnam; Gary L. Christopherson
2005-01-01
The demand for strategic planning tools that account for climate and human influences on wildfire hazard is growing. In response, the University of Arizona, through an EPA STAR Grant has undertaken interdisciplinary research to characterize the human and climate dimensions of wildfire. The resulting Fire-Climate-Society (FCS-1) prototype model developed for Sky Islands...
ERIC Educational Resources Information Center
Sanders, Jack
The Educational Services Office (ESO) of the Appalachia Educational Laboratory (AEL) sought an organizational strategy that would improve its ability to meet client demand without sacrificing the integrity of its programs or the fulfillment of its institutional responsibilities. Three alternative organizational strategies were identified:…
Grebenstein, Patricia E; Burroughs, Danielle; Roiko, Samuel A; Pentel, Paul R; LeSage, Mark G
2015-06-01
The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. The present study examined these issues in a rodent nicotine self-administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Grebenstein, Patricia E.; Burroughs, Danielle; Roiko, Samuel A.; Pentel, Paul R.; LeSage, Mark G.
2015-01-01
Background The FDA is considering reducing the nicotine content in tobacco products as a population-based strategy to reduce tobacco addiction. Research is needed to determine the threshold level of nicotine needed to maintain smoking and the extent of compensatory smoking that could occur during nicotine reduction. Sources of variability in these measures across sub-populations also need to be identified so that policies can take into account the risks and benefits of nicotine reduction in vulnerable populations. Methods The present study examined these issues in a rodent nicotine self- administration model of nicotine reduction policy to characterize individual differences in nicotine reinforcement thresholds, degree of compensation, and elasticity of demand during progressive reduction of the unit nicotine dose. The ability of individual differences in baseline nicotine intake and nicotine pharmacokinetics to predict responses to dose reduction was also examined. Results Considerable variability in the reinforcement threshold, compensation, and elasticity of demand was evident. High baseline nicotine intake was not correlated with the reinforcement threshold, but predicted less compensation and less elastic demand. Higher nicotine clearance predicted low reinforcement thresholds, greater compensation, and less elastic demand. Less elastic demand also predicted lower reinforcement thresholds. Conclusions These findings suggest that baseline nicotine intake, nicotine clearance, and the essential value of nicotine (i.e. elasticity of demand) moderate the effects of progressive nicotine reduction in rats and warrant further study in humans. They also suggest that smokers with fast nicotine metabolism may be more vulnerable to the risks of nicotine reduction. PMID:25891231
Quantifying the link between crop production and mined groundwater irrigation in China.
Grogan, Danielle S; Zhang, Fan; Prusevich, Alexander; Lammers, Richard B; Wisser, Dominik; Glidden, Stanley; Li, Changsheng; Frolking, Steve
2015-04-01
In response to increasing demand for food, Chinese agriculture has both expanded and intensified over the past several decades. Irrigation has played a key role in increasing crop production, and groundwater is now an important source of irrigation water. Groundwater abstraction in excess of recharge (which we use here to estimate groundwater mining) has resulted in declining groundwater levels and could eventually restrict groundwater availability. In this study we used a hydrological model, WBMplus, in conjunction with a process based crop growth model, DNDC, to evaluate Chinese agriculture's recent dependence upon mined groundwater, and to quantify mined groundwater-dependent crop production across a domain that includes variation in climate, crop choice, and management practices. This methodology allowed for the direct attribution of crop production to irrigation water from rivers and reservoirs, shallow (renewable) groundwater, and mined groundwater. Simulating 20 years of weather variability and circa year 2000 crop areas, we found that mined groundwater fulfilled 20%-49% of gross irrigation water demand, assuming all demand was met. Mined groundwater accounted for 15%-27% of national total crop production. There was high spatial variability across China in irrigation water demand and crop production derived from mined groundwater. We find that climate variability and mined groundwater demand do not operate independently; rather, years in which irrigation water demand is high due to the relatively hot and dry climate also experience limited surface water supplies and therefore have less surface water with which to meet that high irrigation water demand. Copyright © 2014 Elsevier B.V. All rights reserved.
Demand Curves for Hypothetical Cocaine in Cocaine-Dependent Individuals
Bruner, Natalie R.; Johnson, Matthew W.
2013-01-01
Rationale Drug purchasing tasks have been successfully used to examine demand for hypothetical consumption of abused drugs including heroin, nicotine, and alcohol. In these tasks drug users make hypothetical choices whether to buy drugs, and if so, at what quantity, at various potential prices. These tasks allow for behavioral economic assessment of that drug's intensity of demand (preferred level of consumption at extremely low prices) and demand elasticity (sensitivity of consumption to price), among other metrics. However, a purchasing task for cocaine in cocaine-dependent individuals has not been investigated. Objectives This study examined a novel Cocaine Purchasing Task and the relation between resulting demand metrics and self-reported cocaine use data. Methods Participants completed a questionnaire assessing hypothetical purchases of cocaine units at prices ranging from $0.01 to $1,000. Demand curves were generated from responses on the Cocaine Purchasing Task. Correlations compared metrics from the demand curve to measures of real-world cocaine use. Results Group and individual data were well modeled by a demand curve function. The validity of the Cocaine Purchasing Task was supported by a significant correlation between the demand curve metrics of demand intensity and Omax (determined from Cocaine Purchasing Task data) and self-reported measures of cocaine use. Partial correlations revealed that after controlling for demand intensity, demand elasticity and the related measure, Pmax, were significantly correlated with real-world cocaine use. Conclusions Results indicate that the Cocaine Purchasing Task produces orderly demand curve data, and that these data relate to real-world measures of cocaine use. PMID:24217899
An analytics approach to designing patient centered medical homes.
Ajorlou, Saeede; Shams, Issac; Yang, Kai
2015-03-01
Recently the patient centered medical home (PCMH) model has become a popular team based approach focused on delivering more streamlined care to patients. In current practices of medical homes, a clinical based prediction frame is recommended because it can help match the portfolio capacity of PCMH teams with the actual load generated by a set of patients. Without such balances in clinical supply and demand, issues such as excessive under and over utilization of physicians, long waiting time for receiving the appropriate treatment, and non-continuity of care will eliminate many advantages of the medical home strategy. In this paper, by using the hierarchical generalized linear model with multivariate responses, we develop a clinical workload prediction model for care portfolio demands in a Bayesian framework. The model allows for heterogeneous variances and unstructured covariance matrices for nested random effects that arise through complex hierarchical care systems. We show that using a multivariate approach substantially enhances the precision of workload predictions at both primary and non primary care levels. We also demonstrate that care demands depend not only on patient demographics but also on other utilization factors, such as length of stay. Our analyses of a recent data from Veteran Health Administration further indicate that risk adjustment for patient health conditions can considerably improve the prediction power of the model.
Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application
NASA Astrophysics Data System (ADS)
Chen, Jinduan; Boccelli, Dominic L.
2018-02-01
Consumer water demands are not typically measured at temporal or spatial scales adequate to support real-time decision making, and recent approaches for estimating unobserved demands using observed hydraulic measurements are generally not capable of forecasting demands and uncertainty information. While time series modeling has shown promise for representing total system demands, these models have generally not been evaluated at spatial scales appropriate for representative real-time modeling. This study investigates the use of a double-seasonal time series model to capture daily and weekly autocorrelations to both total system demands and regional aggregated demands at a scale that would capture demand variability across a distribution system. Emphasis was placed on the ability to forecast demands and quantify uncertainties with results compared to traditional time series pattern-based demand models as well as nonseasonal and single-seasonal time series models. Additional research included the implementation of an adaptive-parameter estimation scheme to update the time series model when unobserved changes occurred in the system. For two case studies, results showed that (1) for the smaller-scale aggregated water demands, the log-transformed time series model resulted in improved forecasts, (2) the double-seasonal model outperformed other models in terms of forecasting errors, and (3) the adaptive adjustment of parameters during forecasting improved the accuracy of the generated prediction intervals. These results illustrate the capabilities of time series modeling to forecast both water demands and uncertainty estimates at spatial scales commensurate for real-time modeling applications and provide a foundation for developing a real-time integrated demand-hydraulic model.
Water stress, water salience, and the implications for water supply planning
NASA Astrophysics Data System (ADS)
Garcia, M. E.; Islam, S.
2017-12-01
Effectively addressing the water supply challenges posed by urbanization and climate change requires a holistic understanding of the water supply system, including the impact of human behavior on system dynamics. Decision makers have limits to available information and information processing capacity, and their attention is not equally distributed among risks. The salience of a given risk is higher when increased attention is directed to it and though perceived risk may increase, real risk does not change. Relevant to water supply planning is how and when water stress results in an increased salience of water risks. This work takes a socio-hydrological approach to develop a water supply planning model that includes water consumption as an endogenous variable, in the context of Las Vegas, NV. To understand the benefits and limitations of this approach, this model is compared to a traditional planning model that uses water consumption scenarios. Both models are applied to project system reliability and water stress under four streamflow and demographic scenarios, and to assess supply side responses to changing conditions. The endogenous demand model enables the identification of feedback between both supply and demand management decisions on future water consumption and system performance. This model, while specific to the Las Vegas case, demonstrates a prototypical modeling framework capable of examining water-supply demand interactions by incorporating water stress driven conservation.
Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network
Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun
2016-01-01
A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0–1 integer programming to describe passengers’ responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated. PMID:27935963
Modeling and Simulating Passenger Behavior for a Station Closure in a Rail Transit Network.
Yin, Haodong; Han, Baoming; Li, Dewei; Wu, Jianjun; Sun, Huijun
2016-01-01
A station closure is an abnormal operational situation in which the entrances or exits of a rail transit station have to be closed for some time due to an unexpected incident. A novel approach is developed to estimate the impacts of the alternative station closure scenarios on both passenger behavioral choices at the individual level and passenger demand at the disaggregate level in a rail transit network. Therefore, the contributions of this study are two-fold: (1) A basic passenger behavior optimization model is mathematically constructed based on 0-1 integer programming to describe passengers' responses to alternative origin station closure scenarios and destination station closure scenarios; this model also considers the availability of multi-mode transportation and the uncertain duration of the station closure; (2) An integrated solution algorithm based on the passenger simulation is developed to solve the proposed model and to estimate the effects of a station closure on passenger demand in a rail transit network. Furthermore, 13 groups of numerical experiments based on the Beijing rail transit network are performed as case studies with 2,074,267 records of smart card data. The comparisons of the model outputs and the manual survey show that the accuracy of our proposed behavior optimization model is approximately 80%. The results also show that our model can be used to capture the passenger behavior and to quantitatively estimate the effects of alternative closure scenarios on passenger flow demand for the rail transit network. Moreover, the closure duration and its overestimation greatly influence the individual behavioral choices of the affected passengers and the passenger demand. Furthermore, if the rail transit operator can more accurately estimate the closure duration (namely, as g approaches 1), the impact of the closure can be somewhat mitigated.
Correlations between Energy and Displacement Demands for Performance-Based Seismic Engineering
NASA Astrophysics Data System (ADS)
Mollaioli, Fabrizio; Bruno, Silvia; Decanini, Luis; Saragoni, Rodolfo
2011-01-01
The development of a scientific framework for performance-based seismic engineering requires, among other steps, the evaluation of ground motion intensity measures at a site and the characterization of their relationship with suitable engineering demand parameters (EDPs) which describe the performance of a structure. In order to be able to predict the damage resulting from earthquake ground motions in a structural system, it is first necessary to properly identify ground motion parameters that are well correlated with structural response and, in turn, with damage. Since structural damage during an earthquake ground motion may be due to excessive deformation or to cumulative cyclic damage, reliable methods for estimating displacement demands on structures are needed. Even though the seismic performance is directly related to the global and local deformations of the structure, energy-based methodologies appear more helpful in concept, as they permit a rational assessment of the energy absorption and dissipation mechanisms that can be effectively accomplished to balance the energy imparted to the structure. Moreover, energy-based parameters are directly related to cycles of response of the structure and, therefore, they can implicitly capture the effect of ground motion duration, which is ignored by conventional spectral parameters. Therefore, the identification of reliable relationships between energy and displacement demands represents a fundamental issue in both the development of more reliable seismic code provisions and the evaluation of seismic vulnerability aimed at the upgrading of existing hazardous facilities. As these two aspects could become consistently integrated within a performance-based seismic design methodology, understanding how input and dissipated energy are correlated with displacement demands emerges as a decisive prerequisite. The aim of the present study is the establishment of functional relationships between input and dissipated energy (that can be considered as parameters representative of the amplitude, frequency content and duration of earthquake ground motions) and displacement-based response measures that are well correlated to structural and non-structural damage. For the purpose of quantifying the EDPs to be related to the energy measures, for comprehensive range of ground motion and structural characteristics, both simplified and more accurate numerical models will be used in this study for the estimation of local and global displacement and energy demands. Parametric linear and nonlinear time-history analyses will be performed on elastic and inelastic SDOF and MDOF systems, in order to assume information on the seismic response of a wide range of current structures. Hysteretic models typical of frame force/displacement behavior will be assumed for the local inelastic cyclic response of the systems. A wide range of vibration periods will be taken into account so as to define displacement, interstory drift and energy spectra for MDOF systems. Various scalar measures related to the deformation demand will be used in this research. These include the spectral displacements, the peak roof drift ratio, and the peak interstory drift ratio. A total of about 900 recorded ground motions covering a broad variety of condition in terms of frequency content, duration and amplitude will be used as input in the dynamic analyses. The records are obtained from 40 earthquakes and grouped as a function of magnitude of the event, source-to-site condition and site soil condition. In addition, in the data-set of records a considerable number of near-fault signals is included, in recognition of the particular significance of pulse-like time histories in causing large seismic demands to the structures.
O'Donnell, Emma; Landolt, Kathleen; Hazi, Agnes; Dragano, Nico; Wright, Bradley J
2015-01-01
We assessed in an experimental design whether the stress response towards a work task was moderated by the autonomy to choose a break during the assigned time to complete the task. This setting is defined in accordance with the theoretical framework of the job-demand-control (JDC) model of work related stress. The findings from naturalistic investigations of a stress-buffering effect of autonomy (or 'buffer hypothesis') are equivocal and the experimental evidence is limited, especially with relation to physiological indices of stress. Our objective was to investigate if increased autonomy in a particular domain (break time control) was related with adaptive physiology using objective physiological markers of stress; heart rate variability (HRV) and salivary alpha amylase (sAA). We used a within-subject design and the 60 female participants were randomly assigned to an autonomy (free timing of break) and standard conditions (fixed timing of break) of a word processing task in a simulated office environment in a random order. Participants reported increased perceptions of autonomy, no difference in demand and performed worse in the task in the break-time autonomy versus the standard condition. The results revealed support for the manipulation of increased autonomy, but in the opposing direction. Increased autonomy was related with dysregulated physiological reactivity, synonymous with typical increased stress responses. Potentially, our findings may indicate that autonomy is not necessary a resource but could become an additional stressor when it adds additional complexity while the amount of work (demands) remains unchanged. Further, our findings underscore the need to collect objective physiological evidence of stress to supplement self-reported information. Self-report biases may partially explain the inconsistent findings with the buffer hypothesis. Copyright © 2014 Elsevier Ltd. All rights reserved.
Spatial effects, sampling errors, and task specialization in the honey bee.
Johnson, B R
2010-05-01
Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists.
Designing for Productive Adaptations of Curriculum Interventions
ERIC Educational Resources Information Center
Debarger, Angela Haydel; Choppin, Jeffrey; Beauvineau, Yves; Moorthy, Savitha
2013-01-01
Productive adaptations at the classroom level are evidence-based curriculum adaptations that are responsive to the demands of a particular classroom context and still consistent with the core design principles and intentions of a curriculum intervention. The model of design-based implementation research (DBIR) offers insights into complexities and…
Development of a sheep challenge model for Rift Valley fever
USDA-ARS?s Scientific Manuscript database
Rift Valley fever is a zoonotic disease responsible for severe outbreaks in ruminant livestock characterized by mass abortion and high mortality rates in younger animals. The lack of a fully licensed vaccine in the US has spurred increased demand for a protective vaccine. Thus, development of a reli...
ERIC Educational Resources Information Center
Kedian, Jeremy; Giles, David; Morrison, Michele; Fletcher, Murray
2016-01-01
Rapidly changing educational contexts demand deft leadership responses. In this fluid environment, it is imperative that leadership learning models sound educational praxis. Such praxis necessitates the inclusion of participant voices within relational and dialogic processes that enable authentic, creative and collaborative thinking. This paper…
Shared Governance in Times of Change: A Practical Guide for Universities and Colleges
ERIC Educational Resources Information Center
Bahls, Steven S.
2014-01-01
Today's challenging higher education environment demands a new way of making decisions. Changing business models and methodologies for delivering academic programs present new opportunities (as well as risks) and call for innovative responses. This publication aims to "reboot" dialogues among boards, presidents, and faculties. It creates…
Industry into Teaching: An Alternative Model
ERIC Educational Resources Information Center
Green, Annette; Randall, Rachael; Francis, Rod
2004-01-01
Teacher shortages have encouraged initiatives to tailor training programs to meet the demand in both past, current and future contexts. Such programs have been streamlined to ensure a rapid response to shortages, in addition to also drawing participants from non-traditional groups as a source of potential educators. More broadly in teacher…
OpenADR Specification to Ease Saving Power in Buildings
None
2017-12-09
A new data model developed by researchers at the Department of Energys Lawrence Berkeley National Laboratory and their colleagues at other universities and in the private sector will help facilities and buildings save power through automated demand response technology, and advance the development of the Smart Grid.
Work Satisfaction and Family Responsibility Correlates of Employment among Nurses.
ERIC Educational Resources Information Center
Gaertner, Karen N.
1984-01-01
Employment status of nurses is examined in the context of a role conflict-job satisfaction model. It is proposed that women become nurses to provide important care to patients but are pushed away from the profession if there are competing demands for their time from children or spouse. (CT)
ERIC Educational Resources Information Center
Jeffreys, Andrea
2012-01-01
The Australian Government decision in response to the Bradley review to introduce a demand-driven funding model for undergraduate university places from 2012 was met with mixed reaction across the higher education sector. The removal of caps without subsequent fee deregulation is considered by some to be unsustainable. Opinions suggest that…
Foresee: A user-centric home energy management system for energy efficiency and demand response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Xin; Baker, Kyri A.; Christensen, Dane T.
This paper presents foresee, a user-centric home energy management system that can help optimize how a home operates to concurrently meet users' needs, achieve energy efficiency and commensurate utility cost savings, and reliably deliver grid services based on utility signals. Foresee is built on a multiobjective model predictive control framework, wherein the objectives consist of energy cost, thermal comfort, user convenience, and carbon emission. Foresee learns user preferences on different objectives and acts on their behalf to operate building equipment, such as home appliances, photovoltaic systems, and battery storage. In this work, machine-learning algorithms were used to derive data-driven appliancemore » models and usage patterns to predict the home's future energy consumption. This approach enables highly accurate predictions of comfort needs, energy costs, environmental impacts, and grid service availability. Simulation studies were performed on field data from a residential building stock data set collected in the Pacific Northwest. Results indicated that foresee generated up to 7.6% whole-home energy savings without requiring substantial behavioral changes. When responding to demand response events, foresee was able to provide load forecasts upon receipt of event notifications and delivered the committed demand response services with 10% or fewer errors. Foresee fully utilized the potential of the battery storage and controllable building loads and delivered up to 7.0-kW load reduction and 13.5-kW load increase. As a result, these benefits are provided while maintaining the occupants' thermal comfort or convenience in using their appliances.« less
Vastamäki, Heidi; Vastamäki, Martti; Laimi, Katri; Saltychev, Michail
2017-07-01
Poorly functioning work environments may lead to dissatisfaction for the employees and financial loss for the employers. The Job Content Questionnaire (JCQ) was designed to measure social and psychological characteristics of work environments. To investigate the factor construct of the Finnish 14-item version of JCQ when applied to professional orchestra musicians. In a cross-sectional survey, the questionnaire was sent by mail to 1550 orchestra musicians and students. 630 responses were received. Full data were available for 590 respondents (response rate 38%).The questionnaire also contained questions on demographics, job satisfaction, health status, health behaviors, and intensity of playing music. Confirmatory factor analysis of the 2-factor model of JCQ was conducted. Of the 5 estimates, JCQ items in the "job demand" construct, the "conflicting demands" (question 5) explained most of the total variance in this construct (79%) demonstrating almost perfect correlation of 0.63. In the construct of "job control," "opinions influential" (question 10) demonstrated a perfect correlation index of 0.84 and the items "little decision freedom" (question 14) and "allows own decisions" (question 6) showed substantial correlations of 0.77 and 0.65. The 2-factor model of the Finnish 14-item version of JCQ proposed in this study fitted well into the observed data. The "conflicting demands," "opinions influential," "little decision freedom," and "allows own decisions" items demonstrated the strongest correlations with latent factors suggesting that in a population similar to the studied one, especially these items should be taken into account when observed in the response of a population.
Tovar, Alison; Choumenkovitch, Silvina F; Hennessy, Erin; Boulos, Rebecca; Must, Aviva; Hughes, Sheryl O; Gute, David M; Vikre, Emily Kuross; Economos, Christina D
2015-12-01
We explored the influence of immigrant mothers feeding style on their children's fruit, vegetable and whole grain intake and how this relationship differed by mother's time in the U.S. Baseline data were collected on mother-child (3-12 yrs) dyads enrolled in Live Well (n = 313), a community-based, participatory, randomized controlled lifestyle intervention (2008-2013). Socio-demographics, years of residence in the U.S., behavioral data, and responses to the Caregiver's Feeding Styles Questionnaire (CFSQ) were obtained from the mother. Measured heights and weights were obtained for both mother and child. Child dietary intake was assessed using the Block Food Screener. Separate multiple linear regression models were run, adjusting for child and mother covariates. Interactions between feeding styles and years in the U.S. (<5 and ≥ 5 years), ethnicity, and child age were tested. Sixty-nine percent of mothers were overweight or obese, 46% of the children were overweight or obese. For mothers in the U.S. for<5 years, having a low demanding/high responsive style was associated with lower child intake of whole grains in adjusted models vs. a high demanding/high responsive style (p < 0.05). This was not seen for mothers in the U.S. for≥5 years. Thus, the influence of feeding style on dietary intake may change with length of time in the U.S. These hypotheses-generating findings call for future research to understand how broader socio-cultural factors influence the feeding dynamic among immigrants. Copyright © 2015 Elsevier Ltd. All rights reserved.
Foresee: A user-centric home energy management system for energy efficiency and demand response
Jin, Xin; Baker, Kyri A.; Christensen, Dane T.; ...
2017-08-23
This paper presents foresee, a user-centric home energy management system that can help optimize how a home operates to concurrently meet users' needs, achieve energy efficiency and commensurate utility cost savings, and reliably deliver grid services based on utility signals. Foresee is built on a multiobjective model predictive control framework, wherein the objectives consist of energy cost, thermal comfort, user convenience, and carbon emission. Foresee learns user preferences on different objectives and acts on their behalf to operate building equipment, such as home appliances, photovoltaic systems, and battery storage. In this work, machine-learning algorithms were used to derive data-driven appliancemore » models and usage patterns to predict the home's future energy consumption. This approach enables highly accurate predictions of comfort needs, energy costs, environmental impacts, and grid service availability. Simulation studies were performed on field data from a residential building stock data set collected in the Pacific Northwest. Results indicated that foresee generated up to 7.6% whole-home energy savings without requiring substantial behavioral changes. When responding to demand response events, foresee was able to provide load forecasts upon receipt of event notifications and delivered the committed demand response services with 10% or fewer errors. Foresee fully utilized the potential of the battery storage and controllable building loads and delivered up to 7.0-kW load reduction and 13.5-kW load increase. As a result, these benefits are provided while maintaining the occupants' thermal comfort or convenience in using their appliances.« less
Choumenkovitch, Silvina F.; Hennessy, Erin; Boulos, Rebecca; Must, Aviva; Hughes, Sheryl O.; Gute, David M.; Vikre, Emily Kuross; Economos, Christina D.
2015-01-01
We explored the influence of immigrant mothers feeding style on their children’s fruit, vegetable and whole grain intake and how this relationship differed by mother’s time in the U.S. Baseline data were collected on mother-child (3–12 yrs.) dyads enrolled in Live Well (n=313), a community-based, participatory, randomized controlled lifestyle intervention (2008–2013). Socio-demographics, years of residence in the U.S., behavioral data, and responses to the Caregiver’s Feeding Styles Questionnaire (CFSQ) were obtained from the mother. Measured heights and weights were obtained for both mother and child. Child dietary intake was assessed using the Block Food Screener. Separate multiple linear regression models were run, adjusting for child and mother covariates. Interactions between feeding styles and years in the U.S. (<5 and ≥5 years), ethnicity, and child age were tested. Sixty-nine percent of mothers were overweight or obese, 46% of the children were overweight or obese. For mothers in the U.S. for <5 years, having a low demanding/high responsive style was associated with lower child intake of whole grains in adjusted models vs. a high demanding/high responsive style (p<0.05). This was not seen for mothers in the U.S. for ≥5 years. Thus, the influence of feeding style on dietary intake may change with length of time in the U.S. These hypotheses-generating findings call for future research to understand how broader socio-cultural factors influence the feeding dynamic among immigrants. PMID:26122753
32 CFR 1805.4 - Procedure for production.
Code of Federal Regulations, 2010 CFR
2010-07-01
... responsibility for the information sought in the demand shall determine whether any information or materials may properly be produced in response to the demand, except that NACIC Counsel may assert any and all legal... demand for production is made upon an employee, the employee shall immediately notify NACIC Counsel, who...
NASA Astrophysics Data System (ADS)
Perera, Kushan C.; Western, Andrew W.; Robertson, David E.; George, Biju; Nawarathna, Bandara
2016-06-01
Irrigation demands fluctuate in response to weather variations and a range of irrigation management decisions, which creates challenges for water supply system operators. This paper develops a method for real-time ensemble forecasting of irrigation demand and applies it to irrigation command areas of various sizes for lead times of 1 to 5 days. The ensemble forecasts are based on a deterministic time series model coupled with ensemble representations of the various inputs to that model. Forecast inputs include past flow, precipitation, and potential evapotranspiration. These inputs are variously derived from flow observations from a modernized irrigation delivery system; short-term weather forecasts derived from numerical weather prediction models and observed weather data available from automatic weather stations. The predictive performance for the ensemble spread of irrigation demand was quantified using rank histograms, the mean continuous rank probability score (CRPS), the mean CRPS reliability and the temporal mean of the ensemble root mean squared error (MRMSE). The mean forecast was evaluated using root mean squared error (RMSE), Nash-Sutcliffe model efficiency (NSE) and bias. The NSE values for evaluation periods ranged between 0.96 (1 day lead time, whole study area) and 0.42 (5 days lead time, smallest command area). Rank histograms and comparison of MRMSE, mean CRPS, mean CRPS reliability and RMSE indicated that the ensemble spread is generally a reliable representation of the forecast uncertainty for short lead times but underestimates the uncertainty for long lead times.
NASA Astrophysics Data System (ADS)
Bertazzon, Stefania
The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new directions for further work in the field of spatial analysis, in conjunction with the development of specific software.
NASA Astrophysics Data System (ADS)
Jin, L.; Borgeson, S.; Fredman, D.; Hans, L.; Spurlock, A.; Todd, A.
2015-12-01
California's renewable portfolio standard (2012) requires the state to get 33% of its electricity from renewable sources by 2020. Increased share of variable renewable sources such as solar and wind in the California electricity system may require more grid flexibility to insure reliable power services. Such grid flexibility can be potentially provided by changes in end use electricity consumptions in response to grid conditions (demand-response). In the solar case, residential consumption in the late afternoon can be used as reserve capacity to balance the drop in solar generation. This study presents our initial attempt to identify, from a behavior perspective, residential demand response potentials in relation to solar ramp events using a data-driven approach. Based on hourly residential energy consumption data, we derive representative daily load shapes focusing on discretionary consumption with an innovative clustering analysis technique. We aggregate the representative load shapes into behavior groups in terms of the timing and rhythm of energy use in the context of solar ramp events. Households of different behavior groups that are active during hours with high solar ramp rates are identified for capturing demand response potential. Insights into the nature and predictability of response to demand-response programs are provided.
Humanitarian response: improving logistics to save lives.
McCoy, Jessica
2008-01-01
Each year, millions of people worldwide are affected by disasters, underscoring the importance of effective relief efforts. Many highly visible disaster responses have been inefficient and ineffective. Humanitarian agencies typically play a key role in disaster response (eg, procuring and distributing relief items to an affected population, assisting with evacuation, providing healthcare, assisting in the development of long-term shelter), and thus their efficiency is critical for a successful disaster response. The field of disaster and emergency response modeling is well established, but the application of such techniques to humanitarian logistics is relatively recent. This article surveys models of humanitarian response logistics and identifies promising opportunities for future work. Existing models analyze a variety of preparation and response decisions (eg, warehouse location and the distribution of relief supplies), consider both natural and manmade disasters, and typically seek to minimize cost or unmet demand. Opportunities to enhance the logistics of humanitarian response include the adaptation of models developed for general disaster response; the use of existing models, techniques, and insights from the literature on commercial supply chain management; the development of working partnerships between humanitarian aid organizations and private companies with expertise in logistics; and the consideration of behavioral factors relevant to a response. Implementable, realistic models that support the logistics of humanitarian relief can improve the preparation for and the response to disasters, which in turn can save lives.
Guerrero-López, Carlos M; Unar-Munguía, Mishel; Colchero, M Arantxa
2017-02-10
Chile is the second world's largest per capita consumer of caloric beverages. Caloric beverages are associated with overweight, obesity and other chronic diseases. The objective of this study is to estimate the price elasticity of demand for soft drinks, other sugar-sweetened beverages and high-energy dense foods in urban areas in Chile in order to evaluate the potential response of households' consumption to changes in prices. We used microdata from the VII Family Budget Survey 2012-2013, which collects information on expenditures made by Chilean urban households on items such as beverages and foods. We estimated a Linear Approximation of an Almost Ideal Demand System Model to derive own and cross price elasticities of milk, coffee, tea and other infusions, plain water, soft drinks, other flavored beverages, sweet snacks, sugar and honey, and desserts. We considered the censored nature of the data and included the Inverse Mills Ratio in each equation of the demand system. We estimated a Quadratic Almost Ideal Demand System and a two-part model as sensitivity analysis. We found an own price-elasticity of -1.37 for soft drinks. This implies that a price increase of 10% is associated with a reduction in consumption of 13.7%. We found that the rest of food and beverages included in the demand system behave as substitutes for soft drinks. For instance, plain water showed a cross-price elasticity of 0.63: a 10% increase in price of soft drinks could lead to an increase of 6.3% of plain water. Own and cross price elasticities were similar between models. The demand of soft drinks is price sensitive among Chilean households. An incentive system such as subsidies to non-sweetened beverages and tax to soft drinks could lead to increases in the substitutions for other healthier beverages.
Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan
2016-10-28
Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems' architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation.
Palomar, Esther; Chen, Xiaohong; Liu, Zhiming; Maharjan, Sabita; Bowen, Jonathan
2016-01-01
Smart city systems embrace major challenges associated with climate change, energy efficiency, mobility and future services by embedding the virtual space into a complex cyber-physical system. Those systems are constantly evolving and scaling up, involving a wide range of integration among users, devices, utilities, public services and also policies. Modelling such complex dynamic systems’ architectures has always been essential for the development and application of techniques/tools to support design and deployment of integration of new components, as well as for the analysis, verification, simulation and testing to ensure trustworthiness. This article reports on the definition and implementation of a scalable component-based architecture that supports a cooperative energy demand response (DR) system coordinating energy usage between neighbouring households. The proposed architecture, called refinement of Cyber-Physical Component Systems (rCPCS), which extends the refinement calculus for component and object system (rCOS) modelling method, is implemented using Eclipse Extensible Coordination Tools (ECT), i.e., Reo coordination language. With rCPCS implementation in Reo, we specify the communication, synchronisation and co-operation amongst the heterogeneous components of the system assuring, by design scalability and the interoperability, correctness of component cooperation. PMID:27801829
Thermal Profiling of Residential Energy Use
DOE Office of Scientific and Technical Information (OSTI.GOV)
Albert, A; Rajagopal, R
This work describes a methodology for informing targeted demand-response (DR) and marketing programs that focus on the temperature-sensitive part of residential electricity demand. Our methodology uses data that is becoming readily available at utility companies-hourly energy consumption readings collected from "smart" electricity meters, as well as hourly temperature readings. To decompose individual consumption into a thermal-sensitive part and a base load (non-thermally-sensitive), we propose a model of temperature response that is based on thermal regimes, i.e., unobserved decisions of consumers to use their heating or cooling appliances. We use this model to extract useful benchmarks that compose thermal profiles ofmore » individual users, i.e., terse characterizations of the statistics of these users' temperature-sensitive consumption. We present example profiles generated using our model on real consumers, and show its performance on a large sample of residential users. This knowledge may, in turn, inform the DR program by allowing scarce operational and marketing budgets to be spent on the right users-those whose influencing will yield highest energy reductions-at the right time. We show that such segmentation and targeting of users may offer savings exceeding 100% of a random strategy.« less
NASA Astrophysics Data System (ADS)
Wang, Kunpeng; Tan, Handong
2017-11-01
Controlled-source audio-frequency magnetotellurics (CSAMT) has developed rapidly in recent years and are widely used in the area of mineral and oil resource exploration as well as other fields. The current theory, numerical simulation, and inversion research are based on the assumption that the underground media have resistivity isotropy. However a large number of rock and mineral physical property tests show the resistivity of underground media is generally anisotropic. With the increasing application of CSAMT, the demand for probe accuracy of practical exploration to complex targets continues to increase. The question of how to evaluate the influence of anisotropic resistivity to CSAMT response is becoming important. To meet the demand for CSAMT response research of resistivity anisotropic media, this paper examines the CSAMT electric equations, derives and realizes a three-dimensional (3D) staggered-grid finite difference numerical simulation method of CSAMT resistivity axial anisotropy. Through building a two-dimensional (2D) resistivity anisotropy geoelectric model, we validate the 3D computation result by comparing it to the result of controlled-source electromagnetic method (CSEM) resistivity anisotropy 2D finite element program. Through simulating a 3D resistivity axial anisotropy geoelectric model, we compare and analyze the responses of equatorial configuration, axial configuration, two oblique sources and tensor source. The research shows that the tensor source is suitable for CSAMT to recognize the anisotropic effect of underground structure.
NASA Astrophysics Data System (ADS)
Milano, M.; Ruelland, D.; Dezetter, A.; Ardoin-Bardin, S.; Thivet, G.; Servat, E.
2012-04-01
Worldwide studies modelling the hydrological response to global changes have proven the Mediterranean area as one of the most vulnerable region to water crisis. It is characterised by limited and unequally distributed water resources, as well as by important development of its human activities. Since the late 1950s, water demand in the Mediterranean basin has doubled due to a significant expansion of irrigated land and urban areas, and has maintained on a constant upward curve. The Ebro catchment, third largest Mediterranean basin, is very representative of this context. Since the late 1970s, a negative trend in mean rainfall has been observed as well as an increase in mean temperature. Meanwhile, the Ebro River discharge has decreased by about 40%. However, climate alone cannot explain this downward trend. Another factor is the increase in water consumption for agricultural and domestic uses. Indeed, the Ebro catchment is a key element in the Spanish agricultural production with respectively 30% and 60% of the meat and fruit production of the country. Moreover, population has increased by 20% over the catchment since 1970 and the number of inhabitant doubles each summer due to tourism attraction. Finally, more than 250 storage dams have been built over the Ebro River for hydropower production and irrigation water supply purposes, hence regulating river discharge. In order to better understand the respective influence of climatic and anthropogenic pressures on the Ebro hydrological regime, an integrated water resources modelling framework was developed. This model is driven by water supplies, generated by a conceptual rainfall-runoff model and by a storage dam module that accounts for water demands and environmental flow requirements. Water demands were evaluated for the most water-demanding sector, i.e. irrigated agriculture (5 670 Hm3/year), and the domestic sector (252 Hm3/year), often defined as being of prior importance for water supply. A water allocation module has also been implemented in the model. The ability of water resources to satisfy the water demands is assessed by computing a water allocation index which depends on site priorities and supply preferences. This modelling framework was applied to eight sub-catchments, each one representative of typical climatic or water use conditions within the basin, over the 1971-1990 period. The results show the interest of integrated modelling to address water resources vulnerability. The hydrological response to climatic and anthropogenic variations witnesses the influence of both these pressures on water resources availability. Moreover, the water allocation index makes it possible to highlight the growing competition among users, especially during the summer season. The developed methodology hence provides us a more complete analysis to support decision-making compared to uncoupled analysis. This study is a first step towards evaluating future water resources availability and ability to satisfy water demands under climatic and anthropogenic pressures scenarios.
Electricity demand and storage dispatch modeling for buildings and implications for the smartgrid
NASA Astrophysics Data System (ADS)
Zheng, Menglian; Meinrenken, Christoph
2013-04-01
As an enabler for demand response (DR), electricity storage in buildings has the potential to lower costs and carbon footprint of grid electricity while simultaneously mitigating grid strain and increasing its flexibility to integrate renewables (central or distributed). We present a stochastic model to simulate minute-by-minute electricity demand of buildings and analyze the resulting electricity costs under actual, currently available DR-enabling tariffs in New York State, namely a peak/offpeak tariff charging by consumed energy (monthly total kWh) and a time of use tariff charging by power demand (monthly peak kW). We then introduce a variety of electrical storage options (from flow batteries to flywheels) and determine how DR via temporary storage may increase the overall net present value (NPV) for consumers (comparing the reduced cost of electricity to capital and maintenance costs of the storage). We find that, under the total-energy tariff, only medium-term storage options such as batteries offer positive NPV, and only at the low end of storage costs (optimistic scenario). Under the peak-demand tariff, however, even short-term storage such as flywheels and superconducting magnetic energy offer positive NPV. Therefore, these offer significant economic incentive to enable DR without affecting the consumption habits of buildings' residents. We discuss implications for smartgrid communication and our future work on real-time price tariffs.
Refrigerated Warehouse Demand Response Strategy Guide
DOE Office of Scientific and Technical Information (OSTI.GOV)
Scott, Doug; Castillo, Rafael; Larson, Kyle
This guide summarizes demand response measures that can be implemented in refrigerated warehouses. In an appendix, it also addresses related energy efficiency opportunities. Reducing overall grid demand during peak periods and energy consumption has benefits for facility operators, grid operators, utility companies, and society. State wide demand response potential for the refrigerated warehouse sector in California is estimated to be over 22.1 Megawatts. Two categories of demand response strategies are described in this guide: load shifting and load shedding. Load shifting can be accomplished via pre-cooling, capacity limiting, and battery charger load management. Load shedding can be achieved by lightingmore » reduction, demand defrost and defrost termination, infiltration reduction, and shutting down miscellaneous equipment. Estimation of the costs and benefits of demand response participation yields simple payback periods of 2-4 years. To improve demand response performance, it’s suggested to install air curtains and another form of infiltration barrier, such as a rollup door, for the passageways. Further modifications to increase efficiency of the refrigeration unit are also analyzed. A larger condenser can maintain the minimum saturated condensing temperature (SCT) for more hours of the day. Lowering the SCT reduces the compressor lift, which results in an overall increase in refrigeration system capacity and energy efficiency. Another way of saving energy in refrigerated warehouses is eliminating the use of under-floor resistance heaters. A more energy efficient alternative to resistance heaters is to utilize the heat that is being rejected from the condenser through a heat exchanger. These energy efficiency measures improve efficiency either by reducing the required electric energy input for the refrigeration system, by helping to curtail the refrigeration load on the system, or by reducing both the load and required energy input.« less
Modeling and Analysis of Commercial Building Electrical Loads for Demand Side Management
NASA Astrophysics Data System (ADS)
Berardino, Jonathan
In recent years there has been a push in the electric power industry for more customer involvement in the electricity markets. Traditionally the end user has played a passive role in the planning and operation of the power grid. However, many energy markets have begun opening up opportunities to consumers who wish to commit a certain amount of their electrical load under various demand side management programs. The potential benefits of more demand participation include reduced operating costs and new revenue opportunities for the consumer, as well as more reliable and secure operations for the utilities. The management of these load resources creates challenges and opportunities to the end user that were not present in previous market structures. This work examines the behavior of commercial-type building electrical loads and their capacity for supporting demand side management actions. This work is motivated by the need for accurate and dynamic tools to aid in the advancement of demand side operations. A dynamic load model is proposed for capturing the response of controllable building loads. Building-specific load forecasting techniques are developed, with particular focus paid to the integration of building management system (BMS) information. These approaches are tested using Drexel University building data. The application of building-specific load forecasts and dynamic load modeling to the optimal scheduling of multi-building systems in the energy market is proposed. Sources of potential load uncertainty are introduced in the proposed energy management problem formulation in order to investigate the impact on the resulting load schedule.
USDA-ARS?s Scientific Manuscript database
Biophysical models intended for routine applications at a range of scales should attempt to balance the competing demands of generality and simplicity and be capable of realistically simulating the response of CO2 and energy fluxes to environmental and physiological forcings. At the same time they m...
Reduced-Order Models for Load Management in the Power Grid
NASA Astrophysics Data System (ADS)
Alizadeh, Mahnoosh
In recent years, considerable research efforts have been directed towards designing control schemes that can leverage the inherent flexibility of electricity demand that is not tapped into in today's electricity markets. It is expected that these control schemes will be carried out by for-profit entities referred to as aggregators that operate at the edge of the power grid network. While the aggregator control problem is receiving much attention, more high-level questions of how these aggregators should plan their market participation, interact with the main grid and with each other, remain rather understudied. Answering these questions requires a large-scale model for the aggregate flexibility that can be harnessed from the a population of customers, particularly for residences and small businesses. The contribution of this thesis towards this goal is divided into three parts: In Chapter 3, a reduced-order model for a large population of heterogeneous appliances is provided by clustering load profiles that share similar degrees of freedom together. The use of such reduced-order model for system planning and optimal market decision making requires a foresighted approximation of the number of appliances that will join each cluster. Thus, Chapter 4 provides a systematic framework to generate such forecasts for the case of Electric Vehicles, based on real-world battery charging data. While these two chapters set aside the economic side that is naturally involved with participation in demand response programs and mainly focus on the control problem, Chapter 5 is dedicated to the study of optimal pricing mechanisms in order to recruit heterogeneous customers in a demand response program in which an aggregator can directly manage their appliances' load under their specified preferences. Prices are proportional to the wholesale market savings that can result from each recruitment event.
Dynamic Resource Allocation in Disaster Response: Tradeoffs in Wildfire Suppression
Petrovic, Nada; Alderson, David L.; Carlson, Jean M.
2012-01-01
Challenges associated with the allocation of limited resources to mitigate the impact of natural disasters inspire fundamentally new theoretical questions for dynamic decision making in coupled human and natural systems. Wildfires are one of several types of disaster phenomena, including oil spills and disease epidemics, where (1) the disaster evolves on the same timescale as the response effort, and (2) delays in response can lead to increased disaster severity and thus greater demand for resources. We introduce a minimal stochastic process to represent wildfire progression that nonetheless accurately captures the heavy tailed statistical distribution of fire sizes observed in nature. We then couple this model for fire spread to a series of response models that isolate fundamental tradeoffs both in the strength and timing of response and also in division of limited resources across multiple competing suppression efforts. Using this framework, we compute optimal strategies for decision making scenarios that arise in fire response policy. PMID:22514605
Day, Arla; Paquet, Stephanie; Scott, Natasha; Hambley, Laura
2012-10-01
Although many employees are using more information communication technology (ICT) as part of their jobs, few studies have examined the impact of ICT on their well-being, and there is a lack of validated measures designed to assess the ICT factors that may impact employee well-being. Therefore, we developed and validated a measure of ICT demands and supports. Using Exploratory Structural Equation Modeling, we found support for 8 ICT demands (i.e., availability, communication, ICT control, ICT hassles, employee monitoring, learning, response expectations, and workload) and two facets of ICT support (personal assistance and resources/upgrades support). Jointly, the ICT demands were associated with increased strain, stress, and burnout and were still associated with stress and strain after controlling for demographics, job variables, and job demands. The two types of ICT support were associated with lower stress, strain, and burnout. Resources/upgrades support moderated the relationship between learning expectations and most strain outcomes and between ICT hassles and strain. Personal assistance support moderated the relationship between ICT hassles and strain.
Eason, Christianne M; Mazerolle, Stephanie M; Goodman, Ashley
2014-01-01
One of the greatest catalysts for turnover among female athletic trainers (ATs) is motherhood, especially if employed at the National Collegiate Athletic Association Division I level. The medical education literature regularly identifies the importance of role models in professional character formation. However, few researchers have examined the responsibility of mentorship and professional role models as it relates to female ATs' perceptions of motherhood and retention. To evaluate perceptions of motherhood and retention in relation to mentorship and role models among female ATs currently employed in the collegiate setting. Qualitative study. Female athletic trainers working in National Collegiate Athletic Association Division I. Twenty-seven female ATs employed in the National Collegiate Athletic Association Division I setting volunteered. Average age of the participants was 35 ± 9 years. All were full-time ATs with an average of 11 ± 8 years of clinical experience. Participants responded to questions by journaling their thoughts and experiences. Multiple-analyst triangulation and peer review were included as steps to establish data credibility. Male and female role models and mentors can positively or negatively influence the career and work-life balance perceptions of female ATs working in the Division I setting. Female ATs have a desire to see more women in the profession handle the demands of motherhood and the demands of their clinical setting. Women who have had female mentors are more positive about the prospect of balancing the rigors of motherhood and job demands. Role models and mentors are valuable resources for promoting perseverance in the profession in the highly demanding clinical settings. As more female ATs remain in the profession who are able to maintain work-life balance and are available to serve as role models, the attitudes of other women may start to change.
NASA Astrophysics Data System (ADS)
Hill, M. C.; Jakeman, J.; Razavi, S.; Tolson, B.
2015-12-01
For many environmental systems model runtimes have remained very long as more capable computers have been used to add more processes and more time and space discretization. Scientists have also added more parameters and kinds of observations, and many model runs are needed to explore the models. Computational demand equals run time multiplied by number of model runs divided by parallelization opportunities. Model exploration is conducted using sensitivity analysis, optimization, and uncertainty quantification. Sensitivity analysis is used to reveal consequences of what may be very complex simulated relations, optimization is used to identify parameter values that fit the data best, or at least better, and uncertainty quantification is used to evaluate the precision of simulated results. The long execution times make such analyses a challenge. Methods for addressing this challenges include computationally frugal analysis of the demanding original model and a number of ingenious surrogate modeling methods. Both commonly use about 50-100 runs of the demanding original model. In this talk we consider the tradeoffs between (1) original model development decisions, (2) computationally frugal analysis of the original model, and (3) using many model runs of the fast surrogate model. Some questions of interest are as follows. If the added processes and discretization invested in (1) are compared with the restrictions and approximations in model analysis produced by long model execution times, is there a net benefit related of the goals of the model? Are there changes to the numerical methods that could reduce the computational demands while giving up less fidelity than is compromised by using computationally frugal methods or surrogate models for model analysis? Both the computationally frugal methods and surrogate models require that the solution of interest be a smooth function of the parameters or interest. How does the information obtained from the local methods typical of (2) and the global averaged methods typical of (3) compare for typical systems? The discussion will use examples of response of the Greenland glacier to global warming and surface and groundwater modeling.
NASA Astrophysics Data System (ADS)
Wisittipanit, Nuttachat; Wisittipanich, Warisa
2018-07-01
Demand response (DR) refers to changes in the electricity use patterns of end-users in response to incentive payment designed to prompt lower electricity use during peak periods. Typically, there are three players in the DR system: an electric utility operator, a set of aggregators and a set of end-users. The DR model used in this study aims to minimize the operator's operational cost and offer rewards to aggregators, while profit-maximizing aggregators compete to sell DR services to the operator and provide compensation to end-users for altering their consumption profiles. This article presents the first application of two metaheuristics in the DR system: particle swarm optimization (PSO) and differential evolution (DE). The objective is to optimize the incentive payments during various periods to satisfy all stakeholders. The results show that DE significantly outperforms PSO, since it can attain better compensation rates, lower operational costs and higher aggregator profits.
Demand Response Compensation Methodologies: Case Studies for Mexico
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gagne, Douglas A; Settle, Donald E; Aznar, Alexandra Y
This report examines various compensation methodologies for demand response programs in Mexico. This report presents three case studies, including New England, California, and Hawaii. Demand response (DR) can refer to a variety of approaches to changing the amount and timing of customers' electricity use, allowing the electricity supplier to more easily balance electricity supply and demand. The level of compensation for a DR program will depend greatly upon both the regulatory context of the electricity supplier, as well as the economic circumstances of the DR providers. For a regulated utility, a proposed compensation level may need to pass regulatory approval.more » To determine the value of DR resources, a regulatory body typically seeks to determine the costs that the utility would avoid if demand-side resources 'produce' energy.« less
Willemse, Bernadette M; de Jonge, Jan; Smit, Dieneke; Depla, Marja F I A; Pot, Anne Margriet
2012-07-01
Healthcare workers in nursing homes are faced with high job demands that can have a detrimental impact on job-related outcomes, such as job satisfaction. Job resources may have a buffering role on this relationship. The Demand-Control-Support (DCS) Model offers a theoretical framework to study how specific job resources can buffer the adverse effects of high demands, and can even activate positive consequences of high demands. The present study tests the moderating (i.e. buffering and activating) effects of decision authority and coworker- and supervisor support that are assumed by the hypotheses of the DCS Model. A national cross-sectional survey was conducted with an anonymous questionnaire. One hundred and thirty six living arrangements that provide nursing home care for people with dementia in the Netherlands. Fifteen healthcare workers per living arrangement. In total, 1147 people filled out the questionnaires (59% response rate). Hierarchical multilevel regression analyses were conducted to test the assumption that the effect of job demands on the dependent variables is buffered or activated the most when both decision authority and social support are high. This moderation is statistically represented by three-way interactions (i.e. demands×authority×support), while lower-order effects are taken into account (i.e. two-way interactions). The hypotheses are supported when three-way interaction effects are found in the expected direction. The dependent variables studied are job satisfaction, emotional exhaustion, and personal accomplishment. The proposed buffering and activation hypotheses of the DCS Model were not supported in our study. Three-way interaction effects were found for emotional exhaustion and personal accomplishment, though not in the expected direction. In addition, two-way interaction effects were found for job satisfaction and emotional exhaustion. Decision authority was found to buffer the adverse effect of job demands and to activate healthcare staff. Supervisor support was found to buffer the adverse effect of job demands on emotional exhaustion in situations with low decision authority. Finally, coworker support was found to have an adverse effect on personal accomplishment in high strain situations. Findings reveal that decision authority in particular makes healthcare workers in nursing homes less vulnerable to adverse effects of high job demands, and promotes positive consequences of work. Copyright © 2012 Elsevier Ltd. All rights reserved.
Using the PhysX engine for physics-based virtual surgery with force feedback.
Maciel, Anderson; Halic, Tansel; Lu, Zhonghua; Nedel, Luciana P; De, Suvranu
2009-09-01
The development of modern surgical simulators is highly challenging, as they must support complex simulation environments. The demand for higher realism in such simulators has driven researchers to adopt physics-based models, which are computationally very demanding. This poses a major problem, since real-time interactions must permit graphical updates of 30 Hz and a much higher rate of 1 kHz for force feedback (haptics). Recently several physics engines have been developed which offer multi-physics simulation capabilities, including rigid and deformable bodies, cloth and fluids. While such physics engines provide unique opportunities for the development of surgical simulators, their higher latencies, compared to what is necessary for real-time graphics and haptics, offer significant barriers to their use in interactive simulation environments. In this work, we propose solutions to this problem and demonstrate how a multimodal surgical simulation environment may be developed based on NVIDIA's PhysX physics library. Hence, models that are undergoing relatively low-frequency updates in PhysX can exist in an environment that demands much higher frequency updates for haptics. We use a collision handling layer to interface between the physical response provided by PhysX and the haptic rendering device to provide both real-time tissue response and force feedback. Our simulator integrates a bimanual haptic interface for force feedback and per-pixel shaders for graphics realism in real time. To demonstrate the effectiveness of our approach, we present the simulation of the laparoscopic adjustable gastric banding (LAGB) procedure as a case study. To develop complex and realistic surgical trainers with realistic organ geometries and tissue properties demands stable physics-based deformation methods, which are not always compatible with the interaction level required for such trainers. We have shown that combining different modelling strategies for behaviour, collision and graphics is possible and desirable. Such multimodal environments enable suitable rates to simulate the major steps of the LAGB procedure.
Zhang, Jingshu; Everson, Mark P; Wallington, Timothy J; Field, Frank R; Roth, Richard; Kirchain, Randolph E
2016-07-19
Platinum-group metals (PGMs) are technological and economic enablers of many industrial processes. This important role, coupled with their limited geographic availability, has led to PGMs being labeled as "critical materials". Studies of future PGM flows have focused on trends within material flows or macroeconomic indicators. We complement the previous work by introducing a novel technoeconomic model of substitution among PGMs within the automotive sector (the largest user of PGMs) reflecting the rational response of firms to changing prices. The results from the model support previous conclusions that PGM use is likely to grow, in some cases strongly, by 2030 (approximately 45% for Pd and 5% for Pt), driven by the increasing sales of automobiles. The model also indicates that PGM-demand growth will be significantly influenced by the future Pt-to-Pd price ratio, with swings of Pt and Pd demand of as much as 25% if the future price ratio shifts higher or lower even if it stays within the historic range. Fortunately, automotive catalysts are one of the more effectively recycled metals. As such, with proper policy support, recycling can serve to meet some of this growing demand.
Techniques for water demand analysis and forecasting: Puerto Rico, a case study
Attanasi, E.D.; Close, E.R.; Lopez, M.A.
1975-01-01
The rapid economic growth of the Commonwealth-of Puerto Rico since 1947 has brought public pressure on Government agencies for rapid development of public water supply and waste treatment facilities. Since 1945 the Puerto Rico Aqueduct and Sewer Authority has had the responsibility for planning, developing and operating water supply and waste treatment facilities on a municipal basis. The purpose of this study was to develop operational techniques whereby a planning agency, such as the Puerto Rico Aqueduct and Sewer Authority, could project the temporal and spatial distribution of .future water demands. This report is part of a 2-year cooperative study between the U.S. Geological Survey and the Environmental Quality Board of the Commonwealth of Puerto Rico, for the development of systems analysis techniques for use in water resources planning. While the Commonwealth was assisted in the development of techniques to facilitate ongoing planning, the U.S. Geological Survey attempted to gain insights in order to better interface its data collection efforts with the planning process. The report reviews the institutional structure associated with water resources planning for the Commonwealth. A brief description of alternative water demand forecasting procedures is presented and specific techniques and analyses of Puerto Rico demand data are discussed. Water demand models for a specific area of Puerto Rico are then developed. These models provide a framework for making several sets of water demand forecasts based on alternative economic and demographic assumptions. In the second part of this report, the historical impact of water resources investment on regional economic development is analyzed and related to water demand .forecasting. Conclusions and future data needs are in the last section.
Knani, Mouna; Fournier, Pierre-Sébastien; Biron, Caroline
2018-05-01
Despite a rich literature on association between psychosocial factors, the demand-control-support (DCS) model and burnout, there are few integrated frameworks encompassing the DCS model, burnout and intention to quit, particularly in a technological context. This manuscript examines the relationships between psychosocial risks, the demand-control-support (DCS) model, burnout syndrome and intention to quit following the introduction of new software at work. Data was collected from agents and advisors working at a Canadian university and using newstudy management software. An online questionnaire was sent via the university's internal mail. Finally, 112 people completed the online survey for a response rate of 60.9% . The results of structural equation modeling show that psychological demands, decision latitude and social support are associated with burnout. It is also clear that burnout, in particular depersonalization and emotional exhaustion, is positively associated with intention to quit. The few studies that raise the negative consequences of technology on quality of life in the workplace, and particularly on health, have not succeeded in establishing a direct link between a deterioration of health and the use of technology. This is due to the fact that there are few epidemiological studies on the direct consequences of the use of ITC on health.
Beyond Testing: Empirical Models of Insurance Markets
Einav, Liran; Finkelstein, Amy; Levin, Jonathan
2011-01-01
We describe recent advances in the empirical analysis of insurance markets. This new research proposes ways to estimate individual demand for insurance and the relationship between prices and insurer costs in the presence of adverse and advantageous selection. We discuss how these models permit the measurement of welfare distortions arising from asymmetric information and the welfare consequences of potential government policy responses. We also discuss some challenges in modeling imperfect competition between insurers and outline a series of open research questions. PMID:21572939
Time Step Considerations when Simulating Dynamic Behavior of High Performance Homes
DOE Office of Scientific and Technical Information (OSTI.GOV)
Tabares-Velasco, Paulo Cesar
2016-09-01
Building energy simulations, especially those concerning pre-cooling strategies and cooling/heating peak demand management, require careful analysis and detailed understanding of building characteristics. Accurate modeling of the building thermal response and material properties for thermally massive walls or advanced materials like phase change materials (PCMs) are critically important.
In the Laurentian Great Lakes Basin (GLB), corn acreage has been expanding since 2005 in response to high demand for corn as an ethanol feedstock. This study integrated remote sensing-derived products and the Soil and Water Assessment Tool (SWAT) withing a GIS modeling environme...
University Policies under Varying Market Conditions: The Training of Electrical Engineers.
ERIC Educational Resources Information Center
Eckstein, Zvi; And Others
1988-01-01
Analyzes an Israeli university's problem in optimizing the quality and quantity of electrical engineers in response to fluctuating enrollment. An equilibrium model considers the effect of students' occupation choice and the university's decision on the current and future demand and supply of engineers, in order to predict the equilibrium number of…
ERIC Educational Resources Information Center
Velasco-Martínez, Leticia-Concepción; Tójar-Hurtado, Juan-Carlos
2018-01-01
Competency-based learning requires making changes in the higher education model in response to current socio-educational demands. Rubrics are an innovative educational tool for competence evaluation, for both students and educators. Ever since arriving at the university systems, the application of rubrics in evaluation programs has grown…
Organizational Diversity in Chinese Private Higher Education. PROPHE Working Paper Series. WP No. 17
ERIC Educational Resources Information Center
Cai, Yuzhuo; Yan, Fengqiao
2011-01-01
Organizational diversity has been empirically proved as a prevailing phenomenon in the global expansion of private higher education. Chinese private higher education, which surged as a response to supplement public education provision and absorb demands in the education market, demonstrates different organizational forms and operational models.…
Contextualised Performance: Reframing the Skills Debate in Research Education
ERIC Educational Resources Information Center
Cumming, Jim
2010-01-01
In Australia, as in the UK, much of the skills debate in research education has reflected a deficit model, whereby candidates are deemed to be in need of supplementary training. In response to the demands of employers and governments, most universities have added employability skills to postgraduate curricula, while simultaneously boosting their…
A New Approach for New Demands: The Promise of Learning-Oriented School Leadership
ERIC Educational Resources Information Center
Drago-Severson, Eleanor; Blum-DeStefano, Jessica
2013-01-01
In response to the complexity and mounting adaptive challenges of teaching, learning and leadership today, this article presents an overview of a new "learning-oriented model of school leadership," which is composed of four pillar practices--teaming, mentoring, collegial inquiry, and providing leadership roles--that support internal…
Crawford, Robert S.; Albadawi, Hassan; Robaldo, Alessandro; Peck, Michael A.; Abularrage, Christopher J.; Yoo, Hyung-Jin; LaMuraglia, Glenn M.; Watkins, Michael T.
2013-01-01
Introduction Studies were designed to determine whether the ApoE−/− phenotype modulates the local skeletal muscle and systemic inflammatory (plasma) responses to lower extremity demand ischemia. The ApoE−/− phenotype is an experimental model for atherosclerosis in humans. Methods Aged female ApoE −/− and C57BL6 mice underwent femoral artery ligation, then divided into sedentary and demand ischemia (exercise) groups on day 14. Baseline and post exercise limb perfusion and hind limb function were assessed. On day 14, animals in the demand ischemia group underwent daily treadmill exercise through day 28. Sedentary mice were not exercised. On day 28, plasma and skeletal muscle from ischemic limbs were harvested from sedentary and exercised mice. Muscle was assayed for angiogenic and pro-inflammatory proteins, markers of skeletal muscle regeneration, and evidence of skeletal muscle fiber maturation. Results Hind limb ischemia was similar in ApoE −/− and C57 mice prior to the onset of exercise. Under sedentary conditions, plasma VEGF, IL-6, but not KC or MIP-2 were higher in ApoE (P<0.0001). Following exercise, plasma levels of VEGF, KC and MIP-2, but not IL-6 were lower in ApoE (P<0.004). The cytokines KC and MIP-2 in muscle was greater in exercised ApoE−/− mice as compared to C57BL6 mice (p=0.01). Increased PAR activity, and mature muscle regeneration was associated with demand ischemia in the C57BL6 mice as compared to the ApoE −/− mice (p=0.01). Conclusion Demand limb ischemia in the ApoE−/− phenotype exacerbated the expression of select systemic cytokines in plasma and blunted indices of muscle regeneration. PMID:23528286
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hansen, Jacob; Edgar, Thomas W.; Daily, Jeffrey A.
With an ever-evolving power grid, concerns regarding how to maintain system stability, efficiency, and reliability remain constant because of increasing uncertainties and decreasing rotating inertia. To alleviate some of these concerns, demand response represents a viable solution and is virtually an untapped resource in the current power grid. This work describes a hierarchical control framework that allows coordination between distributed energy resources and demand response. This control framework is composed of two control layers: a coordination layer that ensures aggregations of resources are coordinated to achieve system objectives and a device layer that controls individual resources to assure the predeterminedmore » power profile is tracked in real time. Large-scale simulations are executed to study the hierarchical control, requiring advancements in simulation capabilities. Technical advancements necessary to investigate and answer control interaction questions, including the Framework for Network Co-Simulation platform and Arion modeling capability, are detailed. Insights into the interdependencies of controls across a complex system and how they must be tuned, as well as validation of the effectiveness of the proposed control framework, are yielded using a large-scale integrated transmission system model coupled with multiple distribution systems.« less
28 CFR 0.177a - Antitrust civil investigative demands.
Code of Federal Regulations, 2010 CFR
2010-07-01
... JUSTICE Assigning Responsibility Concerning Applications for Orders Compelling Testimony or Production of..., United States Code, to compel testimony in response to antitrust civil investigative demands for oral...
Negative autoregulation matches production and demand in synthetic transcriptional networks.
Franco, Elisa; Giordano, Giulia; Forsberg, Per-Ola; Murray, Richard M
2014-08-15
We propose a negative feedback architecture that regulates activity of artificial genes, or "genelets", to meet their output downstream demand, achieving robustness with respect to uncertain open-loop output production rates. In particular, we consider the case where the outputs of two genelets interact to form a single assembled product. We show with analysis and experiments that negative autoregulation matches the production and demand of the outputs: the magnitude of the regulatory signal is proportional to the "error" between the circuit output concentration and its actual demand. This two-device system is experimentally implemented using in vitro transcriptional networks, where reactions are systematically designed by optimizing nucleic acid sequences with publicly available software packages. We build a predictive ordinary differential equation (ODE) model that captures the dynamics of the system and can be used to numerically assess the scalability of this architecture to larger sets of interconnected genes. Finally, with numerical simulations we contrast our negative autoregulation scheme with a cross-activation architecture, which is less scalable and results in slower response times.
Item response theory - A first approach
NASA Astrophysics Data System (ADS)
Nunes, Sandra; Oliveira, Teresa; Oliveira, Amílcar
2017-07-01
The Item Response Theory (IRT) has become one of the most popular scoring frameworks for measurement data, frequently used in computerized adaptive testing, cognitively diagnostic assessment and test equating. According to Andrade et al. (2000), IRT can be defined as a set of mathematical models (Item Response Models - IRM) constructed to represent the probability of an individual giving the right answer to an item of a particular test. The number of Item Responsible Models available to measurement analysis has increased considerably in the last fifteen years due to increasing computer power and due to a demand for accuracy and more meaningful inferences grounded in complex data. The developments in modeling with Item Response Theory were related with developments in estimation theory, most remarkably Bayesian estimation with Markov chain Monte Carlo algorithms (Patz & Junker, 1999). The popularity of Item Response Theory has also implied numerous overviews in books and journals, and many connections between IRT and other statistical estimation procedures, such as factor analysis and structural equation modeling, have been made repeatedly (Van der Lindem & Hambleton, 1997). As stated before the Item Response Theory covers a variety of measurement models, ranging from basic one-dimensional models for dichotomously and polytomously scored items and their multidimensional analogues to models that incorporate information about cognitive sub-processes which influence the overall item response process. The aim of this work is to introduce the main concepts associated with one-dimensional models of Item Response Theory, to specify the logistic models with one, two and three parameters, to discuss some properties of these models and to present the main estimation procedures.
Smart Buildings and Demand Response
NASA Astrophysics Data System (ADS)
Kiliccote, Sila; Piette, Mary Ann; Ghatikar, Girish
2011-11-01
Advances in communications and control technology, the strengthening of the Internet, and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto-DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components, systems, end-uses and whole building energy performance metrics. The paper presents a framework about when energy is used, levels of services by energy using systems, granularity of control, and speed of telemetry. DR, when defined as a discrete event, requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.
Subsidies and the Demand for Individual Health Insurance in California
Susan Marquis, M; Buntin, Melinda Beeuwkes; Escarce, José J; Kapur, Kanika; Yegian, Jill M
2004-01-01
Objective To estimate the effect of changes in premiums for individual insurance on decisions to purchase individual insurance and how this price response varies among subgroups of the population. Data Source Survey responses from the Current Population Survey (), the Survey of Income and Program Participation (), the National Health Interview Survey (), and data about premiums and plans offered in the individual insurance market in California, 1996–2001. Study Design A logit model was used to estimate the decisions to purchase individual insurance by families without access to group insurance. This was modeled as a function of premiums, controlling for family characteristics and other characteristics of the market. A multinomial model was used to estimate the choice between group coverage, individual coverage, and remaining uninsured for workers offered group coverage as a function of premiums for individual insurance and out-of-pocket costs of group coverage. Principal Findings The elasticity of demand for individual insurance by those without access to group insurance is about −.2 to −.4, as has been found in earlier studies. However, there are substantial differences in price responses among subgroups with low-income, young, and self-employed families showing the greatest response. Among workers offered group insurance, a decrease in individual premiums has very small effects on the choice to purchase individual coverage versus group coverage. Conclusions Subsidy programs may make insurance more affordable for some families, but even sizeable subsidies are unlikely to solve the problem of the uninsured. We do not find evidence that subsidies to individual insurance will produce an unraveling of the employer-based health insurance system. PMID:15333122
Wong, Carol A; Spence Laschinger, Heather K
2015-12-01
The frontline clinical manager role in healthcare is pivotal to the development of safe and healthy working conditions and optimal staff and patient care outcomes. However, in today's dynamic healthcare organizations managers face constant job demands from wider spans of control and complex role responsibilities but may not have adequate decisional authority to support effective work performance resulting in unnecessary job strain. Prolonged job strain can lead to burnout, health complaints, and increased turnover intention. Yet, there is limited research that examines frontline manager job strain and its impact on their well-being and work outcomes. The substantial cost associated with replacing experienced managers calls attention to the need to address job strain in order to retain this valuable organizational asset. Using Karasek's Job Demands-Control theory of job strain, a model was tested examining the effects of frontline manager job strain on their burnout (emotional exhaustion and cynicism), organizational commitment and ultimately, turnover intentions. Secondary analysis of data collected in an online cross-sectional survey of frontline managers was conducted using structural equation modeling. All 500 eligible frontline managers from 14 teaching hospitals in Ontario, Canada, were invited to participate and 159 responded for a 32% response rate. Participants received an email invitation with a secure link for the online survey. Ethics approval was obtained from the university ethics board and the respective ethics review boards of the 14 organizations involved in the study. The model was tested using path analysis techniques within structural equation modeling with maximum likelihood estimation. The final model fit the data acceptably (χ(2)=6.62, df=4, p=.16, IFI=99, CFI=.99, SRMR=.03, RMSEA=.06). Manager job strain was significantly positively associated with burnout which contributed to both lower organizational commitment and higher turnover intention. Organizational commitment was also negatively associated with turnover intention and there was an additional direct positive relationship between job strain and turnover intention. Preliminary support was found for a model showing that manager job strain contributes to burnout, reduced organizational commitment and higher turnover intentions. Findings suggest that organizations need to monitor and address manager job strain by ensuring managers' role demands are reasonable and that they have the requisite decision latitude to balance role demands. Copyright © 2015 Elsevier Ltd. All rights reserved.
Seismic analysis of offshore wind turbines on bottom-fixed support structures.
Alati, Natale; Failla, Giuseppe; Arena, Felice
2015-02-28
This study investigates the seismic response of a horizontal axis wind turbine on two bottom-fixed support structures for transitional water depths (30-60 m), a tripod and a jacket, both resting on pile foundations. Fully coupled, nonlinear time-domain simulations on full system models are carried out under combined wind-wave-earthquake loadings, for different load cases, considering fixed and flexible foundation models. It is shown that earthquake loading may cause a significant increase of stress resultant demands, even for moderate peak ground accelerations, and that fully coupled nonlinear time-domain simulations on full system models are essential to capture relevant information on the moment demand in the rotor blades, which cannot be predicted by analyses on simplified models allowed by existing standards. A comparison with some typical design load cases substantiates the need for an accurate seismic assessment in sites at risk from earthquakes. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Work and Health among Latina Mothers in Farmworker Families
Arcury, Thomas A.; Trejo, Grisel; Suerken, Cynthia K.; Grzywacz, Joseph G.; Ip, Edward H.; Quandt, Sara A.
2014-01-01
Background Work organization is important for the health of vulnerable workers, particularly women. This analysis describes work organization for Latinas in farmworker families and delineates the associations of work organization with health indicators. Methods 220 Latino women in farmworker families completed interviews from October 2012 - July 2013. Interviews addressed job structure, job demand, job control, and job support. Health measures included stress, depressive symptoms, physical activity, family conflict, and family economic security. Results Three-fifths of the women were employed. Several work organization dimensions, including shift, psychological demand, work safety climate, and benefits, were associated with participant health as expected, based on the work organization and job demands-control-support models. Conclusions Research should address women's health and specific work responsibilities. Occupational safety policy must consider the importance of work organization in the health of vulnerable workers. PMID:25742536
On the demand for prescription drugs: heterogeneity in price responses.
Skipper, Niels
2013-07-01
This paper estimates the price elasticity of demand for prescription drugs using an exogenous shift in consumer co-payment caused by a reform in the Danish subsidy scheme for the general public. Using purchasing records for the entire Danish population, I show that the average price response for the most commonly used drug yields demand elasticities in the range of -0.36 to -0.5. The reform is shown to affect women, the elderly, and immigrants the most. Furthermore, this paper shows significant heterogeneity in the price response over different types of antibiotics, suggesting that the price elasticity of demand varies considerably even across relatively similar drugs. Copyright © 2012 John Wiley & Sons, Ltd.
Northwest Open Automated Demand Response Technology Demonstration Project
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao
The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibilitymore » of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wood, E.; Burton, E.; Duran, A.
Understanding the real-world power demand of modern automobiles is of critical importance to engineers using modeling and simulation to inform the intelligent design of increasingly efficient powertrains. Increased use of global positioning system (GPS) devices has made large scale data collection of vehicle speed (and associated power demand) a reality. While the availability of real-world GPS data has improved the industry's understanding of in-use vehicle power demand, relatively little attention has been paid to the incremental power requirements imposed by road grade. This analysis quantifies the incremental efficiency impacts of real-world road grade by appending high fidelity elevation profiles tomore » GPS speed traces and performing a large simulation study. Employing a large real-world dataset from the National Renewable Energy Laboratory's Transportation Secure Data Center, vehicle powertrain simulations are performed with and without road grade under five vehicle models. Aggregate results of this study suggest that road grade could be responsible for 1% to 3% of fuel use in light-duty automobiles.« less
An adaptive load-following control system for a space nuclear power system
NASA Astrophysics Data System (ADS)
Metzger, John D.; El-Genk, Mohamed S.
An adaptive load-following control system is proposed for a space nuclear power system. The conceptual design of the SP-100 space nuclear power system proposes operating the nuclear reactor at a base thermal power and accommodating changes in the electrical power demand with a shunt regulator. It is necessary to increase the reactor thermal power if the payload electrical demand exceeds the peak system electrical output for the associated reactor power. When it is necessary to change the nuclear reactor power to meet a change in the power demand, the power ascension or descension must be accomplished in a predetermined manner to avoid thermal stresses in the system and to achieve the desired reactor period. The load-following control system described has the ability to adapt to changes in the system and to changes in the satellite environment. The application is proposed of the model reference adaptive control (MRAC). The adaptive control system has the ability to control the dynamic response of nonlinear systems. Three basic subsets of adaptive control are: (1) gain scheduling, (2) self-tuning regulators, and (3) model reference adaptive control.
DOT National Transportation Integrated Search
1980-12-01
The report documents revisions made to the Wharton EFA Automobile Demand Model to produce the Wharton EFA Motor Vehicle Demand Model (Mark I). Equations are reestimated for the total desired stock of autos and for desired shares by size class, includ...
Better service, greater efficiency : transit management for demand response systems
DOT National Transportation Integrated Search
1999-01-01
This brochure briefly describes different technologies which can enhance demand response transit systems. It covers automated scheduling and dispatching, mobile data terminals, electronic identification cards, automatic vehicle location, and geograph...
Optimization of the High-speed On-off Valve of an Automatic Transmission
NASA Astrophysics Data System (ADS)
Li-mei, ZHAO; Huai-chao, WU; Lei, ZHAO; Yun-xiang, LONG; Guo-qiao, LI; Shi-hao, TANG
2018-03-01
The response time of the high-speed on-off solenoid valve has a great influence on the performance of the automatic transmission. In order to reduce the response time of the high-speed on-off valve, the simulation model of the valve was built by use of AMESim and Ansoft Maxwell softwares. To reduce the response time, an objective function based on ITAE criterion was built and the Genetic Algorithms was used to optimize five parameters including circle number, working air gap, et al. The comparison between experiment and simulation shows that the model is verified. After optimization, the response time of the valve is reduced by 38.16%, the valve can meet the demands of the automatic transmission well. The results can provide theoretical reference for the improvement of automatic transmission performance.
Free to Choose? Reform, Choice, and Consideration Sets in the English National Health Service.
Gaynor, Martin; Propper, Carol; Seiler, Stephan
2016-11-01
Choice in public services is controversial. We exploit a reform in the English National Health Service to assess the effect of removing constraints on patient choice. We estimate a demand model that explicitly captures the removal of the choice constraints imposed on patients. We find that, post-removal, patients became more responsive to clinical quality. This led to a modest reduction in mortality and a substantial increase in patient welfare. The elasticity of demand faced by hospitals increased substantially post- reform and we find evidence that hospitals responded to the enhanced incentives by improving quality. This suggests greater choice can raise quality.
Towards Organs on Demand: Breakthroughs and Challenges in Models of Organogenesis.
Francipane, Maria Giovanna; Lagasse, Eric
2016-09-01
In recent years, functional three-dimensional (3D) tissue generation in vitro has been significantly advanced by tissue-engineering methods, achieving better reproduction of complex native organs compared to conventional culture systems. This review will discuss traditional 3D cell culture techniques as well as newly developed technology platforms. These recent techniques provide new possibilities in the creation of human body parts and provide more accurate predictions of tissue response to drug and chemical challenges. Given the rapid advancement in the human induced pluripotent stem cell (iPSC) field, these platforms also hold great promise in the development of patient-specific, transplantable tissues and organs on demand.
Murphy, James G; Yurasek, Ali M; Meshesha, Lidia Z; Dennhardt, Ashley A; MacKillop, James; Skidmore, Jessica R; Martens, Matthew P
2014-07-01
Behavioral economic demand curves measure alcohol consumption as a function of price and may capture clinically relevant individual differences in alcohol-reinforcing efficacy. This study used a novel, behavioral-economic, hypothetical demand-curve paradigm to examine the association between family history of alcohol misuse and individual differences in both alcohol demand and the relative sensitivity of alcohol demand to next-day responsibilities. Participants were 207 college students (47% male, 68.5% White, 27.4% African American, Mage = 19.5 years) who reported at least one heavy drinking episode (5/4 or more drinks on one occasion for a man/woman) in the past month and completed two versions of an alcohol purchase task (APT) that assessed hypothetical alcohol consumption across 17 drink prices. In one APT (standard), students imagined they had no next-day responsibilities, and in the other, they imagined having a 10:00 a.m. test the next day. A series of analyses of covariance indicated that participants with at least one biological parent or grandparent who had misused alcohol reported similar levels of alcohol demand on the standard APT but significantly less sensitivity to the next-day academic responsibility as measured by the percentage of reduction in demand intensity and breakpoint across the no-responsibility and next-day-test conditions. These findings provide initial evidence that APTs might clarify one potential mechanism of risk conferred by family history. Young adult heavy drinkers with a family history of problematic drinking may be less sensitive to next-day responsibilities that might modulate drinking in drinkers without a family history of alcohol problems.
Gilbert-Ouimet, Mahée; Brisson, Chantal; Milot, Alain; Vézina, Michel
2017-06-01
Accumulating evidence shows that psychosocial work factors of the demand-control and effort-reward imbalance models may contribute to increase blood pressure (BP). Women are more likely to be exposed to these psychosocial factors than men. Moreover, women spend twice as much time per week performing family responsibilities than men. This study aimed to evaluate the longitudinal association of the double exposure to psychosocial work factors and high family responsibilities in women with BP for a 5-year follow-up. At baseline, the study sample was composed of 1215 working women. Psychosocial work factors were measured using validated scales. Family responsibilities were measured using items related to "the number of children and their age" and "housework and children care." Ambulatory BP measures were taken every 15 minutes during a working day. Associations between psychosocial measures and BP were examined using analyses of covariance. Women with a double exposure to effort-reward imbalance and high family responsibilities had significantly higher BP means than women not exposed to these factors at baseline (diastolic: +2.75 mm Hg), at 3-year follow-up (systolic: +2.22 mm Hg and diastolic: +2.55 mm Hg), and at 5-year follow-up (systolic: +2.94 mm Hg and diastolic: + 3.10 mm Hg). No adverse effect on BP was observed for the double exposure to the psychosocial work factors of the demand-control model and high family responsibilities. A double exposure to effort-reward imbalance at work and high family responsibilities might contribute to elevated ambulatory BP at work among women. BP elevations related to this double exposure may persist for several years.
A Generalized Formulation of Demand Response under Market Environments
NASA Astrophysics Data System (ADS)
Nguyen, Minh Y.; Nguyen, Duc M.
2015-06-01
This paper presents a generalized formulation of Demand Response (DR) under deregulated electricity markets. The problem is scheduling and controls the consumption of electrical loads according to the market price to minimize the energy cost over a day. Taking into account the modeling of customers' comfort (i.e., preference), the formulation can be applied to various types of loads including what was traditionally classified as critical loads (e.g., air conditioning, lights). The proposed DR scheme is based on Dynamic Programming (DP) framework and solved by DP backward algorithm in which the stochastic optimization is used to treat the uncertainty, if any occurred in the problem. The proposed formulation is examined with the DR problem of different loads, including Heat Ventilation and Air Conditioning (HVAC), Electric Vehicles (EVs) and a newly DR on the water supply systems of commercial buildings. The result of simulation shows significant saving can be achieved in comparison with their traditional (On/Off) scheme.
Zhang, Lei; Zhang, Jing
2017-08-07
A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users' private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes.
Zhang, Lei; Zhang, Jing
2017-01-01
A Smart Grid (SG) facilitates bidirectional demand-response communication between individual users and power providers with high computation and communication performance but also brings about the risk of leaking users’ private information. Therefore, improving the individual power requirement and distribution efficiency to ensure communication reliability while preserving user privacy is a new challenge for SG. Based on this issue, we propose an efficient and privacy-preserving power requirement and distribution aggregation scheme (EPPRD) based on a hierarchical communication architecture. In the proposed scheme, an efficient encryption and authentication mechanism is proposed for better fit to each individual demand-response situation. Through extensive analysis and experiment, we demonstrate how the EPPRD resists various security threats and preserves user privacy while satisfying the individual requirement in a semi-honest model; it involves less communication overhead and computation time than the existing competing schemes. PMID:28783122
Modeling and simulation of consumer response to dynamic pricing.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Valenzuela, J.; Thimmapuram, P.; Kim, J
2012-08-01
Assessing the impacts of dynamic-pricing under the smart grid concept is becoming extremely important for deciding its full deployment. In this paper, we develop a model that represents the response of consumers to dynamic pricing. In the model, consumers use forecasted day-ahead prices to shift daily energy consumption from hours when the price is expected to be high to hours when the price is expected to be low while maintaining the total energy consumption as unchanged. We integrate the consumer response model into the Electricity Market Complex Adaptive System (EMCAS). EMCAS is an agent-based model that simulates restructured electricity markets.more » We explore the impacts of dynamic-pricing on price spikes, peak demand, consumer energy bills, power supplier profits, and congestion costs. A simulation of an 11-node test network that includes eight generation companies and five aggregated consumers is performed for a period of 1 month. In addition, we simulate the Korean power system.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prowell, I.; Elgamal, A.; Romanowitz, H.
Demand parameters for turbines, such as tower moment demand, are primarily driven by wind excitation and dynamics associated with operation. For that purpose, computational simulation platforms have been developed, such as FAST, maintained by the National Renewable Energy Laboratory (NREL). For seismically active regions, building codes also require the consideration of earthquake loading. Historically, it has been common to use simple building code approaches to estimate the structural demand from earthquake shaking, as an independent loading scenario. Currently, International Electrotechnical Commission (IEC) design requirements include the consideration of earthquake shaking while the turbine is operating. Numerical and analytical tools usedmore » to consider earthquake loads for buildings and other static civil structures are not well suited for modeling simultaneous wind and earthquake excitation in conjunction with operational dynamics. Through the addition of seismic loading capabilities to FAST, it is possible to simulate earthquake shaking in the time domain, which allows consideration of non-linear effects such as structural nonlinearities, aerodynamic hysteresis, control system influence, and transients. This paper presents a FAST model of a modern 900-kW wind turbine, which is calibrated based on field vibration measurements. With this calibrated model, both coupled and uncoupled simulations are conducted looking at the structural demand for the turbine tower. Response is compared under the conditions of normal operation and potential emergency shutdown due the earthquake induced vibrations. The results highlight the availability of a numerical tool for conducting such studies, and provide insights into the combined wind-earthquake loading mechanism.« less
Clawges, R.M.; Titus, E.O.
1993-01-01
A method was developed to predict water demand for crop uses in New Jersey. A separate method was developed to estimate water use for livestock and selected sectors of the food-processing industry in 1987. Predictions of water demand for field- grown crops in New Jersey were made for 1990, 2000, 2010, and 2020 under three climatological scenarios: (1) wet year, (2) average year, and (3) drought year. These estimates ranged from 4.10 times 10 to the 9th power to 16.82 times 10 to the 9th power gal (gallons). Irrigation amounts calculated for the three climatological scenarios by using a daily water-balance model were multiplied by predicted numbers of irrigated acreage. Irrigated acreage was predicted from historical crop-irrigation data and from predictions of harvested acreage produced by using a statistical model relating population to harvested acreage. Predictions of water demand for cranberries and container-grown nursery crops also were made for 1990, 2000, 2010, and 2020. Predictions of water demand under the three climatological scenarios were made for container- grown nursery crops, but not for cranberries, because water demand for cranberries varies little in response to climatological factors. Water demand for cranberries was predicted to remain constant at 4.43 times 10 to the 9th power gal through the year 2020. Predictions of water demand for container-grown nursery crops ranged from 1.89 times 10 to the 9th power to 3.63 times 10 to the 9th power gal. Water-use for livestock in 1987 was estimated to be 0.78 times 10 to the 9th power gal, and water use for selected sectors of the food-processing industry was estimated to be 3.75 times 10 to the 9th power gal.
Water-Constrained Electric Sector Capacity Expansion Modeling Under Climate Change Scenarios
NASA Astrophysics Data System (ADS)
Cohen, S. M.; Macknick, J.; Miara, A.; Vorosmarty, C. J.; Averyt, K.; Meldrum, J.; Corsi, F.; Prousevitch, A.; Rangwala, I.
2015-12-01
Over 80% of U.S. electricity generation uses a thermoelectric process, which requires significant quantities of water for power plant cooling. This water requirement exposes the electric sector to vulnerabilities related to shifts in water availability driven by climate change as well as reductions in power plant efficiencies. Electricity demand is also sensitive to climate change, which in most of the United States leads to warming temperatures that increase total cooling-degree days. The resulting demand increase is typically greater for peak demand periods. This work examines the sensitivity of the development and operations of the U.S. electric sector to the impacts of climate change using an electric sector capacity expansion model that endogenously represents seasonal and local water resource availability as well as climate impacts on water availability, electricity demand, and electricity system performance. Capacity expansion portfolios and water resource implications from 2010 to 2050 are shown at high spatial resolution under a series of climate scenarios. Results demonstrate the importance of water availability for future electric sector capacity planning and operations, especially under more extreme hotter and drier climate scenarios. In addition, region-specific changes in electricity demand and water resources require region-specific responses that depend on local renewable resource availability and electricity market conditions. Climate change and the associated impacts on water availability and temperature can affect the types of power plants that are built, their location, and their impact on regional water resources.
Residential demand for energy. Volume 1: Residential energy demand in the US
NASA Astrophysics Data System (ADS)
Taylor, L. D.; Blattenberger, G. R.; Rennhack, R. K.
1982-04-01
Updated and improved versions of the residential energy demand models that are currently used in EPRI's Demand 80/81 Model are presented. The primary objective of the study is the development and estimation of econometric demand models that take into account in a theoretically appropriate way the problems caused by decreasing-block pricing in the sale of electricity and natural gas. An ancillary objective is to take into account the impact on electricity, natural gas, and fuel oil demands of differences and changes in the availability of natural gas. Econometric models of residential demand are estimated for all three fuel tyes using time series data by state. Price and income elasticities for a number of alternative models are presented.
Demand forecast model based on CRM
NASA Astrophysics Data System (ADS)
Cai, Yuancui; Chen, Lichao
2006-11-01
With interiorizing day by day management thought that regarding customer as the centre, forecasting customer demand becomes more and more important. In the demand forecast of customer relationship management, the traditional forecast methods have very great limitation because much uncertainty of the demand, these all require new modeling to meet the demands of development. In this paper, the notion is that forecasting the demand according to characteristics of the potential customer, then modeling by it. The model first depicts customer adopting uniform multiple indexes. Secondly, the model acquires characteristic customers on the basis of data warehouse and the technology of data mining. The last, there get the most similar characteristic customer by their comparing and forecast the demands of new customer by the most similar characteristic customer.
Gussow, J D
1994-05-01
Although the recommendation to avoid animal flesh for environmental reasons has been increasingly advanced, especially in the highly industrialized countries, the ecological implications of such avoidance are seldom carefully examined. If sustainable food systems are to be modeled after natural systems that maintain fertility, both plants and animals would be involved. This paper examines the history of the idea that environmental responsibility is linked to vegetarianism and the destructive effects of present methods of animal raising on farmers, animal welfare, and the environment. Finally, it explores the question of whether vegetarianism is the appropriate response to these problems.
NASA Astrophysics Data System (ADS)
Kohler, M. D.; Castillo, J.; Massari, A.; Clayton, R. W.
2017-12-01
Earthquake-induced motions recorded by spatially dense seismic arrays in buildings located in the northern Los Angeles basin suggest the presence of complex, amplified surface wave effects on the seismic demand of mid-rise buildings. Several moderate earthquakes produced large-amplitude, seismic energy with slow shear-wave velocities that cannot be explained or accurately modeled by any published 3D seismic velocity models or by Vs30 values. Numerical experiments are conducted to determine if sedimentary basin features are responsible for these rarely modeled and poorly documented contributions to seismic demand computations. This is accomplished through a physics-based wave propagation examination of the effects of different sedimentary basin geometries on the nonlinear response of a mid-rise structural model based on an existing, instrumented building. Using two-dimensional finite-difference predictive modeling, we show that when an earthquake focal depth is near the vertical edge of an elongated and relatively shallow sedimentary basin, dramatically amplified and complex surface waves are generated as a result of the waveguide effect introduced by this velocity structure. In addition, for certain source-receiver distances and basin geometries, body waves convert to secondary Rayleigh waves that propagate both at the free-surface interface and along the depth interface of the basin that show up as multiple large-amplitude arrivals. This study is motivated by observations from the spatially dense, high-sample-rate acceleration data recorded by the Community Seismic Network, a community-hosted strong-motion network, currently consisting of hundreds of sensors located in the southern California area. The results provide quantitative insight into the causative relationship between a sedimentary basin shape and the generation of Rayleigh waves at depth, surface waves at the free surface, scattered seismic energy, and the sensitivity of building responses to each of these.
Finite-Element Methods for Real-Time Simulation of Surgery
NASA Technical Reports Server (NTRS)
Basdogan, Cagatay
2003-01-01
Two finite-element methods have been developed for mathematical modeling of the time-dependent behaviors of deformable objects and, more specifically, the mechanical responses of soft tissues and organs in contact with surgical tools. These methods may afford the computational efficiency needed to satisfy the requirement to obtain computational results in real time for simulating surgical procedures as described in Simulation System for Training in Laparoscopic Surgery (NPO-21192) on page 31 in this issue of NASA Tech Briefs. Simulation of the behavior of soft tissue in real time is a challenging problem because of the complexity of soft-tissue mechanics. The responses of soft tissues are characterized by nonlinearities and by spatial inhomogeneities and rate and time dependences of material properties. Finite-element methods seem promising for integrating these characteristics of tissues into computational models of organs, but they demand much central-processing-unit (CPU) time and memory, and the demand increases with the number of nodes and degrees of freedom in a given finite-element model. Hence, as finite-element models become more realistic, it becomes more difficult to compute solutions in real time. In both of the present methods, one uses approximate mathematical models trading some accuracy for computational efficiency and thereby increasing the feasibility of attaining real-time up36 NASA Tech Briefs, October 2003 date rates. The first of these methods is based on modal analysis. In this method, one reduces the number of differential equations by selecting only the most significant vibration modes of an object (typically, a suitable number of the lowest-frequency modes) for computing deformations of the object in response to applied forces.
Robboy, Stanley J; Gupta, Saurabh; Crawford, James M; Cohen, Michael B; Karcher, Donald S; Leonard, Debra G B; Magnani, Barbarajean; Novis, David A; Prystowsky, Michael B; Powell, Suzanne Z; Gross, David J; Black-Schaffer, W Stephen
2015-11-01
Pathologists are physicians who make diagnoses based on interpretation of tissue and cellular specimens (surgical/cytopathology, molecular/genomic pathology, autopsy), provide medical leadership and consultation for laboratory medicine, and are integral members of their institutions' interdisciplinary patient care teams. To develop a dynamic modeling tool to examine how individual factors and practice variables can forecast demand for pathologist services. Build and test a computer-based software model populated with data from surveys and best estimates about current and new pathologist efforts. Most pathologists' efforts focus on anatomic (52%), laboratory (14%), and other direct services (8%) for individual patients. Population-focused services (12%) (eg, laboratory medical direction) and other professional responsibilities (14%) (eg, teaching, research, and hospital committees) consume the rest of their time. Modeling scenarios were used to assess the need to increase or decrease efforts related globally to the Affordable Care Act, and specifically, to genomic medicine, laboratory consolidation, laboratory medical direction, and new areas where pathologists' expertise can add value. Our modeling tool allows pathologists, educators, and policy experts to assess how various factors may affect demand for pathologists' services. These factors include an aging population, advances in biomedical technology, and changing roles in capitated, value-based, and team-based medical care systems. In the future, pathologists will likely have to assume new roles, develop new expertise, and become more efficient in practicing medicine to accommodate new value-based delivery models.
Kiparsky, Michael; Joyce, Brian; Purkey, David; Young, Charles
2014-01-01
We present an integrated hydrology/water operations simulation model of the Tuolumne and Merced River Basins, California, using the Water Evaluation and Planning (WEAP) platform. The model represents hydrology as well as water operations, which together influence water supplied for agricultural, urban, and environmental uses. The model is developed for impacts assessment using scenarios for climate change and other drivers of water system behavior. In this paper, we describe the model structure, its representation of historical streamflow, agricultural and urban water demands, and water operations. We describe projected impacts of climate change on hydrology and water supply to the major irrigation districts in the area, using uniform 2°C, 4°C, and 6°C increases applied to climate inputs from the calibration period. Consistent with other studies, we find that the timing of hydrology shifts earlier in the water year in response to temperature warming (5–21 days). The integrated agricultural model responds with increased water demands 2°C (1.4–2.0%), 4°C (2.8–3.9%), and 6°C (4.2–5.8%). In this sensitivity analysis, the combination of altered hydrology and increased demands results in decreased reliability of surface water supplied for agricultural purposes, with modeled quantity-based reliability metrics decreasing from a range of 0.84–0.90 under historical conditions to 0.75–0.79 under 6°C warming scenario. PMID:24465455
An Adaptation Dilemma Caused by Impacts-Modeling Uncertainty
NASA Astrophysics Data System (ADS)
Frieler, K.; Müller, C.; Elliott, J. W.; Heinke, J.; Arneth, A.; Bierkens, M. F.; Ciais, P.; Clark, D. H.; Deryng, D.; Doll, P. M.; Falloon, P.; Fekete, B. M.; Folberth, C.; Friend, A. D.; Gosling, S. N.; Haddeland, I.; Khabarov, N.; Lomas, M. R.; Masaki, Y.; Nishina, K.; Neumann, K.; Oki, T.; Pavlick, R.; Ruane, A. C.; Schmid, E.; Schmitz, C.; Stacke, T.; Stehfest, E.; Tang, Q.; Wisser, D.
2013-12-01
Ensuring future well-being for a growing population under either strong climate change or an aggressive mitigation strategy requires a subtle balance of potentially conflicting response measures. In the case of competing goals, uncertainty in impact estimates plays a central role when high confidence in achieving a primary objective (such as food security) directly implies an increased probability of uncertainty induced failure with regard to a competing target (such as climate protection). We use cross sectoral consistent multi-impact model simulations from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP, www.isi-mip.org) to illustrate this uncertainty dilemma: RCP projections from 7 global crop, 11 hydrological, and 7 biomes models are combined to analyze irrigation and land use changes as possible responses to climate change and increasing crop demand due to population growth and economic development. We show that - while a no-regrets option with regard to climate protection - additional irrigation alone is not expected to balance the demand increase by 2050. In contrast, a strong expansion of cultivated land closes the projected production-demand gap in some crop models. However, it comes at the expense of a loss of natural carbon sinks of order 50%. Given the large uncertainty of state of the art crop model projections even these strong land use changes would not bring us ';on the safe side' with respect to food supply. In a world where increasing carbon emissions continue to shrink the overall solution space, we demonstrate that current impacts-modeling uncertainty is a luxury we cannot afford. ISI-MIP is intended to provide cross sectoral consistent impact projections for model intercomparison and improvement as well as cross-sectoral integration. The results presented here were generated within the first Fast-Track phase of the project covering global impact projections. The second phase will also include regional projections. It is the aim of the project to build up a CMIP like open archive for climate impact projections allowing for the necessary sharpening the our picture of a 1,2,3,4 degrees warmer world.
Grebenstein, Patricia; Burroughs, Danielle; Zhang, Yan; LeSage, Mark G
2013-12-01
Reducing the nicotine content in tobacco products is being considered by the FDA as a policy to reduce the addictiveness of tobacco products. Understanding individual differences in response to nicotine reduction will be critical to developing safe and effective policy. Animal and human research demonstrating sex differences in the reinforcing effects of nicotine suggests that males and females may respond differently to nicotine-reduction policies. However, no studies have directly examined sex differences in the effects of nicotine unit-dose reduction on nicotine self-administration (NSA) in animals. The purpose of the present study was to examine this issue in a rodent self-administration model. Male and female rats were trained to self-administer nicotine (0.06mg/kg) under an FR 3 schedule during daily 23h sessions. Rats were then exposed to saline extinction and reacquisition of NSA, followed by weekly reductions in the unit dose (0.03 to 0.00025mg/kg) until extinction levels of responding were achieved. Males and females were compared with respect to baseline levels of intake, resistance to extinction, degree of compensatory increases in responding during dose reduction, and the threshold reinforcing unit dose of nicotine. Exponential demand-curve analysis was also conducted to compare the sensitivity of males and females to increases in the unit price (FR/unit dose) of nicotine (i.e., elasticity of demand or reinforcing efficacy). Females exhibited significantly higher baseline intake and less compensation than males. However, there were no sex differences in the reinforcement threshold or elasticity of demand. Dose-response relationships were very well described by the exponential demand function (r(2) values>0.96 for individual subjects). These findings suggest that females may exhibit less compensatory smoking in response to nicotine reduction policies, even though their nicotine reinforcement threshold and elasticity of demand may not differ from males. Copyright © 2013 Elsevier Inc. All rights reserved.
Grebenstein, Patricia; Burroughs, Danielle; Zhang, Yan; LeSage, Mark G.
2013-01-01
Reducing the nicotine content in tobacco products is being considered by the FDA as a policy to reduce the addictiveness of tobacco products. Understanding individual differences in response to nicotine reduction will be critical to developing safe and effective policy. Animal and human research demonstrating sex differences in the reinforcing effects of nicotine suggests that males and females may respond differently to nicotine-reduction policies. However, no studies have directly examined sex differences in the effects of nicotine unit-dose reduction on nicotine self-administration (NSA) in animals. The purpose of the present study was to examine this issue in a rodent self-administration model. Male and female rats were trained to self-administer nicotine (0.06 mg/kg) under an FR 3 schedule during daily 23 h sessions. Rats were then exposed to saline extinction and reacquisition of NSA, followed by weekly reductions in the unit dose (0.03 to 0.00025 mg/kg) until extinction levels of responding were achieved. Males and females were compared with respect to baseline levels of intake, resistance to extinction, degree of compensatory increases in responding during dose reduction, and the threshold reinforcing unit dose of nicotine. Exponential demand-curve analysis was also conducted to compare the sensitivity of males and females to increases in the unit price (FR/unit dose) of nicotine (i.e., elasticity of demand or reinforcing efficacy). Females exhibited significantly higher baseline intake and less compensation than males. However, there were no sex differences in the reinforcement threshold or elasticity of demand. Dose–response relationships were very well described by the exponential demand function (r2 values > 0.96 for individual subjects). These findings suggest that females may exhibit less compensatory smoking in response to nicotine reduction policies, even though their nicotine reinforcement threshold and elasticity of demand may not differ from males. PMID:24201048
ERIC Educational Resources Information Center
MacSuga, Ashley S.; Simonsen, Brandi
2011-01-01
Many classroom teachers are faced with challenging student behaviors that impact their ability to facilitate learning in productive, safe environments. At the same time, high-stakes testing, increased emphasis on evidence-based instruction, data-based decision making, and response-to-intervention models have put heavy demands on teacher time and…
ERIC Educational Resources Information Center
Gifford, James F., Jr., Ed.; And Others
In view of increased public demand since 1965 for medical curriculum re-evaluation, the Duke University School of Medicine offered the first new model of medical education responsive to social pressures for change. The new Duke curriculum included presentation by each basic science department of the core of principles and information considered…
Increasing urban development in the arid and semi-arid regions of the southwestern United States has led to greater demand for water in a region with limited water resources and has fundamentally altered the hydrologic response of developed watersheds. Green Infrastructure (GI) p...
ERIC Educational Resources Information Center
Young, Suzanne; Nagpal, Swati
2013-01-01
The current business landscape has created the impetus to develop management graduates with capabilities that foster responsible leadership and sustainability. Through the lens of Gitsham's 3C Model (Complexity, Context and Connection) of graduate capabilities, this paper discusses the experience of implementing the United Nations Principles for…
Evaluating Processes and Platforms for Potential ePortfolio Use: The Role of the Middle Agent
ERIC Educational Resources Information Center
Slade, Christine; Murfin, Keith; Readman, Kylie
2013-01-01
With the changing face of higher education comes a demand to include new technological tools. Universities need to build their capacity to respond to new technology-related challenges. The introduction of ePortfolios is a significant strategy in this response. A number of organizational change management models are used to analyze the…
OpenADR Specification to Ease Saving Power in Buildings
Piette, Mary Ann
2017-12-09
A new data model developed by researchers at the Department of Energys Lawrence Berkeley National Laboratory and their colleagues at other universities and in the private sector will help facilities and buildings save power through automated demand response technology, and advance the development of the Smart Grid. http://newscenter.lbl.gov/press-releases/2009/04/27/openadr-specification/
Donald B.K. English; Amy Horne
1996-01-01
To evaluate how forest management alternatives affect recreation visitation, managers need to know both the changes in demand for the sites being altered and the general changes in regional recreation trip production. This paper shows one way to obtain that information. Trip-generation models developed for the United States Forest Service's national assessments of...
Evaluation of Hybrid Learning in a Construction Engineering Context: A Mixed-Method Approach
ERIC Educational Resources Information Center
Karabulut-Ilgu, Aliye; Jahren, Charles
2016-01-01
Engineering educators call for a widespread implementation of hybrid learning to respond to rapidly changing demands of the 21st century. In response to this call, a junior-level course in the Construction Engineering program entitled Construction Equipment and Heavy Construction Methods was converted into a hybrid learning model. The overarching…
ERIC Educational Resources Information Center
Stebleton, Michael J.; Soria, Krista M.; Cherney, Blythe T.
2013-01-01
Study abroad opportunities continue to be a popular choice for U.S. college students looking to expand their undergraduate education. In response to the increasing demand for international opportunities, campuses have diversified their study abroad program models. On many campuses, students not only have opportunities to study abroad during…
Increasing urban development in the arid and semi-arid regions of the southwestern United States has led to greater demand for water from a region of limited water resources which has fundamentally altered the hydrologic response of developed watersheds. Green Infrastructure (GI)...
78 FR 59775 - Blueberry Promotion, Research and Information Order; Assessment Rate Increase
Federal Register 2010, 2011, 2012, 2013, 2014
2013-09-30
... demand. \\6\\ The econometric model used statistical methods with time series data to measure how strongly... been over 15 times greater than the costs. At the opposite end of the spectrum in the supply response, the average BCR was computed to be 5.36, implying that the benefits of the USHBC were over five times...
Detrick, Paul; Chibnall, John T; Call, Cynthia
2010-09-01
Understanding and detecting response distortion is important in the high-demand circumstances of personnel selection. In this article, we describe positive response distortion on the Revised NEO Personality Inventory (NEO PI-R; Costa & McCrae, 1992) among police officer applicants under high and low demand conditions. Positive response distortion primarily reflected denial/minimization of Neuroticism and accentuation of traits associated with moralistic bias (Agreeableness and Conscientiousness). Validity of the NEO PI-R research validity scale, Positive Presentation Management, was weakly supported with respect to the Neuroticism domain only. Results will be useful in interpreting personality inventory results in the police personnel selection process.
Multiagent intelligent systems
NASA Astrophysics Data System (ADS)
Krause, Lee S.; Dean, Christopher; Lehman, Lynn A.
2003-09-01
This paper will discuss a simulation approach based upon a family of agent-based models. As the demands placed upon simulation technology by such applications as Effects Based Operations (EBO), evaluations of indicators and warnings surrounding homeland defense and commercial demands such financial risk management current single thread based simulations will continue to show serious deficiencies. The types of "what if" analysis required to support these types of applications, demand rapidly re-configurable approaches capable of aggregating large models incorporating multiple viewpoints. The use of agent technology promises to provide a broad spectrum of models incorporating differing viewpoints through a synthesis of a collection of models. Each model would provide estimates to the overall scenario based upon their particular measure or aspect. An agent framework, denoted as the "family" would provide a common ontology in support of differing aspects of the scenario. This approach permits the future of modeling to change from viewing the problem as a single thread simulation, to take into account multiple viewpoints from different models. Even as models are updated or replaced the agent approach permits rapid inclusion in new or modified simulations. In this approach a variety of low and high-resolution information and its synthesis requires a family of models. Each agent "publishes" its support for a given measure and each model provides their own estimates on the scenario based upon their particular measure or aspect. If more than one agent provides the same measure (e.g. cognitive) then the results from these agents are combined to form an aggregate measure response. The objective would be to inform and help calibrate a qualitative model, rather than merely to present highly aggregated statistical information. As each result is processed, the next action can then be determined. This is done by a top-level decision system that communicates to the family at the ontology level without any specific understanding of the processes (or model) behind each agent. The increasingly complex demands upon simulation for the necessity to incorporate the breadth and depth of influencing factors makes a family of agent based models a promising solution. This paper will discuss that solution with syntax and semantics necessary to support the approach.
Microgrid to enable optimal distributed energy retail and end-user demand response
DOE Office of Scientific and Technical Information (OSTI.GOV)
Jin, Ming; Feng, Wei; Marnay, Chris
In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less
Microgrid to enable optimal distributed energy retail and end-user demand response
Jin, Ming; Feng, Wei; Marnay, Chris; ...
2018-06-07
In the face of unprecedented challenges in environmental sustainability and grid resilience, there is an increasingly held consensus regarding the adoption of distributed and renewable energy resources such as microgrids (MGs), and the utilization of flexible electric loads by demand response (DR) to potentially drive a necessary paradigm shift in energy production and consumption patterns. However, the potential value of distributed generation and demand flexibility has not yet been fully realized in the operation of MGs. This study investigates the pricing and operation strategy with DR for a MG retailer in an integrated energy system (IES). Based on co-optimizing retailmore » rates and MG dispatch formulated as a mixed integer quadratic programming (MIQP) problem, our model devises a dynamic pricing scheme that reflects the cost of generation and promotes DR, in tandem with an optimal dispatch plan that exploits spark spread and facilitates the integration of renewables, resulting in improved retailer profits and system stability. Main issues like integrated energy coupling and customer bill reduction are addressed during pricing to ensure rates competitiveness and customer protection. By evaluating on real datasets, the system is demonstrated to optimally coordinate storage, renewables, and combined heat and power (CHP), reduce carbon dioxide emission while maintaining profits, and effectively alleviate the PV curtailment problem. Finally, the model can be used by retailers and MG operators to optimize their operations, as well as regulators to design new utility rates in support of the ongoing transformation of energy systems.« less
China's Rare Earth Supply Chain: Illegal Production, and Response to new Cerium Demand
NASA Astrophysics Data System (ADS)
Nguyen, Ruby Thuy; Imholte, D. Devin
2016-07-01
As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China's supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructed a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the US market starting from 2018. Results showed that market share of the illegal sector has grown since 2007-2015, ranging between 22% and 25% of China's rare earth supply, translating into 59-65% illegal heavy rare earths and 14-16% illegal light rare earths. There will be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Finally, we illustrate revenue streams for different ore compositions in China in 2015.
China’s rare earth supply chain: Illegal production, and response to new cerium demand
Nguyen, Ruby Thuy; Imholte, D. Devin
2016-03-29
As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China’s supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructedmore » a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the U.S. market starting from 2018. Results showed that market share of the illegal sector has grown since 2007 to 2015, ranging between 22% and 25% of China’s rare earth supply, translating into 59–65% illegal heavy rare earths and 14–16% illegal light rare earths. There would be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Lastly, we illustrated revenue streams for different ore compositions in China in 2015.« less
Impacts of Demand-Side Resources on Electric Transmission Planning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hadley, Stanton W.; Sanstad, Alan H.
2015-01-01
Will demand resources such as energy efficiency (EE), demand response (DR), and distributed generation (DG) have an impact on electricity transmission requirements? Five drivers for transmission expansion are discussed: interconnection, reliability, economics, replacement, and policy. With that background, we review the results of a set of transmission studies that were conducted between 2010 and 2013 by electricity regulators, industry representatives, and other stakeholders in the three physical interconnections within the United States. These broad-based studies were funded by the US Department of Energy and included scenarios of reduced load growth due to EE, DR, and DG. While the studies weremore » independent and used different modeling tools and interconnect-specific assumptions, all provided valuable results and insights. However, some caveats exist. Demand resources were evaluated in conjunction with other factors, and limitations on transmission additions between scenarios made understanding the role of demand resources difficult. One study, the western study, included analyses over both 10- and 20-year planning horizons; the 10-year analysis did not show near-term reductions in transmission, but the 20-year indicated fewer transmission additions, yielding a 36percent capital cost reduction. In the eastern study the reductions in demand largely led to reductions in local generation capacity and an increased opportunity for low-cost and renewable generation to export to other regions. The Texas study evaluated generation changes due to demand, and is in the process of examining demand resource impacts on transmission.« less
China’s rare earth supply chain: Illegal production, and response to new cerium demand
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nguyen, Ruby Thuy; Imholte, D. Devin
As the demand for personal electronic devices, wind turbines, and electric vehicles increases, the world becomes more dependent on rare earth elements. Given the volatile, Chinese-concentrated supply chain, global attempts have been made to diversify supply of these materials. However, the overall effect of supply diversification on the entire supply chain, including increasing low-value rare earth demand, is not fully understood. This paper is the first attempt to shed some light on China’s supply chain from both demand and supply perspectives, taking into account different Chinese policies such as mining quotas, separation quotas, export quotas, and resource taxes. We constructedmore » a simulation model using Powersim Studio that analyzes production (both legal and illegal), production costs, Chinese and rest-of-world demand, and market dynamics. We also simulated new demand of an automotive aluminum-cerium alloy in the U.S. market starting from 2018. Results showed that market share of the illegal sector has grown since 2007 to 2015, ranging between 22% and 25% of China’s rare earth supply, translating into 59–65% illegal heavy rare earths and 14–16% illegal light rare earths. There would be a shortage in certain light and heavy rare earths given three production quota scenarios and constant demand growth rate from 2015 to 2030. The new simulated Ce demand would require supply beyond that produced in China. Lastly, we illustrated revenue streams for different ore compositions in China in 2015.« less
Song, Benbo; Scheuner, Donalyn; Ron, David; Pennathur, Subramaniam; Kaufman, Randal J.
2008-01-01
The progression from insulin resistance to type 2 diabetes is caused by the failure of pancreatic β cells to produce sufficient levels of insulin to meet the metabolic demand. Recent studies indicate that nutrient fluctuations and insulin resistance increase proinsulin synthesis in β cells beyond the capacity for folding of nascent polypeptides within the endoplasmic reticulum (ER) lumen, thereby disrupting ER homeostasis and triggering the unfolded protein response (UPR). Chronic ER stress promotes apoptosis, at least in part through the UPR-induced transcription factor C/EBP homologous protein (CHOP). We assessed the effect of Chop deletion in multiple mouse models of type 2 diabetes and found that Chop–/– mice had improved glycemic control and expanded β cell mass in all conditions analyzed. In both genetic and diet-induced models of insulin resistance, CHOP deficiency improved β cell ultrastructure and promoted cell survival. In addition, we found that isolated islets from Chop–/– mice displayed increased expression of UPR and oxidative stress response genes and reduced levels of oxidative damage. These findings suggest that CHOP is a fundamental factor that links protein misfolding in the ER to oxidative stress and apoptosis in β cells under conditions of increased insulin demand. PMID:18776938
NASA Astrophysics Data System (ADS)
Lohmann, Timo
Electric sector models are powerful tools that guide policy makers and stakeholders. Long-term power generation expansion planning models are a prominent example and determine a capacity expansion for an existing power system over a long planning horizon. With the changes in the power industry away from monopolies and regulation, the focus of these models has shifted to competing electric companies maximizing their profit in a deregulated electricity market. In recent years, consumers have started to participate in demand response programs, actively influencing electricity load and price in the power system. We introduce a model that features investment and retirement decisions over a long planning horizon of more than 20 years, as well as an hourly representation of day-ahead electricity markets in which sellers of electricity face buyers. This combination makes our model both unique and challenging to solve. Decomposition algorithms, and especially Benders decomposition, can exploit the model structure. We present a novel method that can be seen as an alternative to generalized Benders decomposition and relies on dynamic linear overestimation. We prove its finite convergence and present computational results, demonstrating its superiority over traditional approaches. In certain special cases of our model, all necessary solution values in the decomposition algorithms can be directly calculated and solving mathematical programming problems becomes entirely obsolete. This leads to highly efficient algorithms that drastically outperform their programming problem-based counterparts. Furthermore, we discuss the implementation of all tailored algorithms and the challenges from a modeling software developer's standpoint, providing an insider's look into the modeling language GAMS. Finally, we apply our model to the Texas power system and design two electricity policies motivated by the U.S. Environment Protection Agency's recently proposed CO2 emissions targets for the power sector.
Stress induced obesity: lessons from rodent models of stress
Patterson, Zachary R.; Abizaid, Alfonso
2013-01-01
Stress was once defined as the non-specific result of the body to any demand or challenge to homeostasis. A more current view of stress is the behavioral and physiological responses generated in the face of, or in anticipation of, a perceived threat. The stress response involves activation of the sympathetic nervous system and recruitment of the hypothalamic-pituitary-adrenal (HPA) axis. When an organism encounters a stressor (social, physical, etc.), these endogenous stress systems are stimulated in order to generate a fight-or-flight response, and manage the stressful situation. As such, an organism is forced to liberate energy resources in attempt to meet the energetic demands posed by the stressor. A change in the energy homeostatic balance is thus required to exploit an appropriate resource and deliver useable energy to the target muscles and tissues involved in the stress response. Acutely, this change in energy homeostasis and the liberation of energy is considered advantageous, as it is required for the survival of the organism. However, when an organism is subjected to a prolonged stressor, as is the case during chronic stress, a continuous irregularity in energy homeostasis is considered detrimental and may lead to the development of metabolic disturbances such as cardiovascular disease, type II diabetes mellitus and obesity. This concept has been studied extensively using animal models, and the neurobiological underpinnings of stress induced metabolic disorders are beginning to surface. However, different animal models of stress continue to produce divergent metabolic phenotypes wherein some animals become anorexic and lose body mass while others increase food intake and body mass and become vulnerable to the development of metabolic disturbances. It remains unclear exactly what factors associated with stress models can be used to predict the metabolic outcome of the organism. This review will explore a variety of rodent stress models and discuss the elements that influence the metabolic outcome in order to further extend our understanding of stress-induced obesity. PMID:23898237
Two-and-a-half-year-olds succeed at a traditional false-belief task with reduced processing demands.
Setoh, Peipei; Scott, Rose M; Baillargeon, Renée
2016-11-22
When tested with traditional false-belief tasks, which require answering a standard question about the likely behavior of an agent with a false belief, children perform below chance until age 4 y or later. When tested without such questions, however, children give evidence of false-belief understanding much earlier. Are traditional tasks difficult because they tap a more advanced form of false-belief understanding (fundamental-change view) or because they impose greater processing demands (processing-demands view)? Evidence that young children succeed at traditional false-belief tasks when processing demands are reduced would support the latter view. In prior research, reductions in inhibitory-control demands led to improvements in young children's performance, but often only to chance (instead of below-chance) levels. Here we examined whether further reductions in processing demands might lead to success. We speculated that: (i) young children could respond randomly in a traditional low-inhibition task because their limited information-processing resources are overwhelmed by the total concurrent processing demands in the task; and (ii) these demands include those from the response-generation process activated by the standard question. This analysis suggested that 2.5-y-old toddlers might succeed at a traditional low-inhibition task if response-generation demands were also reduced via practice trials. As predicted, toddlers performed above chance following two response-generation practice trials; toddlers failed when these trials either were rendered less effective or were used in a high-inhibition task. These results support the processing-demands view: Even toddlers succeed at a traditional false-belief task when overall processing demands are reduced.
Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids.
Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo
2018-01-09
In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced.
Method for Estimating Patronage of Demand Responsive Transportation Systems
DOT National Transportation Integrated Search
1977-12-01
This study has developed a method for estimating patronage of demand responsive transportation (DRT) systems. This procedure requires as inputs a description of the intended service area, current work trip patterns, characteristics of the served popu...
DOT National Transportation Integrated Search
1977-04-01
The Urban Mass Transportation Administration carries out research and developmet on Areawide Demand Responsive Transportation (AWDRT) systems as part of the Bus and Paratransit Technoloy activities. AWDRT systems are basically the interation of flexi...
Idris, Mohd Awang; Dollard, Maureen F; Yulita
2014-07-01
This multilevel longitudinal study investigates a newly identified climate construct, psychosocial safety climate (PSC), as a precursor to job characteristics (e.g., emotional demands), and psychological outcomes (i.e., emotional exhaustion and depression). We argued that PSC, as an organizational climate construct, has cross-level effects on individually perceived job design and psychological outcomes. We hypothesized a mediation process between PSC and emotional exhaustion particularly through emotional demands. In sequence, we predicted that emotional exhaustion would predict depression. At Time 1, data were collected from employees in 36 Malaysian private sector organizations (80% responses rate), n = 253 (56%), and at Time 2 from 27 organizations (60%) and n = 117 (46%). Using hierarchical linear modeling (HLM), we found that there were cross-level effects of PSC Time 1 on emotional demands Time 2 and emotional exhaustion Time 2, but not on depression Time 2, across a 3-month time lag. We found evidence for a lagged mediated effect; emotional demands mediated the relationship between PSC and emotional exhaustion. Emotional exhaustion did not predict depression. Finally, our results suggest that PSC is an important organizational climate construct, and acts to reduce employee psychological problems in the workplace, via working conditions.
Burnout, Engagement, and Organizational Culture: Differences between Physicians and Nurses.
Mijakoski, Dragan; Karadzinska-Bislimovska, Jovanka; Basarovska, Vera; Montgomery, Anthony; Panagopoulou, Efharis; Stoleski, Sasho; Minov, Jordan
2015-09-15
Burnout results from a prolonged response to chronic emotional and interpersonal workplace stressors. The focus of research has been widened to job engagement. Purpose of the study was to examine associations between burnout, job engagement, work demands, and organisational culture (OC) and to demonstrate differences between physicians and nurses working in general hospital in Skopje, Republic of Macedonia. Maslach Burnout Inventory and Utrecht Work Engagement Scale were used for assessment of burnout and job engagement. Work demands and OC were measured with Hospital Experience Scale and Competing Values Framework, respectively. Higher scores of dedication, hierarchy OC, and organizational work demands were found in physicians. Nurses demonstrated higher scores of clan OC. Burnout negatively correlated with clan and market OC in physicians and nurses. Job engagement positively correlated with clan and market OC in nurses. Different work demands were related to different dimensions of burnout and/or job engagement. Our findings support job demands-resources (JD-R) model (Demerouti and Bakker). Data obtained can be used in implementation of specific organizational interventions in the hospital setting. Providing adequate JD-R interaction can lead to prevention of burnout in health professionals (HPs) and contribute positively to better job engagement in HPs and higher quality of patient care.
Venkatraman, Vinod; Rosati, Alexandra G; Taren, Adrienne A; Huettel, Scott A
2009-10-21
The dorsomedial prefrontal cortex (DMPFC) plays a central role in aspects of cognitive control and decision making. Here, we provide evidence for an anterior-to-posterior topography within the DMPFC using tasks that evoke three distinct forms of control demands--response, decision, and strategic--each of which could be mapped onto independent behavioral data. Specifically, we identify three spatially distinct regions within the DMPFC: a posterior region associated with control demands evoked by multiple incompatible responses, a middle region associated with control demands evoked by the relative desirability of decision options, and an anterior region that predicts control demands related to deviations from an individual's preferred decision-making strategy. These results provide new insight into the functional organization of DMPFC and suggest how recent controversies about its role in complex decision making and response mapping can be reconciled.
Venkatraman, Vinod; Rosati, Alexandra G.; Taren, Adrienne A.; Huettel, Scott A.
2009-01-01
The dorsomedial prefrontal cortex (DMPFC) plays a central role in aspects of cognitive control and decision making. Here, we provide evidence for an anterior-to-posterior topography within the DMPFC using tasks that evoke three distinct forms of control demands – response, decision, and strategic – each of which could be mapped on to independent behavioral data. Specifically, we identify three spatially distinct regions within the DMPFC: a posterior region associated with control demands evoked by multiple incompatible responses, a middle region associated with control demands evoked by the relative desirability of decision options, and an anterior region that predicts control demands related to deviations from an individual's preferred decision-making strategy. These results provide new insight into the functional organization of DMPFC, and suggest how recent controversies about its role in complex decision making and response mapping can be reconciled. PMID:19846703
The Focusing of Responsibility: An Alternative Hypothesis in Help-Demanding Situations.
ERIC Educational Resources Information Center
Misavage, Robert; Richardson, James T.
The "diffusion of responsibility" hypothesis as an explanation of helping behavior (or lack of same) is qualified by suggesting that the hypothesis applies only in non-interacting situations. It is hypothesized that interacting groups who are aware of a help-demanding situation actually focus the responsibility and, therefore, take action as a…
Demand forecasting of electricity in Indonesia with limited historical data
NASA Astrophysics Data System (ADS)
Dwi Kartikasari, Mujiati; Rohmad Prayogi, Arif
2018-03-01
Demand forecasting of electricity is an important activity for electrical agents to know the description of electricity demand in future. Prediction of demand electricity can be done using time series models. In this paper, double moving average model, Holt’s exponential smoothing model, and grey model GM(1,1) are used to predict electricity demand in Indonesia under the condition of limited historical data. The result shows that grey model GM(1,1) has the smallest value of MAE (mean absolute error), MSE (mean squared error), and MAPE (mean absolute percentage error).
NASA Technical Reports Server (NTRS)
1974-01-01
The transient and steady state response of the respiratory control system for variations in volumetric fractions of inspired gases and special system parameters are modeled. The program contains the capability to change workload. The program is based on Grodins' respiratory control model and can be envisioned as a feedback control system comprised of a plant (the controlled system) and the regulating component (controlling system). The controlled system is partitioned into 3 compartments corresponding to lungs, brain, and tissue with a fluid interconnecting patch representing the blood.
A novel medical information management and decision model for uncertain demand optimization.
Bi, Ya
2015-01-01
Accurately planning the procurement volume is an effective measure for controlling the medicine inventory cost. Due to uncertain demand it is difficult to make accurate decision on procurement volume. As to the biomedicine sensitive to time and season demand, the uncertain demand fitted by the fuzzy mathematics method is obviously better than general random distribution functions. To establish a novel medical information management and decision model for uncertain demand optimization. A novel optimal management and decision model under uncertain demand has been presented based on fuzzy mathematics and a new comprehensive improved particle swarm algorithm. The optimal management and decision model can effectively reduce the medicine inventory cost. The proposed improved particle swarm optimization is a simple and effective algorithm to improve the Fuzzy interference and hence effectively reduce the calculation complexity of the optimal management and decision model. Therefore the new model can be used for accurate decision on procurement volume under uncertain demand.
Effects of the relative fee structure on the use of surgical operations.
Escarce, J J
1993-10-01
The goal is to develop a theoretical and empirical framework for investigating how the demand for an operation may be affected by the fee for the operation (the own-price) and by fees for other services provided by surgeons in the same specialty (the cross-price). The theory suggests an empirical test of whether surgeons create demand for surgery. The study examines the use of 11 frequently performed surgical operations by elderly Medicare enrollees in a cross-section of 316 U.S. metropolitan areas. Medicare physician claims and enrollment files for 1986 are the principal sources of data. Using econometric methods, a structural demand equation modified to include the own-price and the cross-price is estimated for each study operation. The theory suggests that the utilization response to changes in fees may differ among operations depending on whether demand creation occurs and on the interplay of distinct own-price and cross-price effects. However, the results of the empirical analyses are inconclusive regarding the most appropriate economic model of surgical utilization. Both neoclassical behavior and demand creation are observed, but technical limitations of the analyses, including the cross-sectional design of the study, preclude definitive inferences. Despite the lack of definitive empirical results, the study has several implications for future research regarding the effect of changes in fees on surgical utilization. In particular, future studies should consider the roles of distinct own-price and cross-price effects, examine the importance of the supply-demand balance in physician services markets, and assess whether typologies of operations that are based on the strictness of their clinical indications predict the appropriate economic model of utilization.
[Management of allocation of positions for specialist medical training].
Alonso, M I
2003-01-01
Currently there is a large imbalance between supply and demand for medical specialists in the Spanish Health System. The aim of this study was to demonstrate the possible effects of current policies of allocating vacancies for interns and residents as well as to describe several measures and alternative policies. Using the methodology of System Dynamics, we designed a simulation model of the allocation process. Based on the validated model, possible changes in the system through time in response to diverse allocation policies were simulated. Specifically, changes in the accumulated number of graduates who over the years have remained without specialty, the number of unemployed specialists, and the imbalance between supply and demand in the period under consideration were observed. The results obtained from the simulation indicate that allocation policies such as the current one tends to reduce the accumulated number of graduates without specialty, due to the philosophy characterizing this policy, but that it considerably increases the number of unemployed specialists and aggravates the supply-demand imbalance. In the simulation, this tendency remained over time even though more restrictive measures in numerus clausus and retirement age were adopted. Equally, a policy based on social needs and aware of delays in training would substantially contribute to eliminating unemployment among specialists and supply-demand imbalance over time. If such a policy were combined with the above-mentioned measures the results would be even better, more rapidly eliminating graduates without specialty, unemployed specialists, and supply-demand imbalances. If the Health Administration continues with the current system of allocation of places, the present imbalance in supply and demand will become even worse. Therefore, new and far-sighted measures and policies are required, as well as greater coordination between undergraduate and postgraduate training.
Effects of the relative fee structure on the use of surgical operations.
Escarce, J J
1993-01-01
OBJECTIVE. The goal is to develop a theoretical and empirical framework for investigating how the demand for an operation may be affected by the fee for the operation (the own-price) and by fees for other services provided by surgeons in the same specialty (the cross-price). The theory suggests an empirical test of whether surgeons create demand for surgery. DATA SOURCES AND STUDY SETTING. The study examines the use of 11 frequently performed surgical operations by elderly Medicare enrollees in a cross-section of 316 U.S. metropolitan areas. Medicare physician claims and enrollment files for 1986 are the principal sources of data. STUDY DESIGN. Using econometric methods, a structural demand equation modified to include the own-price and the cross-price is estimated for each study operation. PRINCIPAL FINDINGS. The theory suggests that the utilization response to changes in fees may differ among operations depending on whether demand creation occurs and on the interplay of distinct own-price and cross-price effects. However, the results of the empirical analyses are inconclusive regarding the most appropriate economic model of surgical utilization. Both neoclassical behavior and demand creation are observed, but technical limitations of the analyses, including the cross-sectional design of the study, preclude definitive inferences. CONCLUSIONS. Despite the lack of definitive empirical results, the study has several implications for future research regarding the effect of changes in fees on surgical utilization. In particular, future studies should consider the roles of distinct own-price and cross-price effects, examine the importance of the supply-demand balance in physician services markets, and assess whether typologies of operations that are based on the strictness of their clinical indications predict the appropriate economic model of utilization. PMID:8407339
CO2 Mitigation Measures of Power Sector and Its Integrated Optimization in China
Dai, Pan; Chen, Guang; Zhou, Hao; Su, Meirong; Bao, Haixia
2012-01-01
Power sector is responsible for about 40% of the total CO2 emissions in the world and plays a leading role in climate change mitigation. In this study, measures that lower CO2 emissions from the supply side, demand side, and power grid are discussed, based on which, an integrated optimization model of CO2 mitigation (IOCM) is proposed. Virtual energy, referring to energy saving capacity in both demand side and the power grid, together with conventional energy in supply side, is unified planning for IOCM. Consequently, the optimal plan of energy distribution, considering both economic benefits and mitigation benefits, is figured out through the application of IOCM. The results indicate that development of demand side management (DSM) and smart grid can make great contributions to CO2 mitigation of power sector in China by reducing the CO2 emissions by 10.02% and 12.59%, respectively, in 2015, and in 2020. PMID:23213305
Modeling Integrated Water-User Decisions with Intermittent Supplies
NASA Astrophysics Data System (ADS)
Lund, J. R.; Rosenberg, D.
2006-12-01
We present an economic-engineering method to estimate urban water use demands with intermittent water supplies. A two-stage, probabilistic optimization formulation includes a wide variety of water supply enhancement and conservation actions that individual households can adopt to meet multiple water quality uses with uncertain water availability. We embed the optimization in Monte-Carlo simulations to show aggregate effects at a utility (citywide) scale for a population of user conditions and decisions. Parametric analysis provides derivations of supply curves to subsidize conservation, demand responses to alternative pricing, and customer willingness-to-pay to avoid shortages. Results show a good empirical fit for the average and distribution of billed residential water use in Amman, Jordan. Additional outputs give likely market penetration rates for household conservation actions, associated water savings, and subsidies required to entice further adoption. We discuss new insights to size, target, market, and finance conservation programs and interpret a demand curve with block pricing.
Richter, Michael
2010-05-01
Two experiments assessed the moderating impact of task context on the relationship between reward and cardiovascular response. Randomly assigned to the cells of a 2 (task context: reward vs. demand) x 2 (reward value: low vs. high) between-persons design, participants performed either a memory task with an unclear performance standard (Experiment 1) or a visual scanning task with an unfixed performance standard (Experiment 2). Before performing the task--where participants could earn either a low or a high reward--participants responded to questions about either task reward or task demand. In accordance with the theoretical predictions derived from Wright's (1996) integrative model, reactivity of pre-ejection period increased with reward value if participants had rated aspects of task reward before performing the task. If they had rated task demand, pre-ejection period did not differ as a function of reward. Copyright 2010 Elsevier B.V. All rights reserved.
The economics of tobacco use in Jordan.
Sweis, Nadia J; Chaloupka, Frank J
2014-01-01
We conducted an independent survey of tobacco use in Jordan following the methods and template of the Global Adult Tobacco Survey. Using data collected on cigarette use and cigarette prices, we estimated the price elasticity of cigarette demand in Jordan. We used a 2-part model of cigarette demand. In the first part, we estimate the impact of prices on the decision to smoke while controlling for individual demographic and environmental characteristics. Conditional on smoking, we then estimate the effect of price on the number of cigarettes smoked. The total price elasticity of cigarette demand in Jordan was estimated to be -0.6. Smoking among women was found to be relatively unresponsive to price (elasticity of -0.01), whereas smoking among men was much more responsive to price (elasticity of -0.81). The price elasticity estimates suggest that significant increases in tobacco taxes are likely to be effective in reducing smoking in Jordan, particularly smoking among men.
22 CFR 1506.5 - Demand for payment.
Code of Federal Regulations, 2010 CFR
2010-04-01
... total of three progressively stronger written demands at approximately 30-day intervals will normally be made, unless a response or other information indicates that additional written demands would either be unnecessary or futile. When necessary to protect the Government's interest, written demand may be preceded by...
Szabo, Gergely G.; Armstrong, Caren; Oijala, Mikko; Soltesz, Ivan
2014-01-01
Abstract Cover Figure Krook-Magnuson et al. report a bidirectional functional connectivity between the hippocampus and the cerebellum in a mouse model of temporal lobe epilepsy, and demonstrate that cerebellar directed on-demand optogenetic intervention can stop seizures recorded from the hippocampus. Temporal lobe epilepsy is often medically refractory and new targets for intervention are needed. We used a mouse model of temporal lobe epilepsy, on-line seizure detection, and responsive optogenetic intervention to investigate the potential for cerebellar control of spontaneous temporal lobe seizures. Cerebellar targeted intervention inhibited spontaneous temporal lobe seizures during the chronic phase of the disorder. We further report that the direction of modulation as well as the location of intervention within the cerebellum can affect the outcome of intervention. Specifically, on-demand optogenetic excitation or inhibition of parvalbumin-expressing neurons, including Purkinje cells, in the lateral or midline cerebellum results in a decrease in seizure duration. In contrast, a consistent reduction in spontaneous seizure frequency occurs uniquely with on-demand optogenetic excitation of the midline cerebellum, and was not seen with intervention directly targeting the hippocampal formation. These findings demonstrate that the cerebellum is a powerful modulator of temporal lobe epilepsy, and that intervention targeting the cerebellum as a potential therapy for epilepsy should be revisited. PMID:25599088
Bang-bang Model for Regulation of Local Blood Flow
Golub, Aleksander S.; Pittman, Roland N.
2013-01-01
The classical model of metabolic regulation of blood flow in muscle tissue implies the maintenance of basal tone in arterioles of resting muscle and their dilation in response to exercise and/or tissue hypoxia via the evoked production of vasodilator metabolites by myocytes. A century-long effort to identify specific metabolites responsible for explaining active and reactive hyperemia has not been successful. Furthermore, the metabolic theory is not compatible with new knowledge on the role of physiological radicals (e.g., nitric oxide, NO, and superoxide anion, O2−) in the regulation of microvascular tone. We propose a model of regulation in which muscle contraction and active hyperemia are considered the physiologically normal state. We employ the “bang-bang” or “on/off” regulatory model which makes use of a threshold and hysteresis; a float valve to control the water level in a tank is a common example of this type of regulation. Active bang-bang regulation comes into effect when the supply of oxygen and glucose exceeds the demand, leading to activation of membrane NADPH oxidase, release of O2− into the interstitial space and subsequent neutralization of the interstitial NO. Switching arterioles on/off when local blood flow crosses the threshold is realized by a local cell circuit with the properties of a bang-bang controller, determined by its threshold, hysteresis and dead-band. This model provides a clear and unambiguous interpretation of the mechanism to balance tissue demand with a sufficient supply of nutrients and oxygen. PMID:23441827
Muntaner, C; Schoenbach, C
1994-01-01
The authors use confirmatory factor analysis to investigate the psychosocial dimensions of work environments relevant to health outcomes, in a representative sample of five U.S. metropolitan areas. Through an aggregated inference system, scales from Schwartz and associates' job scoring system and from the Dictionary of Occupational Titles (DOT) were employed to examine two alternative models: the demand-control model of Karasek and Theorell and Johnson's demand-control-support model. Confirmatory factor analysis was used to test the two models. The two multidimensional models yielded better fits than an unstructured model. After allowing for the measurement error variance due to the method of assessment (Schwartz and associates' system or DOT), both models yielded acceptable goodness-of-fit indices, but the fit of the demand-control-support model was significantly better. Overall these results indicate that the dimensions of Control (substantive complexity of work, skill discretion, decision authority), Demands (physical exertion, physical demands and hazards), and Social Support (coworker and supervisor social supports) provide an acceptable account of the psychosocial dimensions of work associated with health outcomes.
Characterisation of the responsive properties of two running-specific prosthetic models.
Grobler, Lara; Ferreira, Suzanne; Vanwanseele, Benedicte; Terblanche, Elmarie E
2017-04-01
The need for information regarding running-specific prosthetic properties has previously been voiced. Such information is necessary to assist in athletes' prostheses selection. This study aimed to describe the characteristics of two commercially available running-specific prostheses. The running-specific prostheses were tested (in an experimental setup) without the external interference of athlete performance variations. Four stiffness categories of each running-specific prosthetic model (Xtend ™ and Xtreme ™ ) were tested at seven alignment setups and three drop masses (28, 38 and 48 kg). Results for peak ground reaction force (GRF peak ), contact time ( t c ), flight time ( t f ), reactive strength index (RSI) and maximal compression (Δ L) were determined during controlled dropping of running-specific prostheses onto a force platform with different masses attached to the experimental setup. No statistically significant differences were found between the different setups of the running-specific prostheses. Statistically significant differences were found between the two models for all outcome variables (GRF peak , Xtend > Xtreme; t c , Xtreme > Xtend; t f , Xtreme > Xtend; RSI, Xtend > Xtreme; Δ L, Xtreme > Xtend; p < 0.05). These findings suggest that the Xtreme stores more elastic energy than the Xtend, leading to a greater performance response. The specific responsive features of blades could guide sprint athletes in their choice of running-specific prostheses. Clinical relevance Insights into the running-specific prosthesis (RSP) properties and an understanding of its responsive characteristics have implications for athletes' prosthetic choice. Physiologically and metabolically, a short sprint event (i.e. 100 m) places different demands on the athlete than a long sprint event (i.e. 400 m), and the RSP should match these performance demands.
Subsidies and the demand for individual health insurance in California.
Marquis, M Susan; Buntin, Melinda Beeuwkes; Escarce, José J; Kapur, Kanika; Yegian, Jill M
2004-10-01
To estimate the effect of changes in premiums for individual insurance on decisions to purchase individual insurance and how this price response varies among subgroups of the population. Survey responses from the Current Population Survey (http://www.bls.census.gov/cps/cpsmain.htm), the Survey of Income and Program Participation (http://www.sipp.census.gov/sipp), the National Health Interview Survey (http://www.cdc.gov/nchs/nhis.htm), and data about premiums and plans offered in the individual insurance market in California, 1996-2001. A logit model was used to estimate the decisions to purchase individual insurance by families without access to group insurance. This was modeled as a function of premiums, controlling for family characteristics and other characteristics of the market. A multinomial model was used to estimate the choice between group coverage, individual coverage, and remaining uninsured for workers offered group coverage as a function of premiums for individual insurance and out-of-pocket costs of group coverage. The elasticity of demand for individual insurance by those without access to group insurance is about -.2 to -.4, as has been found in earlier studies. However, there are substantial differences in price responses among subgroups with low-income, young, and self-employed families showing the greatest response. Among workers offered group insurance, a decrease in individual premiums has very small effects on the choice to purchase individual coverage versus group coverage. Subsidy programs may make insurance more affordable for some families, but even sizeable subsidies are unlikely to solve the problem of the uninsured. We do not find evidence that subsidies to individual insurance will produce an unraveling of the employer-based health insurance system.
NASA Astrophysics Data System (ADS)
Zhou, Cong; Chase, J. Geoffrey; Rodgers, Geoffrey W.; Xu, Chao
2017-02-01
The model-free hysteresis loop analysis (HLA) method for structural health monitoring (SHM) has significant advantages over the traditional model-based SHM methods that require a suitable baseline model to represent the actual system response. This paper provides a unique validation against both an experimental reinforced concrete (RC) building and a calibrated numerical model to delineate the capability of the model-free HLA method and the adaptive least mean squares (LMS) model-based method in detecting, localizing and quantifying damage that may not be visible, observable in overall structural response. Results clearly show the model-free HLA method is capable of adapting to changes in how structures transfer load or demand across structural elements over time and multiple events of different size. However, the adaptive LMS model-based method presented an image of greater spread of lesser damage over time and story when the baseline model is not well defined. Finally, the two algorithms are tested over a simpler hysteretic behaviour typical steel structure to quantify the impact of model mismatch between the baseline model used for identification and the actual response. The overall results highlight the need for model-based methods to have an appropriate model that can capture the observed response, in order to yield accurate results, even in small events where the structure remains linear.
A multivariate time series approach to modeling and forecasting demand in the emergency department.
Jones, Spencer S; Evans, R Scott; Allen, Todd L; Thomas, Alun; Haug, Peter J; Welch, Shari J; Snow, Gregory L
2009-02-01
The goals of this investigation were to study the temporal relationships between the demands for key resources in the emergency department (ED) and the inpatient hospital, and to develop multivariate forecasting models. Hourly data were collected from three diverse hospitals for the year 2006. Descriptive analysis and model fitting were carried out using graphical and multivariate time series methods. Multivariate models were compared to a univariate benchmark model in terms of their ability to provide out-of-sample forecasts of ED census and the demands for diagnostic resources. Descriptive analyses revealed little temporal interaction between the demand for inpatient resources and the demand for ED resources at the facilities considered. Multivariate models provided more accurate forecasts of ED census and of the demands for diagnostic resources. Our results suggest that multivariate time series models can be used to reliably forecast ED patient census; however, forecasts of the demands for diagnostic resources were not sufficiently reliable to be useful in the clinical setting.
A sustainable model for training teachers to use pivotal response training.
Suhrheinrich, Jessica
2015-08-01
The increase in the rate of autism diagnoses has created a growing demand for teachers who are trained to use effective interventions. The train-the-trainer model, which involves training supervisors to train others, may be ideal for providing cost-effective training and ongoing support to teachers. Although research supports interventions, such as pivotal response training, as evidence-based, dissemination to school environments has been problematic. This study assessed the benefits of using the train-the-trainer model to disseminate pivotal response training to school settings. A multiple-baseline design was conducted across three training groups, each consisting of one school staff member (trainer), three special education teachers, and six students. Trainers conducted the teacher-training workshop with high adherence to training protocol and met mastery criteria in their ability to implement pivotal response training, assess implementation of pivotal response training, and provide feedback to teachers. Six of the nine teachers mastered all components of pivotal response training. The remaining three teachers implemented 89% of the pivotal response training components correctly. The majority of trainers and teachers maintained their abilities at follow-up. These results support the use of the train-the-trainer model as an effective method of disseminating evidence-based practices in school settings. © The Author(s) 2014.
A Small Aircraft Transportation System (SATS) Demand Model
NASA Technical Reports Server (NTRS)
Long, Dou; Lee, David; Johnson, Jesse; Kostiuk, Peter; Yackovetsky, Robert (Technical Monitor)
2001-01-01
The Small Aircraft Transportation System (SATS) demand modeling is a tool that will be useful for decision-makers to analyze SATS demands in both airport and airspace. We constructed a series of models following the general top-down, modular principles in systems engineering. There are three principal models, SATS Airport Demand Model (SATS-ADM), SATS Flight Demand Model (SATS-FDM), and LMINET-SATS. SATS-ADM models SATS operations, by aircraft type, from the forecasts in fleet, configuration and performance, utilization, and traffic mixture. Given the SATS airport operations such as the ones generated by SATS-ADM, SATS-FDM constructs the SATS origin and destination (O&D) traffic flow based on the solution of the gravity model, from which it then generates SATS flights using the Monte Carlo simulation based on the departure time-of-day profile. LMINET-SATS, an extension of LMINET, models SATS demands at airspace and airport by all aircraft operations in US The models use parameters to provide the user with flexibility and ease of use to generate SATS demand for different scenarios. Several case studies are included to illustrate the use of the models, which are useful to identify the need for a new air traffic management system to cope with SATS.
Scott, Rose M; Roby, Erin
2015-01-01
Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children's ability to demonstrate this capacity depends on the processing demands of the task and children's processing skills. When processing demands exceed young children's processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children's performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children's performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character's false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children's performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task involves an elicited response, children's performance depends on the processing demands of the task and their processing skills. These findings also have implications for alternative, deflationary accounts of early false-belief understanding.
Scott, Rose M.; Roby, Erin
2015-01-01
Prior to age four, children succeed in non-elicited-response false-belief tasks but fail elicited-response false-belief tasks. To explain this discrepancy, the processing-load account argues that the capacity to represent beliefs emerges in infancy, as indicated by early success on non-elicited-response tasks, but that children’s ability to demonstrate this capacity depends on the processing demands of the task and children’s processing skills. When processing demands exceed young children’s processing abilities, such as in standard elicited-response tasks, children fail despite their capacity to represent beliefs. Support for this account comes from recent evidence that reducing processing demands improves young children’s performance: when demands are sufficiently reduced, 2.5-year-olds succeed in elicited-response tasks. Here we sought complementary evidence for the processing-load account by examining whether increasing processing demands impeded children’s performance in a non-elicited-response task. 3-year-olds were tested in a preferential-looking task in which they heard a change-of-location false-belief story accompanied by a picture book; across children, we manipulated the amount of linguistic ambiguity in the story. The final page of the book showed two images: one that was consistent with the main character’s false belief and one that was consistent with reality. When the story was relatively unambiguous, children looked reliably longer at the false-belief-consistent image, successfully demonstrating their false-belief understanding. When the story was ambiguous, however, this undermined children’s performance: looking times to the belief-consistent image were correlated with verbal ability, and only children with verbal skills in the upper quartile of the sample demonstrated a significant preference for the belief-consistent image. These results support the processing-load account by demonstrating that regardless of whether a task involves an elicited response, children’s performance depends on the processing demands of the task and their processing skills. These findings also have implications for alternative, deflationary accounts of early false-belief understanding. PMID:26562840
Feeding styles and child weight status among recent immigrant mother-child dyads.
Tovar, Alison; Hennessy, Erin; Pirie, Alex; Must, Aviva; Gute, David M; Hyatt, Raymond R; Kamins, Christina Luongo; Hughes, Sheryl O; Boulos, Rebecca; Sliwa, Sarah; Galvão, Heloisa; Economos, Christina D
2012-05-29
Research has shown that parental feeding styles may influence children's food consumption, energy intake, and ultimately, weight status. We examine this relationship, among recent immigrants to the US. Given that immigrant parents and children are at greater risk for becoming overweight/obese with increased time in the US, identification of risk factors for weight gain is critical. Baseline data was collected on 383 mother-child dyads enrolled in Live Well, a community-based, participatory, randomized controlled lifestyle intervention to prevent weight gain in recent immigrant mothers. Socio-demographic information together with heights and weights were collected for both mother and child. Acculturation, behavioral data, and responses to the Caregiver's Feeding Styles Questionnaire (CFSQ) were also obtained from the mother. The children's average age was 6.2 ± 2.7 years, 58% male. Mothers had been in the country for an average of 6.0 ± 3.3 years, and are Brazilian (36%), Haitian (34%) and Latino (30%). Seventy-two percent of the mothers were overweight/obese, while 43% of the children were overweight/obese. Fifteen percent of mothers reported their feeding style as being high demanding/high responsive; 32% as being high demanding/low responsive; 34% as being low demanding/high responsive and 18% as being low demanding/low responsive. In bivariate analyses, feeding styles significantly differed by child BMIz-score, ethnic group, and mother's perceived stress. In multiple linear regression, a low demanding/high responsive feeding style was found to be positively associated (ß = 0.56) with a higher child weight as compared to high demanding/high responsive, controlling for known covariates (p = 0.01). Most mothers report having a low demanding/high responsive feeding style, which is associated with higher child weight status in this diverse immigrant population. This finding adds to the growing literature that suggests this type of feeding style may be a risk factor for childhood obesity. Further research is needed to help understand the larger socio-cultural context and its influence on feeding dynamics among immigrant families and families of lower incomes. How parents establish a certain feeding style in their home country compared to when they move to the US "obesogenic" environment, should also be explored.
MATLAB/Simulink Pulse-Echo Ultrasound System Simulator Based on Experimentally Validated Models.
Kim, Taehoon; Shin, Sangmin; Lee, Hyongmin; Lee, Hyunsook; Kim, Heewon; Shin, Eunhee; Kim, Suhwan
2016-02-01
A flexible clinical ultrasound system must operate with different transducers, which have characteristic impulse responses and widely varying impedances. The impulse response determines the shape of the high-voltage pulse that is transmitted and the specifications of the front-end electronics that receive the echo; the impedance determines the specification of the matching network through which the transducer is connected. System-level optimization of these subsystems requires accurate modeling of pulse-echo (two-way) response, which in turn demands a unified simulation of the ultrasonics and electronics. In this paper, this is realized by combining MATLAB/Simulink models of the high-voltage transmitter, the transmission interface, the acoustic subsystem which includes wave propagation and reflection, the receiving interface, and the front-end receiver. To demonstrate the effectiveness of our simulator, the models are experimentally validated by comparing the simulation results with the measured data from a commercial ultrasound system. This simulator could be used to quickly provide system-level feedback for an optimized tuning of electronic design parameters.
NASA Astrophysics Data System (ADS)
Zheng, Han; Yu, Guirui; Wang, Qiufeng; Zhu, Xianjin; Yan, Junhua; Wang, Huimin; Shi, Peili; Zhao, Fenghua; Li, Yingnian; Zhao, Liang; Zhang, Junhui; Wang, Yanfen
2017-08-01
Estimates of atmospheric evaporative demand have been widely required for a variety of hydrological analyses, with potential evapotranspiration (PET) being an important measure representing evaporative demand of actual vegetated surfaces under given metrological conditions. In this study, we assessed the ability of various PET models in capturing long-term (typically 2003-2011) dynamics of evaporative demand at eight ecosystems across various biomes and climatic regimes in China. Prior to assessing PET dynamics, we first examined the reasonability of fourteen PET models in representing the magnitudes of evaporative demand using eddy-covariance actual evapotranspiration (AET) as an indicator. Results showed that the robustness of the fourteen PET models differed somewhat across the sites, and only three PET models could produce reasonable magnitudes of evaporative demand (i.e., PET ≥ AET on average) for all eight sites, including the: (i) Penman; (ii) Priestly-Taylor and (iii) Linacre models. Then, we assessed the ability of these three PET models in capturing dynamics of evaporative demand by comparing the annual and seasonal trends in PET against the equivalent trends in AET and precipitation (P) for particular sites. Results indicated that nearly all the three PET models could faithfully reproduce the dynamics in evaporative demand for the energy-limited conditions at both annual and seasonal scales, while only the Penman and Linacre models could represent dynamics in evaporative demand for the water-limited conditions. However, the Linacre model was unable to reproduce the seasonal switches between water- and energy-limited states for some sites. Our findings demonstrated that the choice of PET models would be essential for the evaporative demand analyses and other related hydrological analyses at different temporal and spatial scales.
An integrated communications demand model
NASA Astrophysics Data System (ADS)
Doubleday, C. F.
1980-11-01
A computer model of communications demand is being developed to permit dynamic simulations of the long-term evolution of demand for communications media in the U.K. to be made under alternative assumptions about social, economic and technological trends in British Telecom's business environment. The context and objectives of the project and the potential uses of the model are reviewed, and four key concepts in the demand for communications media, around which the model is being structured are discussed: (1) the generation of communications demand; (2) substitution between media; (3) technological convergence; and (4) competition. Two outline perspectives on the model itself are given.
A gap analysis for future supply of and demand for psychiatrists in Austria.
Riedel, Monika; Röehrling, Gerald; Czypionka, Thomas; Kasper, Siegfried
2014-03-01
In the recent past, a rising caseload demonstrates increasing demand for psychiatrists, and ageing of the current mental health workforce will soon result in growing numbers of retirees. Under these conditions there is some concern whether we soon will face widening gaps in supply. This study calculates projections of future use and supply of psychiatrists' services in Austria until 2030. Resulting gaps are calculated for different scenarios. We mostly use administrative data from several public authorities. To estimate the demand for services, we start from utilization data rather than medical need for services, as we do not have sufficient epidemiological information for Austria. We define several scenarios for the future development of use, all calculated separately for hospital and non-hospital services. Future supply of psychiatric services is projected by applying activity levels to projected numbers of physicians, which are calculated using a stock and flow model. Outflows are modeled using assumptions derived from past activity patterns and current legislation on retirement. To model inflows, we need to gauge the impact of recent developments: Entrance barriers into medical education were introduced, Austria experienced a surge of medical students coming from Germany, and medical schools implemented quotas for different nationalities. Scenarios take several factors into account, like the shifting sex composition of the medical workforce, re-migration of foreign students, and the impact of entrance barriers on enrolment and drop-out rates. Depending on scenario assumptions, demand for psychiatrists will increase by 8% to 52%. But in all supply scenarios, supply will decline from 2016 onwards, thus widening gaps between supply and demand. Even in the most optimistic scenario, supply will have fallen below current levels by 2030. Compared to current rates of service use, a gap between supply and demand will start to widen soon. In the most optimistic combination of scenarios, demand will exceed supply from 2028 onwards, and the projected gap will amount to about 5% of projected demand for services in 2030. Gaps could be miscalculated due to lack of more detailed data, such as retirement patterns of psychiatrists. Shifting responsibilities between psychiatrists and other (mental) health workers as well as changes in psychiatrists' "productivity", e.g. due to more effective medications, were not modeled but would affect results. It will be necessary to improve working and training conditions in order to avoid emigration and to attract a sufficient number of young entrants into the profession.
A Handbook For Acquiring Demand-Responsive Transit Software, Tcrp Report 18
DOT National Transportation Integrated Search
1996-01-01
THIS HANDBOOK WILL BE OF INTEREST TO AGENCIES ENGAGED IN MANAGING AND OPERATING DEMAND-RESPONSIVE TRANSIT (DRT) SERVICES. THE HANDBOOK IS INTENDED TO ASSIST DRTPROVIDERS WITH ASSESSMENT OF SOFTWARE NEEDS AND PROCUREMENT OF SOFTWARE TO MEET THOSE NEED...
Evaluating the use of transfers for improving demand responsive systems adopting zoning strategies.
DOT National Transportation Integrated Search
2011-08-01
Due to widely dispersed population density over large and sparsely suburban/rural areas, : conventional fixed route transit services hardly satisfy the travel needs of their residents. As an : alternative, demand responsive transit (DRT) systems have...
DOE Office of Scientific and Technical Information (OSTI.GOV)
Thompson, Lisa; Lekov, Alex; McKane, Aimee
2010-08-20
This case study enhances the understanding of open automated demand response opportunities in municipal wastewater treatment facilities. The report summarizes the findings of a 100 day submetering project at the San Luis Rey Wastewater Treatment Plant, a municipal wastewater treatment facility in Oceanside, California. The report reveals that key energy-intensive equipment such as pumps and centrifuges can be targeted for large load reductions. Demand response tests on the effluent pumps resulted a 300 kW load reduction and tests on centrifuges resulted in a 40 kW load reduction. Although tests on the facility?s blowers resulted in peak period load reductions ofmore » 78 kW sharp, short-lived increases in the turbidity of the wastewater effluent were experienced within 24 hours of the test. The results of these tests, which were conducted on blowers without variable speed drive capability, would not be acceptable and warrant further study. This study finds that wastewater treatment facilities have significant open automated demand response potential. However, limiting factors to implementing demand response are the reaction of effluent turbidity to reduced aeration load, along with the cogeneration capabilities of municipal facilities, including existing power purchase agreements and utility receptiveness to purchasing electricity from cogeneration facilities.« less
ERIC Educational Resources Information Center
Kenny, John
This article explores the perennial tension between the demands of management for quality projects that can be used to attract new markets and students and the traditional scholarly approach to learning. Universities are unique environments compared to industry settings. They are unique in that the responsibility for the quality of the teaching…
USDA-ARS?s Scientific Manuscript database
Southeastern Brazil has experienced drought conditions that have impacted the conservation of watersheds and the management of water quality and quantity for agricultural and urban demands. The Ribeirão das Posses watershed is being monitored as a headwater of the Jaguarí River, which is one of the ...
ERIC Educational Resources Information Center
Rummel, Jan; Wesslein, Ann-Katrin; Meiser, Thorsten
2017-01-01
Event-based prospective memory (PM) is the ability to remember to perform an intention in response to an environmental cue. Recent microstructure models postulate four distinguishable stages of successful event-based PM fulfillment. That is, (a) the event must be noticed, (b) the intention must be retrieved, (c) the context must be verified, and…
Leadership and the emergency department.
LaSalle, Gar
2004-02-01
Emergency medicine, as the nation's health care system's safety net, is facing ever increasing demands on its resources and infrastructure. Classic and modern theories of leadership, which include broader based models that in corporate team responsibilities, should be studied by anyone wearing the mantle of leadership in emergency medicine, and the Realpolitik of the modern hospital must be accommodated if leadership efforts are to succeed.
Improving a Family's Overall Quality of Life through Parent Training in Pivotal Response Treatment
ERIC Educational Resources Information Center
Buckley, Trevor W.; Ente, Angela P.; Ruef, Michael B.
2014-01-01
As the diagnoses of autism in young children continually increase, the need for families to have access to research-based treatment models that are effective and efficient has become clear. Current research demonstrates the demand for parent-delivered behavioral interventions. The aim of this single-case study, conducted as part of an integrated…
Jacoby, Oscar; Hall, Sarah E; Mattingley, Jason B
2012-07-16
Mechanisms of attention are required to prioritise goal-relevant sensory events under conditions of stimulus competition. According to the perceptual load model of attention, the extent to which task-irrelevant inputs are processed is determined by the relative demands of discriminating the target: the more perceptually demanding the target task, the less unattended stimuli will be processed. Although much evidence supports the perceptual load model for competing stimuli within a single sensory modality, the effects of perceptual load in one modality on distractor processing in another is less clear. Here we used steady-state evoked potentials (SSEPs) to measure neural responses to irrelevant visual checkerboard stimuli while participants performed either a visual or auditory task that varied in perceptual load. Consistent with perceptual load theory, increasing visual task load suppressed SSEPs to the ignored visual checkerboards. In contrast, increasing auditory task load enhanced SSEPs to the ignored visual checkerboards. This enhanced neural response to irrelevant visual stimuli under auditory load suggests that exhausting capacity within one modality selectively compromises inhibitory processes required for filtering stimuli in another. Copyright © 2012 Elsevier Inc. All rights reserved.
Two-and-a-half-year-olds succeed at a traditional false-belief task with reduced processing demands
Scott, Rose M.; Baillargeon, Renée
2016-01-01
When tested with traditional false-belief tasks, which require answering a standard question about the likely behavior of an agent with a false belief, children perform below chance until age 4 y or later. When tested without such questions, however, children give evidence of false-belief understanding much earlier. Are traditional tasks difficult because they tap a more advanced form of false-belief understanding (fundamental-change view) or because they impose greater processing demands (processing-demands view)? Evidence that young children succeed at traditional false-belief tasks when processing demands are reduced would support the latter view. In prior research, reductions in inhibitory-control demands led to improvements in young children’s performance, but often only to chance (instead of below-chance) levels. Here we examined whether further reductions in processing demands might lead to success. We speculated that: (i) young children could respond randomly in a traditional low-inhibition task because their limited information-processing resources are overwhelmed by the total concurrent processing demands in the task; and (ii) these demands include those from the response-generation process activated by the standard question. This analysis suggested that 2.5-y-old toddlers might succeed at a traditional low-inhibition task if response-generation demands were also reduced via practice trials. As predicted, toddlers performed above chance following two response-generation practice trials; toddlers failed when these trials either were rendered less effective or were used in a high-inhibition task. These results support the processing-demands view: Even toddlers succeed at a traditional false-belief task when overall processing demands are reduced. PMID:27821728
Pornkamol, Unrean; Franzen, Carl J
2015-08-01
Achieving efficient and economical lignocellulose-based bioprocess requires a robust organism tolerant to furfural, a major inhibitory compound present in lignocellulosic hydrolysate. The aim of this study was to develop a model that could generate quantitative descriptions of cell metabolism for elucidating the cell's adaptive response to furfural. Such a modelling tool could provide strategies for the design of more robust cells. A dynamic flux balance (dFBA) model of Saccharomyces cerevisiae was created by coupling a kinetic fermentation model with a previously published genome-scale stoichiometric model. The dFBA model was used for studying intracellular and extracellular flux responses to furfural perturbations under steady state and dynamic conditions. The predicted effects of furfural on dynamic flux profiles agreed well with previously published experimental results. The model showed that the yeast cell adjusts its metabolism in response to furfural challenge by increasing fluxes through the pentose phosphate pathway, TCA cycle, and proline and serine biosynthesis in order to meet the high demand of NAD(P)H cofactors. The model described here can be used to aid in systematic optimization of the yeast, as well as of the fermentation process, for efficient lignocellulosic ethanol production. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
NASA Astrophysics Data System (ADS)
Jia, Heping; Jin, Wende; Ding, Yi; Song, Yonghua; Yu, Dezhao
2017-01-01
With the expanding proportion of renewable energy generation and development of smart grid technologies, flexible demand resources (FDRs) have been utilized as an approach to accommodating renewable energies. However, multiple uncertainties of FDRs may influence reliable and secure operation of smart grid. Multi-state reliability models for a single FDR and aggregating FDRs have been proposed in this paper with regard to responsive abilities for FDRs and random failures for both FDR devices and information system. The proposed reliability evaluation technique is based on Lz transform method which can formulate time-varying reliability indices. A modified IEEE-RTS has been utilized as an illustration of the proposed technique.
Hegemony in the marketplace of biomedical innovation: consumer demand and stem cell science.
Salter, Brian; Zhou, Yinhua; Datta, Saheli
2015-04-01
The global political economy of stem cell therapies is characterised by an established biomedical hegemony of expertise, governance and values in collision with an increasingly informed health consumer demand able to define and pursue its own interest. How does the hegemony then deal with the challenge from the consumer market and what does this tell us about its modus operandi? In developing a theoretical framework to answer these questions, the paper begins with an analysis of the nature of the hegemony of biomedical innovation in general, its close relationship with the research funding market, the current political modes of consumer incorporation, and the ideological role performed by bioethics as legitimating agency. Secondly, taking the case of stem cell innovation, it explores the hegemonic challenge posed by consumer demand working through the global practice based market of medical innovation, the response of the national and international institutions of science and their reassertion of the values of the orthodox model, and the supporting contribution of bioethics. Finally, the paper addresses the tensions within the hegemonic model of stem cell innovation between the key roles and values of scientist and clinician, the exacerbation of these tensions by the increasingly visible demands of health consumers, and the emergence of political compromise. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
Explaining regional variation in home care use by demand and supply variables.
van Noort, Olivier; Schotanus, Fredo; van de Klundert, Joris; Telgen, Jan
2018-02-01
In the Netherlands, home care services like district nursing and personal assistance are provided by private service provider organizations and covered by private health insurance companies which bear legal responsibility for purchasing these services. To improve value for money, their procurement increasingly replaces fee-for-service payments with population based budgets. Setting appropriate population budgets requires adaptation to the legitimate needs of the population, whereas historical costs are likely to be influenced by supply factors as well, not all of which are necessarily legitimate. Our purpose is to explain home care costs in terms of demand and supply factors. This allows for adjusting historical cost patterns when setting population based budgets. Using expenses claims of 60 Dutch municipalities, we analyze eight demand variables and five supply variables with a multiple regression model to explain variance in the number of clients per inhabitant, costs per client and costs per inhabitant. Our models explain 69% of variation in the number of clients per inhabitant, 28% of costs per client and 56% of costs per inhabitant using demand factors. Moreover, we find that supply factors explain an additional 17-23% of variation. Predictors of higher utilization are home care organizations that are integrated with intramural nursing homes, higher competition levels among home care organizations and the availability of complementary services. Copyright © 2017. Published by Elsevier B.V.
Eason, Christianne M.; Mazerolle, Stephanie M.; Goodman, Ashley
2014-01-01
Context: One of the greatest catalysts for turnover among female athletic trainers (ATs) is motherhood, especially if employed at the National Collegiate Athletic Association Division I level. The medical education literature regularly identifies the importance of role models in professional character formation. However, few researchers have examined the responsibility of mentorship and professional role models as it relates to female ATs' perceptions of motherhood and retention. Objective: To evaluate perceptions of motherhood and retention in relation to mentorship and role models among female ATs currently employed in the collegiate setting. Design: Qualitative study. Setting: Female athletic trainers working in National Collegiate Athletic Association Division I. Patients or Other Participants: Twenty-seven female ATs employed in the National Collegiate Athletic Association Division I setting volunteered. Average age of the participants was 35 ± 9 years. All were full-time ATs with an average of 11 ± 8 years of clinical experience. Data Collection and Analysis: Participants responded to questions by journaling their thoughts and experiences. Multiple-analyst triangulation and peer review were included as steps to establish data credibility. Results: Male and female role models and mentors can positively or negatively influence the career and work–life balance perceptions of female ATs working in the Division I setting. Female ATs have a desire to see more women in the profession handle the demands of motherhood and the demands of their clinical setting. Women who have had female mentors are more positive about the prospect of balancing the rigors of motherhood and job demands. Conclusions: Role models and mentors are valuable resources for promoting perseverance in the profession in the highly demanding clinical settings. As more female ATs remain in the profession who are able to maintain work–life balance and are available to serve as role models, the attitudes of other women may start to change. PMID:24972042
Vanagas, Giedrius; Bihari-Axelsson, Susanna
2005-06-10
There are number of studies showing that general practice is one of the most stressful workplace among health care workers. Since Baltic States regained independence in 1990, the reform of the health care system took place in which new role and more responsibilities were allocated to general practitioners' in Lithuania. This study aimed to explore the psychosocial stress level among Lithuanian general practitioner's and examine the relationship between psychosocial stress and work characteristics. The cross-sectional study of 300 Lithuanian General practitioners. Psychosocial stress was investigated with a questionnaire based on the Reeder scale. Job demands were investigated with the R. Karasek scale. The analysis included descriptive statistics; interrelationship analysis between characteristics and multivariate logistic regression to estimate odds ratios for each of the independent variables in the model. Response rate 66% (N = 197). Our study highlighted highest prevalence of psychosocial stress among widowed, single and female general practitioners. Lowest prevalence of psychosocial stress was among males and older age general practitioners. Psychosocial stress occurs when job demands are high and job decision latitude is low (chi2 = 18,9; p < 0,01). The multivariate analysis shows that high job demands (OR 4,128; CI 2,102-8,104; p < 0,001), patient load more than 18 patients per day (OR 5,863; CI 1,549-22,188; p < 0,01) and young age of GP's (OR 6,874; CI 1,292-36,582; p < 0,05) can be assigned as significant predictors for psychosocial stress. One half of respondents suffering from work related psychosocial stress. High psychological workload demands combined with low decision latitude has the greatest impact to stress caseness among GP's. High job demands, high patient load and young age of GP's can be assigned as significant predictors of psychosocial stress among GP's.
Harding, Ian H; Yücel, Murat; Harrison, Ben J; Pantelis, Christos; Breakspear, Michael
2015-02-01
Cognitive control and working memory rely upon a common fronto-parietal network that includes the inferior frontal junction (IFJ), dorsolateral prefrontal cortex (dlPFC), pre-supplementary motor area/dorsal anterior cingulate cortex (pSMA/dACC), and intraparietal sulcus (IPS). This network is able to flexibly adapt its function in response to changing behavioral goals, mediating a wide range of cognitive demands. Here we apply dynamic causal modeling to functional magnetic resonance imaging data to characterize task-related alterations in the strength of network interactions across distinct cognitive processes. Evidence in favor of task-related connectivity dynamics was accrued across a very large space of possible network structures. Cognitive control and working memory demands were manipulated using a factorial combination of the multi-source interference task and a verbal 2-back working memory task, respectively. Both were found to alter the sensitivity of the IFJ to perceptual information, and to increase IFJ-to-pSMA/dACC connectivity. In contrast, increased connectivity from the pSMA/dACC to the IPS, as well as from the dlPFC to the IFJ, was uniquely driven by cognitive control demands; a task-induced negative influence of the dlPFC on the pSMA/dACC was specific to working memory demands. These results reflect a system of both shared and unique context-dependent dynamics within the fronto-parietal network. Mechanisms supporting cognitive engagement, response selection, and action evaluation may be shared across cognitive domains, while dynamic updating of task and context representations within this network are potentially specific to changing demands on cognitive control. Copyright © 2014 Elsevier Inc. All rights reserved.
NASA Technical Reports Server (NTRS)
Rau, G. H.; Takahashi, T.; Des Marais, D. J.; Repeta, D. J.; Martin, J. H.
1992-01-01
Consistent with the hypothesis that plankton delta C-14 and (CO2(aq)) are inversely related, increases in both sinking and suspended particulate organic matter (POM) delta C-13 detected by the Joint Global Ocean Flux Study (JGOFS) were highly negatively correlated with mixed-layer (CO2(aq)). A model of plant delta C-13 by Farquhar et al. (1982) is adapted to show that under a constant phytoplankton demand for CO2 an inverse nonlinear suspended POM delta C-13 response to ambient (CO2(aq)) is expected. Differences between predicted and observed suspended POM delta C-13 vs. (CO2(aq)) trends and among observed relationships can be reconciled if biological CO2 demand is allowed to vary.
Feasibility of solid oxide fuel cell dynamic hydrogen coproduction to meet building demand
NASA Astrophysics Data System (ADS)
Shaffer, Brendan; Brouwer, Jacob
2014-02-01
A dynamic internal reforming-solid oxide fuel cell system model is developed and used to simulate the coproduction of electricity and hydrogen while meeting the measured dynamic load of a typical southern California commercial building. The simulated direct internal reforming-solid oxide fuel cell (DIR-SOFC) system is controlled to become an electrical load following device that well follows the measured building load data (3-s resolution). The feasibility of the DIR-SOFC system to meet the dynamic building demand while co-producing hydrogen is demonstrated. The resulting thermal responses of the system to the electrical load dynamics as well as those dynamics associated with the filling of a hydrogen collection tank are investigated. The DIR-SOFC system model also allows for resolution of the fuel cell species and temperature distributions during these dynamics since thermal gradients are a concern for DIR-SOFC.
The Effects of Demand-Responsive Parking on Transit Usage and Congestion: Evidence From Sfpark
DOT National Transportation Integrated Search
2017-09-01
Parking is a serious issue in many urban areas, especially those experiencing rapid population growth. To address this problem, some cities have implemented demand-responsive pricing programs, where parking prices vary depending on the occupancy rate...
A Simultaneous Equation Demand Model for Block Rates
NASA Astrophysics Data System (ADS)
Agthe, Donald E.; Billings, R. Bruce; Dobra, John L.; Raffiee, Kambiz
1986-01-01
This paper examines the problem of simultaneous-equations bias in estimation of the water demand function under an increasing block rate structure. The Hausman specification test is used to detect the presence of simultaneous-equations bias arising from correlation of the price measures with the regression error term in the results of a previously published study of water demand in Tucson, Arizona. An alternative simultaneous equation model is proposed for estimating the elasticity of demand in the presence of block rate pricing structures and availability of service charges. This model is used to reestimate the price and rate premium elasticities of demand in Tucson, Arizona for both the usual long-run static model and for a simple short-run demand model. The results from these simultaneous equation models are consistent with a priori expectations and are unbiased.
Development of S-ARIMA Model for Forecasting Demand in a Beverage Supply Chain
NASA Astrophysics Data System (ADS)
Mircetic, Dejan; Nikolicic, Svetlana; Maslaric, Marinko; Ralevic, Nebojsa; Debelic, Borna
2016-11-01
Demand forecasting is one of the key activities in planning the freight flows in supply chains, and accordingly it is essential for planning and scheduling of logistic activities within observed supply chain. Accurate demand forecasting models directly influence the decrease of logistics costs, since they provide an assessment of customer demand. Customer demand is a key component for planning all logistic processes in supply chain, and therefore determining levels of customer demand is of great interest for supply chain managers. In this paper we deal with exactly this kind of problem, and we develop the seasonal Autoregressive IntegratedMoving Average (SARIMA) model for forecasting demand patterns of a major product of an observed beverage company. The model is easy to understand, flexible to use and appropriate for assisting the expert in decision making process about consumer demand in particular periods.
Walker, Berkley J; Strand, Deserah D; Kramer, David M; Cousins, Asaph B
2014-05-01
Photosynthesis captures light energy to produce ATP and NADPH. These molecules are consumed in the conversion of CO2 to sugar, photorespiration, and NO3(-) assimilation. The production and consumption of ATP and NADPH must be balanced to prevent photoinhibition or photodamage. This balancing may occur via cyclic electron flow around photosystem I (CEF), which increases ATP/NADPH production during photosynthetic electron transport; however, it is not clear under what conditions CEF changes with ATP/NADPH demand. Measurements of chlorophyll fluorescence and dark interval relaxation kinetics were used to determine the contribution of CEF in balancing ATP/NADPH in hydroponically grown Arabidopsis (Arabidopsis thaliana) supplied different forms of nitrogen (nitrate versus ammonium) under changes in atmospheric CO2 and oxygen. Measurements of CEF were made under low and high light and compared with ATP/NADPH demand estimated from CO2 gas exchange. Under low light, contributions of CEF did not shift despite an up to 17% change in modeled ATP/NADPH demand. Under high light, CEF increased under photorespiratory conditions (high oxygen and low CO2), consistent with a primary role in energy balancing. However, nitrogen form had little impact on rates of CEF under high or low light. We conclude that, according to modeled ATP/NADPH demand, CEF responded to energy demand under high light but not low light. These findings suggest that other mechanisms, such as the malate valve and the Mehler reaction, were able to maintain energy balance when electron flow was low but that CEF was required under higher flow.
Blockchain Based Decentralized Management of Demand Response Programs in Smart Energy Grids
Pop, Claudia; Cioara, Tudor; Antal, Marcel; Anghel, Ionut; Salomie, Ioan; Bertoncini, Massimo
2018-01-01
In this paper, we investigate the use of decentralized blockchain mechanisms for delivering transparent, secure, reliable, and timely energy flexibility, under the form of adaptation of energy demand profiles of Distributed Energy Prosumers, to all the stakeholders involved in the flexibility markets (Distribution System Operators primarily, retailers, aggregators, etc.). In our approach, a blockchain based distributed ledger stores in a tamper proof manner the energy prosumption information collected from Internet of Things smart metering devices, while self-enforcing smart contracts programmatically define the expected energy flexibility at the level of each prosumer, the associated rewards or penalties, and the rules for balancing the energy demand with the energy production at grid level. Consensus based validation will be used for demand response programs validation and to activate the appropriate financial settlement for the flexibility providers. The approach was validated using a prototype implemented in an Ethereum platform using energy consumption and production traces of several buildings from literature data sets. The results show that our blockchain based distributed demand side management can be used for matching energy demand and production at smart grid level, the demand response signal being followed with high accuracy, while the amount of energy flexibility needed for convergence is reduced. PMID:29315250
Tan, Lavinia; Hackenberg, Timothy D
2015-11-01
Pigeons' demand and preference for specific and generalized tokens was examined in a token economy. Pigeons could produce and exchange different colored tokens for food, for water, or for food or water. Token production was measured across three phases, which examined: (1) across-session price increases (typical demand curve method); (2) within-session price increases (progressive-ratio, PR, schedule); and (3) concurrent pairwise choices between the token types. Exponential demand curves were fitted to the response data and accounted for over 90% total variance. Demand curve parameter values, Pmax , Omax and α showed that demand was ordered in the following way: food tokens, generalized tokens, water tokens, both in Phase 1 and in Phase 3. This suggests that the preferences were predictable on the basis of elasticity and response output from the demand analysis. Pmax and Omax values failed to consistently predict breakpoints and peak response rates in the PR schedules in Phase 2, however, suggesting limits on a unitary conception of reinforcer efficacy. The patterns of generalized token production and exchange in Phase 3 suggest that the generalized tokens served as substitutes for the specific food and water tokens. Taken together, the present findings demonstrate the utility of behavioral economic concepts in the analysis of generalized reinforcement. © Society for the Experimental Analysis of Behavior.
NASA Astrophysics Data System (ADS)
Wang, S. Y.; Ho, C. C.; Chang, L. C.
2017-12-01
The public use water in Hsinchu are mainly supplied from Baoshan Reservoir, Second Baoshan Reservoir, Yongheshan Reservoir and Longen Weir. However, the increasing water demand, caused by development of the Hsinchu Science and Industrial Park, results in supply stable water getting more difficult. For stabilize water supply in Hsinchu, the study applies long-term and short-term plans to fulfill the water shortage. Developing an efficient methodology to define a cost-effective action portfolio is an important task. Hence, the study develops a novel decision model, the Stochastic Programming with Recourse Decision Model (SPRDM), to estimate a cost-effective action portfolio. The first-stage of SPRDM determine the long-term action portfolio and the portfolio accompany recourse information (the probability for water shortage event). The second-stage of SPRDM optimize the cost-effective action portfolio in response to the recourse information. In order to consider the uncertainty of reservoir sediment and demand growth, the study set 9 scenarios comprise optimistic, most likely, and pessimistic reservoir sediment and demand growth. The results show the optimal action portfolio consist of FengTain Lake and Panlon Weir, Hsinchu Desalination Plant, Domestic and Industrial Water long-term plans, and Emergency Backup Well, Irrigation Water Transference, Preliminary Water Rationing, Advanced Water Rationing and Water Transport from Other Districts short-term plans. The minimum expected cost of optimal action portfolio is NT$1.1002 billion. The results can be used as a reference for decision making because the results have considered the uncertainty of varied hydrology, reservoir sediment, and water demand growth.
The Influence of Load and Speed on Individuals' Movement Behavior.
Frost, David M; Beach, Tyson A C; Callaghan, Jack P; McGill, Stuart M
2015-09-01
Because individuals' movement patterns have been linked to their risk of future injury, movement evaluations have become a topic of interest. However, if individuals adapt their movement behavior in response to the demands of a task, the utility of evaluations comprising only low-demand activities could have limited application with regard to the prediction of future injury. This investigation examined the impact of load and speed on individuals' movement behavior. Fifty-two firefighters performed 5 low-demand (i.e., light load, low movement speed) whole-body tasks (i.e., lift, squat, lunge, push, and pull). Each task was then modified by increasing the speed, external load, or speed and load. Select measures of motion were used to characterize the performance of each task, and comparisons were made between conditions. The participants adapted their movement behavior in response to the external demands of a task (64 and 70% of all the variables were influenced [p ≤ 0.05] by changing the load and speed, respectively), but in a manner unique to the task and type of demand. The participants exhibited greater spine and frontal plane knee motion in response to an increase in speed when compared with increasing loads. However, there were a large number of movement strategies exhibited by individual firefighters that differed from the group's response. The data obtained here imply that individuals may not be physically prepared to perform safely or effectively when a task's demands are elevated simply because they exhibit the ability to perform a low-demand activity with competence. Therefore, movement screens comprising only low-demand activities may not adequately reflect an individual's capacity, or their risk of injury, and could adversely affect any recommendations that are made for training or job performance.
DOT National Transportation Integrated Search
2013-08-01
The Texas Department of Transportation : (TxDOT) created a standardized trip-based : modeling approach for travel demand modeling : called the Texas Package Suite of Travel Demand : Models (referred to as the Texas Package) to : oversee the travel de...
Wang, Lei; Li, Baoqiang; Xu, Feng; Xu, Zheheng; Wei, Daqing; Feng, Yujie; Wang, Yaming; Jia, Dechang; Zhou, Yu
2017-10-15
Innovative drug delivery technologies based on smart hydrogels for localized on-demand drug delivery had aroused great interest. To acquire smart UV-crosslinkable chitosan hydrogel for NIR-triggered localized on-demanded drug release, a novel UV-crosslinkable and thermo-responsive chitosan was first designed and synthesized by grafting with poly N-isopropylacrylamide, acetylation of methacryloyl groups and embedding with photothermal carbon. The UV-crosslinkable unit (methacryloyl groups) endowed chitosan with gelation via UV irradiation. The thermo-responsive unit (poly N-isopropylacrylamide) endowed chitosan hydrogel with temperature-triggered volume shrinkage and reversible swelling/de-swelling behavior. The chitosan hybrid hydrogel embedded with photothermal carbon exhibited distinct NIR-triggered volume shrinkage (∼42% shrinkage) in response to temperature elevation as induced by NIR laser irradiation. As a demonstration, doxorubicin release rate was accelerated and approximately 40 times higher than that from non-irradiated hydrogels. The UV-crosslinkable and thermal-responsive hybrid hydrogel served as in situ forming hydrogel-based drug depot is developed for NIR-triggered localized on-demand release. Copyright © 2017 Elsevier Ltd. All rights reserved.
Design of capacity incentive and energy compensation for demand response programs
NASA Astrophysics Data System (ADS)
Liu, Zhoubin; Cui, Wenqi; Shen, Ran; Hu, Yishuang; Wu, Hui; Ye, Chengjin
2018-02-01
Variability and Uncertainties caused by renewable energy sources have called for large amount of balancing services. Demand side resources (DSRs) can be a good alternative of traditional generating units to provide balancing service. In the areas where the electricity market has not been fully established, e.g., China, DSRs can help balance the power system with incentive-based demand response programs. However, there is a lack of information about the interruption cost of consumers in these areas, making it hard to determine the rational amount of capacity incentive and energy compensation for the participants of demand response programs. This paper proposes an algorithm to calculate the amount of capacity incentive and energy compensation for demand response programs when there lacks the information about interruption cost. Available statistical information of interruption cost in referenced areas is selected as the referenced data. Interruption cost of the targeted area is converted from the referenced area by product per electricity consumption. On this basis, capacity incentive and energy compensation are obtained to minimize the payment to consumers. Moreover, the loss of consumers is guaranteed to be covered by the revenue they earned from load serving entities.
Validity of a demand curve measure of nicotine reinforcement with adolescent smokers.
Murphy, James G; MacKillop, James; Tidey, Jennifer W; Brazil, Linda A; Colby, Suzanne M
2011-01-15
High or inelastic demand for drugs is central to many laboratory and theoretical models of drug abuse, but it has not been widely measured with human substance abusers. The authors used a simulated cigarette purchase task to generate a demand curve measure of nicotine reinforcement in a sample of 138 adolescent smokers. Participants reported the number of cigarettes they would purchase and smoke in a hypothetical day across a range of prices, and their responses were well-described by a regression equation that has been used to construct demand curves in drug self-administration studies. Several demand curve measures were generated, including breakpoint, intensity, elasticity, P(max), and O(max). Although simulated cigarette smoking was price sensitive, smoking levels were high (8+ cigarettes/day) at prices up to 50¢ per cigarette, and the majority of the sample reported that they would purchase at least 1 cigarette at prices as high as $2.50 per cigarette. Higher scores on the demand indices O(max) (maximum cigarette purchase expenditure), intensity (reported smoking level when cigarettes were free), and breakpoint (the first price to completely suppress consumption), and lower elasticity (sensitivity of cigarette consumption to increases in cost), were associated with greater levels of naturalistic smoking and nicotine dependence. Greater demand intensity was associated with lower motivation to change smoking. These results provide initial support for the validity of a self-report cigarette purchase task as a measure of economic demand for nicotine with adolescent smokers. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.
Managing job stress in nursing: what kind of resources do we need?
van den Tooren, Marieke; de Jonge, Jan
2008-07-01
This paper is a report of a study to investigate the functionality of different kinds of job resources for managing job stress in nursing. There is increasing recognition that healthcare staff, and especially nurses, are at high risk for burnout and physical complaints. Several researchers have proposed that job resources moderate the relationship between job demands and job-related outcomes, particularly when there is a match between the type of demands, resources, and outcomes. Based on the Demand-Induced Strain Compensation Model, cross-sectional survey data were collected between November 2006 and February 2007 by a paper-and-pencil questionnaire. The final sample consisted of 69 nurses from a Dutch nursing home (response rate 59.4%). Data were analyzed by hierarchical regression analyses. High physical demands had adverse effects on both physical complaints and emotional exhaustion (i.e. burnout), unless employees had high physical resources. A similar pattern was found for high physical demands and emotional resources in predicting emotional exhaustion. The likelihood of finding theoretically-valid moderating effects was related to the degree of match between demands, resources, and outcomes. Job resources do not randomly moderate the relationship between job demands and job-related outcomes. Both physical and emotional resources seem to be important stress buffers for human service employees such as nurses, and their moderating effects underline the importance of specific job resources in healthcare work. Job redesign in nursing homes should therefore primarily focus on matching job resources to job demands in order to diminish poor health and ill-being.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Piette, Mary Ann; Sezgen, Osman; Watson, David S.
This report describes the results of a research project to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through costmore » of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).« less
NASA Astrophysics Data System (ADS)
Cheng, Y.; Niemeyer, R. J.; Mao, Y.; Yearsley, J. R.; Nijssen, B.
2016-12-01
In the coming decades, climate change and population growth are expected to affect water and energy supply as well as demand in the southeastern United States. Changes in temperature and precipitation impact river flow and stream temperature with implications for hydropower generation, industrial and municipal water supply, cooling for thermo-electric power plants, agricultural irrigation, ecosystem functions and flood control. At the same time, water and energy demand are expected to change in response to temperature increase, population growth and changing crop water requirements. As part of a multi-institution study of the food-energy-water nexus in the southeastern U.S., we are developing coupled hydrological and stream temperature models that will be linked to water resources, power systems and crop models at a later stage. Here we evaluate the ability of our system to simulate water supply and stream temperature in the Tennessee River Basin using the Variable Infiltration Capacity (VIC) macroscale hydrology model coupled to the River Basin Model (RBM), a 1-D semi-Lagrangian river temperature model, which has recently been expanded with a two-layer reservoir temperature model. Simulations with VIC-RBM were performed for the Tennessee River Basin at 1/8-degree spatial resolution and a temporal resolution of 1 day or less. Reservoir releases were prescribed based on historic operating rules. In future iterations, these releases will be modeled directly by a water resources model that incorporates flood control, and power and agricultural water demands. We compare simulated flows, as well as stream and reservoir temperatures with observed flows and temperatures throughout the basin. In preparation for later stages of the project, we also perform a set of climate change sensitivity experiments to evaluate how changes in climate may impact river and reservoir temperature.
Decision on risk-averse dual-channel supply chain under demand disruption
NASA Astrophysics Data System (ADS)
Yan, Bo; Jin, Zijie; Liu, Yanping; Yang, Jianbo
2018-02-01
We studied dual-channel supply chains using centralized and decentralized decision-making models. We also conducted a comparative analysis of the decisions before and after demand disruption. The study shows that the amount of change in decision-making is a linear function of the amount of demand disruption, and it is independent of the risk-averse coefficient. The optimal sales volume decision of the disturbing supply chain is related to market share and demand disruption in the decentralized decision-making model. The optimal decision is only influenced by demand disruption in the centralized decision-making model. The stability of the sales volume of the two models is related to market share and demand disruption. The optimal system production of the two models shows robustness, but their stable internals are different.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Chin, Shih-Miao; Hwang, Ho-Ling
2007-01-01
This paper describes a development of national freight demand models for 27 industry sectors covered by the 2002 Commodity Flow Survey. It postulates that the national freight demands are consistent with U.S. business patterns. Furthermore, the study hypothesizes that the flow of goods, which make up the national production processes of industries, is coherent with the information described in the 2002 Annual Input-Output Accounts developed by the Bureau of Economic Analysis. The model estimation framework hinges largely on the assumption that a relatively simple relationship exists between freight production/consumption and business patterns for each industry defined by the three-digit Northmore » American Industry Classification System industry codes (NAICS). The national freight demand model for each selected industry sector consists of two models; a freight generation model and a freight attraction model. Thus, a total of 54 simple regression models were estimated under this study. Preliminary results indicated promising freight generation and freight attraction models. Among all models, only four of them had a R2 value lower than 0.70. With additional modeling efforts, these freight demand models could be enhanced to allow transportation analysts to assess regional economic impacts associated with temporary lost of transportation services on U.S. transportation network infrastructures. Using such freight demand models and available U.S. business forecasts, future national freight demands could be forecasted within certain degrees of accuracy. These freight demand models could also enable transportation analysts to further disaggregate the CFS state-level origin-destination tables to county or zip code level.« less
Crawford, Robert S; Albadawi, Hassan; Robaldo, Alessandro; Peck, Michael A; Abularrage, Christopher J; Yoo, Hyung-Jin; Lamuraglia, Glenn M; Watkins, Michael T
2013-08-01
We designed studies to determine whether the ApoE-/- phenotype modulates the local skeletal muscle and systemic inflammatory (plasma) responses to lower extremity demand ischemia. The ApoE-/- phenotype is an experimental model for atherosclerosis in humans. Aged female ApoE-/- and C57BL6 mice underwent femoral artery ligation, then were divided into sedentary and demand ischemia (exercise) groups on day 14. We assessed baseline and postexercise limb perfusion and hind limb function. On day 14, animals in the demand ischemia group underwent daily treadmill exercise through day 28. Sedentary mice were not exercised. On day 28, we harvested plasma and skeletal muscle from ischemic limbs from sedentary and exercised mice. We assayed muscle for angiogenic and proinflammatory proteins, markers of skeletal muscle regeneration, and evidence of skeletal muscle fiber maturation. Hind limb ischemia was similar in ApoE-/- and C57 mice before the onset of exercise. Under sedentary conditions, plasma vascular endothelial cell growth factor and interleukin-6, but not keratinocyte chemoattractant factor (KC) or macrophage inflammatory protein-2 (MIP-2), were higher in ApoE (P < 0.0001). After exercise, plasma levels of vascular endothelial cell growth factor, KC, and MIP-2, but not IL-6, were lower in ApoE (P < 0.004). The cytokines KC and MIP-2 in muscle were greater in exercised ApoE-/- mice compared with C57BL6 mice (P = 0.01). Increased poly-ADP-ribose activity and mature muscle regeneration were associated with demand ischemia in the C57BL6 mice, compared with the ApoE-/- mice (P = 0.01). Demand limb ischemia in the ApoE-/- phenotype exacerbated the expression of select systemic cytokines in plasma and blunted indices of muscle regeneration. Copyright © 2013 Elsevier Inc. All rights reserved.
Housing and mobility demands of individual households and their life cycle assessment.
Saner, Dominik; Heeren, Niko; Jäggi, Boris; Waraich, Rashid A; Hellweg, Stefanie
2013-06-04
Household consumption, apart from governmental consumption, is the main driver of worldwide economy. Attached to each household purchase are economic activities along the preceding supply chain, with the associated resource use and emissions. A method to capture and assess all these resource uses and emissions is life cycle assessment. We developed a model for the life cycle assessment of housing and land-based mobility (excluding air travel) consumption of individual households a small village in Switzerland. Statistical census and dwelling register data are the foundations of the model. In a case study performed on a midsized community, we found a median value of greenhouse gas emissions of 3.12 t CO2 equiv and a mean value of 4.30 t CO2 equiv per capita and year for housing and mobility. Twenty-one percent of the households in the investigated region were responsible for 50% of the total greenhouse gas emissions, meaning that if their emissions could be halved the total emissions of the community would be reduced by 25%. Furthermore, a cluster analysis revealed that driving factors for large environmental footprints are demands of large living area heated by fossil energy carriers, as well as large demands of motorized private transportation.
An integrative assessment of the commercial air transportation system via adaptive agents
NASA Astrophysics Data System (ADS)
Lim, Choon Giap
The overarching research objective is to address the tightly-coupled interactions between the demand-side and supply-side components of the United States Commercial Air Transportation System (CATS) in a time-variant environment. A system-of-system perspective is adopted, where the scope is extended beyond the National Airspace System (NAS) level to the National Transportation System (NTS) level to capture the intermodal and multimodal relationships between the NTS stakeholders. The Agent-Based Modeling and Simulation technique is employed where the NTS/NAS is treated as an integrated Multi-Agent System comprising of consumer and service provider agents, representing the demand-side and supply-side components respectively. Successful calibration and validation of both model components against the observable real world data resulted in a CATS simulation tool where the aviation demand is estimated from socioeconomic and demographic properties of the population instead of merely based on enplanement growth multipliers. This valuable achievement enabled a 20-year outlook simulation study to investigate the implications of a global fuel price hike on the airline industry and the U.S. CATS at large. Simulation outcomes revealed insights into the airline competitive behaviors and the subsequent responses from transportation consumers.
Evaluating the Impacts of Real-Time Pricing on the Cost and Value of Wind Generation
Siohansi, Ramteen
2010-05-01
One of the costs associated with integrating wind generation into a power system is the cost of redispatching the system in real-time due to day-ahead wind resource forecast errors. One possible way of reducing these redispatch costs is to introduce demand response in the form of real-time pricing (RTP), which could allow electricity demand to respond to actual real-time wind resource availability using price signals. A day-ahead unit commitment model with day-ahead wind forecasts and a real-time dispatch model with actual wind resource availability is used to estimate system operations in a high wind penetration scenario. System operations are comparedmore » to a perfect foresight benchmark, in which actual wind resource availability is known day-ahead. The results show that wind integration costs with fixed demands can be high, both due to real-time redispatch costs and lost load. It is demonstrated that introducing RTP can reduce redispatch costs and eliminate loss of load events. Finally, social surplus with wind generation and RTP is compared to a system with neither and the results demonstrate that introducing wind and RTP into a market can result in superadditive surplus gains.« less
Pauliuk, Stefan; Milford, Rachel L; Müller, Daniel B; Allwood, Julian M
2013-04-02
Steel production accounts for 25% of industrial carbon emissions. Long-term forecasts of steel demand and scrap supply are needed to develop strategies for how the steel industry could respond to industrialization and urbanization in the developing world while simultaneously reducing its environmental impact, and in particular, its carbon footprint. We developed a dynamic stock model to estimate future final demand for steel and the available scrap for 10 world regions. Based on evidence from developed countries, we assumed that per capita in-use stocks will saturate eventually. We determined the response of the entire steel cycle to stock saturation, in particular the future split between primary and secondary steel production. During the 21st century, steel demand may peak in the developed world, China, the Middle East, Latin America, and India. As China completes its industrialization, global primary steel production may peak between 2020 and 2030 and decline thereafter. We developed a capacity model to show how extensive trade of finished steel could prolong the lifetime of the Chinese steelmaking assets. Secondary steel production will more than double by 2050, and it may surpass primary production between 2050 and 2060: the late 21st century can become the steel scrap age.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pal, Ranjan; Chelmis, Charalampos; Aman, Saima
The advent of smart meters and advanced communication infrastructures catalyzes numerous smart grid applications such as dynamic demand response, and paves the way to solve challenging research problems in sustainable energy consumption. The space of solution possibilities are restricted primarily by the huge amount of generated data requiring considerable computational resources and efficient algorithms. To overcome this Big Data challenge, data clustering techniques have been proposed. Current approaches however do not scale in the face of the “increasing dimensionality” problem where a cluster point is represented by the entire customer consumption time series. To overcome this aspect we first rethinkmore » the way cluster points are created and designed, and then design an efficient online clustering technique for demand response (DR) in order to analyze high volume, high dimensional energy consumption time series data at scale, and on the fly. Our online algorithm is randomized in nature, and provides optimal performance guarantees in a computationally efficient manner. Unlike prior work we (i) study the consumption properties of the whole population simultaneously rather than developing individual models for each customer separately, claiming it to be a ‘killer’ approach that breaks the “curse of dimensionality” in online time series clustering, and (ii) provide tight performance guarantees in theory to validate our approach. Our insights are driven by the field of sociology, where collective behavior often emerges as the result of individual patterns and lifestyles.« less
Umehara, Katsura; Ohya, Yukihiro; Kawakami, Norito; Tsutsumi, Akizumi; Fujimura, Masanori
2007-11-01
A cross-sectional study was conducted to explore what work-related factors were associated with job stress among pediatricians in Japan, as determined by the demand-control-support model and psychosomatic symptoms. We sent an anonymous questionnaire to a random sample of 3,000 members selected from the nationwide register of the Japan Pediatric Society and received 850 responses (response rate, 28%). Data from the 590 respondents who worked more than 35 h per week as a pediatrician and had no missing responses in the questionnaire were analyzed. We measured workload-related variables (e.g. working hours, work schedule) and recovery-related variables (e.g. workdays with no overtime, days off with no work in the past month) as exposure variables, and psychosocial job stressors (the Brief Job Stress Questionnaire) and psychosomatic symptoms as outcome variables. Longer working hours per week was significantly associated with greater job demand, lower job control and more psychosomatic symptoms (p<0.05). After adjusting for working hours, more workdays with no overtime was significantly associated with lower job demand, greater job control and fewer psychosomatic symptoms (p<0.05). Our findings suggest that long working hours is a risk factor for job stressors and psychosomatic symptoms, and that workdays with no overtime is a protective factor which may facilitate recovery. Controlling working hours and encouraging non-overtime workdays may be important for reducing job stressors and psychosomatic symptoms among pediatricians in Japan.
van Lankveld, Jacques J D M; van den Hout, Marcel A; Schouten, Erik G W
2004-08-01
Sexually functional (N=26) and sexually dysfunctional heterosexual men with psychogenic erectile disorder (N=23) viewed two sexually explicit videos. Performance demand was manipulated through verbal instruction that a substantial genital response was to be expected from the videos. Self-focused attention was manipulated by introducing a camera pointed at the participant. Dispositional self-consciousness was assessed by questionnaire. Performance demand was found to independently inhibit the genital response. No main effect of self-focus was found. Self-focus inhibited genital response in men scoring high on general and sexual self-consciousness traits, whereas it enhanced penile tumescence in low self-conscious men. Inhibition effects were found in both volunteers and patients. No interaction effects of performance demand and self-focus were found. Subjective sexual arousal in sexually functional men was highest in the self-focus condition. In sexually dysfunctional men, subjective sexual response proved dependent on locus of attention as well as presentation order.
Laboratory Testing of Demand-Response Enabled Household Appliances
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sparn, B.; Jin, X.; Earle, L.
2013-10-01
With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond tomore » demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.« less
Laboratory Testing of Demand-Response Enabled Household Appliances
DOE Office of Scientific and Technical Information (OSTI.GOV)
Sparn, B.; Jin, X.; Earle, L.
2013-10-01
With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond tomore » demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.« less
Caregiver responses to early cleft palate care: A mixed method approach.
Sischo, Lacey; Clouston, Sean A P; Phillips, Ceib; Broder, Hillary L
2016-05-01
This study sought to understand caregivers' (CGs') responses to early cleft lip/palate care for their infants. A prospective, mixed methods multicenter longitudinal study was conducted among CGs (N = 118) seeking treatment for their infants' cleft lip and palate or cleft lip only at 1 of 6 cleft treatment centers in the United States. Participants were in 1 of 2 treatment groups: traditional care only or nasoalveolar molding (NAM) plus traditional care. The CGs completed semistructured interviews and standardized questionnaires assessing psychosocial well-being and family impact at 3 time points: the beginning of treatment (∼1 month of age), prelip surgery (∼3-5 months of age), and postpalate surgery (∼12-13 months of age). Multilevel modeling was used to longitudinally assess CGs' psychosocial outcomes. Although the first year was demanding for all CGs, NAM onset and the child's lip surgery were particularly stressful times. CGs used optimism, problem-solving behavior, and social support to cope with this stress. Qualitatively, CGs' ability to balance cleft treatment demands with their psychosocial resources and coping strategies influenced family adaptation. Qualitative and quantitative results indicated CGs of NAM-treated infants experienced more rapid declines in anxiety and depressive symptoms and better coping skills over time than CGs whose infants had traditional care. CGs of NAM-treated infants experienced more positive psychosocial outcomes than CGs whose infants had traditional care. Results from the mixed model support the family adjustment and adaptation response model as used in pediatric chronic condition research. (c) 2016 APA, all rights reserved).
Distributed Generation Market Demand Model | NREL
Demand Model The Distributed Generation Market Demand (dGen) model simulates the potential adoption of distributed energy resources (DERs) for residential, commercial, and industrial entities in the dGen model can help develop deployment forecasts for distributed resources, including sensitivity to
29 CFR 20.4 - Determination of delinquency; notice.
Code of Federal Regulations, 2011 CFR
2011-07-01
... appropriate written demands for payment in terms which inform the debtor of the consequences of failure to... progressively stronger written demands at not more than 30-day intervals will normally be made unless a response to the first or second demand indicates that a further demand would be futile and the debtor's...
Apollo, Seth; Onyango, Maurice S; Ochieng, Aoyi
2016-10-01
Anaerobic digestion (AD) is efficient in organic load removal and bioenergy recovery when applied in treating distillery effluent; however, it is ineffective in colour reduction. In contrast, ultraviolet (UV) photodegradation post-treatment for the AD-treated distillery effluent is effective in colour reduction but has high energy requirement. The effects of operating parameters on bioenergy production and energy demand of photodegradation were modelled using response surface methodology (RSM) with a view of developing a sustainable process in which the biological step could supply energy to the energy-intensive photodegradation step. The organic loading rate (OLRAD) and hydraulic retention time (HRTAD) of the initial biological step were the variables investigated. It was found that the initial biological step removed about 90% of COD and only about 50% colour while photodegradation post-treatment removed 98% of the remaining colour. Maximum bioenergy production of 180.5 kWh/m(3) was achieved. Energy demand of the UV lamp was lowest at low OLRAD irrespective of HRTAD, with values ranging between 87 and 496 kWh/m(3). The bioenergy produced formed 93% of the UV lamp energy demand when the system was operated at OLRAD of 3 kg COD/m(3) d and HRT of 20 days. The presumed carbon dioxide emission reduction when electricity from bioenergy was used to power the UV lamp was 28.8 kg CO2 e/m(3), which could reduce carbon emission by 31% compared to when electricity from the grid was used, leading to environmental conservation.
Field Testing and Modeling of Supermarket Refrigeration Systems as a Demand Response Resource
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deru, Michael; Hirsch, Adam; Clark, Jordan
Supermarkets offer a substantial demand response (DR) resource because of their high energy intensity and use patterns; however, refrigeration as the largest load has been challenging to access. Previous work has analyzed supermarket DR using heating, ventilating, and air conditioning; lighting; and anti-sweat heaters. This project evaluated and quantified the DR potential inherent in supermarket refrigeration systems in the Bonneville Power Administration service territory. DR events were carried out and results measured in an operational 45,590-ft2 supermarket located in Hillsboro, Oregon. Key results from the project include the rate of temperature increase in freezer reach-in cases and walk-ins when refrigerationmore » is suspended, the load shed amount for DR tests, and the development of calibrated models to quantify available DR resources. Simulations showed that demand savings of 15 to 20 kilowatts (kW) are available for 1.5 hours for a typical store without precooling and for about 2.5 hours with precooling using only the low-temperature, non-ice cream cases. This represents an aggregated potential of 20 megawatts within BPA's service territory. Inability to shed loads for medium-temperature (MT) products because of the tighter temperature requirements is a significant barrier to realizing larger DR for supermarkets. Store owners are reluctant to allow MT case set point changes, and laboratory tests of MT case DR strategies are needed so that owners become comfortable testing, and implementing, MT case DR. The next-largest barrier is the lack of proper controls in most supermarket displays over ancillary equipment, such as anti-sweat heaters, lights, and fans.« less
Data-driven modeling, control and tools for cyber-physical energy systems
NASA Astrophysics Data System (ADS)
Behl, Madhur
Energy systems are experiencing a gradual but substantial change in moving away from being non-interactive and manually-controlled systems to utilizing tight integration of both cyber (computation, communications, and control) and physical representations guided by first principles based models, at all scales and levels. Furthermore, peak power reduction programs like demand response (DR) are becoming increasingly important as the volatility on the grid continues to increase due to regulation, integration of renewables and extreme weather conditions. In order to shield themselves from the risk of price volatility, end-user electricity consumers must monitor electricity prices and be flexible in the ways they choose to use electricity. This requires the use of control-oriented predictive models of an energy system's dynamics and energy consumption. Such models are needed for understanding and improving the overall energy efficiency and operating costs. However, learning dynamical models using grey/white box approaches is very cost and time prohibitive since it often requires significant financial investments in retrofitting the system with several sensors and hiring domain experts for building the model. We present the use of data-driven methods for making model capture easy and efficient for cyber-physical energy systems. We develop Model-IQ, a methodology for analysis of uncertainty propagation for building inverse modeling and controls. Given a grey-box model structure and real input data from a temporary set of sensors, Model-IQ evaluates the effect of the uncertainty propagation from sensor data to model accuracy and to closed-loop control performance. We also developed a statistical method to quantify the bias in the sensor measurement and to determine near optimal sensor placement and density for accurate data collection for model training and control. Using a real building test-bed, we show how performing an uncertainty analysis can reveal trends about inverse model accuracy and control performance, which can be used to make informed decisions about sensor requirements and data accuracy. We also present DR-Advisor, a data-driven demand response recommender system for the building's facilities manager which provides suitable control actions to meet the desired load curtailment while maintaining operations and maximizing the economic reward. We develop a model based control with regression trees algorithm (mbCRT), which allows us to perform closed-loop control for DR strategy synthesis for large commercial buildings. Our data-driven control synthesis algorithm outperforms rule-based demand response methods for a large DoE commercial reference building and leads to a significant amount of load curtailment (of 380kW) and over $45,000 in savings which is 37.9% of the summer energy bill for the building. The performance of DR-Advisor is also evaluated for 8 buildings on Penn's campus; where it achieves 92.8% to 98.9% prediction accuracy. We also compare DR-Advisor with other data driven methods and rank 2nd on ASHRAE's benchmarking data-set for energy prediction.
Modeling, Analysis, and Control of Demand Response Resources
DOE Office of Scientific and Technical Information (OSTI.GOV)
Mathieu, Johanna L.
2012-05-01
While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can plan an active role in power systems via Demand Response (DR), defined by the Department of Energy (DOE) as “a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give incentive payments designed to induce lower electricity use at times of high market prices or when grid reliability is jeopardized” [29]. DR can provide a variety of benefits including reducing peak electric loadsmore » when the power system is stressed and fast timescale energy balancing. Therefore, DR can improve grid reliability and reduce wholesale energy prices and their volatility. This dissertation focuses on analyzing both recent and emerging DR paradigms. Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present methods for using 15-minute-interval electric load data, commonly available from C&I facilities, to help building managers understand building energy consumption and ‘ask the right questions’ to discover opportunities for DR. Additionally, we present a regression-based model of whole building electric load, i.e., a baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of 38 C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are expected to exhibit the same response each DR event. We find that baseline model error makes it difficult to precisely quantify changes in electricity consumption and understand if C&I facilities exhibit event-to-event variability in their response to DR signals. Therefore, we present a method to compute baseline model error and a metric to determine how much observed DR variability results from baseline model error rather than real variability in response. We find that, in general, baseline model error is large. Though some facilities exhibit real DR variability, most observed variability results from baseline model error. In some cases, however, aggregations of C&I facilities exhibit real DR variability, which could create challenges for power system operation. These results have implications for DR program design and deployment. Emerging DR paradigms focus on faster timescale DR. Here, we investigate methods to coordinate aggregations of residential thermostatically controlled loads (TCLs), including air conditioners and refrigerators, to manage frequency and energy imbalances in power systems. We focus on opportunities to centrally control loads with high accuracy but low requirements for sensing and communications infrastructure. Specifically, we compare cases when measured load state information (e.g., power consumption and temperature) is 1) available in real time; 2) available, but not in real time; and 3) not available. We develop Markov Chain models to describe the temperature state evolution of heterogeneous populations of TCLs, and use Kalman filtering for both state and joint parameter/state estimation. We present a look-ahead proportional controller to broadcast control signals to all TCLs, which always remain in their temperature dead-band. Simulations indicate that it is possible to achieve power tracking RMS errors in the range of 0.26–9.3% of steady state aggregated power consumption. Results depend upon the information available for system identification, state estimation, and control. We find that, depending upon the performance required, TCLs may not need to provide state information to the central controller in real time or at all. We also estimate the size of the TCL potential resource; potential revenue from participation in markets; and break-even costs associated with deploying DR-enabling technologies. We find that current TCL energy storage capacity in California is 8–11 GWh, with refrigerators contributing the most. Annual revenues from participation in regulation vary from $10 to $220 per TCL per year depending upon the type of TCL and climate zone, while load following and arbitrage revenues are more modest at $2 to $35 per TCL per year. These results lead to a number of policy recommendations that will make it easier to engage residential loads in fast timescale DR.« less
Zarriello, Phillip J.
2002-01-01
A Hydrologic Simulation Program FORTRAN (HSPF) model previously developed for the Ipswich River Basin was modified to simulate the hydrologic response and firm yields of the water-supply systems of Lynn, Peabody, and Salem-Beverly. The updated model, expanded to include a portion of the Saugus River Basin that supplies water to Lynn, simulated reservoir system storage over a 35-year period (1961-95) under permitted withdrawals and hypothetical restrictions designed to maintain seasonally varied streamflow for aquatic habitat. A firm yield was calculated for each system and each withdrawal restriction by altering demands until the system failed. This is considered the maximum withdrawal rate that satisfies demands, but depletes reservoir storage. Simulations indicate that, under the permitted withdrawals, Lynn and Salem-Beverly were able to meet demands and generally have their reservoir system recover to full capacity during most years; reservoir storage averaged 83 and 82 percent of capacity, respectively. The firm yields for the Lynn and Salem-Beverly systems were 11.4 and 12.2 million gallons per day (Mgal/d), respectively, or 8 and 21 percent more than average 1998-2000 demands, respectively. Under permitted withdrawals and average 1998-2000 demands, the Peabody system failed in all years; thus Peabody purchased water to meet demands. The firm yield for the Peabody system is 3.70 Mgal/d, or 37 percent less than the average 1998-2000 demand. Simulations that limit withdrawals to levels recommended by the Ipswich River Fisheries Restoration Task Group (IRFRTG) indicate that under average 1998-2000 demands, reservoir storage was depleted in each of the three systems. Reservoir storage under average 1998-2000 demands and IRFRTG-recommended streamflow requirements averaged 15, 22, and 71 percent of capacity for the Lynn, Peabody, Salem-Beverly systems, respectively. The firm-yield estimates under the IRFRTG-recommended streamflow requirements were 6.02, 1.94, and 7.69 Mgal/d or 43, 64, and 34 percent less than the average 1998-2000 demands for the Lynn, Peabody, and Salem-Beverly systems, respectively. Simulations that limit withdrawals from the Saugus River to a less stringent set of restrictions (based on an Instream Flow Incremental Methodology study) than those previously simulated indicate that the firm yield of the Lynn system is about 31 percent less than the average 1998-2000 withdrawals (7.31 Mgal/d).
Bam, L; McLaren, Z M; Coetzee, E; von Leipzig, K H
2017-10-01
The under-performance of supply chains presents a significant hindrance to disease control in developing countries. Stock-outs of essential medicines lead to treatment interruption which can force changes in patient drug regimens, drive drug resistance and increase mortality. This study is one of few to quantitatively evaluate the effectiveness of supply chain policies in reducing shortages and costs. This study develops a systems dynamics simulation model of the downstream supply chain for amikacin, a second-line tuberculosis drug using 10 years of South African data. We evaluate current supply chain performance in terms of reliability, responsiveness and agility, following the widely-used Supply Chain Operation Reference framework. We simulate 141 scenarios that represent different combinations of supplier characteristics, inventory management strategies and demand forecasting methods to identify the Pareto optimal set of management policies that jointly minimize the number of shortages and total cost. Despite long supplier lead times and unpredictable demand, the amikacin supply chain is 98% reliable and agile enough to accommodate a 20% increase in demand without a shortage. However, this is accomplished by overstocking amikacin by 167%, which incurs high holding costs. The responsiveness of suppliers is low: only 57% of orders are delivered to the central provincial drug depot within one month. We identify three Pareto optimal safety stock management policies. Short supplier lead time can produce Pareto optimal outcomes even in the absence of other optimal policies. This study produces concrete, actionable guidelines to cost-effectively reduce stock-outs by implementing optimal supply chain policies. Preferentially selecting drug suppliers with short lead times accommodates unexpected changes in demand. Optimal supply chain management should be an essential component of national policy to reduce the mortality rate. © The Author 2017. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
A Community-Based Approach to Leading the Nation in Smart Energy Use
DOE Office of Scientific and Technical Information (OSTI.GOV)
None, None
2013-12-31
Project Objectives The AEP Ohio gridSMART® Demonstration Project (Project) achieved the following objectives: • Built a secure, interoperable, and integrated smart grid infrastructure in northeast central Ohio that demonstrated the ability to maximize distribution system efficiency and reliability and consumer use of demand response programs that reduced energy consumption, peak demand, and fossil fuel emissions. • Actively attracted, educated, enlisted, and retained consumers in innovative business models that provided tools and information reducing consumption and peak demand. • Provided the U.S. Department of Energy (DOE) information to evaluate technologies and preferred smart grid business models to be extended nationally. Projectmore » Description Ohio Power Company (the surviving company of a merger with Columbus Southern Power Company), doing business as AEP Ohio (AEP Ohio), took a community-based approach and incorporated a full suite of advanced smart grid technologies for 110,000 consumers in an area selected for its concentration and diversity of distribution infrastructure and consumers. It was organized and aligned around: • Technology, implementation, and operations • Consumer and stakeholder acceptance • Data management and benefit assessment Combined, these functional areas served as the foundation of the Project to integrate commercially available products, innovative technologies, and new consumer products and services within a secure two-way communication network between the utility and consumers. The Project included Advanced Metering Infrastructure (AMI), Distribution Management System (DMS), Distribution Automation Circuit Reconfiguration (DACR), Volt VAR Optimization (VVO), and Consumer Programs (CP). These technologies were combined with two-way consumer communication and information sharing, demand response, dynamic pricing, and consumer products, such as plug-in electric vehicles and smart appliances. In addition, the Project incorporated comprehensive cyber security capabilities, interoperability, and a data assessment that, with grid simulation capabilities, made the demonstration results an adaptable, integrated solution for AEP Ohio and the nation.« less
A coupled nuclear reactor thermal energy storage system for enhanced load following operation
NASA Astrophysics Data System (ADS)
Alameri, Saeed A.
Nuclear power plants usually provide base-load electric power and operate most economically at a constant power level. In an energy grid with a high fraction of renewable energy sources, future nuclear reactors may be subject to significantly variable power demands. These variable power demands can negatively impact the effective capacity factor of the reactor and result in severe economic penalties. Coupling the reactor to a large Thermal Energy Storage (TES) block will allow the reactor to better respond to variable power demands. In the system described in this thesis, a Prismatic-core Advanced High Temperature Reactor (PAHTR) operates at constant power with heat provided to a TES block that supplies power as needed to a secondary energy conversion system. The PAHTR is designed to have a power rating of 300 MW th, with 19.75 wt% enriched Tri-Structural-Isotropic UO 2 fuel and a five year operating cycle. The passive molten salt TES system will operate in the latent heat region with an energy storage capacity of 150 MWd. Multiple smaller TES blocks are used instead of one large block to enhance the efficiency and maintenance complexity of the system. A transient model of the coupled reactor/TES system is developed to study the behavior of the system in response to varying load demands. The model uses six-delayed group point kinetics and decay heat models coupled to thermal-hydraulic and heat transfer models of the reactor and TES system. Based on the transient results, the preferred TES design consists of 1000 blocks, each containing 11000 LiCl phase change material tubes. A safety assessment of major reactor events demonstrates the inherent safety of the coupled system. The loss of forced circulation study determined the minimum required air convection heat removal rate from the reactor core and the lowest possible reduced primary flow rate that can maintain the reactor in a safe condition. The loss of ultimate heat sink study demonstrated the ability of the TES to absorb the decay heat of the reactor fuel while cooling the PAHTR after an emergency shutdown. The simulated reactivity insertion accident assessment determined the maximum allowable reactivity insertion to the PAHTR as a function of shutdown response times.
Self-Efficacy and Workaholism as Initiators of the Job Demands-Resources Model
ERIC Educational Resources Information Center
Guglielmi, Dina; Simbula, Silvia; Schaufeli, Wilmar B.; Depolo, Marco
2012-01-01
Purpose: This study aims to investigate school principals' well-being by using the job demands-resources (JD-R) model as a theoretical framework. It aims at making a significant contribution to the development of this model by considering not only job demands and job resources, but also the role of personal resources and personal demands as…
NASA Astrophysics Data System (ADS)
Gnann, Till; Klingler, Anna-Lena; Kühnbach, Matthias
2018-06-01
Plug-in electric vehicles are the currently favoured option to decarbonize the passenger car sector. However, a decarbonisation is only possible with electricity from renewable energies and plug-in electric vehicles might cause peak loads if they started to charge at the same time. Both these issues could be solved with coordinated load shifting (demand response). Previous studies analyzed this research question by focusing on private vehicles with domestic and work charging infrastructure. This study additionally includes the important early adopter group of commercial fleet vehicles and reflects the impact of domestic, commercial, work and public charging. For this purpose, two models are combined. In a comparison of three scenarios, we find that charging of commercial vehicles does not inflict evening load peaks in the same magnitude as purely domestic charging of private cars does. Also for private cars, charging at work occurs during the day and may reduce the necessity of load shifting while public charging plays a less important role in total charging demand as well as load shifting potential. Nonetheless, demand response reduces the system load by about 2.2 GW or 2.8% when domestic and work charging are considered compared to a scenario with only domestic charging.
NASA Astrophysics Data System (ADS)
Frieler, K.; Levermann, A.; Elliott, J.; Heinke, J.; Arneth, A.; Bierkens, M. F. P.; Ciais, P.; Clark, D. B.; Deryng, D.; Döll, P.; Falloon, P.; Fekete, B.; Folberth, C.; Friend, A. D.; Gellhorn, C.; Gosling, S. N.; Haddeland, I.; Khabarov, N.; Lomas, M.; Masaki, Y.; Nishina, K.; Neumann, K.; Oki, T.; Pavlick, R.; Ruane, A. C.; Schmid, E.; Schmitz, C.; Stacke, T.; Stehfest, E.; Tang, Q.; Wisser, D.; Huber, V.; Piontek, F.; Warszawski, L.; Schewe, J.; Lotze-Campen, H.; Schellnhuber, H. J.
2015-07-01
Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.
Berzosa, Álvaro; Barandica, Jesús M; Fernández-Sánchez, Gonzalo
2014-01-01
In recent years, several methodologies have been developed for the quantification of greenhouse gas (GHG) emissions. However, determining who is responsible for these emissions is also quite challenging. The most common approach is to assign emissions to the producer (based on the Kyoto Protocol), but proposals also exist for its allocation to the consumer (based on an ecological footprint perspective) and for a hybrid approach called shared responsibility. In this study, the existing proposals and standards regarding the allocation of GHG emissions responsibilities are analyzed, focusing on their main advantages and problems. A new model of shared responsibility that overcomes some of the existing problems is also proposed. This model is based on applying the best available technologies (BATs). This new approach allocates the responsibility between the producers and the final consumers based on the real capacity of each agent to reduce emissions. The proposed approach is demonstrated using a simple case study of a 4-step life cycle of ammonia nitrate (AN) fertilizer production. The proposed model has the characteristics that the standards and publications for assignment of GHG emissions responsibilities demand. This study presents a new way to assign responsibilities that pushes all the actors in the production chain, including consumers, to reduce pollution. © 2013 SETAC.
75 FR 20901 - Standards for Business Practices and Communication Protocols for Public Utilities
Federal Register 2010, 2011, 2012, 2013, 2014
2010-04-22
... markets. This rule ensures that participants in wholesale energy markets where demand response products... those markets and addresses performance evaluation methods appropriate to use for demand response... markets, reducing transaction costs and providing an opportunity for more customers to participate in...
Policy impacts on agricultural irrigation electricity demand in the Columbia Basin
DOE Office of Scientific and Technical Information (OSTI.GOV)
Martin, M.; Cox, L.; Nakamoto, S.
Accurately estimating the price elasticity of demand for irrigation electricity is important to major electricity suppliers such as the Bonneville Power Administration (BPA) of the Pacific Northwest. The BPA has a revenue maximization objective, and the elasticity of demand is central to its rate setting process. Several studies have attempted to estimate demand for irrigation electricity, but none has explicitly included federal agricultural policy and program variables. Tins paper discusses how agricultural programs may influence farmers' irrigation decisions and thus their demand for irrigation electricity. It suggests that existing programs serve to make farmers more responsive to electricity rate increasesmore » than would otherwise be the case. Thus, studies that fail to include them may underestimate the responsiveness of farmers to electricity rate increases.« less
Some comments on the World Energy Conference (WEC) energy demand model
NASA Astrophysics Data System (ADS)
Brandell, L.
1982-04-01
The WEC model, relating the energy demand for a region in a year to gross national product (GNP), aggregated energy prices and elasticity constants, is generalized. The changes that result from the assumption that the elasticity factors are not constant are examined. The resulting differential equation contains the variables energy demand per capita and GNP per capita for the region considered. The effect of time lag in energy demand and the influence of the population growth rate are also included in the model. No projections of the future energy demand were made, but model sensitiveness to the modifications were studied. Time lag effects and population growth effects can raise the projected energy demand for a region by 10% or more.
Role of the Freight Sector in Future Climate Change Mitigation Scenarios
Muratori, Matteo; Smith, Steven J.; Kyle, Page; ...
2017-02-27
The freight sector's role is examined using the Global Change Assessment Model (GCAM) for a range of climate change mitigation scenarios and future freight demand assumptions. Energy usage and CO 2 emissions from freight have historically grown with a correlation to GDP, and there is limited evidence of near-term global decoupling of freight demand from GDP. Over the 21 st century, greenhouse gas (GHG) emissions from freight are projected to grow faster than passenger transportation or other major end-use sectors, with the magnitude of growth dependent on the assumed extent of long-term decoupling. In climate change mitigation scenarios that applymore » a price to GHG emissions, mitigation of freight emissions (including the effects of demand elasticity, mode and technology shifting, and fuel substitution) is more limited than for other demand sectors. In such scenarios, shifting to less-emitting transportation modes and technologies is projected to play a relatively small role in reducing freight emissions in GCAM. Finally, by contrast, changes in the supply chain of liquid fuels that reduce the fuel carbon intensity, especially deriving from large-scale use of biofuels coupled to carbon capture and storage technologies, are responsible for the majority of freight emissions mitigation, followed by price-induced reduction in freight demand services.« less
Role of the Freight Sector in Future Climate Change Mitigation Scenarios
DOE Office of Scientific and Technical Information (OSTI.GOV)
Muratori, Matteo; Smith, Steven J.; Kyle, Page
The freight sector's role is examined using the Global Change Assessment Model (GCAM) for a range of climate change mitigation scenarios and future freight demand assumptions. Energy usage and CO 2 emissions from freight have historically grown with a correlation to GDP, and there is limited evidence of near-term global decoupling of freight demand from GDP. Over the 21 st century, greenhouse gas (GHG) emissions from freight are projected to grow faster than passenger transportation or other major end-use sectors, with the magnitude of growth dependent on the assumed extent of long-term decoupling. In climate change mitigation scenarios that applymore » a price to GHG emissions, mitigation of freight emissions (including the effects of demand elasticity, mode and technology shifting, and fuel substitution) is more limited than for other demand sectors. In such scenarios, shifting to less-emitting transportation modes and technologies is projected to play a relatively small role in reducing freight emissions in GCAM. Finally, by contrast, changes in the supply chain of liquid fuels that reduce the fuel carbon intensity, especially deriving from large-scale use of biofuels coupled to carbon capture and storage technologies, are responsible for the majority of freight emissions mitigation, followed by price-induced reduction in freight demand services.« less
Role of the Freight Sector in Future Climate Change Mitigation Scenarios.
Muratori, Matteo; Smith, Steven J; Kyle, Page; Link, Robert; Mignone, Bryan K; Kheshgi, Haroon S
2017-03-21
The freight sector's role is examined using the Global Change Assessment Model (GCAM) for a range of climate change mitigation scenarios and future freight demand assumptions. Energy usage and CO 2 emissions from freight have historically grown with a correlation to GDP, and there is limited evidence of near-term global decoupling of freight demand from GDP. Over the 21 st century, greenhouse gas (GHG) emissions from freight are projected to grow faster than passenger transportation or other major end-use sectors, with the magnitude of growth dependent on the assumed extent of long-term decoupling. In climate change mitigation scenarios that apply a price to GHG emissions, mitigation of freight emissions (including the effects of demand elasticity, mode and technology shifting, and fuel substitution) is more limited than for other demand sectors. In such scenarios, shifting to less-emitting transportation modes and technologies is projected to play a relatively small role in reducing freight emissions in GCAM. By contrast, changes in the supply chain of liquid fuels that reduce the fuel carbon intensity, especially deriving from large-scale use of biofuels coupled to carbon capture and storage technologies, are responsible for the majority of freight emissions mitigation, followed by price-induced reduction in freight demand services.
Burnout, Engagement, and Organizational Culture: Differences between Physicians and Nurses
Mijakoski, Dragan; Karadzinska-Bislimovska, Jovanka; Basarovska, Vera; Montgomery, Anthony; Panagopoulou, Efharis; Stoleski, Sasho; Minov, Jordan
2015-01-01
BACKGROUND: Burnout results from a prolonged response to chronic emotional and interpersonal workplace stressors. The focus of research has been widened to job engagement. AIM: Purpose of the study was to examine associations between burnout, job engagement, work demands, and organisational culture (OC) and to demonstrate differences between physicians and nurses working in general hospital in Skopje, Republic of Macedonia. MATERIAL AND METHODS: Maslach Burnout Inventory and Utrecht Work Engagement Scale were used for assessment of burnout and job engagement. Work demands and OC were measured with Hospital Experience Scale and Competing Values Framework, respectively. RESULTS: Higher scores of dedication, hierarchy OC, and organizational work demands were found in physicians. Nurses demonstrated higher scores of clan OC. Burnout negatively correlated with clan and market OC in physicians and nurses. Job engagement positively correlated with clan and market OC in nurses. Different work demands were related to different dimensions of burnout and/or job engagement. Our findings support job demands-resources (JD-R) model (Demerouti and Bakker). CONCLUSIONS: Data obtained can be used in implementation of specific organizational interventions in the hospital setting. Providing adequate JD-R interaction can lead to prevention of burnout in health professionals (HPs) and contribute positively to better job engagement in HPs and higher quality of patient care. PMID:27275279
Be All That We Can Be: Lessons from the Military for Improving Our Nation's Child Care System.
ERIC Educational Resources Information Center
Campbell, Nancy Duff; Appelbaum, Judith C.; Martinson, Karin; Martin, Emily
In response to increasing demands for military child care and lack of comprehensive care standards, the Military Child Care Act of 1989 (MCCA) mandated improvements in military child care. Today, the Department of Defense runs a model child care system serving over 200,000 children daily at over 300 locations worldwide. Noting that most of the…
Henley, David
2006-11-01
This paper examines the past transition from low to high fertility which, in Indonesia as elsewhere, preceded the return to lower birth rates. Data from two parts of the island of Sulawesi where fertility rose during the colonial period are used to explain both why it rose, and why it was originally low. Economic conditions, it is argued, were the most important factors, affecting fertility via the supply of income and the demand for labour. Two schematic models of the 'first fertility transition' are proposed. In areas with low population densities and area-extensive forms of agriculture responsive to commercial stimuli, birth rates rose as the growth of commerce raised levels of prosperity, facilitated marriage, and undermined institutions such as debt-slavery which had previously acted to restrict marital fertility. In densely populated areas with labour-intensive agriculture and heavy state taxation in labour, fertility rose in response to demands for women's (and possibly child) labour that did not necessarily lead to gains in income.
NASA Astrophysics Data System (ADS)
Bandres Motola, Miguel A.
Essay one estimates changes in small business customer energy consumption (kWh) patterns resulting from a seasonally differentiated pricing structure. Econometric analysis leverages cross-sectional time series data across the entire population of affected customers, from 2007 through the present. Observations include: monthly energy usage (kWh), relevant customer segmentations, local daily temperature, energy price, and region-specific economic conditions, among other variables. The study identifies the determinants of responsiveness to seasonal price differentiation. In addition, estimated energy consumption changes occurring during the 2010 summer season are reported for the average customer and in aggregate grouped by relevant customer segments, climate zone, and total customer base. Essay two develops an econometric modeling methodology to evaluate load impacts for short duration demand response events. The study analyzes time series data from a season of direct load control program tests aimed at integrating demand response into the wholesale electricity market. I have combined "fuzzy logic" with binary variables to create "fuzzy indicator variables" that allow for measurement of short duration events while using industry standard model specifications. Typically, binary variables for every hour are applied in load impact analysis of programs dispatched in hourly intervals. As programs evolve towards integration with the wholesale market, event durations become irregular and often occur for periods of only a few minutes. This methodology is innovative in that it conserves the degrees of freedom in the model while allowing for analysis of high frequency data using fixed effects. Essay three examines the effects of strategies, intangibles, and FDA news on the stocks of young biopharmaceutical firms. An event study methodology is used to explore those effects. This study investigates 20,839 announcements from 1990 to 2005. Announcements on drug development, alliances, publications, presentations, and FDA approval have a positive effect on the short-term performance of young biopharmaceutical firms. Announcements on goals not met, FDA drug approval denied, and changes in structural organizations have a negative effect on the short-term performance of young biopharmaceutical firms.
A Study of Energy Management Systems and its Failure Modes in Smart Grid Power Distribution
NASA Astrophysics Data System (ADS)
Musani, Aatif
The subject of this thesis is distribution level load management using a pricing signal in a smart grid infrastructure. The project relates to energy management in a spe-cialized distribution system known as the Future Renewable Electric Energy Delivery and Management (FREEDM) system. Energy management through demand response is one of the key applications of smart grid. Demand response today is envisioned as a method in which the price could be communicated to the consumers and they may shift their loads from high price periods to the low price periods. The development and deployment of the FREEDM system necessitates controls of energy and power at the point of end use. In this thesis, the main objective is to develop the control model of the Energy Management System (EMS). The energy and power management in the FREEDM system is digitally controlled therefore all signals containing system states are discrete. The EMS is modeled as a discrete closed loop transfer function in the z-domain. A breakdown of power and energy control devices such as EMS components may result in energy con-sumption error. This leads to one of the main focuses of the thesis which is to identify and study component failures of the designed control system. Moreover, H-infinity ro-bust control method is applied to ensure effectiveness of the control architecture. A focus of the study is cyber security attack, specifically bad data detection in price. Test cases are used to illustrate the performance of the EMS control design, the effect of failure modes and the application of robust control technique. The EMS was represented by a linear z-domain model. The transfer function be-tween the pricing signal and the demand response was designed and used as a test bed. EMS potential failure modes were identified and studied. Three bad data detection meth-odologies were implemented and a voting policy was used to declare bad data. The run-ning mean and standard deviation analysis method proves to be the best method to detect bad data. An H-infinity robust control technique was applied for the first time to design discrete EMS controller for the FREEDM system.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Kim, Joyce Jihyun; Schetrit, Oren; Yin, Rongxin
Demand response (DR) – allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern – continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. From October 2011 to December 2013, the Demand Response Research Center at Lawrence Berkeley National Laboratory, the New York State Energy Research and Development Authority, and partners Honeywell and Akuacom, have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR)more » communication protocols. In particular, this project focuses on demonstrating how the OpenADR platform, enabled by Akuacom, can automate and simplify interactions between buildings and various stakeholders in New York State and enable the automation of customers’ price response to yield bill savings under dynamic pricing. In this paper, the cost control opportunities under day-ahead hourly pricing and Auto-DR control strategies are presented for four demonstration buildings; present the breakdown of Auto-DR enablement costs; summarize the field test results and their load impact; and show potential bill savings by enabling automated price response under Consolidated Edison’s Mandatory Hourly Pricing (MHP) tariff. For one of the sites, the potential bill savings at the site’s current retail rate are shown. Facility managers were given granular equipment-level opt-out capability to ensure full control of the sites during the Auto-DR implementation. The expected bill savings ranged from 1.1% to 8.0% of the total MHP bill. The automation and enablement costs ranged from $70 to $725 per kW shed. The results show that OpenADR can facilitate the automation of price response, deliver savings to the customers and opt-out capability of the implementation retains control of the sites by facility managers.« less
Aboagye-Sarfo, Patrick; Mai, Qun; Sanfilippo, Frank M; Preen, David B; Stewart, Louise M; Fatovich, Daniel M
2015-10-01
To develop multivariate vector-ARMA (VARMA) forecast models for predicting emergency department (ED) demand in Western Australia (WA) and compare them to the benchmark univariate autoregressive moving average (ARMA) and Winters' models. Seven-year monthly WA state-wide public hospital ED presentation data from 2006/07 to 2012/13 were modelled. Graphical and VARMA modelling methods were used for descriptive analysis and model fitting. The VARMA models were compared to the benchmark univariate ARMA and Winters' models to determine their accuracy to predict ED demand. The best models were evaluated by using error correction methods for accuracy. Descriptive analysis of all the dependent variables showed an increasing pattern of ED use with seasonal trends over time. The VARMA models provided a more precise and accurate forecast with smaller confidence intervals and better measures of accuracy in predicting ED demand in WA than the ARMA and Winters' method. VARMA models are a reliable forecasting method to predict ED demand for strategic planning and resource allocation. While the ARMA models are a closely competing alternative, they under-estimated future ED demand. Copyright © 2015 Elsevier Inc. All rights reserved.
This paper compares the climate change impacts on U.S. electricity demand and supply from three models: the Integrated Planning Model (IPM), the Regional Energy Deployment System (ReEDS) model, and GCAM. Rising temperatures cause an appreciable net increase in electricity demand....
Modelling the side impact of carbon fibre tubes
NASA Astrophysics Data System (ADS)
Sudharsan, Ms R.; Rolfe, B. F., Dr; Hodgson, P. D., Prof
2010-06-01
Metallic tubes have been extensively studied for their crashworthiness as they closely resemble automotive crash rails. Recently, the demand to improve fuel economy and reduce vehicle emissions has led automobile manufacturers to explore the crash properties of light weight materials such as fibre reinforced polymer composites, metallic foams and sandwich structures in order to use them as crash barriers. This paper discusses the response of carbon fibre reinforced polymer (CFRP) tubes and their failure mechanisms during side impact. The energy absorption of CFRP tubes is compared to similar Aluminium tubes. The response of the CFRP tubes during impact was modelled using Abaqus finite element software with a composite fabric material model. The material inputs were given based on standard tension and compression test results and the in-plane damage was defined based on cyclic shear tests. The failure modes and energy absorption observed during the tests were well represented by the finite element model.
Danker, Jared F; Anderson, John R
2007-04-15
In naturalistic algebra problem solving, the cognitive processes of representation and retrieval are typically confounded, in that transformations of the equations typically require retrieval of mathematical facts. Previous work using cognitive modeling has associated activity in the prefrontal cortex with the retrieval demands of algebra problems and activity in the posterior parietal cortex with the transformational demands of algebra problems, but these regions tend to behave similarly in response to task manipulations (Anderson, J.R., Qin, Y., Sohn, M.-H., Stenger, V.A., Carter, C.S., 2003. An information-processing model of the BOLD response in symbol manipulation tasks. Psychon. Bull. Rev. 10, 241-261; Qin, Y., Carter, C.S., Silk, E.M., Stenger, A., Fissell, K., Goode, A., Anderson, J.R., 2004. The change of brain activation patterns as children learn algebra equation solving. Proc. Natl. Acad. Sci. 101, 5686-5691). With this study we attempt to isolate activity in these two regions by using a multi-step algebra task in which transformation (parietal) is manipulated in the first step and retrieval (prefrontal) is manipulated in the second step. Counter to our initial predictions, both brain regions were differentially active during both steps. We designed two cognitive models, one encompassing our initial assumptions and one in which both processes were engaged during both steps. The first model provided a poor fit to the behavioral and neural data, while the second model fit both well. This simultaneously emphasizes the strong relationship between retrieval and representation in mathematical reasoning and demonstrates that cognitive modeling can serve as a useful tool for understanding task manipulations in neuroimaging experiments.
NASA Astrophysics Data System (ADS)
Blokker, Mirjam; Agudelo-Vera, Claudia; Moerman, Andreas; van Thienen, Peter; Pieterse-Quirijns, Ilse
2017-04-01
Many researchers have developed drinking water demand models with various temporal and spatial scales. A limited number of models is available at a temporal scale of 1 s and a spatial scale of a single home. The reasons for building these models were described in the papers in which the models were introduced, along with a discussion on their potential applications. However, the predicted applications are seldom re-examined. SIMDEUM, a stochastic end-use model for drinking water demand, has often been applied in research and practice since it was developed. We are therefore re-examining its applications in this paper. SIMDEUM's original purpose was to calculate maximum demands in order to design self-cleaning networks. Yet, the model has been useful in many more applications. This paper gives an overview of the many fields of application for SIMDEUM and shows where this type of demand model is indispensable and where it has limited practical value. This overview also leads to an understanding of the requirements for demand models in various applications.
Flynn, Niamh; James, Jack E
2009-05-01
The hypothesis that work control has beneficial effects on well-being is the basis of the widely applied, yet inconsistently supported, Job Demand Control (JDC) Model [Karasek, R.A., 1979. Job demands, job decision latitude and mental strain: Implications for job redesign. Adm. Sci. Q. 24, 285-308.; Karasek, R., Theorell, T., 1990. Healthy Work: Stress, Productivity, and the Reconstruction of Working Life. Basic Books, Oxford]. The model was tested in an experiment (N=60) using a cognitive stressor paradigm that sought to prevent confounding between demand and control. High-demand was found to be associated with deleterious effects on physiological, subjective, and performance outcomes. In contrast, few main effects were found for control. Evidence for the buffer interpretation of the JDC Model was limited to a significant demand-control interaction for performance accuracy, whereas substantial support was found for the strain interpretation of the model [van der Doef, M., Maes, S., 1998. The job demand-control(-support) model and physical health outcomes: A review of the strain and buffer hypotheses. Psychol. Health 13, 909-936., van der Doef, M., Maes, S., 1999. The Job Demand-Control(-Support) model and psychological well-being: A review of 20 years of empirical research. Work Stress 13, 87-114]. Manipulation checks revealed that objective control altered perceptions of control but not perceptions of demand. It is suggested that beneficial effects of work-related control are unlikely to occur in the absence of reductions in perceived demand. Thus, contrary to the propositions of Karasek and colleagues, demand and control do not appear to be independent factors.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Brandt, C.C.; Weinstein, D.A.; Shugart, H.H.
1980-10-01
The Quechua Indians of the Peruvian Andes are an example of a human population which has developed special cultural adaptations to deal with hypocaloric stress imposed by a harsh environment. A highly detailed human ecosystem model, NUNOA, which simulates the yearly energy balance of individuals, families, and extended families in a hypothetical farming and herding Quechua community of the high Andes was developed. Unlike most population models which use sets of differential equations in which individuals are aggregated into groups, this model considers the response of each individual to a stochastic environment. The model calculates the yearly energy demand formore » each family based on caloric requirements of its members. For each family, the model simulates the cultivation of seven different crops and the impact of precipitation, temperature, and disease on yield. Herding, slaughter, and market sales of three different animal species are also simulated. Any energy production in excess of the family's energy demand is placed into extended family storage for possible redistribution. A family failing to meet their annual energy demand may slaughter additional herd animals, temporarily migrate from the community, or borrow food from the extended family storage. The energy balance is used in determining births, deaths, marriages, and resource sharing in the Indian community. In addition, the model maintains a record of each individual's ancestry as well as seven genetic traits for use in tracing lineage and gene flow. The model user has the opportunity to investigate the effect of changes in marriage patterns, resource sharing patterns, or subsistence activities on the ability of the human population to survive in the harsh Andean environment. In addition, the user may investigate the impact of external technology on the Indian culture.« less
Lagi, Marco; Bar-Yam, Yavni; Bertrand, Karla Z.; Bar-Yam, Yaneer
2015-01-01
Recent increases in basic food prices are severely affecting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the United States, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time to our knowledge, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, whereas an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities, and bonds to take advantage of increased expected returns. Claims that speculators cannot influence grain prices are shown to be invalid by direct analysis of price-setting practices of granaries. Both causes of price increase, speculative investment and ethanol conversion, are promoted by recent regulatory changes—deregulation of the commodity markets, and policies promoting the conversion of corn to ethanol. Rapid action is needed to reduce the impacts of the price increases on global hunger. PMID:26504216
Lagi, Marco; Bar-Yam, Yavni; Bertrand, Karla Z; Bar-Yam, Yaneer
2015-11-10
Recent increases in basic food prices are severely affecting vulnerable populations worldwide. Proposed causes such as shortages of grain due to adverse weather, increasing meat consumption in China and India, conversion of corn to ethanol in the United States, and investor speculation on commodity markets lead to widely differing implications for policy. A lack of clarity about which factors are responsible reinforces policy inaction. Here, for the first time to our knowledge, we construct a dynamic model that quantitatively agrees with food prices. The results show that the dominant causes of price increases are investor speculation and ethanol conversion. Models that just treat supply and demand are not consistent with the actual price dynamics. The two sharp peaks in 2007/2008 and 2010/2011 are specifically due to investor speculation, whereas an underlying upward trend is due to increasing demand from ethanol conversion. The model includes investor trend following as well as shifting between commodities, equities, and bonds to take advantage of increased expected returns. Claims that speculators cannot influence grain prices are shown to be invalid by direct analysis of price-setting practices of granaries. Both causes of price increase, speculative investment and ethanol conversion, are promoted by recent regulatory changes-deregulation of the commodity markets, and policies promoting the conversion of corn to ethanol. Rapid action is needed to reduce the impacts of the price increases on global hunger.
Chiu, Yu-Chin; Egner, Tobias
2015-08-26
Response inhibition is a key component of executive control, but its relation to other cognitive processes is not well understood. We recently documented the "inhibition-induced forgetting effect": no-go cues are remembered more poorly than go cues. We attributed this effect to central-resource competition, whereby response inhibition saps attention away from memory encoding. However, this proposal is difficult to test with behavioral means alone. We therefore used fMRI in humans to test two neural predictions of the "common resource hypothesis": (1) brain regions associated with response inhibition should exhibit greater resource demands during encoding of subsequently forgotten than remembered no-go cues; and (2) this higher inhibitory resource demand should lead to memory encoding regions having less resources available during encoding of subsequently forgotten no-go cues. Participants categorized face stimuli by gender in a go/no-go task and, following a delay, performed a surprise recognition memory test for those faces. Replicating previous findings, memory was worse for no-go than for go stimuli. Crucially, forgetting of no-go cues was predicted by high inhibitory resource demand, as quantified by the trial-by-trial ratio of activity in neural "no-go" versus "go" networks. Moreover, this index of inhibitory demand exhibited an inverse trial-by-trial relationship with activity in brain regions responsible for the encoding of no-go cues into memory, notably the ventrolateral prefrontal cortex. This seesaw pattern between the neural resource demand of response inhibition and activity related to memory encoding directly supports the hypothesis that response inhibition temporarily saps attentional resources away from stimulus processing. Recent behavioral experiments showed that inhibiting a motor response to a stimulus (a "no-go cue") impairs subsequent memory for that cue. Here, we used fMRI to test whether this "inhibition-induced forgetting effect" is caused by competition for neural resources between the processes of response inhibition and memory encoding. We found that trial-by-trial variations in neural inhibitory resource demand predicted subsequent forgetting of no-go cues and that higher inhibitory demand was furthermore associated with lower concurrent activation in brain regions responsible for successful memory encoding of no-go cues. Thus, motor inhibition and stimulus encoding appear to compete with each other: when more resources have to be devoted to inhibiting action, less are available for encoding sensory stimuli. Copyright © 2015 the authors 0270-6474/15/3511936-10$15.00/0.
Capturing well-being in activity pattern models within activity-based travel demand models.
DOT National Transportation Integrated Search
2013-03-01
The activity-based approach which is based on the premise that the demand for travel is derived : from the demand for activities, currently constitutes the state of the art in metropolitan travel : demand forecasting and particularly in a form known ...
Capturing well-being in activity pattern models within activity-based travel demand models.
DOT National Transportation Integrated Search
2013-04-01
The activity-based approach which is based on the premise that the demand for travel is derived : from the demand for activities, currently constitutes the state of the art in metropolitan travel : demand forecasting and particularly in a form known ...
Aaron, Grant J.; Strutt, Nicholas; Boateng, Nathaniel Amoh; Guevarra, Ernest; Siling, Katja; Norris, Alison; Ghosh, Shibani; Nyamikeh, Mercy; Attiogbe, Antoine; Burns, Richard; Foriwa, Esi; Toride, Yasuhiko; Kitamura, Satoshi; Tano-Debrah, Kwaku; Sarpong, Daniel; Myatt, Mark
2016-01-01
The work reported here assesses the coverage achieved by two sales-based approaches to distributing a complementary food supplement (KOKO Plus™) to infants and young children in Ghana. Delivery Model 1 was conducted in the Northern Region of Ghana and used a mixture of health extension workers (delivering behavior change communications and demand creation activities at primary healthcare centers and in the community) and petty traders recruited from among beneficiaries of a local microfinance initiative (responsible for the sale of the complementary food supplement at market stalls and house to house). Delivery Model 2 was conducted in the Eastern Region of Ghana and used a market-based approach, with the product being sold through micro-retail routes (i.e., small shops and roadside stalls) in three districts supported by behavior change communications and demand creation activities led by a local social marketing company. Both delivery models were implemented sub-nationally as 1-year pilot programs, with the aim of informing the design of a scaled-up program. A series of cross-sectional coverage surveys was implemented in each program area. Results from these surveys show that Delivery Model 1 was successful in achieving and sustaining high (i.e., 86%) effective coverage (i.e., the child had been given the product at least once in the previous 7 days) during implementation. Effective coverage fell to 62% within 3 months of the behavior change communications and demand creation activities stopping. Delivery Model 2 was successful in raising awareness of the product (i.e., 90% message coverage), but effective coverage was low (i.e., 9.4%). Future programming efforts should use the health extension / microfinance / petty trader approach in rural settings and consider adapting this approach for use in urban and peri-urban settings. Ongoing behavior change communications and demand creation activities is likely to be essential to the continued success of such programming. PMID:27755554
Aaron, Grant J; Strutt, Nicholas; Boateng, Nathaniel Amoh; Guevarra, Ernest; Siling, Katja; Norris, Alison; Ghosh, Shibani; Nyamikeh, Mercy; Attiogbe, Antoine; Burns, Richard; Foriwa, Esi; Toride, Yasuhiko; Kitamura, Satoshi; Tano-Debrah, Kwaku; Sarpong, Daniel; Myatt, Mark
2016-01-01
The work reported here assesses the coverage achieved by two sales-based approaches to distributing a complementary food supplement (KOKO Plus™) to infants and young children in Ghana. Delivery Model 1 was conducted in the Northern Region of Ghana and used a mixture of health extension workers (delivering behavior change communications and demand creation activities at primary healthcare centers and in the community) and petty traders recruited from among beneficiaries of a local microfinance initiative (responsible for the sale of the complementary food supplement at market stalls and house to house). Delivery Model 2 was conducted in the Eastern Region of Ghana and used a market-based approach, with the product being sold through micro-retail routes (i.e., small shops and roadside stalls) in three districts supported by behavior change communications and demand creation activities led by a local social marketing company. Both delivery models were implemented sub-nationally as 1-year pilot programs, with the aim of informing the design of a scaled-up program. A series of cross-sectional coverage surveys was implemented in each program area. Results from these surveys show that Delivery Model 1 was successful in achieving and sustaining high (i.e., 86%) effective coverage (i.e., the child had been given the product at least once in the previous 7 days) during implementation. Effective coverage fell to 62% within 3 months of the behavior change communications and demand creation activities stopping. Delivery Model 2 was successful in raising awareness of the product (i.e., 90% message coverage), but effective coverage was low (i.e., 9.4%). Future programming efforts should use the health extension / microfinance / petty trader approach in rural settings and consider adapting this approach for use in urban and peri-urban settings. Ongoing behavior change communications and demand creation activities is likely to be essential to the continued success of such programming.
Brumbelow, Kelly; Georgakakos, Aris P.
2000-01-01
Past assessments of climate change on U.S. agriculture have mostly focused on changes in crop yield. Few studies have included the entire conterminous U.S., and few studies have assessed changing irrigation requirements. None have included the effects of changing soil moisture characteristics as determined by changing climatic forcing. This study assesses changes in irrigation requirements and crop yields for five crops in the areas of the U.S. where they have traditionally been grown. Physiologically-based crop models are used to incorporate inputs of climate, soils, agricultural management, and drought stress tolerance. Soil moisture values from a macroscale hydrologic model run under a future climate scenario are used to initialize soil moisture content at the beginning of each growing season. Historical crop yield data is used to calibrate model parameters and determine locally acceptable drought stress as a management parameter. Changes in irrigation demand and crop yield are assessed for both means and extremes by comparing results for atmospheric forcing close to the present climate with those for a future climate scenario. Assessments using the Canadian Center for Climate Modeling and Analysis General Circulation Model (CGCM1) indicate greater irrigation demands in the southern U.S. and decreased irrigation demands in the northern and western U.S. Crop yields typically increase except for winter wheat in the southern U.S. and corn. Variability in both irrigation demands and crop yields increases in most cases. Assessment results for the CGCM1 climate scenario are compared to those for the Hadley Centre for Climate Prediction and Research GCM (HadCM2) scenario for southwestern Georgia. The comparison shows significant differences in irrigation and yield trends, both in magnitude and direction. The differences reflect the high forecast uncertainty of current GCMs. Nonetheless, both GCMs indicate higher variability in future climatic forcing and, consequently, in the response of agricultural systems.