Flat-Top Sector Beams Using Only Array Element Phase Weighting: A Metaheuristic Optimization Approach

DTIC Science & Technology

2012-10-10

IrwIn D. OlIn Flat-Top Sector Beams Using Only Array Element Phase Weighting: A Metaheuristic Optimization Approach Sotera Defense Solutions, Inc...2012 Formal Report Flat-Top Sector Beams Using Only Array Element Phase Weighting: A Metaheuristic Optimization Approach Irwin D. Olin* Naval...Manuscript approved June 30, 2012. 1 FLAT-TOP SECTOR BEAMS USING ONLY ARRAY ELEMENT PHASE WEIGHTING: A METAHEURISTIC

Impact of climate change on electricity systems and markets

NASA Astrophysics Data System (ADS)

Chandramowli, Shankar N.

Climate change poses a serious threat to human welfare. There is now unequivocal scientific evidence that human actions are the primary cause of climate change. The principal climate forcing factor is the increasing accumulation of atmospheric carbon dioxide (CO2) due to combustion of fossil fuels for transportation and electricity generation. Generation of electricity account for nearly one-third of the greenhouse (GHG) emissions globally (on a CO2-equivalent basis). Any kind of economy-wide mitigation or adaptation effort to climate change must have a prominent focus on the electric power sector. I have developed a capacity expansion model for the power sector called LP-CEM (Linear Programming based Capacity Expansion Model). LP-CEM incorporates both the long-term climate change effects and the state/regional-level macroeconomic trends. This modeling framework is demonstrated for the electric power system in the Northeast region of United States. Some of the methodological advances introduced in this research are: the use of high-resolution temperature projections in a power sector capacity expansion model; the incorporation of changes in sectoral composition of electricity demand over time; the incorporation of the effects of climate change and variability on both the demand and supply-side of power sector using parameters estimated in the literature; and an inter-model coupling link with a macroeconomic model to account for price elasticity of demand and other effects on the broader macro-economy. LP-CEM-type models can be of use to state/regional level policymakers to plan for future mitigation and adaptation measures for the electric power sector. From the simulation runs, it is shown that scenarios with climate change effects and with high economic growth rates have resulted in higher capacity addition, optimal supply costs, wholesale/retail prices and total ratepayers' costs. LP-CEM is also adapted to model the implications of the proposed Clean Power Plan (Section 111 (d)) rules for the U.S. Northeast region. This dissertation applies an analytical model and an optimization model to investigate the implications of co-implementing an emission cap and an RPS policy for this region. A simplified analytical model of LP-CEM is specified and the first order optimality conditions are derived. The results from this analytical model are corroborated by running LP-CEM simulations under different carbon cap and RPS policy assumptions. A combination of these policies is shown to have a long-term beneficial effect for the final ratepayers in the region. This research conceptually explores the future implications of climate change and extreme weather events on the regional electricity market framework. The significant findings from this research and future policy considerations are discussed in the conclusion chapter.

GREENHOUSE GAS MITIGATION POTENTIAL IN U.S. FORESTRY AND AGRICULTURE

EPA Science Inventory

This report describes the FASOM-GHG model (Forestry and Agriculture Sector Optimization Model with Greenhouse Gases), the GHG mitigation scenarios for U.S. forestry and agriculture run through the FASOM-GHG model, and the results and insights that are generated. GHG mitigation po...

Development of an Empirical Model for Optimization of Machining Parameters to Minimize Power Consumption

NASA Astrophysics Data System (ADS)

Kant Garg, Girish; Garg, Suman; Sangwan, K. S.

2018-04-01

The manufacturing sector consumes huge energy demand and the machine tools used in this sector have very less energy efficiency. Selection of the optimum machining parameters for machine tools is significant for energy saving and for reduction of environmental emission. In this work an empirical model is developed to minimize the power consumption using response surface methodology. The experiments are performed on a lathe machine tool during the turning of AISI 6061 Aluminum with coated tungsten inserts. The relationship between the power consumption and machining parameters is adequately modeled. This model is used for formulation of minimum power consumption criterion as a function of optimal machining parameters using desirability function approach. The influence of machining parameters on the energy consumption has been found using the analysis of variance. The validation of the developed empirical model is proved using the confirmation experiments. The results indicate that the developed model is effective and has potential to be adopted by the industry for minimum power consumption of machine tools.

Models for residential-and commercial-sector energy conservation analysis: Applications, limitations, and future potential

NASA Astrophysics Data System (ADS)

Cole, H. E.; Fuller, R. E.

1980-09-01

Four of the major models used by DOE for energy conservation analyses in the residential and commercial building sectors are reviewed and critically analyzed to determine how these models can serve as tools for DOE and its Conservation Policy Office in evaluating and quantifying their policy and program requirements. The most effective role for each model in addressing future issues of buildings energy conservation policy and analysis is assessed. The four models covered are: Oak Ridge Residential Energy Model; Micro Analysis of Transfers to Households/Comprehensive Human Resources Data System (MATH/CHRDS) Model; Oak Ridge Commercial Energy Model; and Brookhaven Buildings Energy Conservation Optimization Model (BECOM).

Perfection Of Methods Of Mathematical Analysis For Increasing The Completeness Of Subsoil Development

NASA Astrophysics Data System (ADS)

Fokina, Mariya

2017-11-01

The economy of Russia is based around the mineral-raw material complex to the highest degree. The mining industry is a prioritized and important area. Given the high competitiveness of businesses in this sector, increasing the efficiency of completed work and manufactured products will become a central issue. Improvement of planning and management in this sector should be based on multivariant study and the optimization of planning decisions, the appraisal of their immediate and long-term results, taking the dynamic of economic development into account. All of this requires the use of economic mathematic models and methodsApplying an economic-mathematic model to determine optimal ore mine production capacity, we receive a figure of 4,712,000 tons. The production capacity of the Uchalinsky ore mine is 1560 thousand tons, and the Uzelginsky ore mine - 3650 thousand. Conducting a corresponding analysis of the production of OAO "Uchalinsky Gok", an optimal production plan was received: the optimal production of copper - 77961,4 rubles; the optimal production of zinc - 17975.66 rubles. The residual production volume of the two main ore mines of OAO "UGOK" is 160 million tons of ore.

Optimal security investments and extreme risk.

PubMed

Mohtadi, Hamid; Agiwal, Swati

2012-08-01

In the aftermath of 9/11, concern over security increased dramatically in both the public and the private sector. Yet, no clear algorithm exists to inform firms on the amount and the timing of security investments to mitigate the impact of catastrophic risks. The goal of this article is to devise an optimum investment strategy for firms to mitigate exposure to catastrophic risks, focusing on how much to invest and when to invest. The latter question addresses the issue of whether postponing a risk mitigating decision is an optimal strategy or not. Accordingly, we develop and estimate both a one-period model and a multiperiod model within the framework of extreme value theory (EVT). We calibrate these models using probability measures for catastrophic terrorism risks associated with attacks on the food sector. We then compare our findings with the purchase of catastrophic risk insurance. © 2012 Society for Risk Analysis.

Water resources planning in a strategic context: Linking the water sector to the national economy

NASA Astrophysics Data System (ADS)

Rogers, Peter; Hurst, Christopher; Harshadeep, Nagaraja

1993-07-01

In many parts of the developing world investment in water resources takes a large proportion of the available public investment funds. As the conflicts for funds between the water and other sectors become more severe, the traditional ways of analyzing and planning water investments has to move away from project-by-project (or even a river basin-by-river basin) approaches to include the relationships of water investments to other sectors and to overall national development policies. Current approaches to water resources investments are too narrow. There is a need for ways to expand the strategic thinking of water sector managers. This paper develops a water resources planning methodology with the primary objective of giving insights into the linking of water sector investments and macroeconomic policies. The model optimizes the present value of investments for water resources development, while embedding a macroeconomic model into the framework to allow for an examination of the interactions between water investments, the growth in the agricultural sector, and the performance of the overall economy. A case study of Bangladesh is presented which shows how strategic thinking could lead to widely differing implications for water investments than would conventional water resources systems planning models.

Systems modeling and analysis for Saudi Arabian electric power requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Al-Mohawes, N.A.

This thesis addresses the long-range generation planning problem in Saudi Arabia up to the year 2000. The first part presents various models for electric energy consumption in the residential and industrial sectors. These models can be used by the decision makers for the purposes of policy analysis, evaluation, and forecasting. Forecasts of energy in each sector are obtained from two different models for each sector. These models are based on two forecasting techniques: (1) Hybrid econometric/time series model. The idea of adaptive smoothing was utilized to produce forecasts under several scenarios. (2) Box-Jenkins time series technique. Box-Jenkins models and forecastsmore » are developed for the monthly number of electric consumers and the monthly energy consumption per consumer. The results obtained indicate that high energy consumption is expected during the coming two decades which necessitate serious energy assessment and optimization. Optimization of a mix of energy sources was considered using the group multiattribute utility (MAU) function. The results of MAU for three classes of decision makers (managerial, technical, and consumers) are developed through personal interactions. The computer package WASP was also used to develop a tentative optimum plan. According to this plan, four heavy-water nuclear power plants (800 MW) and four light-water nuclear power plants (1200 MW) have to be introduced by the year 2000 in addition to sixteen oil-fired power plants (400 MW) and nine gas turbines (100 MW).« less

Measuring energy efficiency in economics: Shadow value approach

NASA Astrophysics Data System (ADS)

Khademvatani, Asgar

For decades, academic scholars and policy makers have commonly applied a simple average measure, energy intensity, for studying energy efficiency. In contrast, we introduce a distinctive marginal measure called energy shadow value (SV) for modeling energy efficiency drawn on economic theory. This thesis demonstrates energy SV advantages, conceptually and empirically, over the average measure recognizing marginal technical energy efficiency and unveiling allocative energy efficiency (energy SV to energy price). Using a dual profit function, the study illustrates how treating energy as quasi-fixed factor called quasi-fixed approach offers modeling advantages and is appropriate in developing an explicit model for energy efficiency. We address fallacies and misleading results using average measure and demonstrate energy SV advantage in inter- and intra-country energy efficiency comparison. Energy efficiency dynamics and determination of efficient allocation of energy use are shown through factors impacting energy SV: capital, technology, and environmental obligations. To validate the energy SV, we applied a dual restricted cost model using KLEM dataset for the 35 US sectors stretching from 1958 to 2000 and selected a sample of the four sectors. Following the empirical results, predicted wedges between energy price and the SV growth indicate a misallocation of energy use in stone, clay and glass (SCG) and communications (Com) sectors with more evidence in the SCG compared to the Com sector, showing overshoot in energy use relative to optimal paths and cost increases from sub-optimal energy use. The results show that energy productivity is a measure of technical efficiency and is void of information on the economic efficiency of energy use. Decomposing energy SV reveals that energy, capital and technology played key roles in energy SV increases helping to consider and analyze policy implications of energy efficiency improvement. Applying the marginal measure, we also contributed to energy efficiency convergence analysis employing the delta-convergence and unconditional & conditional beta-convergence concepts, investigating economic energy efficiency differences across the four US sectors using panel data models. The results show that, in terms of technical and allocative energy efficiency, the energy-intensive sectors, SCG and textile mill products, tend to catch the energy extensive sectors, the Com and furniture & fixtures, being conditional on sector-specific characteristics. Conditional convergence results indicate that technology, capital and energy are crucial factors in determining energy efficiency differences across the US sectors, implying that environmental or energy policies, and technological changes should be industry specific across the US sectors. The main finding is that the marginal value measure conveys information on both technical and allocative energy efficiency and accounts for all costs and benefits of energy consumption including environmental and externality costs.

Using Satellite Data for Environmental Impact Analysis in Economic Growth: the Case of Mongolia

NASA Astrophysics Data System (ADS)

Tungalag, A.; Tsolmon, R.; Ochirkhuyag, L.; Oyunjargal, J.

2016-06-01

The Mongolian economy is based on the primary and secondary economic sectors of agriculture and industry. In addition, minerals and mining become a key sector of its economy. The main mining resources are gold, copper, coal, fluorspar and steel. However, the environment and green economy is one of the big problems among most of the countries and especially for countries like Mongolia where the mining is major part of economy; it is a number one problem. The research of the work tested how environmental elements effect to current Mongolian economic growth, which is growing economy because of mining sector. The study of economic growth but the starting point for any study of economic growth is the neoclassical growth model emphasizing the role of capital accumulation. The growth is analysed either in terms of models with exogenous saving rates (the Solow-Swan model), or models where consumption and hence savings are determined by optimizing individuals. These are the so-called optimal growth or Ramsey-Cass-Koopmans. The study extends the Solow model and the Ramsey-Cass-Koopmans model, including environmental elements which are satellite data determine to degraded land and vegetation value from 1995 to 2013. In contrast, we can see the degraded land area increases from 1995 (4856 m2) to 2013 (10478 m2) and vegetation value decrease at same time. A description of the methodology of the study conducted follows together with the data collected and econometric estimations and calibration with environmental elements.

Dynamically Evolving Sectors for Convective Weather Impact

NASA Technical Reports Server (NTRS)

Drew, Michael C.

2010-01-01

A new strategy for altering existing sector boundaries in response to blocking convective weather is presented. This method seeks to improve the reduced capacity of sectors directly affected by weather by moving boundaries in a direction that offers the greatest capacity improvement. The boundary deformations are shared by neighboring sectors within the region in a manner that preserves their shapes and sizes as much as possible. This reduces the controller workload involved with learning new sector designs. The algorithm that produces the altered sectors is based on a force-deflection mesh model that needs only nominal traffic patterns and the shape of the blocking weather for input. It does not require weather-affected traffic patterns that would have to be predicted by simulation. When compared to an existing optimal sector design method, the sectors produced by the new algorithm are more similar to the original sector shapes, resulting in sectors that may be more suitable for operational use because the change is not as drastic. Also, preliminary results show that this method produces sectors that can equitably distribute the workload of rerouted weather-affected traffic throughout the region where inclement weather is present. This is demonstrated by sector aircraft count distributions of simulated traffic in weather-affected regions.

Three Essays on Macroeconomics

NASA Astrophysics Data System (ADS)

Doda, Lider Baran

This dissertation consists of three independent essays in macroeconomics. The first essay studies the transition to a low carbon economy using an extension of the neoclassical growth model featuring endogenous energy efficiency, exhaustible energy and explicit climate-economy interaction. I derive the properties of the laissez faire equilibrium and compare them to the optimal allocations of a social planner who internalizes the climate change externality. Three main results emerge. First, the exhaustibility of energy generates strong market based incentives to improve energy efficiency and reduce CO 2 emissions without any government intervention. Second, the market and optimal allocations are substantially different suggesting a role for the government. Third, high and persistent taxes are required to implement the optimal allocations as a competitive equilibrium with taxes. The second essay focuses on coal fired power plants (CFPP) - one of the largest sources of CO2 emissions globally - and their generation efficiency using a macroeconomic model with an embedded CFPP sector. A key feature of the model is the endogenous choice of production technologies which differ in their energy efficiency. After establishing four empirical facts about the CFPP sector, I analyze the long run quantitative effects of energy taxes. Using the calibrated model, I find that sector-specific coal taxes have large effects on generation efficiency by inducing the use of more efficient technologies. Moreover, such taxes achieve large CO2 emissions reductions with relatively small effects on consumption and output. The final essay studies the procyclicality of fiscal policy in developing countries, which is a well-documented empirical observation seemingly at odds with Neoclassical and Keynesian policy prescriptions. I examine this issue by solving the optimal fiscal policy problem of a small open economy government when the interest rates on external debt are endogenous. Given an incomplete asset market, endogeneity is achieved by removing the government's ability to commit to repaying its external obligations. When calibrated to Argentina, the model generates procyclical government spending and countercyclical labor income tax rates. Simultaneously, the model's implications for key business cycle moments align well with the data.

Configuring Airspace Sectors with Approximate Dynamic Programming

NASA Technical Reports Server (NTRS)

Bloem, Michael; Gupta, Pramod

2010-01-01

In response to changing traffic and staffing conditions, supervisors dynamically configure airspace sectors by assigning them to control positions. A finite horizon airspace sector configuration problem models this supervisor decision. The problem is to select an airspace configuration at each time step while considering a workload cost, a reconfiguration cost, and a constraint on the number of control positions at each time step. Three algorithms for this problem are proposed and evaluated: a myopic heuristic, an exact dynamic programming algorithm, and a rollouts approximate dynamic programming algorithm. On problem instances from current operations with only dozens of possible configurations, an exact dynamic programming solution gives the optimal cost value. The rollouts algorithm achieves costs within 2% of optimal for these instances, on average. For larger problem instances that are representative of future operations and have thousands of possible configurations, excessive computation time prohibits the use of exact dynamic programming. On such problem instances, the rollouts algorithm reduces the cost achieved by the heuristic by more than 15% on average with an acceptable computation time.

Patent landscape of countermeasures against smallpox and estimation of grant attraction capability through patent landscape data.

PubMed

Mayburd, Anatoly L; Kedia, Govind; Evans, Haydn W; Kaslival, Pritesh C

2010-11-01

The study was concerned with countermeasures against a possible smallpox outbreak. In the process of assessment 18 landscaping sectors were defined and described, the advantages and drawbacks of the corresponding countermeasures being reviewed. The data of the previously published influenza landscape were revisited. The current economic climate of deficit cutting (austerity) also puts emphasis on the optimization of capital investment. We used the materials of the landscape to define and analyze metrics of capital placement optimization. Value score was obtained by fitting patent landscape internals to the sale price of individual patents. Success score was obtained as a product of a-priori parameters that measure likelihood of emergence of a marketable product in a technological sector. Both scores were combined in a qualitative metric. Our methodology defined weight as a product of the sector size by the success score. We hypothesized - based on the material of two landscapes- that a life cycle of a technology begins in IP space with a high patent quality low volume "bud" of low weight, reaches maximum weight and then weight falls again when the technology becomes outdated. The weight and the annual dynamic of weight can serve a measure of investment risk and return. In this report we modeled investment by issue of government grants or purchase of patents by government. In the smallpox landscape the number of patents purchased by government agencies was the highest in the sectors with the highest weight and the trend was confirmed by the count of NIH grants issued in support of the technological sectors. In the influenza landscape only grant issue count was statistically meaningful and the trend was also confirmed. To better fit the grant support levels, the weight expression was optimized by using training coefficients. We propose to use value scores for evaluation of individual patent publications/company portfolios and to use weights for assessment of technological sectors. Such a combination of automated analytical tools may lead to optimized allocation of capital and is intended to support the decisions taken by human experts.

Using a water-food-energy nexus approach for optimal irrigation management during drought events in Nebraska

NASA Astrophysics Data System (ADS)

Campana, P. E.; Zhang, J.; Yao, T.; Melton, F. S.; Yan, J.

2017-12-01

Climate change and drought have severe impacts on the agricultural sector affecting crop yields, water availability, and energy consumption for irrigation. Monitoring, assessing and mitigating the effects of climate change and drought on the agricultural and energy sectors are fundamental challenges that require investigation for water, food, and energy security issues. Using an integrated water-food-energy nexus approach, this study is developing a comprehensive drought management system through integration of real-time drought monitoring with real-time irrigation management. The spatially explicit model developed, GIS-OptiCE, can be used for simulation, multi-criteria optimization and generation of forecasts to support irrigation management. To demonstrate the value of the approach, the model has been applied to one major corn region in Nebraska to study the effects of the 2012 drought on crop yield and irrigation water/energy requirements as compared to a wet year such as 2009. The water-food-energy interrelationships evaluated show that significant water volumes and energy are required to halt the negative effects of drought on the crop yield. The multi-criteria optimization problem applied in this study indicates that the optimal solutions of irrigation do not necessarily correspond to those that would produce the maximum crop yields, depending on both water and economic constraints. In particular, crop pricing forecasts are extremely important to define the optimal irrigation management strategy. The model developed shows great potential in precision agriculture by providing near real-time data products including information on evapotranspiration, irrigation volumes, energy requirements, predicted crop growth, and nutrient requirements.

Assessment of the Electrification of the Road Transport Sector on Net System Emissions

NASA Astrophysics Data System (ADS)

Miller, James

As worldwide environmental consciousness grows, electric vehicles (EVs) are becoming more common and despite the incredible potential for emissions reduction, the net emissions of the power system supply side plus the transportation system are dependent on the generation matrix. Current EV charging patterns tend to correspond directly with the peak consumption hours and have the potential to increase demand sharply allowing for only a small penetration of Electric Vehicles. Using the National Household Travel Survey (NHTS) data a model is created for vehicle travel patterns using trip chaining. Charging schemes are modeled to include uncontrolled residential, uncontrolled residential/industrial charging, optimized charging and optimized charging with vehicle to grid discharging. A charging profile is then determined based upon the assumption that electric vehicles would directly replace a percentage of standard petroleum-fueled vehicles in a known system. Using the generation profile for the specified region, a unit commitment model is created to establish not only the generation dispatch, but also the net CO2 profile for variable EV penetrations and charging profiles. This model is then used to assess the impact of the electrification of the road transport sector on the system net emissions.

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.

maxwell brown | NREL

Science.gov Websites

Research Interests Optimization and modeling techniques Economic impacts of energy sector transformation . Transportation Research Record. Caron, J, S Cohen, J Reilly, M Brown. 2018. Exploring the Impacts of a National : Economic and GHG Impacts of a National Low Carbon Fuel Standard. Transportation Research Record: Journal of

Targeted intervention strategies to optimise diversion of BMW in the Dublin, Ireland region

DOE Office of Scientific and Technical Information (OSTI.GOV)

Purcell, M., E-mail: mary.purcell@cit.ie; Centre for Water Resources Research, School of Architecture, Landscape and Civil Engineering, University College Dublin, Newstead, Belfield, Dublin 4; Magette, W.L.

Highlights: > Previous research indicates that targeted strategies designed for specific areas should lead to improved diversion. > Survey responses and GIS model predictions from previous research were the basis for goal setting. > Then logic modelling and behavioural research were employed to develop site-specific management intervention strategies. > Waste management initiatives can be tailored to specific needs of areas rather than one size fits all means currently used. - Abstract: Urgent transformation is required in Ireland to divert biodegradable municipal waste (BMW) from landfill and prevent increases in overall waste generation. When BMW is optimally managed, it becomes amore » resource with value instead of an unwanted by-product requiring disposal. An analysis of survey responses from commercial and residential sectors for the Dublin region in previous research by the authors proved that attitudes towards and behaviour regarding municipal solid waste is spatially variable. This finding indicates that targeted intervention strategies designed for specific geographic areas should lead to improved diversion rates of BMW from landfill, a requirement of the Landfill Directive 1999/31/EC. In the research described in this paper, survey responses and GIS model predictions from previous research were the basis for goal setting, after which logic modelling and behavioural research were employed to develop site-specific waste management intervention strategies. The main strategies devised include (a) roll out of the Brown Bin (Organics) Collection and Community Workshops in Dun Laoghaire Rathdown, (b) initiation of a Community Composting Project in Dublin City (c) implementation of a Waste Promotion and Motivation Scheme in South Dublin (d) development and distribution of a Waste Booklet to promote waste reduction activities in Fingal (e) region wide distribution of a Waste Booklet to the commercial sector and (f) Greening Irish Pubs Initiative. Each of these strategies was devised after interviews with both the residential and commercial sectors to help make optimal waste management the norm for both sectors. Strategy (b), (e) and (f) are detailed in this paper. By integrating a human element into accepted waste management approaches, these strategies will make optimal waste behaviour easier to achieve. Ultimately this will help divert waste from landfill and improve waste management practice as a whole for the region. This method of devising targeted intervention strategies can be adapted for many other regions.« less

ReEDS-Mexico: A Capacity Expansion Model of the Mexican Power System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ho, Jonathan L; Cole, Wesley J; Spyrou, Evangelia

This report documents the ReEDS-Mexico capacity expansion model, which is an extension of the ReEDS model to the Mexican power system. In recent years Mexico’s power sector has undergone considerable reform that has significant potential to impact the future electricity mix (Alpizar–Castro and Rodríguez–Monroy 2016). Day-ahead and real-time trading in Mexico’s power markets opened in early 2016. In addition to this reform, Mexico is striving to ensure that 35% of its electricity is generated from clean energy sources by 2024, 40% by 2035, and 50% by 2050 (Presidencia de la República 2016). These rapid changes in both the market andmore » the generation mix create a need for robust tools that can help electricity sector stakeholders make informed decisions. The purpose of this report is to document the extension of the National Renewable Energy Laboratory’s (NREL’s) Regional Energy Deployment System (ReEDS) model (Eurek et al. 2016) to cover the Mexico power system. This extension, which we will refer to throughout this paper as ReEDS-Mexico, provides a model of the Mexico power sector using a system-wide, least-cost optimization framework.« less

Using simulation and data envelopment analysis to evaluate Iraqi regions in producing strategic crops

NASA Astrophysics Data System (ADS)

Chaloob, Ibrahim Z.; Ramli, Razamin; Nawawi, Mohd Kamal Mohd

2014-12-01

Productivity of the agriculture sector in Iraq has yet to reach an acceptable level. In this paper, we introduce a practical method to help manage Iraqi agriculture sector to control resources and increase production to meet the modern century requirements of good crops. These important resources are identified as water, fertilizer, natural fertilizer, pesticides and labour. The current agricultural patterns in Iraq affect the strategic crops cultivation in the country and lessen agricultural production to some life-threatening limits. Data Envelopment Analysis (DEA), which is a non-parametric tool, is proposed to identify solutions that can maximize farmers' net benefit making an optimal use of the five resources. This model also improves optimal mix of the resources. In reference to the production of each one of the three strategic crops in Iraq, the DEA model is used to find the efficiency of one region among four others in its agriculture sector, with the main problem being the constraint in the number of lands available in the situation. Hence, the simulation technique is used to generate additional regions to the four main regions adopted. This is to resolve the constriction of DEA when the decision making unit is less than the number of variables (outputs and inputs). The result is expected to show the efficiency of each of the evaluated region.

Setting capitation payments in markets for health services

PubMed Central

Ellis, Randall P.; McGuire, Thomas G.

1987-01-01

Health maintenance organizations (HMO's) are paid a capitated amount for enrolled Medicare beneficiaries that is 95 percent of what these enrollees would be expected to cost in the fee-for-service sector. However, it appears that HMO enrollees are less costly than other Medicare beneficiaries. With a simulation model, we demonstrate that with a 95-percent pricing rule, any significant degree of biased selection leads to increased cost to the payer, even when HMO's are cost effective compared with the fee-for-service sector. Optimal pricing percentages from the point of view of cost minimization are considerably less than 95 percent. PMID:10312188

Assembly line performance and modeling

NASA Astrophysics Data System (ADS)

Rane, Arun B.; Sunnapwar, Vivek K.

2017-09-01

Automobile sector forms the backbone of manufacturing sector. Vehicle assembly line is important section in automobile plant where repetitive tasks are performed one after another at different workstations. In this thesis, a methodology is proposed to reduce cycle time and time loss due to important factors like equipment failure, shortage of inventory, absenteeism, set-up, material handling, rejection and fatigue to improve output within given cost constraints. Various relationships between these factors, corresponding cost and output are established by scientific approach. This methodology is validated in three different vehicle assembly plants. Proposed methodology may help practitioners to optimize the assembly line using lean techniques.

Mathematical model of information process of protection of the social sector

NASA Astrophysics Data System (ADS)

Novikov, D. A.; Tsarkova, E. G.; Dubrovin, A. S.; Soloviev, A. S.

2018-03-01

In work the mathematical model of information protection of society against distribution of extremist moods by means of impact on mass consciousness of information placed in media is investigated. Internal and external channels on which there is a dissemination of information are designated. The problem of optimization consisting in search of the optimum strategy allowing to use most effectively media for dissemination of antiterrorist information with the minimum financial expenses is solved. The algorithm of a numerical method of the solution of a problem of optimization is constructed and also the analysis of results of a computing experiment is carried out.

Optimization of carbon mitigation paths in the power sector of Shenzhen, China

NASA Astrophysics Data System (ADS)

Li, Xin; Hu, Guangxiao; Duan, Ying; Ji, Junping

2017-08-01

This paper studied the carbon mitigation paths of the power sector in Shenzhen, China from a supply-side perspective. We investigated the carbon mitigation potentials and investments of seventeen mitigation technologies in the power sector, and employed a linear programming method to optimize the mitigation paths. The results show that: 1) The total carbon mitigation potential is 5.95 MtCO2 in 2020 in which the adjustment of power supply structure, technical improvements of existing coal- and gas-fired power plant account for 87.5%,6.5% and 6.0%, respectively. 2) In the optimal path, the avoided carbon dioxide to meet the local government’s mitigation goal in power sector is 1.26 MtCO2.The adjustment of power supply structure and technical improvement of the coal-fired power plants are the driving factors of carbon mitigation, with contributions to total carbon mitigation are 72.6% and 27.4%, respectively.

Trading the Economic Value of Unsatisfied Municipal Water Demand

NASA Astrophysics Data System (ADS)

Telfah, Dua'a. B.; Minciardi, Riccardo; Roth, Giorgio

2018-06-01

Modelling and optimization techniques for water resources allocation are proposed to identify the economic value of the unsatisfied municipal water demand against demands emerging from other sectors. While this is always an important step in integrated water resource management perspective, it became crucial for water scarce Countries. In fact, since the competition for the resource is high, they are in crucial need to trade values which will help them in satisfying their policies and needs. In this framework, hydro-economic, social equity and environmental constraints need to be satisfied. In the present study, a hydro-economic decision model based on optimization schemes has been developed for water resources allocation, that enable the evaluation of the economic cost of a deficiency in fulfilling the municipal demand. Moreover, the model enables efficient water resources management, satisfying the demand and proposing additional water resources options. The formulated model is designed to maximize the demand satisfaction and minimize water production cost subject to system priorities, preferences and constraints. The demand priorities are defined based on the effect of demand dissatisfaction, while hydrogeological and physical characteristics of the resources are embedded as constraints in the optimization problem. The application to the City of Amman is presented. Amman is the Capital City of the Hashemite Kingdom of Jordan, a Country located in the south-eastern area of the Mediterranean, on the East Bank of the Jordan River. The main challenge for Jordan, that threat the development and prosperity of all sectors, is the extreme water scarcity. In fact, Jordan is classified as semi-arid to arid region with limited financial resources and unprecedented population growth. While the easy solution directly goes to the simple but expensive approach to cover the demand, case study results show that the proposed model plays a major role in providing directions to decision makers to orient their policies and strategies in order to achieve sustainability of scarce water resources, satisfaction of the minimum required demand as well as financial sustainability. In addition, results map out national needs and priorities that are crucial in understanding and controlling the complexity of Jordan's water sector, mainly for the city of Amman.

Prevention through Design Adoption Readiness Model (PtD ARM): An integrated conceptual model.

PubMed

Weidman, Justin; Dickerson, Deborah E; Koebel, Charles T

2015-01-01

Prevention through Design (PtD), eliminating hazards at the design-stage of tools and systems, is the optimal method of mitigating occupational health and safety risks. A recent National Institute of Safety and Health initiative has established a goal to increase adoption of PtD innovation in industry. The construction industry has traditionally lagged behind other sectors in the adoption of innovation, in general; and of safety and health prevention innovation, in particular. Therefore, as a first step toward improving adoption trends in this sector, a conceptual model was developed to describe the parameters and causal relationships that influence and predict construction stakeholder "adoption readiness" for PtD technology innovation. This model was built upon three well-established theoretical frameworks: the Health Belief Model, the Diffusion of Innovation Model, and the Technology Acceptance Model. Earp and Ennett's model development methodology was employed to build a depiction of the key constructs and directionality and magnitude of relationships among them. Key constructs were identified from the literature associated with the three theoretical frameworks, with special emphasis given to studies related to construction or OHS technology adoption. A conceptual model is presented. Recommendations for future research are described and include confirmatory structural equation modeling of model parameters and relationships, additional descriptive investigation of barriers to adoption in some trade sectors, and design and evaluation of an intervention strategy.

Cross-sectoral optimization and visualization of transformation processes in urban water infrastructures in rural areas.

PubMed

Baron, S; Kaufmann Alves, I; Schmitt, T G; Schöffel, S; Schwank, J

2015-01-01

Predicted demographic, climatic and socio-economic changes will require adaptations of existing water supply and wastewater disposal systems. Especially in rural areas, these new challenges will affect the functionality of the present systems. This paper presents a joint interdisciplinary research project with the objective of developing an innovative software-based optimization and decision support system for the implementation of long-term transformations of existing infrastructures of water supply, wastewater and energy. The concept of the decision support and optimization tool is described and visualization methods for the presentation of results are illustrated. The model is tested in a rural case study region in the Southwest of Germany. A transformation strategy for a decentralized wastewater treatment concept and its visualization are presented for a model village.

Optimizing cutting conditions on sustainable machining of aluminum alloy to minimize power consumption

NASA Astrophysics Data System (ADS)

Nur, Rusdi; Suyuti, Muhammad Arsyad; Susanto, Tri Agus

2017-06-01

Aluminum is widely utilized in the industrial sector. There are several advantages of aluminum, i.e. good flexibility and formability, high corrosion resistance and electrical conductivity, and high heat. Despite of these characteristics, however, pure aluminum is rarely used because of its lacks of strength. Thus, most of the aluminum used in the industrial sectors was in the form of alloy form. Sustainable machining can be considered to link with the transformation of input materials and energy/power demand into finished goods. Machining processes are responsible for environmental effects accepting to their power consumption. The cutting conditions have been optimized to minimize the cutting power, which is the power consumed for cutting. This paper presents an experimental study of sustainable machining of Al-11%Si base alloy that was operated without any cooling system to assess the capacity in reducing power consumption. The cutting force was measured and the cutting power was calculated. Both of cutting force and cutting power were analyzed and modeled by using the central composite design (CCD). The result of this study indicated that the cutting speed has an effect on machining performance and that optimum cutting conditions have to be determined, while sustainable machining can be followed in terms of minimizing power consumption and cutting force. The model developed from this study can be used for evaluation process and optimization to determine optimal cutting conditions for the performance of the whole process.

Artificial intelligent techniques for optimizing water allocation in a reservoir watershed

NASA Astrophysics Data System (ADS)

Chang, Fi-John; Chang, Li-Chiu; Wang, Yu-Chung

2014-05-01

This study proposes a systematical water allocation scheme that integrates system analysis with artificial intelligence techniques for reservoir operation in consideration of the great uncertainty upon hydrometeorology for mitigating droughts impacts on public and irrigation sectors. The AI techniques mainly include a genetic algorithm and adaptive-network based fuzzy inference system (ANFIS). We first derive evaluation diagrams through systematic interactive evaluations on long-term hydrological data to provide a clear simulation perspective of all possible drought conditions tagged with their corresponding water shortages; then search the optimal reservoir operating histogram using genetic algorithm (GA) based on given demands and hydrological conditions that can be recognized as the optimal base of input-output training patterns for modelling; and finally build a suitable water allocation scheme through constructing an adaptive neuro-fuzzy inference system (ANFIS) model with a learning of the mechanism between designed inputs (water discount rates and hydrological conditions) and outputs (two scenarios: simulated and optimized water deficiency levels). The effectiveness of the proposed approach is tested on the operation of the Shihmen Reservoir in northern Taiwan for the first paddy crop in the study area to assess the water allocation mechanism during drought periods. We demonstrate that the proposed water allocation scheme significantly and substantially avails water managers of reliably determining a suitable discount rate on water supply for both irrigation and public sectors, and thus can reduce the drought risk and the compensation amount induced by making restrictions on agricultural use water.

Urinary bladder cancer T-staging from T2-weighted MR images using an optimal biomarker approach

NASA Astrophysics Data System (ADS)

Wang, Chuang; Udupa, Jayaram K.; Tong, Yubing; Chen, Jerry; Venigalla, Sriram; Odhner, Dewey; Guzzo, Thomas J.; Christodouleas, John; Torigian, Drew A.

2018-02-01

Magnetic resonance imaging (MRI) is often used in clinical practice to stage patients with bladder cancer to help plan treatment. However, qualitative assessment of MR images is prone to inaccuracies, adversely affecting patient outcomes. In this paper, T2-weighted MR image-based quantitative features were extracted from the bladder wall in 65 patients with bladder cancer to classify them into two primary tumor (T) stage groups: group 1 - T stage < T2, with primary tumor locally confined to the bladder, and group 2 - T stage < T2, with primary tumor locally extending beyond the bladder. The bladder was divided into 8 sectors in the axial plane, where each sector has a corresponding reference standard T stage that is based on expert radiology qualitative MR image review and histopathologic results. The performance of the classification for correct assignment of T stage grouping was then evaluated at both the patient level and the sector level. Each bladder sector was divided into 3 shells (inner, middle, and outer), and 15,834 features including intensity features and texture features from local binary pattern and gray-level co-occurrence matrix were extracted from the 3 shells of each sector. An optimal feature set was selected from all features using an optimal biomarker approach. Nine optimal biomarker features were derived based on texture properties from the middle shell, with an area under the ROC curve of AUC value at the sector and patient level of 0.813 and 0.806, respectively.

A Novel Biobjective Risk-Based Model for Stochastic Air Traffic Network Flow Optimization Problem.

PubMed

Cai, Kaiquan; Jia, Yaoguang; Zhu, Yanbo; Xiao, Mingming

2015-01-01

Network-wide air traffic flow management (ATFM) is an effective way to alleviate demand-capacity imbalances globally and thereafter reduce airspace congestion and flight delays. The conventional ATFM models assume the capacities of airports or airspace sectors are all predetermined. However, the capacity uncertainties due to the dynamics of convective weather may make the deterministic ATFM measures impractical. This paper investigates the stochastic air traffic network flow optimization (SATNFO) problem, which is formulated as a weighted biobjective 0-1 integer programming model. In order to evaluate the effect of capacity uncertainties on ATFM, the operational risk is modeled via probabilistic risk assessment and introduced as an extra objective in SATNFO problem. Computation experiments using real-world air traffic network data associated with simulated weather data show that presented model has far less constraints compared to stochastic model with nonanticipative constraints, which means our proposed model reduces the computation complexity.

Three Dimensional Sector Design with Optimal Number of Sectors

NASA Technical Reports Server (NTRS)

Xue, Min

2010-01-01

In the national airspace system, sectors get overloaded due to high traffic demand and inefficient airspace designs. Overloads can be eliminated in some cases by redesigning sector boundaries. This paper extends the Voronoi-based sector design method by automatically selecting the number of sectors, allowing three-dimensional partitions, and enforcing traffic pattern conformance. The method was used to design sectors at Fort-Worth and Indianapolis centers for current traffic scenarios. Results show that new designs can eliminate overloaded sectors, although not in all cases, reduce the number of necessary sectors, and conform to major traffic patterns. Overall, the new methodology produces enhanced and efficient sector designs.

Review of optimization techniques of polygeneration systems for building applications

NASA Astrophysics Data System (ADS)

Y, Rong A.; Y, Su; R, Lahdelma

2016-08-01

Polygeneration means simultaneous production of two or more energy products in a single integrated process. Polygeneration is an energy-efficient technology and plays an important role in transition into future low-carbon energy systems. It can find wide applications in utilities, different types of industrial sectors and building sectors. This paper mainly focus on polygeneration applications in building sectors. The scales of polygeneration systems in building sectors range from the micro-level for a single home building to the large- level for residential districts. Also the development of polygeneration microgrid is related to building applications. The paper aims at giving a comprehensive review for optimization techniques for designing, synthesizing and operating different types of polygeneration systems for building applications.

Greenhouse Gas Mitigation Options in ISEEM Global Energy Model: 2010-2050 Scenario Analysis for Least-Cost Carbon Reduction in Iron and Steel Sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Xu, Tengfang; Sathaye, Jayant

The goal of the modeling work carried out in this project was to quantify long-term scenarios for the future emission reduction potentials in the iron and steel sector. The main focus of the project is to examine the impacts of carbon reduction options in the U.S. iron and steel sector under a set of selected scenarios. In order to advance the understanding of carbon emission reduction potential on the national and global scales, and to evaluate the regional impacts of potential U.S. mitigation strategies (e.g., commodity and carbon trading), we also included and examined the carbon reduction scenarios in China’smore » and India’s iron and steel sectors in this project. For this purpose, a new bottom-up energy modeling framework, the Industrial Sector Energy Efficiency Modeling (ISEEM), (Karali et al. 2012) was used to provide detailed annual projections starting from 2010 through 2050. We used the ISEEM modeling framework to carry out detailed analysis, on a country-by-country basis, for the U.S., China’s, and India’s iron and steel sectors. The ISEEM model applicable to iron and steel section, called ISEEM-IS, is developed to estimate and evaluate carbon emissions scenarios under several alternative mitigation options - including policies (e.g., carbon caps), commodity trading, and carbon trading. The projections will help us to better understand emission reduction potentials with technological and economic implications. The database for input of ISEEM-IS model consists of data and information compiled from various resources such as World Steel Association (WSA), the U.S. Geological Survey (USGS), China Steel Year Books, India Bureau of Mines (IBM), Energy Information Administration (EIA), and recent LBNL studies on bottom-up techno-economic analysis of energy efficiency measures in the iron and steel sector of the U.S., China, and India, including long-term steel production in China. In the ISEEM-IS model, production technology and manufacturing details are represented, in addition to the extensive data compiled from recent studies on bottom-up representation of efficiency measures for the sector. We also defined various mitigation scenarios including long-term production trends to project country-specific production, energy use, trading, carbon emissions, and costs of mitigation. Such analyses can provide useful information to assist policy-makers when considering and shaping future emissions mitigation strategies and policies. The technical objective is to analyze the costs of production and CO 2 emission reduction in the U.S, China, and India’s iron and steel sectors under different emission reduction scenarios, using the ISEEM-IS as a cost optimization model. The scenarios included in this project correspond to various CO 2 emission reduction targets for the iron and steel sector under different strategies such as simple CO 2 emission caps (e.g., specific reduction goals), emission reduction via commodity trading, and emission reduction via carbon trading.« less

Optimising The Available Scarce Water Resources At European Scale In A Modelling Environment: Results And Challenges

NASA Astrophysics Data System (ADS)

de Roo, Ad; Burek, Peter; Gentile, Alessandro; Udias, Angel; Bouraoui, Faycal

2013-04-01

As a next step to European drought monitoring and forecasting, which is covered in the European Drought Observatory (EDO) activity of JRC, a modeling environment has been developed to assess optimum measures to match water availability and water demand, while keeping ecological, water quality and flood risk aspects also into account. A multi-modelling environment has been developed to assess combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. These simulations have been carried out to assess the effects of those measures on several hydro-chemical indicators, such as the Water Exploitation Index, Environmental Flow indicators, low-flow frequency, N and P concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the industrial sector, and the public sector. Also, potential flood damage of a 100-year return period flood has been used as an indicator. This modeling environment consists of linking the agricultural CAPRI model, the land use LUMP model, the water quantity LISFLOOD model, the water quality EPIC model, the combined water quantity/quality and hydro-economic LISQUAL model and a multi-criteria optimization routine. A python interface platform (IMO) has been built to link the different models. The work was carried out in the framework of a new European Commission policy document "Blueprint to Safeguard Europe's Water Resources", COM(2012)673), launched in November 2012. Simulations have been carried out to assess the effects of water retention measures, water savings measures, and nutrient reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index, Environmental Flow indicators, N and P concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the manufacturing-industry sector, the energy-production sector and the domestic sector. Also, potential flood damage of a 100-year return period flood has been used as an indicator. The study has shown that technically this modelling software environment can deliver optimum scenario combinations of packages of measures that improve various water quantity and water quality indicators, but that additional work is needed before final conclusions can be made using the tool. Further work is necessary, especially in the economic loss estimations, the water prices and price-elasticity, as well as the implementation and maintenance costs of individual scenarios. First results and challenges will be presented and discussed.

Optimization of educational paths for higher education

NASA Astrophysics Data System (ADS)

Tarasyev, Alexandr A.; Agarkov, Gavriil; Medvedev, Aleksandr

2017-11-01

In our research, we combine the theory of economic behavior and the methodology of increasing efficiency of the human capital to estimate the optimal educational paths. We provide an optimization model for higher education process to analyze possible educational paths for each rational individual. The preferences of each rational individual are compared to the best economically possible educational path. The main factor of the individual choice, which is formed by the formation of optimal educational path, deals with higher salaries level in the chosen economic sector after graduation. Another factor that influences on the economic profit is the reduction of educational costs or the possibility of the budget support for the student. The main outcome of this research consists in correction of the governmental policy of investment in human capital based on the results of educational paths optimal control.

Uncertainty Analysis and Order-by-Order Optimization of Chiral Nuclear Interactions

DOE PAGES

Carlsson, Boris; Forssen, Christian; Fahlin Strömberg, D.; ...

2016-02-24

Chiral effective field theory ( ΧEFT) provides a systematic approach to describe low-energy nuclear forces. Moreover, EFT is able to provide well-founded estimates of statistical and systematic uncertainties | although this unique advantage has not yet been fully exploited. We ll this gap by performing an optimization and statistical analysis of all the low-energy constants (LECs) up to next-to-next-to-leading order. Our optimization protocol corresponds to a simultaneous t to scattering and bound-state observables in the pion-nucleon, nucleon-nucleon, and few-nucleon sectors, thereby utilizing the full model capabilities of EFT. Finally, we study the effect on other observables by demonstrating forward-error-propagation methodsmore » that can easily be adopted by future works. We employ mathematical optimization and implement automatic differentiation to attain e cient and machine-precise first- and second-order derivatives of the objective function with respect to the LECs. This is also vital for the regression analysis. We use power-counting arguments to estimate the systematic uncertainty that is inherent to EFT and we construct chiral interactions at different orders with quantified uncertainties. Statistical error propagation is compared with Monte Carlo sampling showing that statistical errors are in general small compared to systematic ones. In conclusion, we find that a simultaneous t to different sets of data is critical to (i) identify the optimal set of LECs, (ii) capture all relevant correlations, (iii) reduce the statistical uncertainty, and (iv) attain order-by-order convergence in EFT. Furthermore, certain systematic uncertainties in the few-nucleon sector are shown to get substantially magnified in the many-body sector; in particlar when varying the cutoff in the chiral potentials. The methodology and results presented in this Paper open a new frontier for uncertainty quantification in ab initio nuclear theory.« less

Forecasting of municipal solid waste quantity in a developing country using multivariate grey models.

PubMed

Intharathirat, Rotchana; Abdul Salam, P; Kumar, S; Untong, Akarapong

2015-05-01

In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435-44,994 tonnes per day in 2013 to 55,177-56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period. Copyright © 2015 Elsevier Ltd. All rights reserved.

A multi-period optimization model for energy planning with CO(2) emission consideration.

PubMed

Mirzaesmaeeli, H; Elkamel, A; Douglas, P L; Croiset, E; Gupta, M

2010-05-01

A novel deterministic multi-period mixed-integer linear programming (MILP) model for the power generation planning of electric systems is described and evaluated in this paper. The model is developed with the objective of determining the optimal mix of energy supply sources and pollutant mitigation options that meet a specified electricity demand and CO(2) emission targets at minimum cost. Several time-dependent parameters are included in the model formulation; they include forecasted energy demand, fuel price variability, construction lead time, conservation initiatives, and increase in fixed operational and maintenance costs over time. The developed model is applied to two case studies. The objective of the case studies is to examine the economical, structural, and environmental effects that would result if the electricity sector was required to reduce its CO(2) emissions to a specified limit. Copyright 2009 Elsevier Ltd. All rights reserved.

Assessing CO2 Mitigation Options Utilizing Detailed Electricity Characteristics and Including Renewable Generation

NASA Astrophysics Data System (ADS)

Bensaida, K.; Alie, Colin; Elkamel, A.; Almansoori, A.

2017-08-01

This paper presents a novel techno-economic optimization model for assessing the effectiveness of CO2 mitigation options for the electricity generation sub-sector that includes renewable energy generation. The optimization problem was formulated as a MINLP model using the GAMS modeling system. The model seeks the minimization of the power generation costs under CO2 emission constraints by dispatching power from low CO2 emission-intensity units. The model considers the detailed operation of the electricity system to effectively assess the performance of GHG mitigation strategies and integrates load balancing, carbon capture and carbon taxes as methods for reducing CO2 emissions. Two case studies are discussed to analyze the benefits and challenges of the CO2 reduction methods in the electricity system. The proposed mitigations options would not only benefit the environment, but they will as well improve the marginal cost of producing energy which represents an advantage for stakeholders.

Spatio-temporal modelling of electrical supply systems to optimize the site planning process for the "power to mobility" technology

NASA Astrophysics Data System (ADS)

Karl, Florian; Zink, Roland

2016-04-01

The transformation of the energy sector towards decentralized renewable energies (RE) requires also storage systems to ensure security of supply. The new "Power to Mobility" (PtM) technology is one potential solution to use electrical overproduction to produce methane for i.e. gas vehicles. Motivated by these fact, the paper presents a methodology for a GIS-based temporal modelling of the power grid, to optimize the site planning process for the new PtM-technology. The modelling approach is based on a combination of the software QuantumGIS for the geographical and topological energy supply structure and OpenDSS for the net modelling. For a case study (work in progress) of the city of Straubing (Lower Bavaria) the parameters of the model are quantified. The presentation will discuss the methodology as well as the first results with a view to the application on a regional scale.

Photochemical grid model implementation and application of ...

EPA Pesticide Factsheets

For the purposes of developing optimal emissions control strategies, efficient approaches are needed to identify the major sources or groups of sources that contribute to elevated ozone (O3) concentrations. Source-based apportionment techniques implemented in photochemical grid models track sources through the physical and chemical processes important to the formation and transport of air pollutants. Photochemical model source apportionment has been used to track source impacts of specific sources, groups of sources (sectors), sources in specific geographic areas, and stratospheric and lateral boundary inflow on O3. The implementation and application of a source apportionment technique for O3 and its precursors, nitrogen oxides (NOx) and volatile organic compounds (VOCs), for the Community Multiscale Air Quality (CMAQ) model are described here. The Integrated Source Apportionment Method (ISAM) O3 approach is a hybrid of source apportionment and source sensitivity in that O3 production is attributed to precursor sources based on O3 formation regime (e.g., for a NOx-sensitive regime, O3 is apportioned to participating NOx emissions). This implementation is illustrated by tracking multiple emissions source sectors and lateral boundary inflow. NOx, VOC, and O3 attribution to tracked sectors in the application are consistent with spatial and temporal patterns of precursor emissions. The O3 ISAM implementation is further evaluated through comparisons of apportioned am

What could infant and young child nutrition learn from sweatshops?

PubMed Central

2011-01-01

Background Adequate infant and young child nutrition demands high rates of breastfeeding and good access to nutrient rich complementary foods, requiring public sector action to promote breastfeeding and home based complementary feeding, and private sector action to refrain from undermining breastfeeding and to provide affordable, nutrient rich complementary foods. Unfortunately, due to a lack of trust, the public and private sectors, from both the North and the South, do not work well together in achieving optimal infant and young child nutrition. Discussion As the current debate in infant and young child nutrition is reminiscent of the "sweatshop" debate fifteen years ago, we argue that lessons from the sweatshops debate regarding cooperation between public and private sectors - and specific organizational experiences such as the Ethical Trading Initiative in which companies, trade unions, and civil society organizations work together to enhance implementation of labour standards and address alleged allegations - could serve as a model for improving cooperation and trust between public, civil society and private groups, and ultimately health, in infant and young child nutrition. Summary Lessons from the sweatshops debate could serve as a model to promote cooperation and trust between public and private groups, such that they learn to work together towards their common goal of improving infant and young child nutrition. PMID:21545745

What could infant and young child nutrition learn from sweatshops?

PubMed

Singer, Peter A; Ansett, Sean; Sagoe-Moses, Isabella

2011-05-05

Adequate infant and young child nutrition demands high rates of breastfeeding and good access to nutrient rich complementary foods, requiring public sector action to promote breastfeeding and home based complementary feeding, and private sector action to refrain from undermining breastfeeding and to provide affordable, nutrient rich complementary foods. Unfortunately, due to a lack of trust, the public and private sectors, from both the North and the South, do not work well together in achieving optimal infant and young child nutrition. As the current debate in infant and young child nutrition is reminiscent of the "sweatshop" debate fifteen years ago, we argue that lessons from the sweatshops debate regarding cooperation between public and private sectors - and specific organizational experiences such as the Ethical Trading Initiative in which companies, trade unions, and civil society organizations work together to enhance implementation of labour standards and address alleged allegations - could serve as a model for improving cooperation and trust between public, civil society and private groups, and ultimately health, in infant and young child nutrition. Lessons from the sweatshops debate could serve as a model to promote cooperation and trust between public and private groups, such that they learn to work together towards their common goal of improving infant and young child nutrition.

Smart Transportation CO2 Emission Reduction Strategies

NASA Astrophysics Data System (ADS)

Tarulescu, S.; Tarulescu, R.; Soica, A.; Leahu, C. I.

2017-10-01

Transport represents the sector with the fastest growing greenhouse gas emissions around the world. The main global objective is to reduce energy usage and associated greenhouse gas emissions from the transportation sector. For this study it was analyzed the road transportation system from Brasov Metropolitan area. The study was made for the transportation route that connects Ghimbav city to the main surrounding objectives. In this study ware considered four optimization measures: vehicle fleet renewal; building the detour belt for the city; road increasing the average travel speed; making bicycle lanes; and implementing an urban public transport system for Ghimbav. For each measure it was used a mathematical model to calculate the energy consumption and carbon emissions from the road transportation sector. After all four measures was analyzed is calculated the general energy consumption and CO2 reduction if this are applied from year 2017 to 2020.

Development of a coupled model of a distributed hydrological model and a rice growth model for optimizing irrigation schedule

NASA Astrophysics Data System (ADS)

Tsujimoto, Kumiko; Homma, Koki; Koike, Toshio; Ohta, Tetsu

2013-04-01

A coupled model of a distributed hydrological model and a rice growth model was developed in this study. The distributed hydrological model used in this study is the Water and Energy Budget-based Distributed Hydrological Model (WEB-DHM) developed by Wang et al. (2009). This model includes a modified SiB2 (Simple Biosphere Model, Sellers et al., 1996) and the Geomorphology-Based Hydrological Model (GBHM) and thus it can physically calculate both water and energy fluxes. The rice growth model used in this study is the Simulation Model for Rice-Weather relations (SIMRIW) - rainfed developed by Homma et al. (2009). This is an updated version of the original SIMRIW (Horie et al., 1987) and can calculate rice growth by considering the yield reduction due to water stress. The purpose of the coupling is the integration of hydrology and crop science to develop a tool to support decision making 1) for determining the necessary agricultural water resources and 2) for allocating limited water resources to various sectors. The efficient water use and optimal water allocation in the agricultural sector are necessary to balance supply and demand of limited water resources. In addition, variations in available soil moisture are the main reasons of variations in rice yield. In our model, soil moisture and the Leaf Area Index (LAI) are calculated inside SIMRIW-rainfed so that these variables can be simulated dynamically and more precisely based on the rice than the more general calculations is the original WEB-DHM. At the same time by coupling SIMRIW-rainfed with WEB-DHM, lateral flow of soil water, increases in soil moisture and reduction of river discharge due to the irrigation, and its effects on the rice growth can be calculated. Agricultural information such as planting date, rice cultivar, fertilization amount are given in a fully distributed manner. The coupled model was validated using LAI and soil moisture in a small basin in western Cambodia (Sangker River Basin). This basin is mostly rainfed paddy so that irrigation scheme was firstly switched off. Several simulations with varying irrigation scheme were performed to determine the optimal irrigation schedule in this basin.

How Conjunctive Use of Surface and Ground Water could Increase Resiliency in US?

NASA Astrophysics Data System (ADS)

Josset, L.; Rising, J. A.; Russo, T. A.; Troy, T. J.; Lall, U.; Allaire, M.

2016-12-01

Optimized management practices are crucial to ensuring water availability in the future. However this presents a tremendous challenge due to the many functions of water: water is not only central for our survival as drinking water or for irrigation, but it is also valued for industrial and recreational use. Sources of water meeting these needs range from rain water harvesting to reservoirs, water reuse, groundwater abstraction and desalination. A global conjunctive management approach is thus necessary to develop sustainable practices as all sectors are strongly coupled. Policy-makers and researchers have identified pluralism in water sources as a key solution to reach water security. We propose a novel approach to sustainable water management that accounts for multiple sources of water in an integrated manner. We formulate this challenge as an optimization problem where the choice of water sources is driven both by the availability of the sources and their relative cost. The results determine the optimal operational decisions for each sources (e.g. reservoirs releases, surface water withdrawals, groundwater abstraction and/or desalination water use) at each time step for a given time horizon. The physical surface and ground water systems are simulated inside the optimization by setting state equations as constraints. Additional constraints may be added to the model to represent the influence of policy decisions. To account for uncertainty in weather conditions and its impact on availability, the optimization is performed for an ensemble of climate scenarios. While many sectors and their interactions are represented, the computational cost is limited as the problem remains linear and thus enables large-scale applications and the propagation of uncertainty. The formulation is implemented within the model "America's Water Analysis, Synthesis and Heuristic", an integrated model for the conterminous US discretized at the county-scale. This enables a systematic evaluation of stresses on water resources. We explore in particular geographic and temporal trends in function of user-types to develop a better understanding of the dynamics at play. We conclude with a comparison between the optimization results and current water use to identify potential solutions to increase resiliency.

Modelling fourier regression for time series data- a case study: modelling inflation in foods sector in Indonesia

NASA Astrophysics Data System (ADS)

Prahutama, Alan; Suparti; Wahyu Utami, Tiani

2018-03-01

Regression analysis is an analysis to model the relationship between response variables and predictor variables. The parametric approach to the regression model is very strict with the assumption, but nonparametric regression model isn’t need assumption of model. Time series data is the data of a variable that is observed based on a certain time, so if the time series data wanted to be modeled by regression, then we should determined the response and predictor variables first. Determination of the response variable in time series is variable in t-th (yt), while the predictor variable is a significant lag. In nonparametric regression modeling, one developing approach is to use the Fourier series approach. One of the advantages of nonparametric regression approach using Fourier series is able to overcome data having trigonometric distribution. In modeling using Fourier series needs parameter of K. To determine the number of K can be used Generalized Cross Validation method. In inflation modeling for the transportation sector, communication and financial services using Fourier series yields an optimal K of 120 parameters with R-square 99%. Whereas if it was modeled by multiple linear regression yield R-square 90%.

Optimizing Irrigation Water Allocation under Multiple Sources of Uncertainty in an Arid River Basin

NASA Astrophysics Data System (ADS)

Wei, Y.; Tang, D.; Gao, H.; Ding, Y.

2015-12-01

Population growth and climate change add additional pressures affecting water resources management strategies for meeting demands from different economic sectors. It is especially challenging in arid regions where fresh water is limited. For instance, in the Tailanhe River Basin (Xinjiang, China), a compromise must be made between water suppliers and users during drought years. This study presents a multi-objective irrigation water allocation model to cope with water scarcity in arid river basins. To deal with the uncertainties from multiple sources in the water allocation system (e.g., variations of available water amount, crop yield, crop prices, and water price), the model employs a interval linear programming approach. The multi-objective optimization model developed from this study is characterized by integrating eco-system service theory into water-saving measures. For evaluation purposes, the model is used to construct an optimal allocation system for irrigation areas fed by the Tailan River (Xinjiang Province, China). The objective functions to be optimized are formulated based on these irrigation areas' economic, social, and ecological benefits. The optimal irrigation water allocation plans are made under different hydroclimate conditions (wet year, normal year, and dry year), with multiple sources of uncertainty represented. The modeling tool and results are valuable for advising decision making by the local water authority—and the agricultural community—especially on measures for coping with water scarcity (by incorporating uncertain factors associated with crop production planning).

General Mission Analysis Tool (GMAT) Acceptance Test Plan [Draft

NASA Technical Reports Server (NTRS)

Dove, Edwin; Hughes, Steve

2007-01-01

The information presented in this Acceptance Test Plan document shows the current status of the General Mission Analysis Tool (GMAT). GMAT is a software system developed by NASA Goddard Space Flight Center (GSFC) in collaboration with the private sector. The GMAT development team continuously performs acceptance tests in order to verify that the software continues to operate properly after updates are made. The GMAT Development team consists of NASA/GSFC Code 583 software developers, NASA/GSFC Code 595 analysts, and contractors of varying professions. GMAT was developed to provide a development approach that maintains involvement from the private sector and academia, encourages collaborative funding from multiple government agencies and the private sector, and promotes the transfer of technology from government funded research to the private sector. GMAT contains many capabilities, such as integrated formation flying modeling and MATLAB compatibility. The propagation capabilities in GMAT allow for fully coupled dynamics modeling of multiple spacecraft, in any flight regime. Other capabilities in GMAT inclucle: user definable coordinate systems, 3-D graphics in any coordinate system GMAT can calculate, 2-D plots, branch commands, solvers, optimizers, GMAT functions, planetary ephemeris sources including DE405, DE200, SLP and analytic models, script events, impulsive and finite maneuver models, and many more. GMAT runs on Windows, Mac, and Linux platforms. Both the Graphical User Interface (GUI) and the GMAT engine were built and tested on all of the mentioned platforms. GMAT was designed for intuitive use from both the GUI and with an importable script language similar to that of MATLAB.

Estimating criteria pollutant emissions using the California Regional Multisector Air Quality Emissions (CA-REMARQUE) model v1.0

NASA Astrophysics Data System (ADS)

Zapata, Christina B.; Yang, Chris; Yeh, Sonia; Ogden, Joan; Kleeman, Michael J.

2018-04-01

The California Regional Multisector Air Quality Emissions (CA-REMARQUE) model is developed to predict changes to criteria pollutant emissions inventories in California in response to sophisticated emissions control programs implemented to achieve deep greenhouse gas (GHG) emissions reductions. Two scenarios for the year 2050 act as the starting point for calculations: a business-as-usual (BAU) scenario and an 80 % GHG reduction (GHG-Step) scenario. Each of these scenarios was developed with an energy economic model to optimize costs across the entire California economy and so they include changes in activity, fuels, and technology across economic sectors. Separate algorithms are developed to estimate emissions of criteria pollutants (or their precursors) that are consistent with the future GHG scenarios for the following economic sectors: (i) on-road, (ii) rail and off-road, (iii) marine and aviation, (iv) residential and commercial, (v) electricity generation, and (vi) biorefineries. Properly accounting for new technologies involving electrification, biofuels, and hydrogen plays a central role in these calculations. Critically, criteria pollutant emissions do not decrease uniformly across all sectors of the economy. Emissions of certain criteria pollutants (or their precursors) increase in some sectors as part of the overall optimization within each of the scenarios. This produces nonuniform changes to criteria pollutant emissions in close proximity to heavily populated regions when viewed at 4 km spatial resolution with implications for exposure to air pollution for those populations. As a further complication, changing fuels and technology also modify the composition of reactive organic gas emissions and the size and composition of particulate matter emissions. This is most notably apparent through a comparison of emissions reductions for different size fractions of primary particulate matter. Primary PM2.5 emissions decrease by 4 % in the GHG-Step scenario vs. the BAU scenario while corresponding primary PM0.1 emissions decrease by 36 %. Ultrafine particles (PM0.1) are an emerging pollutant of concern expected to impact public health in future scenarios. The complexity of this situation illustrates the need for realistic treatment of criteria pollutant emissions inventories linked to GHG emissions policies designed for fully developed countries and states with strict existing environmental regulations.

Micromechanics-Based Damage Analysis of Fracture in Ti5553 Alloy with Application to Bolted Sectors

NASA Astrophysics Data System (ADS)

Bettaieb, Mohamed Ben; Van Hoof, Thibaut; Minnebo, Hans; Pardoen, Thomas; Dufour, Philippe; Jacques, Pascal J.; Habraken, Anne Marie

2015-03-01

A physics-based, uncoupled damage model is calibrated using cylindrical notched round tensile specimens made of Ti5553 and Ti-6Al-4V alloys. The fracture strain of Ti5553 is lower than for Ti-6Al-4V in the full range of stress triaxiality. This lower ductility originates from a higher volume fraction of damage sites. By proper heat treatment, the fracture strain of Ti5553 increases by almost a factor of two, as a result of a larger damage nucleation stress. This result proves the potential for further optimization of the damage resistance of the Ti5553 alloy. The damage model is combined with an elastoviscoplastic law in order to predict failure in a wide range of loading conditions. In particular, a specific application involving bolted sectors is addressed in order to determine the potential of replacing the Ti-6Al-4V by the Ti5553 alloy.

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir Hossein; Goldbert, Alan; Bagasol, Leonard Neil; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it is shown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Applying Graph Theory to Problems in Air Traffic Management

NASA Technical Reports Server (NTRS)

Farrahi, Amir H.; Goldberg, Alan T.; Bagasol, Leonard N.; Jung, Jaewoo

2017-01-01

Graph theory is used to investigate three different problems arising in air traffic management. First, using a polynomial reduction from a graph partitioning problem, it isshown that both the airspace sectorization problem and its incremental counterpart, the sector combination problem are NP-hard, in general, under several simple workload models. Second, using a polynomial time reduction from maximum independent set in graphs, it is shown that for any fixed e, the problem of finding a solution to the minimum delay scheduling problem in traffic flow management that is guaranteed to be within n1-e of the optimal, where n is the number of aircraft in the problem instance, is NP-hard. Finally, a problem arising in precision arrival scheduling is formulated and solved using graph reachability. These results demonstrate that graph theory provides a powerful framework for modeling, reasoning about, and devising algorithmic solutions to diverse problems arising in air traffic management.

Spatio-temporal optimization of agricultural practices to achieve a sustainable development at basin level; framework of a case study in Colombia

NASA Astrophysics Data System (ADS)

Uribe, Natalia; corzo, Gerald; Solomatine, Dimitri

2016-04-01

The flood events present during the last years in different basins of the Colombian territory have raised questions on the sensitivity of the regions and if this regions have common features. From previous studies it seems important features in the sensitivity of the flood process were: land cover change, precipitation anomalies and these related to impacts of agriculture management and water management deficiencies, among others. A significant government investment in the outreach activities for adopting and promoting the Colombia National Action Plan on Climate Change (NAPCC) is being carried out in different sectors and regions, having as a priority the agriculture sector. However, more information is still needed in the local environment in order to assess were the regions have this sensitivity. Also the continuous change in one region with seasonal agricultural practices have been pointed out as a critical information for optimal sustainable development. This combined spatio-temporal dynamics of crops cycle in relation to climate change (or variations) has an important impact on flooding events at basin areas. This research will develop on the assessment and optimization of the aggregated impact of flood events due to determinate the spatio-temporal dynamic of changes in agricultural management practices. A number of common best agricultural practices have been identified to explore their effect in a spatial hydrological model that will evaluate overall changes. The optimization process consists on the evaluation of best performance in the agricultural production, without having to change crops activities or move to other regions. To achieve this objectives a deep analysis of different models combined with current and future climate scenarios have been planned. An algorithm have been formulated to cover the parametric updates such that the optimal temporal identification will be evaluated in different region on the case study area. Different hydroinformatics techniques for optimization and uncertainty analysis are included in a framework that will solve partially the computational load found in the pre-runs of the case study. The work will focus on the region Fuquene basin in Colombia but this will not limit the scope of this study to have general methodological applications to other areas. Key words Modelling, WFlow_sbm, agriculture practices, climate change, optimization, flooding, spatial and temporal analysis

Wealth, mother's education and physical access as determinants of retail sector net use in rural Kenya

PubMed Central

2006-01-01

Background Insecticide-treated bed nets (ITN) provide real hope for the reduction of the malaria burden across Africa. Understanding factors that determine access to ITN is crucial to debates surrounding the optimal delivery systems. The influence of homestead wealth on use of nets purchased from the retail sector is well documented, however, the competing influence of mother's education and physical access to net providers is less well understood. Methods Between December 2004 and January 2005, a random sample of 72 rural communities was selected across four Kenyan districts. Demographic, assets, education and net use data were collected at homestead, mother and child (aged < 5 years) levels. An assets-based wealth index was developed using principal components analysis, travel time to net sources was modelled using geographic information systems, and factors influencing the use of retail sector nets explored using a multivariable logistic regression model. Results Homestead heads and guardians of 3,755 children < 5 years of age were interviewed. Approximately 15% (562) of children slept under a net the night before the interview; 58% (327) of the nets used were purchased from the retail sector. Homestead wealth (adjusted OR = 10.17, 95% CI = 5.45–18.98), travel time to nearest market centres (adjusted OR = 0.51, 95% CI = 0.37–0.72) and mother's education (adjusted OR = 2.92, 95% CI = 1.93–4.41) were significantly associated with use of retail sector nets by children aged less than 5 years. Conclusion Approaches to promoting access to nets through the retail sector disadvantage poor and remote communities where mothers are less well educated. PMID:16436216

Optimization Strategies for Bruch's Membrane Opening Minimum Rim Area Calculation: Sequential versus Simultaneous Minimization.

PubMed

Enders, Philip; Adler, Werner; Schaub, Friederike; Hermann, Manuel M; Diestelhorst, Michael; Dietlein, Thomas; Cursiefen, Claus; Heindl, Ludwig M

2017-10-24

To compare a simultaneously optimized continuous minimum rim surface parameter between Bruch's membrane opening (BMO) and the internal limiting membrane to the standard sequential minimization used for calculating the BMO minimum rim area in spectral domain optical coherence tomography (SD-OCT). In this case-control, cross-sectional study, 704 eyes of 445 participants underwent SD-OCT of the optic nerve head (ONH), visual field testing, and clinical examination. Globally and clock-hour sector-wise optimized BMO-based minimum rim area was calculated independently. Outcome parameters included BMO-globally optimized minimum rim area (BMO-gMRA) and sector-wise optimized BMO-minimum rim area (BMO-MRA). BMO area was 1.89 ± 0.05 mm 2 . Mean global BMO-MRA was 0.97 ± 0.34 mm 2 , mean global BMO-gMRA was 1.01 ± 0.36 mm 2 . Both parameters correlated with r = 0.995 (P < 0.001); mean difference was 0.04 mm 2 (P < 0.001). In all sectors, parameters differed by 3.0-4.2%. In receiver operating characteristics, the calculated area under the curve (AUC) to differentiate glaucoma was 0.873 for BMO-MRA, compared to 0.866 for BMO-gMRA (P = 0.004). Among ONH sectors, the temporal inferior location showed the highest AUC. Optimization strategies to calculate BMO-based minimum rim area led to significantly different results. Imposing an additional adjacency constraint within calculation of BMO-MRA does not improve diagnostic power. Global and temporal inferior BMO-MRA performed best in differentiating glaucoma patients.

Modeling Water Resource Systems Accounting for Water-Related Energy Use, GHG Emissions and Water-Dependent Energy Generation in California

NASA Astrophysics Data System (ADS)

Escriva-Bou, A.; Lund, J. R.; Pulido-Velazquez, M.; Medellin-Azuara, J.

2015-12-01

Most individual processes relating water and energy interdependence have been assessed in many different ways over the last decade. It is time to step up and include the results of these studies in management by proportionating a tool for integrating these processes in decision-making to effectively understand the tradeoffs between water and energy from management options and scenarios. A simple but powerful decision support system (DSS) for water management is described that includes water-related energy use and GHG emissions not solely from the water operations, but also from final water end uses, including demands from cities, agriculture, environment and the energy sector. Because one of the main drivers of energy use and GHG emissions is water pumping from aquifers, the DSS combines a surface water management model with a simple groundwater model, accounting for their interrelationships. The model also explicitly includes economic data to optimize water use across sectors during shortages and calculate return flows from different uses. Capabilities of the DSS are demonstrated on a case study over California's intertied water system. Results show that urban end uses account for most GHG emissions of the entire water cycle, but large water conveyance produces significant peaks over the summer season. Also the development of more efficient water application on the agricultural sector has increased the total energy consumption and the net water use in the basins.

Beyond vanilla dark matter: New channels in the multifaceted search for dark matter

NASA Astrophysics Data System (ADS)

Yaylali, David E.

Though we are extremely confident that non-baryonic dark matter exists in our universe, very little is known about its fundamental nature or its relationship with the Standard Model. Guided by theoretical motivations, a desire for generality in our experimental strategies, and a certain amount of hopeful optimism, we have established a basic framework and set of assumptions about the dark sector which we are now actively testing. After years of probing the parameter spaces of these vanilla dark-matter scenarios, through a variety of different search channels, a conclusive direct (non-gravitational) discovery of dark matter eludes us. This very well may suggest that our first-order expectations of the dark sector are too simplistic. This work describes two ways in which we can expand the experimental reach of vanilla dark-matter scenarios while maintaining the model-independent generality which is at this point still warranted. One way in which this is done is to consider coupling structures between the SM and the dark sector other than the two canonical types --- scalar and axial-vector --- leading to spin dependent and independent interactions at direct-detection experiments. The second way we generalize the vanilla scenarios is to consider multi-component dark sectors. We find that both of these generalizations lead to new and interesting phenomenology, and provide a richer complementarity structure between the different experimental probes we are using to search for dark matter.

An integrated radar model solution for mission level performance and cost trades

NASA Astrophysics Data System (ADS)

Hodge, John; Duncan, Kerron; Zimmerman, Madeline; Drupp, Rob; Manno, Mike; Barrett, Donald; Smith, Amelia

2017-05-01

A fully integrated Mission-Level Radar model is in development as part of a multi-year effort under the Northrop Grumman Mission Systems (NGMS) sector's Model Based Engineering (MBE) initiative to digitally interconnect and unify previously separate performance and cost models. In 2016, an NGMS internal research and development (IR and D) funded multidisciplinary team integrated radio frequency (RF), power, control, size, weight, thermal, and cost models together using a commercial-off-the-shelf software, ModelCenter, for an Active Electronically Scanned Array (AESA) radar system. Each represented model was digitally connected with standard interfaces and unified to allow end-to-end mission system optimization and trade studies. The radar model was then linked to the Air Force's own mission modeling framework (AFSIM). The team first had to identify the necessary models, and with the aid of subject matter experts (SMEs) understand and document the inputs, outputs, and behaviors of the component models. This agile development process and collaboration enabled rapid integration of disparate models and the validation of their combined system performance. This MBE framework will allow NGMS to design systems more efficiently and affordably, optimize architectures, and provide increased value to the customer. The model integrates detailed component models that validate cost and performance at the physics level with high-level models that provide visualization of a platform mission. This connectivity of component to mission models allows hardware and software design solutions to be better optimized to meet mission needs, creating cost-optimal solutions for the customer, while reducing design cycle time through risk mitigation and early validation of design decisions.

A feedback control model for network flow with multiple pure time delays

NASA Technical Reports Server (NTRS)

Press, J.

1972-01-01

A control model describing a network flow hindered by multiple pure time (or transport) delays is formulated. Feedbacks connect each desired output with a single control sector situated at the origin. The dynamic formulation invokes the use of differential difference equations. This causes the characteristic equation of the model to consist of transcendental functions instead of a common algebraic polynomial. A general graphical criterion is developed to evaluate the stability of such a problem. A digital computer simulation confirms the validity of such criterion. An optimal decision making process with multiple delays is presented.

Reinforcement Learning Based Web Service Compositions for Mobile Business

NASA Astrophysics Data System (ADS)

Zhou, Juan; Chen, Shouming

In this paper, we propose a new solution to Reactive Web Service Composition, via molding with Reinforcement Learning, and introducing modified (alterable) QoS variables into the model as elements in the Markov Decision Process tuple. Moreover, we give an example of Reactive-WSC-based mobile banking, to demonstrate the intrinsic capability of the solution in question of obtaining the optimized service composition, characterized by (alterable) target QoS variable sets with optimized values. Consequently, we come to the conclusion that the solution has decent potentials in boosting customer experiences and qualities of services in Web Services, and those in applications in the whole electronic commerce and business sector.

Linear quadratic regulators with eigenvalue placement in a specified region

NASA Technical Reports Server (NTRS)

Shieh, Leang S.; Dib, Hani M.; Ganesan, Sekar

1988-01-01

A linear optimal quadratic regulator is developed for optimally placing the closed-loop poles of multivariable continuous-time systems within the common region of an open sector, bounded by lines inclined at + or - pi/2k (k = 2 or 3) from the negative real axis with a sector angle of pi/2 or less, and the left-hand side of a line parallel to the imaginary axis in the complex s-plane. The design method is mainly based on the solution of a linear matrix Liapunov equation, and the resultant closed-loop system with its eigenvalues in the desired region is optimal with respect to a quadratic performance index.

A multi-objective model for closed-loop supply chain optimization and efficient supplier selection in a competitive environment considering quantity discount policy

NASA Astrophysics Data System (ADS)

Jahangoshai Rezaee, Mustafa; Yousefi, Samuel; Hayati, Jamileh

2017-06-01

Supplier selection and allocation of optimal order quantity are two of the most important processes in closed-loop supply chain (CLSC) and reverse logistic (RL). So that providing high quality raw material is considered as a basic requirement for a manufacturer to produce popular products, as well as achieve more market shares. On the other hand, considering the existence of competitive environment, suppliers have to offer customers incentives like discounts and enhance the quality of their products in a competition with other manufacturers. Therefore, in this study, a model is presented for CLSC optimization, efficient supplier selection, as well as orders allocation considering quantity discount policy. It is modeled using multi-objective programming based on the integrated simultaneous data envelopment analysis-Nash bargaining game. In this study, maximizing profit and efficiency and minimizing defective and functions of delivery delay rate are taken into accounts. Beside supplier selection, the suggested model selects refurbishing sites, as well as determining the number of products and parts in each network's sector. The suggested model's solution is carried out using global criteria method. Furthermore, based on related studies, a numerical example is examined to validate it.

Modelling and Optimization Studies on a Novel Lipase Production by Staphylococcus arlettae through Submerged Fermentation

PubMed Central

Chauhan, Mamta; Chauhan, Rajinder Singh; Garlapati, Vijay Kumar

2013-01-01

Microbial enzymes from extremophilic regions such as hot spring serve as an important source of various stable and valuable industrial enzymes. The present paper encompasses the modeling and optimization approach for production of halophilic, solvent, tolerant, and alkaline lipase from Staphylococcus arlettae through response surface methodology integrated nature inspired genetic algorithm. Response surface model based on central composite design has been developed by considering the individual and interaction effects of fermentation conditions on lipase production through submerged fermentation. The validated input space of response surface model (with R 2 value of 96.6%) has been utilized for optimization through genetic algorithm. An optimum lipase yield of 6.5 U/mL has been obtained using binary coded genetic algorithm predicted conditions of 9.39% inoculum with the oil concentration of 10.285% in 2.99 hrs using pH of 7.32 at 38.8°C. This outcome could contribute to introducing this extremophilic lipase (halophilic, solvent, and tolerant) to industrial biotechnology sector and will be a probable choice for different food, detergent, chemical, and pharmaceutical industries. The present work also demonstrated the feasibility of statistical design tools integration with computational tools for optimization of fermentation conditions for maximum lipase production. PMID:24455210

Designing Optimal LNG Station Network for U.S. Heavy-Duty Freight Trucks using Temporally and Spatially Explicit Supply Chain Optimization

NASA Astrophysics Data System (ADS)

Lee, Allen

The recent natural gas boom has opened much discussion about the potential of natural gas and specifically Liquefied Natural Gas (LNG) in the United States transportation sector. The switch from diesel to natural gas vehicles would reduce foreign dependence on oil, spur domestic economic growth, and potentially reduce greenhouse gas emissions. LNG provides the most potential for the medium to heavy-duty vehicle market partially due to unstable oil prices and stagnant natural gas prices. As long as the abundance of unconventional gas in the United States remains cheap, fuel switching to natural gas could provide significant cost savings for long haul freight industry. Amid a growing LNG station network and ever increasing demand for freight movement, LNG heavy-duty truck sales are less than anticipated and the industry as a whole is less economic than expected. In spite of much existing and mature natural gas infrastructure, the supply chain for LNG is different and requires explicit and careful planning. This thesis proposes research to explore the claim that the largest obstacle to widespread LNG market penetration is sub-optimal infrastructure planning. No other study we are aware of has explicitly explored the LNG transportation fuel supply chain for heavy-duty freight trucks. This thesis presents a novel methodology that links a network infrastructure optimization model (represents supply side) with a vehicle stock and economic payback model (represents demand side). The model characterizes both a temporal and spatial optimization model of future LNG transportation fuel supply chains in the United States. The principal research goal is to assess the economic feasibility of the current LNG transportation fuel industry and to determine an optimal pathway to achieve ubiquitous commercialization of LNG vehicles in the heavy-duty transport sector. The results indicate that LNG is not economic as a heavy-duty truck fuel until 2030 under current market conditions unless a significant station capital subsidy, upwards of 50 percent and even then it might not be enough. However, a doubling of LNG truck demand will initialize network commercialization in the modeling base year, 2012 (the same year Clean Energy Corp. launched their national LNG network) in California and then gradually establish in other hotspot regions in Mid-West and Mid-Atlantic throughout the time horizon. The model shows that trucking routes in California are highly commercial due to high traffic volume and regional advantages. The model can be used by industry to inform necessary policies and to plan future infrastructure deployment along trucking routes that are likely to provide the highest returns.

Optimization of Water Resources and Agricultural Activities for Economic Benefit in Colorado

NASA Astrophysics Data System (ADS)

LIM, J.; Lall, U.

2017-12-01

The limited water resources available for irrigation are a key constraint for the important agricultural sector of Colorado's economy. As climate change and groundwater depletion reshape these resources, it is essential to understand the economic potential of water resources under different agricultural production practices. This study uses a linear programming optimization at the county spatial scale and annual temporal scales to study the optimal allocation of water withdrawal and crop choices. The model, AWASH, reflects streamflow constraints between different extraction points, six field crops, and a distinct irrigation decision for maize and wheat. The optimized decision variables, under different environmental, social, economic, and physical constraints, provide long-term solutions for ground and surface water distribution and for land use decisions so that the state can generate the maximum net revenue. Colorado, one of the largest agricultural producers, is tested as a case study and the sensitivity on water price and on climate variability is explored.

Food and energy choices for India: a programming model with partial endogenous energy requirements.

PubMed

Parikh, K S; Srinivasan, T N

1980-09-01

This paper presents a mathematical model for all matter-energy processing subsystems at the level of the society, specifically India. It explores India's choices in the food and energy sectors over the coming decades. Alternative land intensive, irrigation energy intensive, and fertilizer intensive techniques of food production are identified using a nonlinear programming model. The land saved is devoted to growing firewood. The optimum combination of railway (steam, diesel, and electric traction) and road (automobiles, diesel trucks, and diesel and gasoline buses) transport is determined. For the oil sector, two alternative sources of supply of crude oil and petroleum products are included, namely, domestic production and imports. The optimum choice is determined through a linear programming model. While the model is basically a static one, designed to determine the optimal choice for the target year of 2000-2001, certain intertemporal detail is incorporated for electricity generation. The model minimizes the costs of meeting the needs for food, transport in terms of passenger kilometers and goods per ton per kilometer, energy needs for domestic cooking and lighting, and the energy needs of the rest of the economy.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model.

PubMed

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders' expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day's price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately.

Predicting the Direction of Stock Market Index Movement Using an Optimized Artificial Neural Network Model

PubMed Central

Qiu, Mingyue; Song, Yu

2016-01-01

In the business sector, it has always been a difficult task to predict the exact daily price of the stock market index; hence, there is a great deal of research being conducted regarding the prediction of the direction of stock price index movement. Many factors such as political events, general economic conditions, and traders’ expectations may have an influence on the stock market index. There are numerous research studies that use similar indicators to forecast the direction of the stock market index. In this study, we compare two basic types of input variables to predict the direction of the daily stock market index. The main contribution of this study is the ability to predict the direction of the next day’s price of the Japanese stock market index by using an optimized artificial neural network (ANN) model. To improve the prediction accuracy of the trend of the stock market index in the future, we optimize the ANN model using genetic algorithms (GA). We demonstrate and verify the predictability of stock price direction by using the hybrid GA-ANN model and then compare the performance with prior studies. Empirical results show that the Type 2 input variables can generate a higher forecast accuracy and that it is possible to enhance the performance of the optimized ANN model by selecting input variables appropriately. PMID:27196055

A computer network with scada and case tools for on-line process control in greenhouses

NASA Astrophysics Data System (ADS)

Gieling, Th. H.; van Meurs, W. Th. M.; Janssen, H. J. J.

Climate control computers in greenhouses are used to control heating and ventilation, supply water and dilute and dispense nutrients. They integrate models into optimally controlled systems. This paper describes how information technology, as in use in other sectors of industry, is applied to greenhouse control. The introduction of modern software and hardware concepts in horticulture adds power and extra opportunities to climate control in greenhouses.

A computer network with SCADA and case tools for on-line process control in greenhouses.

PubMed

Gieling ThH; van Meurs WTh; Janssen, H J

1996-01-01

Climate control computers in greenhouses are used to control heating and ventilation, supply water and dilute and dispense nutrients. They integrate models into optimally controlled systems. This paper describes how information technology, as in use in other sectors of industry, is applied to greenhouse control. The introduction of modern software and hardware concepts in horticulture adds power and extra oppurtunities to climate contol in greenhouses.

Environmental effects of interstate power trading on electricity consumption mixes.

PubMed

Marriott, Joe; Matthews, H Scott

2005-11-15

Although many studies of electricity generation use national or state average generation mix assumptions, in reality a great deal of electricity is transferred between states with very different mixes of fossil and renewable fuels, and using the average numbers could result in incorrect conclusions in these studies. We create electricity consumption profiles for each state and for key industry sectors in the U.S. based on existing state generation profiles, net state power imports, industry presence by state, and an optimization model to estimate interstate electricity trading. Using these "consumption mixes" can provide a more accurate assessment of electricity use in life-cycle analyses. We conclude that the published generation mixes for states that import power are misleading, since the power consumed in-state has a different makeup than the power that was generated. And, while most industry sectors have consumption mixes similar to the U.S. average, some of the most critical sectors of the economy--such as resource extraction and material processing sectors--are very different. This result does validate the average mix assumption made in many environmental assessments, but it is important to accurately quantify the generation methods for electricity used when doing life-cycle analyses.

Water-Energy-Food Nexus: Compelling Issues for Geophysical Research

NASA Astrophysics Data System (ADS)

Akhbari, M.; Grigg, N. S.; Waskom, R.

2014-12-01

The joint security of water, food, and energy systems is an urgent issue everywhere, and strong drivers of development and land use change, exacerbated by climate change, require new knowledge to achieve integrated solution using a nexus-based approach to assess inter-dependencies. Effective research-based decision support tools are essential to identify the major issues and interconnections to help in implementation of the nexus approach. The major needs are models and data to clearly and unambiguously present decision scenarios to local cooperative groups of farmers, electric energy generators and water officials for joint decisions. These can be developed by integrated models to link hydrology, land use, energy use, cropping simulation, and optimization with economic objectives and socio-physical constraints. The first step in modeling is to have a good conceptual model and then to get data. As the linking of models increases uncertainties, each one should be supplied with adequate data at suitable spatial and temporal resolutions. Most models are supplied with data by geophysical scientists, such as hydrologists, geologists, atmospheric scientists, soil scientists, and climatologists, among others. Outcomes of a recently-completed project to study the water-energy-food nexus will be explained to illuminate the model and data needs to inform future management actions across the nexus. The project included a workshop of experts from government, business, academia, and the non-profit sector who met to define and explain nexus interactions and needs. An example of the findings is that data inconsistencies among sectors create barriers to integrated planning. A nexus-based systems model is needed to outline sectoral inter-dependencies and identify data demands and gaps. Geophysical scientists can help to create this model and take leadership on designing data systems to facilitate sharing and enable integrated management.

Economic Influences on Re-Enlistment. The Draft Era.

DTIC Science & Technology

1982-10-01

for each individual in jobs covered by Social Security (over 90 percent of all private - sector jobs, plus military service and half of non-federal...disappeared as real military wages have increased significantly over cyclical swings in the private sector . Despite the Navy’s apparent success in...maintaining optimal retention rates in selective ratings is due to the wage pressures exerted in the private sector . Military wage increases must be

Role of natural gas in meeting an electric sector emissions ...

EPA Pesticide Factsheets

With advances in natural gas extraction technologies, there is an increase in availability of domestic natural gas, and natural gas is gaining a larger share of use as a fuel in electricity production. At the power plant, natural gas is a cleaner burning fuel than coal, but uncertainties exist in the amount of methane leakage occurring upstream in the extraction and production of natural gas. At high leakage levels, these methane emissions could outweigh the benefits of switching from coal to natural gas. This analysis uses the MARKAL linear optimization model to compare the carbon emissions profiles and system-wide global warming potential of the U.S. energy system over a series of model runs in which the power sector is asked to meet a specific CO2 reduction target and the availability of natural gas changes. Scenarios are run with a range of upstream methane emission leakage rates from natural gas production. While the total CO2 emissions are reduced in most scenarios, total greenhouse gas emissions show an increase or no change when both natural gas availability and methane emissions from natural gas production are high. Article presents summary of results from an analyses of natural gas resource availability and power sector emissions reduction strategies under different estimates of methane leakage rates during natural gas extraction and production. This was study was undertaken as part of the Energy Modeling Forum Study #31:

Forecasting of municipal solid waste quantity in a developing country using multivariate grey models

DOE Office of Scientific and Technical Information (OSTI.GOV)

Intharathirat, Rotchana, E-mail: rotchana.in@gmail.com; Abdul Salam, P., E-mail: salam@ait.ac.th; Kumar, S., E-mail: kumar@ait.ac.th

Highlights: • Grey model can be used to forecast MSW quantity accurately with the limited data. • Prediction interval overcomes the uncertainty of MSW forecast effectively. • A multivariate model gives accuracy associated with factors affecting MSW quantity. • Population, urbanization, employment and household size play role for MSW quantity. - Abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developingmore » countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435–44,994 tonnes per day in 2013 to 55,177–56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.« less

Optimal policy for mitigating emissions in the European transport sector

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Piera, Patrizio; Sennai, Mesfun; Igor, Staritsky; Berien, Elbersen; Tijs, Lammens; Florian, Kraxner

2017-04-01

A geographic explicit techno-economic model, BeWhere (www.iiasa.ac.at/bewhere), has been developed at the European scale (Europe 28, the Balkans countries, Turkey, Moldavia and Ukraine) at a 40km grid size, to assess the potential of bioenergy from non-food feedstock. Based on the minimization of the supply chain from feedstock collection to the final energy product distribution, the model identifies the optimal bioenergy production plants in terms of spatial location, technology and capacity. The feedstock of interests are woody biomass (divided into eight types from conifers and non-conifers) and five different crop residuals. For each type of feedstock, one or multiple technologies can be applied for either heat, electricity or biofuel production. The model is run for different policy tools such as carbon cost, biofuel support, or subsidies, and the optimal mix of technologies and biomass needed is optimized to reach a production cost competitive against the actual reference system which is fossil fuel based. From this approach, the optimal mix of policy tools that can be applied country wide in Europe will be identified. The preliminary results show that high carbon tax and biofuel support contribute to the development of large scale biofuel production based on woody biomass plants mainly located in the northern part of Europe. Finally the highest emission reduction is reached with low biofuel support and high carbon tax evenly distributed in Europe.

Quantifying the Impacts of Large Scale Integration of Renewables in Indian Power Sector

NASA Astrophysics Data System (ADS)

Kumar, P.; Mishra, T.; Banerjee, R.

2017-12-01

India's power sector is responsible for nearly 37 percent of India's greenhouse gas emissions. For a fast emerging economy like India whose population and energy consumption are poised to rise rapidly in the coming decades, renewable energy can play a vital role in decarbonizing power sector. In this context, India has targeted 33-35 percent emission intensity reduction (with respect to 2005 levels) along with large scale renewable energy targets (100GW solar, 60GW wind, and 10GW biomass energy by 2022) in INDCs submitted at Paris agreement. But large scale integration of renewable energy is a complex process which faces a number of problems like capital intensiveness, matching intermittent loads with least storage capacity and reliability. In this context, this study attempts to assess the technical feasibility of integrating renewables into Indian electricity mix by 2022 and analyze its implications on power sector operations. This study uses TIMES, a bottom up energy optimization model with unit commitment and dispatch features. We model coal and gas fired units discretely with region-wise representation of wind and solar resources. The dispatch features are used for operational analysis of power plant units under ramp rate and minimum generation constraints. The study analyzes India's electricity sector transition for the year 2022 with three scenarios. The base case scenario (no RE addition) along with INDC scenario (with 100GW solar, 60GW wind, 10GW biomass) and low RE scenario (50GW solar, 30GW wind) have been created to analyze the implications of large scale integration of variable renewable energy. The results provide us insights on trade-offs involved in achieving mitigation targets and investment decisions involved. The study also examines operational reliability and flexibility requirements of the system for integrating renewables.

Estimation of GHG emissions in Egypt up to the year 2020

DOE Office of Scientific and Technical Information (OSTI.GOV)

ElMahgary, Y.; Abdel-Fattah, A.I.; Shama, M.A.

1994-09-01

Within the frame of UNEP's project on the Methodologies of Determining the Costs of Abatement of GHG Emissions, a case study on Egypt was undertaken by VTT (Technical Research Centre of Finland) in cooperation with the Egyptian Environment Authority Agency (EEAA). Both the bottom-up or engineering models and the top-down or the macroeconomic models were used. In the bottom-up approach, the economic sectors were divided into seven groups: petroleum industry, power generation, heavy industry, light industry, residential and commercial sector, transport and agriculture and domestic wastes. First, a comprehensive inventory for the year 1990 was prepared for all the GHGmore » emissions mainly, but not exclusively, from energy sources. This included CO[sub 2], CH[sub 4] and N[sub 2]O. A base scenario of economic and energy growth of Egypt for business-as-usual alternative was fixed using the results of several optimization processes undertaken earlier by the National Committee of Egypt. GHG emissions of the different sources in this base scenario were then determined using LEAP model and spread sheets.« less

Planning a Target Renewable Portfolio using Atmospheric Modeling and Stochastic Optimization

NASA Astrophysics Data System (ADS)

Hart, E.; Jacobson, M. Z.

2009-12-01

A number of organizations have suggested that an 80% reduction in carbon emissions by 2050 is a necessary step to mitigate climate change and that decarbonization of the electricity sector is a crucial component of any strategy to meet this target. Integration of large renewable and intermittent generators poses many new problems in power system planning. In this study, we attempt to determine an optimal portfolio of renewable resources to meet best the fluctuating California load while also meeting an 80% carbon emissions reduction requirement. A stochastic optimization scheme is proposed that is based on a simplified model of the California electricity grid. In this single-busbar power system model, the load is met with generation from wind, solar thermal, photovoltaic, hydroelectric, geothermal, and natural gas plants. Wind speeds and insolation are calculated using GATOR-GCMOM, a global-through-urban climate-weather-air pollution model. Fields were produced for California and Nevada at 21km SN by 14 km WE spatial resolution every 15 minutes for the year 2006. Load data for 2006 were obtained from the California ISO OASIS database. Maximum installed capacities for wind and solar thermal generation were determined using a GIS analysis of potential development sites throughout the state. The stochastic optimization scheme requires that power balance be achieved in a number of meteorological and load scenarios that deviate from the forecasted (or modeled) data. By adjusting the error distributions of the forecasts, the model describes how improvements in wind speed and insolation forecasting may affect the optimal renewable portfolio. Using a simple model, we describe the diversity, size, and sensitivities of a renewable portfolio that is best suited to the resources and needs of California and that contributes significantly to reduction of the state’s carbon emissions.

The Use of EPI-Splines to Model Empirical Semivariograms for Optimal Spatial Estimation

DTIC Science & Technology

2016-09-01

proliferation of unmanned systems in military and civilian sectors has occurred at lightning speed. In the case of Autonomous Underwater Vehicles or...SLAM is a method of position estimation that relies on map data [3]. In this process, the creation of the map occurs as the vehicle is navigating the...that ensures minimal errors. This technique is accomplished in two steps. The first step is creation of the semivariogram. The semivariogram is a

A benchmark system to optimize our defense against an attack on the US food supply using the Risk Reduction Effectiveness and Capabilities Assessment Program.

PubMed

Hodoh, Ofia; Dallas, Cham E; Williams, Paul; Jaine, Andrew M; Harris, Curt

2015-01-01

A predictive system was developed and tested in a series of exercises with the objective of evaluating the preparedness and effectiveness of the multiagency response to food terrorism attacks. A computerized simulation model, Risk Reduction Effectiveness and Capabilities Assessment Program (RRECAP), was developed to identify the key factors that influence the outcomes of an attack and quantify the relative reduction of such outcomes caused by each factor. The model was evaluated in a set of Tabletop and Full-Scale Exercises that simulate biological and chemical attacks on the food system. More than 300 participants representing more than 60 federal, state, local, and private sector agencies and organizations. The exercises showed that agencies could use RRECAP to identify and prioritize their advance preparation to mitigate such attacks with minimal expense. RRECAP also demonstrated the relative utility and limitations of the ability of medical resources to treat patients if responders do not recognize and mitigate the attack rapidly, and the exercise results showed that proper advance preparation would reduce these deficiencies. Using computer simulation prediction of the medical outcomes of food supply attacks to identify optimal remediation activities and quantify the benefits of various measures provides a significant tool to agencies in both the public and private sector as they seek to prepare for such an attack.

Cost-Effectiveness Thresholds in Global Health: Taking a Multisectoral Perspective.

PubMed

Remme, Michelle; Martinez-Alvarez, Melisa; Vassall, Anna

2017-04-01

Good health is a function of a range of biological, environmental, behavioral, and social factors. The consumption of quality health care services is therefore only a part of how good health is produced. Although few would argue with this, the economic framework used to allocate resources to optimize population health is applied in a way that constrains the analyst and the decision maker to health care services. This approach risks missing two critical issues: 1) multiple sectors contribute to health gain and 2) the goods and services produced by the health sector can have multiple benefits besides health. We illustrate how present cost-effectiveness thresholds could result in health losses, particularly when considering health-producing interventions in other sectors or public health interventions with multisectoral outcomes. We then propose a potentially more optimal second best approach, the so-called cofinancing approach, in which the health payer could redistribute part of its budget to other sectors, where specific nonhealth interventions achieved a health gain more efficiently than the health sector's marginal productivity (opportunity cost). Likewise, other sectors would determine how much to contribute toward such an intervention, given the current marginal productivity of their budgets. Further research is certainly required to test and validate different measurement approaches and to assess the efficiency gains from cofinancing after deducting the transaction costs that would come with such cross-sectoral coordination. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Impact of Fishery Policy on Fishery Manufacture Output, Economy and Welfare in Indonesia

NASA Astrophysics Data System (ADS)

Firmansyah; Oktavilia, Shanty; Sugiyanto, F. X.; Hamzah, Ibnu N.

2018-02-01

The fisheries sector and fish manufacturing industry are the bright prospect sectors of Indonesia, due to its huge potency, which has not been worked out optimally. In facts, these sectors can generate a large amount of foreign exchange. The Government has paid significant attention to the development of these sectors. This study simulates the impact of fishery policies on the production of fish manufacturing industry, national economic and welfare in Indonesia. By employing the Input-Output Analysis approach, impacts of various government policy scenarios are developed, covering fisheries technical policy, as well as infrastructure development policies in the fisheries sector. This study indicates that the policies in the fisheries sector increase the output of fishery, the production of fish manufacturing industry, the sectoral and national outputs, as well as the level of national income.

A hybrid system dynamics and optimization approach for supporting sustainable water resources planning in Zhengzhou City, China

NASA Astrophysics Data System (ADS)

Li, Zhi; Li, Chunhui; Wang, Xuan; Peng, Cong; Cai, Yanpeng; Huang, Weichen

2018-01-01

Problems with water resources restrict the sustainable development of a city with water shortages. Based on system dynamics (SD) theory, a model of sustainable utilization of water resources using the STELLA software has been established. This model consists of four subsystems: population system, economic system, water supply system and water demand system. The boundaries of the four subsystems are vague, but they are closely related and interdependent. The model is applied to Zhengzhou City, China, which has a serious water shortage. The difference between the water supply and demand is very prominent in Zhengzhou City. The model was verified with data from 2009 to 2013. The results show that water demand of Zhengzhou City will reach 2.57 billion m3 in 2020. A water resources optimization model is developed based on interval-parameter two-stage stochastic programming. The objective of the model is to allocate water resources to each water sector and make the lowest cost under the minimum water demand. Using the simulation results, decision makers can easily weigh the costs of the system, the water allocation objectives, and the system risk. The hybrid system dynamics method and optimization model is a rational try to support water resources management in many cities, particularly for cities with potential water shortage and it is solidly supported with previous studies and collected data.

Modified Mahalanobis Taguchi System for Imbalance Data Classification

PubMed Central

2017-01-01

The Mahalanobis Taguchi System (MTS) is considered one of the most promising binary classification algorithms to handle imbalance data. Unfortunately, MTS lacks a method for determining an efficient threshold for the binary classification. In this paper, a nonlinear optimization model is formulated based on minimizing the distance between MTS Receiver Operating Characteristics (ROC) curve and the theoretical optimal point named Modified Mahalanobis Taguchi System (MMTS). To validate the MMTS classification efficacy, it has been benchmarked with Support Vector Machines (SVMs), Naive Bayes (NB), Probabilistic Mahalanobis Taguchi Systems (PTM), Synthetic Minority Oversampling Technique (SMOTE), Adaptive Conformal Transformation (ACT), Kernel Boundary Alignment (KBA), Hidden Naive Bayes (HNB), and other improved Naive Bayes algorithms. MMTS outperforms the benchmarked algorithms especially when the imbalance ratio is greater than 400. A real life case study on manufacturing sector is used to demonstrate the applicability of the proposed model and to compare its performance with Mahalanobis Genetic Algorithm (MGA). PMID:28811820

Hidden from view: coupled dark sector physics and small scales

NASA Astrophysics Data System (ADS)

Elahi, Pascal J.; Lewis, Geraint F.; Power, Chris; Carlesi, Edoardo; Knebe, Alexander

2015-09-01

We study cluster mass dark matter (DM) haloes, their progenitors and surroundings in a coupled dark matter-dark energy (DE) model and compare it to quintessence and Λ cold dark matter (ΛCDM) models with adiabatic zoom simulations. When comparing cosmologies with different expansions histories, growth functions and power spectra, care must be taken to identify unambiguous signatures of alternative cosmologies. Shared cosmological parameters, such as σ8, need not be the same for optimal fits to observational data. We choose to set our parameters to ΛCDM z = 0 values. We find that in coupled models, where DM decays into DE, haloes appear remarkably similar to ΛCDM haloes despite DM experiencing an additional frictional force. Density profiles are not systematically different and the subhalo populations have similar mass, spin, and spatial distributions, although (sub)haloes are less concentrated on average in coupled cosmologies. However, given the scatter in related observables (V_max,R_{V_max}), this difference is unlikely to distinguish between coupled and uncoupled DM. Observations of satellites of Milky Way and M31 indicate a significant subpopulation reside in a plane. Coupled models do produce planar arrangements of satellites of higher statistical significance than ΛCDM models; however, in all models these planes are dynamically unstable. In general, the non-linear dynamics within and near large haloes masks the effects of a coupled dark sector. The sole environmental signature we find is that small haloes residing in the outskirts are more deficient in baryons than their ΛCDM counterparts. The lack of a pronounced signal for a coupled dark sector strongly suggests that such a phenomena would be effectively hidden from view.

A heterogeneous fleet vehicle routing model for solving the LPG distribution problem: A case study

NASA Astrophysics Data System (ADS)

Onut, S.; Kamber, M. R.; Altay, G.

2014-03-01

Vehicle Routing Problem (VRP) is an important management problem in the field of distribution and logistics. In VRPs, routes from a distribution point to geographically distributed points are designed with minimum cost and considering customer demands. All points should be visited only once and by one vehicle in one route. Total demand in one route should not exceed the capacity of the vehicle that assigned to that route. VRPs are varied due to real life constraints related to vehicle types, number of depots, transportation conditions and time periods, etc. Heterogeneous fleet vehicle routing problem is a kind of VRP that vehicles have different capacity and costs. There are two types of vehicles in our problem. In this study, it is used the real world data and obtained from a company that operates in LPG sector in Turkey. An optimization model is established for planning daily routes and assigned vehicles. The model is solved by GAMS and optimal solution is found in a reasonable time.

Integration and Optimization of Alternative Sources of Energy in a Remote Region

NASA Astrophysics Data System (ADS)

Berberi, Pellumb; Inodnorjani, Spiro; Aleti, Riza

2010-01-01

In a remote coastal region supply of energy from national grid is insufficient for a sustainable development. Integration and optimization of local alternative renewable energy sources is an optional solution of the problem. In this paper we have studied the energetic potential of local sources of renewable energy (water, solar, wind and biomass). A bottom-up energy system optimization model is proposed in order to support planning policies for promoting the use of renewable energy sources. A software, based on multiple factors and constrains analysis for optimization energy flow is proposed, which provides detailed information for exploitation each source of energy, power and heat generation, GHG emissions and end-use sectors. Economical analysis shows that with existing technologies both stand alone and regional facilities may be feasible. Improving specific legislation will foster investments from Central or Local Governments and also from individuals, private companies or small families. The study is carried on the frame work of a FP6 project "Integrated Renewable Energy System."

Environmental effects of interstate power trading on electricity consumption mixes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Joe Marriott; H. Scott Matthews

2005-11-15

Although many studies of electricity generation use national or state average generation mix assumptions, in reality a great deal of electricity is transferred between states with very different mixes of fossil and renewable fuels, and using the average numbers could result in incorrect conclusions in these studies. The authors create electricity consumption profiles for each state and for key industry sectors in the U.S. based on existing state generation profiles, net state power imports, industry presence by state, and an optimization model to estimate interstate electricity trading. Using these 'consumption mixes' can provide a more accurate assessment of electricity usemore » in life-cycle analyses. It is concluded that the published generation mixes for states that import power are misleading, since the power consumed in-state has a different makeup than the power that was generated. And, while most industry sectors have consumption mixes similar to the U.S. average, some of the most critical sectors of the economy - such as resource extraction and material processing sectors - are very different. This result does validate the average mix assumption made in many environmental assessments, but it is important to accurately quantify the generation methods for electricity used when doing life-cycle analyses. 16 refs., 7 figs., 2 tabs.« less

A view to the future of natural gas and electricity: An integrated modeling approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, Wesley J.; Medlock, Kenneth B.; Jani, Aditya

This paper demonstrates the value of integrating two highly spatially resolved models: the Rice World Gas Trade Model (RWGTM) of the natural gas sector and the Regional Energy Deployment System (ReEDS) model of the U.S. electricity sector. The RWGTM passes electricity-sector natural gas prices to the ReEDS model, while the ReEDS model returns electricity-sector natural gas demand to the RWGTM. The two models successfully converge to a solution under reference scenario conditions. We present electricity-sector and natural gas sector evolution using the integrated models for this reference scenario. This paper demonstrates that the integrated models produced similar national-level results asmore » when running in a stand-alone form, but that regional and state-level results can vary considerably. As we highlight, these regional differences have potentially significant implications for electric sector planners especially in the wake of substantive policy changes for the sector (e.g., the Clean Power Plan).« less

A view to the future of natural gas and electricity: An integrated modeling approach

DOE PAGES

Cole, Wesley J.; Medlock, Kenneth B.; Jani, Aditya

2016-03-17

This paper demonstrates the value of integrating two highly spatially resolved models: the Rice World Gas Trade Model (RWGTM) of the natural gas sector and the Regional Energy Deployment System (ReEDS) model of the U.S. electricity sector. The RWGTM passes electricity-sector natural gas prices to the ReEDS model, while the ReEDS model returns electricity-sector natural gas demand to the RWGTM. The two models successfully converge to a solution under reference scenario conditions. We present electricity-sector and natural gas sector evolution using the integrated models for this reference scenario. This paper demonstrates that the integrated models produced similar national-level results asmore » when running in a stand-alone form, but that regional and state-level results can vary considerably. As we highlight, these regional differences have potentially significant implications for electric sector planners especially in the wake of substantive policy changes for the sector (e.g., the Clean Power Plan).« less

Material saving by means of CWR technology using optimization techniques

NASA Astrophysics Data System (ADS)

Pérez, Iñaki; Ambrosio, Cristina

2017-10-01

Material saving is currently a must for the forging companies, as material costs sum up to 50% for parts made of steel and up to 90% in other materials like titanium. For long products, cross wedge rolling (CWR) technology can be used to obtain forging preforms with a suitable distribution of the material along its own axis. However, defining the correct preform dimensions is not an easy task and it could need an intensive trial-and-error campaign. To speed up the preform definition, it is necessary to apply optimization techniques on Finite Element Models (FEM) able to reproduce the material behaviour when being rolled. Meta-models Assisted Evolution Strategies (MAES), that combine evolutionary algorithms with Kriging meta-models, are implemented in FORGE® software and they allow reducing optimization computation costs in a relevant way. The paper shows the application of these optimization techniques to the definition of the right preform for a shaft from a vehicle of the agricultural sector. First, the current forging process, based on obtaining the forging preform by means of an open die forging operation, is showed. Then, the CWR preform optimization is developed by using the above mentioned optimization techniques. The objective is to reduce, as much as possible, the initial billet weight, so that a calculation of flash weight reduction due to the use of the proposed preform is stated. Finally, a simulation of CWR process for the defined preform is carried out to check that most common failures (necking, spirals,..) in CWR do not appear in this case.

Integrated Traffic Flow Management Decision Making

NASA Technical Reports Server (NTRS)

Grabbe, Shon R.; Sridhar, Banavar; Mukherjee, Avijit

2009-01-01

A generalized approach is proposed to support integrated traffic flow management decision making studies at both the U.S. national and regional levels. It can consider tradeoffs between alternative optimization and heuristic based models, strategic versus tactical flight controls, and system versus fleet preferences. Preliminary testing was accomplished by implementing thirteen unique traffic flow management models, which included all of the key components of the system and conducting 85, six-hour fast-time simulation experiments. These experiments considered variations in the strategic planning look-ahead times, the replanning intervals, and the types of traffic flow management control strategies. Initial testing indicates that longer strategic planning look-ahead times and re-planning intervals result in steadily decreasing levels of sector congestion for a fixed delay level. This applies when accurate estimates of the air traffic demand, airport capacities and airspace capacities are available. In general, the distribution of the delays amongst the users was found to be most equitable when scheduling flights using a heuristic scheduling algorithm, such as ration-by-distance. On the other hand, equity was the worst when using scheduling algorithms that took into account the number of seats aboard each flight. Though the scheduling algorithms were effective at alleviating sector congestion, the tactical rerouting algorithm was the primary control for avoiding en route weather hazards. Finally, the modeled levels of sector congestion, the number of weather incursions, and the total system delays, were found to be in fair agreement with the values that were operationally observed on both good and bad weather days.

ERP System Implementation: An Oil and Gas Exploration Sector Perspective

NASA Astrophysics Data System (ADS)

Mishra, Alok; Mishra, Deepti

Enterprise Resource Planning (ERP) systems provide integration and optimization of various business processes which leads to improved planning and decision quality, smoother coordination between business units resulting in higher efficiency, and quicker response time to customer demands and inquiries. This paper reports challenges, opportunities and outcome of ERP implementation in Oil & Gas exploration sector. This study will facilitate in understanding transition, constraints and implementation of ERP in this sector and also provide guidelines from lessons learned in this regard.

Defense Expenditures in Pakistan: A Source of Stimulus for or Competition With the Private Sector

DTIC Science & Technology

1994-01-01

private sector activity, particularly investment, is the only viable option open to the authorities. It follows that for policy purposes the most important issue involves restructuring government expenditures and their financing in a manner that would provide the maximum inducement to private sector capital formation, especially in manufacturing. Operationally, this means finding an optimal balance between the government’s three most important budgetary items: defense, public consumption and infrastructural development. More importantly because

Health benefit modelling and optimization of vehicular pollution control strategies

NASA Astrophysics Data System (ADS)

Sonawane, Nayan V.; Patil, Rashmi S.; Sethi, Virendra

2012-12-01

This study asserts that the evaluation of pollution reduction strategies should be approached on the basis of health benefits. The framework presented could be used for decision making on the basis of cost effectiveness when the strategies are applied concurrently. Several vehicular pollution control strategies have been proposed in literature for effective management of urban air pollution. The effectiveness of these strategies has been mostly studied as a one at a time approach on the basis of change in pollution concentration. The adequacy and practicality of such an approach is studied in the present work. Also, the assessment of respective benefits of these strategies has been carried out when they are implemented simultaneously. An integrated model has been developed which can be used as a tool for optimal prioritization of various pollution management strategies. The model estimates health benefits associated with specific control strategies. ISC-AERMOD View has been used to provide the cause-effect relation between control options and change in ambient air quality. BenMAP, developed by U.S. EPA, has been applied for estimation of health and economic benefits associated with various management strategies. Valuation of health benefits has been done for impact indicators of premature mortality, hospital admissions and respiratory syndrome. An optimization model has been developed to maximize overall social benefits with determination of optimized percentage implementations for multiple strategies. The model has been applied for sub-urban region of Mumbai city for vehicular sector. Several control scenarios have been considered like revised emission standards, electric, CNG, LPG and hybrid vehicles. Reduction in concentration and resultant health benefits for the pollutants CO, NOx and particulate matter are estimated for different control scenarios. Finally, an optimization model has been applied to determine optimized percentage implementation of specific control strategies with maximization of social benefits, when these strategies are applied simultaneously.

Advising and Optimizing the Deployment of Sustainability-Oriented Technologies in the Integrated Electricity, Light-Duty Transportation, and Water Supply System

NASA Astrophysics Data System (ADS)

Tarroja, Brian

The convergence of increasing populations, decreasing primary resource availability, and uncertain climates have drawn attention to the challenge of shifting the operations of key resource sectors towards a sustainable paradigm. This is prevalent in California, which has set sustainability-oriented policies such as the Renewable Portfolio Standards and Zero-Emission Vehicle mandates. To meet these goals, many options have been identified to potentially carry out these shifts. The electricity sector is focusing on accommodating renewable power generation, the transportation sector on alternative fuel drivetrains and infrastructure, and the water supply sector on conservation, reuse, and unconventional supplies. Historical performance evaluations of these options, however, have not adequately taken into account the impacts on and constraints of co-dependent infrastructures that must accommodate them and their interactions with other simultaneously deployed options. These aspects are critical for optimally choosing options to meet sustainability goals, since the combined system of all resource sectors must satisfy them. Certain operations should not be made sustainable at the expense of rendering others as unsustainable, and certain resource sectors should not meet their individual goals in a way that hinders the ability of the entire system to do so. Therefore, this work develops and utilizes an integrated platform of the electricity, transportation, and water supply sectors to characterize the performance of emerging technology and management options while taking into account their impacts on co-dependent infrastructures and identify synergistic or detrimental interactions between the deployment of different options. This is carried out by first evaluating the performance of each option in the context of individual resource sectors to determine infrastructure impacts, then again in the context of paired resource sectors (electricity-transportation, electricity-water), and finally in the context of the combined tri-sector system. This allows a more robust basis for composing preferred option portfolios to meet sustainability goals and gives a direction for coordinating the paradigm shifts of different resource sectors. Overall, it is determined that taking into account infrastructure constraints and potential operational interactions can significantly change the evaluation of the preferred role that different technologies should fulfill in contributing towards satisfying sustainability goals in the holistic context.

Is the economic value of hydrological forecasts related to their quality? Case study of the hydropower sector.

NASA Astrophysics Data System (ADS)

Cassagnole, Manon; Ramos, Maria-Helena; Thirel, Guillaume; Gailhard, Joël; Garçon, Rémy

2017-04-01

The improvement of a forecasting system and the evaluation of the quality of its forecasts are recurrent steps in operational practice. However, the evaluation of forecast value or forecast usefulness for better decision-making is, to our knowledge, less frequent, even if it might be essential in many sectors such as hydropower and flood warning. In the hydropower sector, forecast value can be quantified by the economic gain obtained with the optimization of operations or reservoir management rules. Several hydropower operational systems use medium-range forecasts (up to 7-10 days ahead) and energy price predictions to optimize hydropower production. Hence, the operation of hydropower systems, including the management of water in reservoirs, is impacted by weather, climate and hydrologic variability as well as extreme events. In order to assess how the quality of hydrometeorological forecasts impact operations, it is essential to first understand if and how operations and management rules are sensitive to input predictions of different quality. This study investigates how 7-day ahead deterministic and ensemble streamflow forecasts of different quality might impact the economic gains of energy production. It is based on a research model developed by Irstea and EDF to investigate issues relevant to the links between quality and value of forecasts in the optimisation of energy production at the short range. Based on streamflow forecasts and pre-defined management constraints, the model defines the best hours (i.e., the hours with high energy prices) to produce electricity. To highlight the link between forecasts quality and their economic value, we built several synthetic ensemble forecasts based on observed streamflow time series. These inputs are generated in a controlled environment in order to obtain forecasts of different quality in terms of accuracy and reliability. These forecasts are used to assess the sensitivity of the decision model to forecast quality. Relationships between forecast quality and economic value are discussed. This work is part of the IMPREX project, a research project supported by the European Commission under the Horizon 2020 Framework programme, with grant No. 641811 (http://www.imprex.eu)

Integrated assessment of water-power grid systems under changing climate

NASA Astrophysics Data System (ADS)

Yan, E.; Zhou, Z.; Betrie, G.

2017-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. In this presentation, we are focusing on recent improvement in model development of thermoelectric power plant water use simulator, power grid operation and cost optimization model, and model integration that facilitate interaction among water and electricity generation under extreme climate events. A process based thermoelectric power water use simulator includes heat-balance, climate, and cooling system modules that account for power plant characteristics, fuel types, and cooling technology. The model is validated with more than 800 power plants of fossil-fired, nuclear and gas-turbine power plants with different cooling systems. The power grid operation and cost optimization model was implemented for a selected regional in the Midwest. The case study will be demonstrated to evaluate the sensitivity and resilience of thermoelectricity generation and power grid under various climate and hydrologic extremes and potential economic consequences.

Optimization of greenhouse gas emissions in second-hand consumer product recovery through reuse platforms.

PubMed

Fortuna, Lorena M; Diyamandoglu, Vasil

2017-08-01

Product reuse in the solid waste management sector is promoted as one of the key strategies for waste prevention. This practice is considered to have favorable impact on the environment, but its benefits have yet to be established. Existing research describes the perspective of "avoided production" only, but has failed to examine the interdependent nature of reuse practices within an entire solid waste management system. This study proposes a new framework that uses optimization to minimize the greenhouse gas emissions of an integrated solid waste management system that includes reuse strategies and practices such as reuse enterprises, online platforms, and materials exchanges along with traditional solid waste management practices such as recycling, landfilling, and incineration. The proposed framework uses material flow analysis in combination with an optimization model to provide the best outcome in terms of GHG emissions by redistributing product flows in the integrated solid waste management system to the least impacting routes and processes. The optimization results provide a basis for understanding the contributions of reuse to the environmental benefits of the integrated solid waste management system and the exploration of the effects of reuse activities on waste prevention. A case study involving second-hand clothing is presented to illustrate the implementation of the proposed framework as applied to the material flow. Results of the case study showed the considerable impact of reuse on GHG emissions even for small replacement rates, and helped illustrate the interdependency of the reuse sector with other waste management practices. One major contribution of this study is the development of a framework centered on product reuse that can be applied to identify the best management strategies to reduce the environmental impact of product disposal and to increase recovery of reusable products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Increased ice flow in Western Palmer Land linked to ocean melting

NASA Astrophysics Data System (ADS)

Hogg, Anna E.; Shepherd, Andrew; Cornford, Stephen L.; Briggs, Kate H.; Gourmelen, Noel; Graham, Jennifer A.; Joughin, Ian; Mouginot, Jeremie; Nagler, Thomas; Payne, Antony J.; Rignot, Eric; Wuite, Jan

2017-05-01

A decrease in the mass and volume of Western Palmer Land has raised the prospect that ice speed has increased in this marine-based sector of Antarctica. To assess this possibility, we measure ice velocity over 25 years using satellite imagery and an optimized modeling approach. More than 30 unnamed outlet glaciers drain the 800 km coastline of Western Palmer Land at speeds ranging from 0.5 to 2.5 m/d, interspersed with near-stagnant ice. Between 1992 and 2015, most of the outlet glaciers sped up by 0.2 to 0.3 m/d, leading to a 13% increase in ice flow and a 15 km3/yr increase in ice discharge across the sector as a whole. Speedup is greatest where glaciers are grounded more than 300 m below sea level, consistent with a loss of buttressing caused by ice shelf thinning in a region of shoaling warm circumpolar water.

Parametrization of turbulence models using 3DVAR data assimilation in laboratory conditions

NASA Astrophysics Data System (ADS)

Olbert, A. I.; Nash, S.; Ragnoli, E.; Hartnett, M.

2013-12-01

In this research the 3DVAR data assimilation scheme is implemented in the numerical model DIVAST in order to optimize the performance of the numerical model by selecting an appropriate turbulence scheme and tuning its parameters. Two turbulence closure schemes: the Prandtl mixing length model and the two-equation k-ɛ model were incorporated into DIVAST and examined with respect to their universality of application, complexity of solutions, computational efficiency and numerical stability. A square harbour with one symmetrical entrance subject to tide-induced flows was selected to investigate the structure of turbulent flows. The experimental part of the research was conducted in a tidal basin. A significant advantage of such laboratory experiment is a fully controlled environment where domain setup and forcing are user-defined. The research shows that the Prandtl mixing length model and the two-equation k-ɛ model, with default parameterization predefined according to literature recommendations, overestimate eddy viscosity which in turn results in a significant underestimation of velocity magnitudes in the harbour. The data assimilation of the model-predicted velocity and laboratory observations significantly improves model predictions for both turbulence models by adjusting modelled flows in the harbour to match de-errored observations. Such analysis gives an optimal solution based on which numerical model parameters can be estimated. The process of turbulence model optimization by reparameterization and tuning towards optimal state led to new constants that may be potentially applied to complex turbulent flows, such as rapidly developing flows or recirculating flows. This research further demonstrates how 3DVAR can be utilized to identify and quantify shortcomings of the numerical model and consequently to improve forecasting by correct parameterization of the turbulence models. Such improvements may greatly benefit physical oceanography in terms of understanding and monitoring of coastal systems and the engineering sector through applications in coastal structure design, marine renewable energy and pollutant transport.

Optimization of the production process using virtual model of a workspace

NASA Astrophysics Data System (ADS)

Monica, Z.

2015-11-01

Optimization of the production process is an element of the design cycle consisting of: problem definition, modelling, simulation, optimization and implementation. Without the use of simulation techniques, the only thing which could be achieved is larger or smaller improvement of the process, not the optimization (i.e., the best result it is possible to get for the conditions under which the process works). Optimization is generally management actions that are ultimately bring savings in time, resources, and raw materials and improve the performance of a specific process. It does not matter whether it is a service or manufacturing process. Optimizing the savings generated by improving and increasing the efficiency of the processes. Optimization consists primarily of organizational activities that require very little investment, or rely solely on the changing organization of work. Modern companies operating in a market economy shows a significant increase in interest in modern methods of production management and services. This trend is due to the high competitiveness among companies that want to achieve success are forced to continually modify the ways to manage and flexible response to changing demand. Modern methods of production management, not only imply a stable position of the company in the sector, but also influence the improvement of health and safety within the company and contribute to the implementation of more efficient rules for standardization work in the company. This is why in the paper is presented the application of such developed environment like Siemens NX to create the virtual model of a production system and to simulate as well as optimize its work. The analyzed system is the robotized workcell consisting of: machine tools, industrial robots, conveyors, auxiliary equipment and buffers. In the program could be defined the control program realizing the main task in the virtual workcell. It is possible, using this tool, to optimize both the object trajectory and the cooperation process.

Hydro-economic modeling of integrated solutions for the water-energy-land nexus in Africa

NASA Astrophysics Data System (ADS)

Parkinson, S.; Kahil, M.; Wada, Y.; Krey, V.; Byers, E.; Johnson, N. A.; Burek, P.; Satoh, Y.; Willaarts, B.; Langan, S.; Riahi, K.

2017-12-01

This study focused on the development of the Extended Continental-scale Hydro-economic Optimization model (ECHO) and its application to the analysis of long-term water, energy and land use pathways for Africa. The framework is important because it integrates multi-decadal decisions surrounding investments into new water infrastructure, electric power generation and irrigation technologies. The improved linkages in ECHO reveal synergies between water allocation strategies across sectors and the greenhouse gas emissions resulting from electricity supply. The African case study features a reduced-form transboundary river network and associated environmental flow constraints covering surface and groundwater withdrawals. Interactions between local water constraints and the continental-scale economy are captured in the model through the combination of regional electricity markets. Spatially-explicit analysis of land availability is used to restrict future reservoir expansion. The analysis demonstrates the massive investments required to ensure rapidly expanding water, energy and food demands in Africa aligned with human development objectives are met in a sustainable way. Modeled constraints on environmental flows in line with presumptive ecological guidelines trigger diffusion of energy-intensive water supply technologies in water-stressed regions, with implications for the cost and speed of the electricity sector decarbonization required to achieve climate targets.

Competing Air Quality and Water Conservation Co-benefits from Power Sector Decarbonization

NASA Astrophysics Data System (ADS)

Peng, W.; Wagner, F.; Mauzerall, D. L.; Ramana, M. V.; Zhai, H.; Small, M.; Zhang, X.; Dalin, C.

2016-12-01

Decarbonizing the power sector can reduce fossil-based generation and associated air pollution and water use. However, power sector configurations that prioritize air quality benefits can be different from those that maximize water conservation benefits. Despite extensive work to optimize the generation mix under an air pollution or water constraint, little research has examined electricity transmission networks and the choice of which fossil fuel units to displace in order to achieve both environmental objectives simultaneously. When air pollution and water stress occur in different regions, the optimal transmission and displacement decisions still depend on priorities placed on air quality and water conservation benefits even if low-carbon generation planning is fixed. Here we use China as a test case, and develop a new optimization framework to study transmission and displacement decisions and the resulting air quality and water use impacts for six power sector decarbonization scenarios in 2030 ( 50% of national generation is low carbon). We fix low-carbon generation in each scenario (e.g. type, location, quantity) and vary technology choices and deployment patterns across scenarios. The objective is to minimize the total physical costs (transmission costs and coal power generation costs) and the estimated environmental costs. Environmental costs are estimated by multiplying effective air pollutant emissions (EMeff, emissions weighted by population density) and effective water use (Weff, water use weighted by a local water stress index) by their unit economic values, Vem and Vw. We are hence able to examine the effect of varying policy priorities by imposing different combinations of Vem and Vw. In all six scenarios, we find that increasing the priority on air quality co-benefits (higher Vem) reduces air pollution impacts (lower EMeff) at the expense of lower water conservation (higher Weff); and vice versa. Such results can largely be explained by differences in optimal transmission decisions due to different locations of air pollution and water stress in China (severe in the east and north respectively). To achieve both co-benefits simultaneously, it is therefore critical to coordinate policies that reduce air pollution (pollution tax) and water use (water pricing) with power sector planning.

Cost versus life cycle assessment-based environmental impact optimization of drinking water production plants.

PubMed

Capitanescu, F; Rege, S; Marvuglia, A; Benetto, E; Ahmadi, A; Gutiérrez, T Navarrete; Tiruta-Barna, L

2016-07-15

Empowering decision makers with cost-effective solutions for reducing industrial processes environmental burden, at both design and operation stages, is nowadays a major worldwide concern. The paper addresses this issue for the sector of drinking water production plants (DWPPs), seeking for optimal solutions trading-off operation cost and life cycle assessment (LCA)-based environmental impact while satisfying outlet water quality criteria. This leads to a challenging bi-objective constrained optimization problem, which relies on a computationally expensive intricate process-modelling simulator of the DWPP and has to be solved with limited computational budget. Since mathematical programming methods are unusable in this case, the paper examines the performances in tackling these challenges of six off-the-shelf state-of-the-art global meta-heuristic optimization algorithms, suitable for such simulation-based optimization, namely Strength Pareto Evolutionary Algorithm (SPEA2), Non-dominated Sorting Genetic Algorithm (NSGA-II), Indicator-based Evolutionary Algorithm (IBEA), Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), Differential Evolution (DE), and Particle Swarm Optimization (PSO). The results of optimization reveal that good reduction in both operating cost and environmental impact of the DWPP can be obtained. Furthermore, NSGA-II outperforms the other competing algorithms while MOEA/D and DE perform unexpectedly poorly. Copyright © 2016 Elsevier Ltd. All rights reserved.

Assessment of air quality and climate co-benefits of decarbonisation of the UK energy system using remote sensing and model simulations - the case for prioritizing end uses in urban areas

NASA Astrophysics Data System (ADS)

Sobral Mourao, Zenaida; Konadu, Daniel Dennis; Damoah, Richard; Li, Pei-hao

2017-04-01

The UK has a binding obligation to reduce GHG emission by 80% (based on 1990 levels) by 2050. Meeting this target requires extensive decarbonisation of the UK energy system. Different pathways that achieve this target at the lowest system costs are being explored at different levels of policy and decisions on future energy infrastructure. Whilst benefits of decarbonisation are mainly focused on the impacts on climate change, there are other potential environmental and health impacts such as air-quality. In particular, a decrease in fossil fuel use by directly substituting current systems with low-carbon technologies could lead to significant reductions in the concentrations of SO2, NOX, CO and other atmospheric pollutants. So far, the proposed decarbonisation pathways tend to target the electricity sector first, followed by a transition in transport and heating technologies and use. However, the spatial dimension of where short term changes in the energy sector occur in relation to high density population areas is not taken into account when defining the energy transition strategies. This may lead to limited short-term improvements in air quality within urban areas, where use of fossil fuels for heating and transport is the main contribution to overall atmospheric pollutant levels. It is therefore imperative to explore decarbonisation strategies that prioritise transition in sectors of the energy system that produce immediate improvements in air quality in key regions of the UK. This study aims to use a combination of Remote Sensing observations and atmospheric chemistry/transport modelling approaches to estimate and map the impact on NOx of the traditional approach of decarbonising electricity first compared to a slower transition in the electricity sector, but faster change in the transport sector. This is done by generating a set of alternative energy system pathways with a higher share of zero emissions vehicles in 2030 than the energy system optimization model would choose if the only goal was the 80% GHG emissions reduction. Our overarching goal is to provide an additional standard to compare future energy system pathways beyond the traditional metrics of cost and GHG emissions reductions.

Modeling and optimization of a hybrid solar combined cycle (HYCS)

NASA Astrophysics Data System (ADS)

Eter, Ahmad Adel

2011-12-01

The main objective of this thesis is to investigate the feasibility of integrating concentrated solar power (CSP) technology with the conventional combined cycle technology for electric generation in Saudi Arabia. The generated electricity can be used locally to meet the annual increasing demand. Specifically, it can be utilized to meet the demand during the hours 10 am-3 pm and prevent blackout hours, of some industrial sectors. The proposed CSP design gives flexibility in the operation system. Since, it works as a conventional combined cycle during night time and it switches to work as a hybrid solar combined cycle during day time. The first objective of the thesis is to develop a thermo-economical mathematical model that can simulate the performance of a hybrid solar-fossil fuel combined cycle. The second objective is to develop a computer simulation code that can solve the thermo-economical mathematical model using available software such as E.E.S. The developed simulation code is used to analyze the thermo-economic performance of different configurations of integrating the CSP with the conventional fossil fuel combined cycle to achieve the optimal integration configuration. This optimal integration configuration has been investigated further to achieve the optimal design of the solar field that gives the optimal solar share. Thermo-economical performance metrics which are available in the literature have been used in the present work to assess the thermo-economic performance of the investigated configurations. The economical and environmental impact of integration CSP with the conventional fossil fuel combined cycle are estimated and discussed. Finally, the optimal integration configuration is found to be solarization steam side in conventional combined cycle with solar multiple 0.38 which needs 29 hectare and LEC of HYCS is 63.17 $/MWh under Dhahran weather conditions.

Leveraging the private health sector to enhance HIV service delivery in lower-income countries.

PubMed

Rao, Pamela; Gabre-Kidan, Tesfai; Mubangizi, Deus Bazira; Sulzbach, Sara

2011-08-01

Evidence that the private health sector is a key player in delivering health services and impacting health outcomes, including those related to HIV/AIDS, underscores the need to optimize the role of the private health sector to scale up national HIV responses in lower-income countries. This article reviews findings on the types of HIV/AIDS services provided by the private health sector in developing countries and elaborates on the role of private providers of HIV services in Ethiopia. Drawing on data from the nation's innovative Private Health Sector Project, a pilot project that has demonstrated the feasibility of public-private partnerships in this area, the article highlights the potential for national governments to scale up HIV/AIDS services by leveraging private health sector resources, innovations, and expertise while working to regulate quality and cost of services. Although concerns about uneven quality and affordability of private sector health services must be addressed through regulation, policy, or other innovative approaches, we argue that the benefits of leveraging the private sector outweigh these challenges, particularly in light of finite donor and public domestic resources.

A techno-economic model for optimum regeneration of surface mined land

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Manas K.; Sinha, Indra N.

2006-07-01

The recent global scenario in the mineral sector may be characterized by rising competitiveness, increasing production costs and a slump in market price. This has pushed the mineral sector in general and that in the developing countries in particular to a situation where the industry has a limited capacity to sustain unproductive costs. This, more often than not, results in a situation where the industry fails to ensure environmental safeguards during and after mineral extraction. The situation is conspicuous in the Indian coal mining industry where more than 73% production comes from surface operations. India has an ambitious power augmentation projection for the coming 10 years. A phenomenal increase in coal production is proposed from the power grade coalfields in India. One of the most likely fall-outs of land degradation due to mining in these areas would be significant reduction of agricultural and other important land-uses. Currently, backfilling costs are perceived as prohibitive and abandonment of land is the easy way out. This study attempts to provide mine planners with a mathematical model that distributes generated overburden at defined disposal options while ensuring maximization of backfilled land area at minimum direct and economic costs. Optimization has been accomplished by linear programming (LP) for optimum distribution of each year’s generated overburden. Previous year’s disposal quantity outputs are processed as one set of the inputs to the LP model for generation of current year’s disposal output. From various geo-mining inputs, site constants of the LP constraints are calculated. Arrived value of economic vectors, which guide the programming statement, decides the optimal overburden distribution in defined options. The case example (with model test run) indicates that overburden distribution is significantly sensitive to coal seam gradient. The model has universal applicability to cyclic system (shovel dumper combination) of opencast mining of stratified deposits.

Content analysis to locate assistive technology in Queensland's motor injury insurance rehabilitation legislation and guidelines.

PubMed

Steel, Emily J

2018-06-08

Reforms to Australia's disability and rehabilitation sectors have espoused the potential of assistive technology as an enabler. As new insurance systems are being developed it is timely to examine the structure of existing systems. This exploratory study examined the policies guiding assistive technology provision in the motor accident insurance sector of one Australian state. Policy documents were analyzed iteratively with set of qualitative questions to understand the intent and interpretation of policies guiding assistive technology provision. Content analysis identified relevant sections and meaningful terminology, and context analysis explored the dominant perspectives informing policy. The concepts and language of assistive technology are not part of the policy frameworks guiding rehabilitation practice in Queensland's motor accident insurance sector. The definition of rehabilitation in the legislation is consistent contemporary international interpretations that focus on optimizing functioning in interaction with the environment. However, the supporting documents are focused on recovery from injuries where decisions are guided by clinical need and affordability. The policies frame rehabilitation in a medical model that assistive technology provision from the rehabilitation plan. The legislative framework provides opportunities to develop and improve assistive technology provision as part of an integrated approach to rehabilitation.

Sectoral linkage analysis of three main air pollutants in China's industry: Comparing 2010 with 2002.

PubMed

He, Weiwei; Wang, Yuan; Zuo, Jian; Luo, Yincheng

2017-11-01

To investigate the driving forces of air pollution in China, the changes in linkages amongst inter-industrial air pollutant emissions were analyzed by hypothetical extraction method under the input-output framework. Results showed that the emissions of SO 2 , soot and dust from industrial sources increased by 56.46%, 36.95% and 11.69% respectively in 2010, compared with 2002. As major contributors to emissions, the power and gas sectors were responsible for the growing SO 2 emissions, the nonmetal products sector for soot emissions, and the metals mining, smelting and pressing sectors for dust emissions. The increasing volume of emissions was mainly driven by the growing demand in the transport equipment and electrical equipment sectors. In addition, the expansion in the metals mining, smelting and pressing sectors could result in even more severe air pollution. Therefore, potential effective strategies to control air pollution in China are: (1) reducing the demand of major import sectors in the equipment manufacturing industry; (2) promoting R&D in low-emissions-production technologies to the power and gas sectors, the metals mining, smelting and pressing sectors, and the nonmetal products sector, and (3) auditing the considerable industrial scale expansion in the metals mining, smelting and pressing sectors and optimizing the industrial structure. Copyright © 2017 Elsevier Ltd. All rights reserved.

Analysis of Different Cost Functions in the Geosect Airspace Partitioning Tool

NASA Technical Reports Server (NTRS)

Wong, Gregory L.

2010-01-01

A new cost function representing air traffic controller workload is implemented in the Geosect airspace partitioning tool. Geosect currently uses a combination of aircraft count and dwell time to select optimal airspace partitions that balance controller workload. This is referred to as the aircraft count/dwell time hybrid cost function. The new cost function is based on Simplified Dynamic Density, a measure of different aspects of air traffic controller workload. Three sectorizations are compared. These are the current sectorization, Geosect's sectorization based on the aircraft count/dwell time hybrid cost function, and Geosect s sectorization based on the Simplified Dynamic Density cost function. Each sectorization is evaluated for maximum and average workload along with workload balance using the Simplified Dynamic Density as the workload measure. In addition, the Airspace Concept Evaluation System, a nationwide air traffic simulator, is used to determine the capacity and delay incurred by each sectorization. The sectorization resulting from the Simplified Dynamic Density cost function had a lower maximum workload measure than the other sectorizations, and the sectorization based on the combination of aircraft count and dwell time did a better job of balancing workload and balancing capacity. However, the current sectorization had the lowest average workload, highest sector capacity, and the least system delay.

Stand-alone hybrid wind-photovoltaic power generation systems optimal sizing

NASA Astrophysics Data System (ADS)

Crǎciunescu, Aurelian; Popescu, Claudia; Popescu, Mihai; Florea, Leonard Marin

2013-10-01

Wind and photovoltaic energy resources have attracted energy sectors to generate power on a large scale. A drawback, common to these options, is their unpredictable nature and dependence on day time and meteorological conditions. Fortunately, the problems caused by the variable nature of these resources can be partially overcome by integrating the two resources in proper combination, using the strengths of one source to overcome the weakness of the other. The hybrid systems that combine wind and solar generating units with battery backup can attenuate their individual fluctuations and can match with the power requirements of the beneficiaries. In order to efficiently and economically utilize the hybrid energy system, one optimum match design sizing method is necessary. In this way, literature offers a variety of methods for multi-objective optimal designing of hybrid wind/photovoltaic (WG/PV) generating systems, one of the last being genetic algorithms (GA) and particle swarm optimization (PSO). In this paper, mathematical models of hybrid WG/PV components and a short description of the last proposed multi-objective optimization algorithms are given.

Creating a framework for the prioritization of biosecurity risks to the New Zealand dairy industry.

PubMed

Muellner, P; Hodges, D; Ahlstrom, C; Newman, M; Davidson, R; Pfeiffer, D; Marshall, J; Morley, C

2018-03-25

The New Zealand dairy sector relies on robust biosecurity measures to control and mitigate a wide range of threats to the industry. To optimize the prioritization of organisms and manage the risk they pose to the sector in a transparent and credible way, the Dairy Biosecurity Risk Evaluation Framework (D-BRiEF) was developed. This comprehensive framework was specifically designed for decision support, using a standardized approach to address the full spectrum of biosecurity threats to the sector, including exotic and endemic animal disease organisms, pest plants and insects. D-BRiEF is underpinned by three main processes, namely (i) hazard identification; (ii) multicriteria risk assessment; and (iii) communication for risk management. Expert knowledge and empirical data, including associated uncertainty, are harnessed in a standardized format. Results feed into a probability-impact model that was developed in close collaboration with dairy sector economists to provide overall comparative 10-year quantitative economic impact estimates for each assessed risk organism. A description of the overarching framework, which applies to diverse organism groups, is presented with detailed methodology on both endemic and exotic animal disease risk organisms. Examples of visual outputs are included, although actual ranking results are not reported due to industry confidentiality. D-BRiEF can provide a decision advantage to DairyNZ biosecurity risk managers and sector stakeholders by creating a transparent process that can be interrogated and updated at multiple levels to fully understand the layers of risk posed by different organisms. © 2018 Blackwell Verlag GmbH.

Assessment of utility side financial benefits of demand side management considering environmental impacts

NASA Astrophysics Data System (ADS)

Abeygunawardane, Saranga Kumudu

2018-02-01

Any electrical utility prefers to implement demand side management and change the shape of the demand curve in a beneficial manner. This paper aims to assess the financial gains (or losses) to the generating sector through the implementation of demand side management programs. An optimization algorithm is developed to find the optimal generation mix that minimizes the daily total generating cost. This daily total generating cost includes the daily generating cost as well as the environmental damage cost. The proposed optimization algorithm is used to find the daily total generating cost for the base case and for several demand side management programs using the data obtained from the Sri Lankan power system. Results obtained for DSM programs are compared with the results obtained for the base case to assess the financial benefits of demand side management to the generating sector.

An empirical model of the auroral oval derived from CHAMP field-aligned current signatures - Part 2

NASA Astrophysics Data System (ADS)

Xiong, C.; Lühr, H.

2014-06-01

In this paper we introduce a new model for the location of the auroral oval. The auroral boundaries are derived from small- and medium-scale field-aligned current (FAC) based on the high-resolution CHAMP (CHAllenging Minisatellite Payload) magnetic field observations during the years 2000-2010. The basic shape of the auroral oval is controlled by the dayside merging electric field, Em, and can be fitted well by ellipses at all levels of activity. All five ellipse parameters show a dependence on Em which can be described by quadratic functions. Optimal delay times for the merging electric field at the bow shock are 30 and 15 min for the equatorward and poleward boundaries, respectively. A comparison between our model and the British Antarctic Survey (BAS) auroral model derived from IMAGE (Imager for Magnetopause-to-Aurora Global Exploration) optical observations has been performed. There is good agreement between the two models regarding both boundaries, and the differences show a Gaussian distribution with a width of ±2° in latitude. The difference of the equatorward boundary shows a local-time dependence, which is 1° in latitude poleward in the morning sector and 1° equatorward in the afternoon sector of the BAS model. We think the difference between the two models is caused by the appearance of auroral forms in connection with upward FACs. All information required for applying our auroral oval model (CH-Aurora-2014) is provided.

The Inter-Sectoral Impact Model Intercomparison Project (ISI–MIP): Project framework

PubMed Central

Warszawski, Lila; Frieler, Katja; Huber, Veronika; Piontek, Franziska; Serdeczny, Olivia; Schewe, Jacob

2014-01-01

The Inter-Sectoral Impact Model Intercomparison Project offers a framework to compare climate impact projections in different sectors and at different scales. Consistent climate and socio-economic input data provide the basis for a cross-sectoral integration of impact projections. The project is designed to enable quantitative synthesis of climate change impacts at different levels of global warming. This report briefly outlines the objectives and framework of the first, fast-tracked phase of Inter-Sectoral Impact Model Intercomparison Project, based on global impact models, and provides an overview of the participating models, input data, and scenario set-up. PMID:24344316

Can marine protected areas enhance both economic and biological situations?

PubMed

Ami, Dominique; Cartigny, Pierre; Rapaport, Alain

2005-04-01

This paper investigates impacts of the creation of Marine Protected Areas (MPAs), in both economic and biological perspectives. The economic indicator is defined as the sum of discounted benefits derived from exploitation of the resource in the fishery sector, assumed to be optimally managed. The biological indicator is taken as the stock density of the resource. The basic fishery model (C.W. Clark, Mathematical Bioeconomics: The Optimal Management of Renewable Resources, second ed., John Wiley and Sons, New York, 1990) will serve as a convenient benchmark in comparing results with those that are derived from a model of two patchy populations (cf. R. Hannesson, Marine reserves: what would they accomplish, Mar. Resour. Econ. 13 (1998) 159). In the latter, a crucial characteristic is the migration coefficient with describes biological linkages between protected and unprotected areas. A set of situations where both economic and biological criteria are enhanced, after introducing a MPA, is presented. These results are obtained with the help of numerical simulations.

Water-Energy Nexus: Examining The Crucial Connection Through Simulation Based Optimization

NASA Astrophysics Data System (ADS)

Erfani, T.; Tan, C. C.

2014-12-01

With a growing urbanisation and the emergence of climate change, the world is facing a more water constrained future. This phenomenon will have direct impacts on the resilience and performance of energy sector as water is playing a key role in electricity generation processes. As energy is becoming a thirstier resource and the pressure on finite water sources is increasing, modelling and analysing this closely interlinked and interdependent loop, called 'water-energy nexus' is becoming an important cross-disciplinary challenge. Conflict often arises in transboundary river where several countries share the same source of water to be used in productive sectors for economic growth. From the perspective of the upstream users, it would be ideal to store the water for hydropower generation and protect the city against drought whereas the downstream users need the supply of water for growth. This research use the case study on the transboundary Blue Nile River basin located in the Middle East where the Ethiopian government decided to invest on building a new dam to store the water and generate hydropower. This leads to an opposition by downstream users as they believe that the introduction of the dam would reduce the amount of water available downstream. This calls for a compromise management where the reservoir operating rules need to be derived considering the interdependencies between the resources available and the requirements proposed by all users. For this, we link multiobjective optimization algorithm to water-energy use simulation model to achieve effective management of the transboundary reservoir operating strategies. The objective functions aim to attain social and economic welfare by minimizing the deficit of water supply and maximizing the hydropower generation. The study helps to improve the policies by understanding the value of water and energy in their alternative uses. The results show how different optimal reservoir release rules generate different trade-off solutions inherently involved in upstream and downstream users requirements and decisions. This study stimulates the research in this context by using simulation based optimization techniques to manage for security for food, water and energy generation, which leads to improve sustainability and long-term political stability.

Structure analysis of tax revenue and inflation rate in Banda Aceh using vector error correction model with multiple alpha

NASA Astrophysics Data System (ADS)

Sofyan, Hizir; Maulia, Eva; Miftahuddin

2017-11-01

A country has several important parameters to achieve economic prosperity, such as tax revenue and inflation rate. One of the largest revenues of the State Budget in Indonesia comes from the tax sector. Meanwhile, the rate of inflation occurring in a country can be used as an indicator, to measure the good and bad economic problems faced by the country. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the structure of tax revenue relations and inflation rate. This study aims to produce the best VECM (Vector Error Correction Model) with optimal lag using various alpha and perform structural analysis using the Impulse Response Function (IRF) of the VECM models to examine the relationship of tax revenue, and inflation in Banda Aceh. The results showed that the best model for the data of tax revenue and inflation rate in Banda Aceh City using alpha 0.01 is VECM with optimal lag 2, while the best model for data of tax revenue and inflation rate in Banda Aceh City using alpha 0.05 and 0,1 VECM with optimal lag 3. However, the VECM model with alpha 0.01 yielded four significant models of income tax model, inflation rate of Banda Aceh, inflation rate of health and inflation rate of education in Banda Aceh. While the VECM model with alpha 0.05 and 0.1 yielded one significant model that is income tax model. Based on the VECM models, then there are two structural analysis IRF which is formed to look at the relationship of tax revenue, and inflation in Banda Aceh, the IRF with VECM (2) and IRF with VECM (3).

Water footprint characteristic of less developed water-rich regions: Case of Yunnan, China.

PubMed

Qian, Yiying; Dong, Huijuan; Geng, Yong; Zhong, Shaozhuo; Tian, Xu; Yu, Yanhong; Chen, Yihui; Moss, Dana Avery

2018-03-30

Rapid industrialization and urbanization pose pressure on water resources in China. Virtual water trade proves to be an increasingly useful tool in water stress alleviation for water-scarce regions, while bringing opportunities and challenges for less developed water-rich regions. In this study, Yunnan, a typical province in southwest China, was selected as the case study area to explore its potential in socio-economic development in the context of water sustainability. Both input-output analysis and structural decomposition analysis on Yunnan's water footprint for the period of 2002-2012 were performed at not only an aggregated level but also a sectoral level. Results show that although the virtual water content of all economic sectors decreased due to technological progress, Yunnan's total water footprint still increased as a result of economic scale expansion. From the sectoral perspective, sectors with large water footprints include construction sector, agriculture sector, food manufacturing & processing sector, and service sector, while metal products sector and food manufacturing & processing sector were the major virtual water exporters, and textile & clothing sector and construction sector were the major importers. Based on local conditions, policy suggestions were proposed, including economic structure and efficiency optimization, technology promotion and appropriate virtual water trade scheme. This study provides valuable insights for regions facing "resource curse" by exploring potential socio-economic progress while ensuring water security. Copyright © 2018 Elsevier Ltd. All rights reserved.

Sampling and modeling of rock discontinuities by terrestrial laser scanning and photogrammetry in railway environment

NASA Astrophysics Data System (ADS)

Assali, P.; Grussenmeyer, P.; Pollet, N.; Viguier, F.; Villemin, T.

2012-04-01

In order to increase its knowledge of rock slope stability along the French national rail network, the SNCF Engineering Management is developing a new approach for sampling and modeling rock discontinuities. The rock face diagnosis is a follow-up and check operation of the field works. This operation allowed to optimize the rock risk treatment at the best price in respect with safety requirements. These operations require the measurement of orientation and location of rock discontinuities at the surface of the rock mass and is followed by a structural modeling in order to extrapolate the data collected at the surface to the inner part of the massif. At present, this work is completed manually with a compass-clinometer, in a simplified way mainly based on the specialist's experience. The analysis remains empirical, and most of the time restricted to the most fractured zone, whereas safety requirements ask for an exhaustive study on the whole of the site. Filling these gaps, the combined use of dense three-dimensional measurement techniques, associating both terrestrial laser scanning and optical imaging, makes it possible to obtain a more complete structural statement. The data acquisition and processing need protocols adapted to the railway environment for obtaining suitable 3D models. Then the exploitation of these models requires the development of semi-automatic process, with an aim of, to support the geologist's on-site expertise with a digital model exploitation. The geometrical characterization of the rock mass is undertaken thanks to a classification of the model in several subsets corresponding to the main directional families. The data on these planar discontinuities, traditionally acquired manually in certain points necessarily accessible of the rock face, result now from dense 3D models covering the whole of the work. Therefore, statistical sampling is stronger, while the time of the on-site survey is reduced. By these means, the diagnosis should be made reliable and the recommendations optimized with the unfavourable sectors. Then, risk analysis can be targeted on the potential disorders zones and not on the whole of the studied sector. Keywords : Discontinuities, fractures, railway exploitation, terrestrial laser-scanner, dense image matching, rock mass characterization, directional families, data processing

Battery management systems (BMS) optimization for electric vehicles (EVs) in Malaysia

NASA Astrophysics Data System (ADS)

Salehen, P. M. W.; Su'ait, M. S.; Razali, H.; Sopian, K.

2017-04-01

Following the UN Climate Change Conference 2009 in Copenhagen, Denmark, Malaysia seriously committed on "Go Green" campaign with the aim to reduce 40% GHG emission by the year 2020. Therefore, the National Green Technology Policy has been legalised in 2009 with transportation as one of its focused sectors, which include hybrid (HEVs), electric vehicles (EVs) and fuel cell vehicles with the purpose of to keep up with the worst scenario. While the number of registered cars has been increasing by 1 million yearly, the amount has doubled in the last two decades. Consequently, CO2 emission in Malaysia reaches up to 97.1% and will continue to increase mainly due to the activities in the transportation sector. Nevertheless, Malaysia is now moving towards on green car which battery-based EVs. This type of transportation mainly needs power performance optimization, which is controlled by the Batteries Management System (BMS). BMS is an essential module which leads to reliable power management, optimal power performance and safe vehicle that lead back for power optimization in EVs. Thus, this paper proposes power performance optimization for various setups of lithium-ion cathode with graphene anode using MATLAB/SIMULINK software for better management performance and extended EVs driving range.

A Comparative Analysis of Financial Reporting Models for Private and Public Sector Organizations.

DTIC Science & Technology

1995-12-01

The objective of this thesis was to describe and compare different existing and evolving financial reporting models used in both the public and...private sector. To accomplish the objective, this thesis identified the existing financial reporting models for private sector business organizations...private sector nonprofit organizations, and state and local governments, as well as the evolving financial reporting model for the federal government

Recent Advances in Stellarator Optimization

NASA Astrophysics Data System (ADS)

Gates, David; Brown, T.; Breslau, J.; Landreman, M.; Lazerson, S. A.; Mynick, H.; Neilson, G. H.; Pomphrey, N.

2016-10-01

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. One criticism that has been levelled at this method of design is the complexity of the resultant field coils. Recently, a new coil optimization code, COILOPT + + , was written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. We have also explored possibilities for generating an experimental database that could check whether the reduction in turbulent transport that is predicted by GENE as a function of local shear would be consistent with experiments. To this end, a series of equilibria that can be made in the now latent QUASAR experiment have been identified. This work was supported by U.S. DoE Contract #DE-AC02-09CH11466.

Imaging the Chicxulub central crater zone from large scale seismic acoustic wave propagation and gravity modeling

NASA Astrophysics Data System (ADS)

Fucugauchi, J. U.; Ortiz-Aleman, C.; Martin, R.

2017-12-01

Large complex craters are characterized by central uplifts that represent large-scale differential movement of deep basement from the transient cavity. Here we investigate the central sector of the large multiring Chicxulub crater, which has been surveyed by an array of marine, aerial and land-borne geophysical methods. Despite high contrasts in physical properties,contrasting results for the central uplift have been obtained, with seismic reflection surveys showing lack of resolution in the central zone. We develop an integrated seismic and gravity model for the main structural elements, imaging the central basement uplift and melt and breccia units. The 3-D velocity model built from interpolation of seismic data is validated using perfectly matched layer seismic acoustic wave propagation modeling, optimized at grazing incidence using shift in the frequency domain. Modeling shows significant lack of illumination in the central sector, masking presence of the central uplift. Seismic energy remains trapped in an upper low velocity zone corresponding to the sedimentary infill, melt/breccias and surrounding faulted blocks. After conversion of seismic velocities into a volume of density values, we use massive parallel forward gravity modeling to constrain the size and shape of the central uplift that lies at 4.5 km depth, providing a high-resolution image of crater structure.The Bouguer anomaly and gravity response of modeled units show asymmetries, corresponding to the crater structure and distribution of post-impact carbonates, breccias, melt and target sediments

Household water demand and welfare loss for future Europe

NASA Astrophysics Data System (ADS)

Bernhard, Jeroen; Reynaud, Arnaud; Lanzanova, Denis; de Roo, Ad

2015-04-01

Matching the availability of water to its demand in Europe is a major challenge for the future due to expected economic and demographic developments and climate change. This means there is a growing need to estimate future water demand and to optimize the water allocation to all end users to counteract welfare loss. At the European scale it is currently not possible to assess the impact of social and economic changes on future water demand or to prioritize water allocation amongst different sectors based on economic damage without extensive use of assumptions and generalizations. Indeed, our review of existing regional optimization models for Europe reveals that the social-economic component of the water use system needs to be improved by complementing them with detailed water use estimates and cost/benefit functions in order to determine the optimal situation. Our study contributes to closing this knowledge gap for the European household sector by quantifying future water demand and the effect of water pricing, as well as providing a method for the calculation of monetary damage due to unmet demand at the highest spatial resolution possible. We used a water demand function approach in which household water consumption depends upon some exogenous drivers including water price, household income, population and household characteristics and climate conditions. For each European country, the annual water consumption per capita was calculated at regional level (NUTS3) and subsequently disaggregated to five kilometer grid level based on a population density map. In order to produce estimates of water demand, the evolution of the explanatory variables of the water demand functions and population density map were simulated until 2050 based on related variables such as GDP and demographic projections. The results of this study will be integrated into the JRC hydro-economic modelling framework for an assessment of the Water-Agriculture-Energy-Ecosystems Nexus.

Innovation evaluation model for macro-construction sector companies: A study in Spain.

PubMed

Zubizarreta, Mikel; Cuadrado, Jesús; Iradi, Jon; García, Harkaitz; Orbe, Aimar

2017-04-01

The innovativeness of the traditional construction sector, composed of construction companies or contractors, is not one of its strong points. Likewise, its poor productivity in comparison with other sectors, such as manufacturing, has historically been criticized. Similar features are found in the Spanish traditional construction sector, which it has been described as not very innovative. However, certain characteristics of the sector may explain this behavior; the companies invest in R+D less than in other sectors and release fewer patents, so traditional innovation evaluation indicators do not reflect the true extent of its innovative activity. While previous research has focused on general innovation evaluation models, limited research has been done regarding innovation evaluation in the macro-construction sector, which includes, apart from the traditional construction companies or contractors, all companies related to the infrastructure life-cycle. Therefore, in this research an innovation evaluation model has been developed for macro-construction sector companies and is applied in the Spanish case. The model may be applied to the macro-construction sector companies in other countries, requiring the adaption of the model to the specific characteristics of the sector in that country, in consultation with a panel of experts at a national level. Copyright © 2016 Elsevier Ltd. All rights reserved.

Building a Comprehensive Mill-Level Database for the Industrial Sectors Integrated Solutions (ISIS) Model of the U.S. Pulp and Paper Sector

EPA Science Inventory

The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant sector-based analyses that are performed in conjunction with ...

Optimal water resources management and system benefit for the Marcellus shale-gas reservoir in Pennsylvania and West Virginia

NASA Astrophysics Data System (ADS)

Cheng, Xi; He, Li; Lu, Hongwei; Chen, Yizhong; Ren, Lixia

2016-09-01

A major concern associated with current shale-gas extraction is high consumption of water resources. However, decision-making problems regarding water consumption and shale-gas extraction have not yet been solved through systematic approaches. This study develops a new bilevel optimization problem based on goals at two different levels: minimization of water demands at the lower level and maximization of system benefit at the upper level. The model is used to solve a real-world case across Pennsylvania and West Virginia. Results show that surface water would be the largest contributor to gas production (with over 80.00% from 2015 to 2030) and groundwater occupies for the least proportion (with less than 2.00% from 2015 to 2030) in both districts over the planning span. Comparative analysis between the proposed model and conventional single-level models indicates that the bilevel model could provide coordinated schemes to comprehensively attain the goals from both water resources authorities and energy sectors. Sensitivity analysis shows that the change of water use of per unit gas production (WU) has significant effects upon system benefit, gas production and pollutants (i.e., barium, chloride and bromide) discharge, but not significantly changes water demands.

Interval Optimization Model Considering Terrestrial Ecological Impacts for Water Rights Transfer from Agriculture to Industry in Ningxia, China.

PubMed

Sun, Lian; Li, Chunhui; Cai, Yanpeng; Wang, Xuan

2017-06-14

In this study, an interval optimization model is developed to maximize the benefits of a water rights transfer system that comprises industry and agriculture sectors in the Ningxia Hui Autonomous Region in China. The model is subjected to a number of constraints including water saving potential from agriculture and ecological groundwater levels. Ecological groundwater levels serve as performance indicators of terrestrial ecology. The interval method is applied to present the uncertainty of parameters in the model. Two scenarios regarding dual industrial development targets (planned and unplanned ones) are used to investigate the difference in potential benefits of water rights transfer. Runoff of the Yellow River as the source of water rights fluctuates significantly in different years. Thus, compensation fees for agriculture are calculated to reflect the influence of differences in the runoff. Results show that there are more available water rights to transfer for industrial development. The benefits are considerable but unbalanced between buyers and sellers. The government should establish a water market that is freer and promote the interest of agriculture and farmers. Though there has been some success of water rights transfer, the ecological impacts and the relationship between sellers and buyers require additional studies.

Economic consequences of population size, structure and growth.

PubMed

Lee, R

1983-01-01

There seems to be 4 major approaches to conceptualizing and modeling demographic influences on economic and social welfare. These approaches are combined in various ways to construct richer and more comprehensive models. The basic approaches are: demographic influences on household or family behavior; population growth and reproducible capital; population size and fixed factors; and population and advantages of scale. These 4 models emphasize the supply side effects of population. A few of the ways in which these theories have been combined are sketched. Neoclassical growth models often have been combined with age distributed populations of individuals (or households), assumed to pursue optimal life cycle consumption and saving. In some well known development models, neoclassical growth models for the modern sector are linked by labor markets and migration to fixed factor (land) models of the traditional (agricultural) sector. A whole series of macro simulation models for developed and developing countries was based on single sector neoclassical growth models with age distributed populations. Yet, typically the household level foundations of assumed age distribution effects were not worked out. Simon's (1977) simulation models are in a class by themselves, for they are the only models that attempt to incorporate all the kinds of effects discussed. The economic demography of the individual and family cycle, as it is affected by regimes of fertility, mortality, and nuptiality, taken as given, are considered. The examination touches on many of the purported consequences of aggregate population growth and age composition, since so many of these are based implicitly or explicitly on assertions about micro level behavior. Demographic influences on saving and consumption, on general labor supply and female labor supply, and on problems of youth and old age dependency frequently fall in this category. Finally, attention is focused specifically on macro economic issues in the consequences of population in both developed and developing countries. In general cross national studies have failed to provide rough and stylized depiction of the consequences of rapid population growth, unless the absence of significant results is itself the result.

Assimilative modeling of low latitude ionosphere

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Wang, Chunining; Hajj, George A.; Rosen, I. Gary; Wilson, Brian D.; Mannucci, Anthony J.

2004-01-01

In this paper we present an observation system simulation experiment for modeling low-latitude ionosphere using a 3-dimensional (3-D) global assimilative ionospheric model (GAIM). The experiment is conducted to test the effectiveness of GAIM with a 4-D variational approach (4DVAR) in estimation of the ExB drift and thermospheric wind in the magnetic meridional planes simultaneously for all longitude or local time sectors. The operational Global Positioning System (GPS) satellites and the ground-based global GPS receiver network of the International GPS Service are used in the experiment as the data assimilation source. 'The optimization of the ionospheric state (electron density) modeling is performed through a nonlinear least-squares minimization process that adjusts the dynamical forces to reduce the difference between the modeled and observed slant total electron content in the entire modeled region. The present experiment for multiple force estimations reinforces our previous assessment made through single driver estimations conducted for the ExB drift only.

Building a comprehensive mill-level database for the Industrial Sectors Integrated Solutions (ISIS) model of the U.S. pulp and paper sector.

PubMed

Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann

2015-01-01

Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector.

Building a Comprehensive Mill-Level Database for the Industrial Sectors Integrated Solutions (ISIS) Model of the U.S. Pulp and Paper Sector

PubMed Central

Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann

2015-01-01

Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector. PMID:25806516

Hydrogen Energy Storage and Power-to-Gas: Establishing Criteria for Successful Business Cases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eichman, Joshua; Melaina, Marc

As the electric sector evolves and increasing amounts of variable generation are installed on the system, there are greater needs for system flexibility, sufficient capacity and greater concern for overgeneration. As a result there is growing interest in exploring the role of energy storage and demand response technologies to support grid needs. Hydrogen is a versatile feedstock that can be used in a variety of applications including chemical and industrial processes, as well as a transportation fuel and heating fuel. Traditionally, hydrogen technologies focus on providing services to a single sector; however, participating in multiple sectors has the potential tomore » provide benefits to each sector and increase the revenue for hydrogen technologies. The goal of this work is to explore promising system configurations for hydrogen systems and the conditions that will make for successful business cases in a renewable, low-carbon future. Current electricity market data, electric and gas infrastructure data and credit and incentive information are used to perform a techno-economic analysis to identify promising criteria and locations for successful hydrogen energy storage and power-to-gas projects. Infrastructure data will be assessed using geographic information system applications. An operation optimization model is used to co-optimizes participation in energy and ancillary service markets as well as the sale of hydrogen. From previous work we recognize the great opportunity that energy storage and power-to-gas but there is a lack of information about the economic favorability of such systems. This work explores criteria for selecting locations and compares the system cost and potential revenue to establish competitiveness for a variety of equipment configurations. Hydrogen technologies offer unique system flexibility that can enable interactions between multiple energy sectors including electric, transport, heating fuel and industrial. Previous research established that hydrogen technologies, and in particular electrolyzers, can respond fast enough and for sufficient duration to participate in electricity markets. This work recognizes that participation in electricity markets and integration with the gas system can enhance the revenue streams available for hydrogen storage systems and quantifies the economic competitiveness and of these systems. A few of the key results include 1) the most valuable revenue stream for hydrogen systems is to sell the produced hydrogen, 2) participation in both energy and ancillary service markets yields the greatest revenue and 3) electrolyzers acting as demand response devices are particularly favorable.« less

Estimation of Scale Deposition in the Water Walls of an Operating Indian Coal Fired Boiler: Predictive Modeling Approach Using Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Kumari, Amrita; Das, Suchandan Kumar; Srivastava, Prem Kumar

2016-04-01

Application of computational intelligence for predicting industrial processes has been in extensive use in various industrial sectors including power sector industry. An ANN model using multi-layer perceptron philosophy has been proposed in this paper to predict the deposition behaviors of oxide scale on waterwall tubes of a coal fired boiler. The input parameters comprises of boiler water chemistry and associated operating parameters, such as, pH, alkalinity, total dissolved solids, specific conductivity, iron and dissolved oxygen concentration of the feed water and local heat flux on boiler tube. An efficient gradient based network optimization algorithm has been employed to minimize neural predictions errors. Effects of heat flux, iron content, pH and the concentrations of total dissolved solids in feed water and other operating variables on the scale deposition behavior have been studied. It has been observed that heat flux, iron content and pH of the feed water have a relatively prime influence on the rate of oxide scale deposition in water walls of an Indian boiler. Reasonably good agreement between ANN model predictions and the measured values of oxide scale deposition rate has been observed which is corroborated by the regression fit between these values.

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model

NASA Astrophysics Data System (ADS)

Voisin, Nathalie; Hejazi, Mohamad I.; Leung, L. Ruby; Liu, Lu; Huang, Maoyi; Li, Hong-Yi; Tesfa, Teklu

2017-05-01

Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.

Cyber Security Audit and Attack Detection Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peterson, Dale

2012-05-31

This goal of this project was to develop cyber security audit and attack detection tools for industrial control systems (ICS). Digital Bond developed and released a tool named Bandolier that audits ICS components commonly used in the energy sector against an optimal security configuration. The Portaledge Project developed a capability for the PI Historian, the most widely used Historian in the energy sector, to aggregate security events and detect cyber attacks.

Conceptual Design of Optimized Fossil Energy Systems with Capture and Sequestration of Carbon Dioxide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nils Johnson; Joan Ogden

2010-12-31

In this final report, we describe research results from Phase 2 of a technical/economic study of fossil hydrogen energy systems with carbon dioxide (CO{sub 2}) capture and storage (CCS). CO{sub 2} capture and storage, or alternatively, CO{sub 2} capture and sequestration, involves capturing CO{sub 2} from large point sources and then injecting it into deep underground reservoirs for long-term storage. By preventing CO{sub 2} emissions into the atmosphere, this technology has significant potential to reduce greenhouse gas (GHG) emissions from fossil-based facilities in the power and industrial sectors. Furthermore, the application of CCS to power plants and hydrogen production facilitiesmore » can reduce CO{sub 2} emissions associated with electric vehicles (EVs) and hydrogen fuel cell vehicles (HFCVs) and, thus, can also improve GHG emissions in the transportation sector. This research specifically examines strategies for transitioning to large-scale coal-derived energy systems with CCS for both hydrogen fuel production and electricity generation. A particular emphasis is on the development of spatially-explicit modeling tools for examining how these energy systems might develop in real geographic regions. We employ an integrated modeling approach that addresses all infrastructure components involved in the transition to these energy systems. The overall objective is to better understand the system design issues and economics associated with the widespread deployment of hydrogen and CCS infrastructure in real regions. Specific objectives of this research are to: Develop improved techno-economic models for all components required for the deployment of both hydrogen and CCS infrastructure, Develop novel modeling methods that combine detailed spatial data with optimization tools to explore spatially-explicit transition strategies, Conduct regional case studies to explore how these energy systems might develop in different regions of the United States, and Examine how the design and cost of coal-based H{sub 2} and CCS infrastructure depend on geography and location.« less

Accelerated reforms in healthcare financing: the need to scale up private sector participation in Nigeria.

PubMed

Ejughemre, Ufuoma John

2014-01-01

The health sector, a foremost service sector in Nigeria, faces a number of challenges; primarily, the persistent under-funding of the health sector by the Nigerian government as evidence reveals low allocations to the health sector and poor health system performance which are reflected in key health indices of the country.Notwithstanding, there is evidence that the private sector could be a key player in delivering health services and impacting health outcomes, including those related to healthcare financing. This underscores the need to optimize the role of private sector in complementing the government's commitment to financing healthcare delivery and strengthening the health system in Nigeria. There are also concerns about uneven quality and affordability of private-driven health systems, which necessitates reforms aimed at regulation. Accordingly, the argument is that the benefits of leveraging the private sector in complementing the national government in healthcare financing outweigh the challenges, particularly in light of lean public resources and finite donor supports. This article, therefore, highlights the potential for the Nigerian government to scale up healthcare financing by leveraging private resources, innovations and expertise, while working to achieve the universal health coverage.

Signaling mechanisms underlying the robustness and tunability of the plant immune network

PubMed Central

Kim, Yungil; Tsuda, Kenichi; Igarashi, Daisuke; Hillmer, Rachel A.; Sakakibara, Hitoshi; Myers, Chad L.; Katagiri, Fumiaki

2014-01-01

Summary How does robust and tunable behavior emerge in a complex biological network? We sought to understand this for the signaling network controlling pattern-triggered immunity (PTI) in Arabidopsis. A dynamic network model containing four major signaling sectors, the jasmonate, ethylene, PAD4, and salicylate sectors, which together explain up to 80% of the PTI level, was built using data for dynamic sector activities and PTI levels under exhaustive combinatorial sector perturbations. Our regularized multiple regression model had a high level of predictive power and captured known and unexpected signal flows in the network. The sole inhibitory sector in the model, the ethylene sector, was central to the network robustness via its inhibition of the jasmonate sector. The model's multiple input sites linked specific signal input patterns varying in strength and timing to different network response patterns, indicating a mechanism enabling tunability. PMID:24439900

Tax revenue and inflation rate predictions in Banda Aceh using Vector Error Correction Model (VECM)

NASA Astrophysics Data System (ADS)

Maulia, Eva; Miftahuddin; Sofyan, Hizir

2018-05-01

A country has some important parameters to achieve the welfare of the economy, such as tax revenues and inflation. One of the largest revenues of the state budget in Indonesia comes from the tax sector. Besides, the rate of inflation occurring in a country can be used as one measure, to measure economic problems that the country facing. Given the importance of tax revenue and inflation rate control in achieving economic prosperity, it is necessary to analyze the relationship and forecasting tax revenue and inflation rate. VECM (Vector Error Correction Model) was chosen as the method used in this research, because of the data used in the form of multivariate time series data. This study aims to produce a VECM model with optimal lag and to predict the tax revenue and inflation rate of the VECM model. The results show that the best model for data of tax revenue and the inflation rate in Banda Aceh City is VECM with 3rd optimal lag or VECM (3). Of the seven models formed, there is a significant model that is the acceptance model of income tax. The predicted results of tax revenue and the inflation rate in Kota Banda Aceh for the next 6, 12 and 24 periods (months) obtained using VECM (3) are considered valid, since they have a minimum error value compared to other models.

The Commercial Energy Consumer: About Whom Are We Speaking?

DOE Office of Scientific and Technical Information (OSTI.GOV)

Payne, Christopher

2006-05-12

Who are commercial sector customers, and how do they make decisions about energy consumption and energy efficiency investment? The energy policy field has not done a thorough job of describing energy consumption in the commercial sector. First, the discussion of the commercial sector itself is dominated by discussion of large businesses/buildings. Second, discussion of this portion of the commercial sectors consumption behavior is driven primarily by theory, with very little field data collected on the way commercial sector decision-makers describe their own options, choices, and reasons for taking action. These limitations artificially constrain energy policy options. This paper reviews themore » extant literature on commercial sector energy consumption behavior and identifies gaps in our knowledge. In particular, it argues that the primary energy policy model of commercial sector energy consumption is a top-down model that uses macro-level investment data to make conclusions about commercial behavior. Missing from the discussion is a model of consumption behavior that builds up to a theoretical framework informed by the micro-level data provided by commercial decision-makers themselves. Such a bottom-up model could enhance the effectiveness of commercial sector energy policy. In particular, translation of some behavioral models from the residential sector to the commercial sector may offer new opportunities for policies to change commercial energy consumption behavior. Utility bill consumption feedback is considered as one example of a policy option that may be applicable to both the residential and small commercial sector.« less

Cost-effectiveness analysis of policy instruments for greenhouse gas emission mitigation in the agricultural sector.

PubMed

Bakam, Innocent; Balana, Bedru Babulo; Matthews, Robin

2012-12-15

Market-based policy instruments to reduce greenhouse gas (GHG) emissions are generally considered more appropriate than command and control tools. However, the omission of transaction costs from policy evaluations and decision-making processes may result in inefficiency in public resource allocation and sub-optimal policy choices and outcomes. This paper aims to assess the relative cost-effectiveness of market-based GHG mitigation policy instruments in the agricultural sector by incorporating transaction costs. Assuming that farmers' responses to mitigation policies are economically rationale, an individual-based model is developed to study the relative performances of an emission tax, a nitrogen fertilizer tax, and a carbon trading scheme using farm data from the Scottish farm account survey (FAS) and emissions and transaction cost data from literature metadata survey. Model simulations show that none of the three schemes could be considered the most cost effective in all circumstances. The cost effectiveness depends both on the tax rate and the amount of free permits allocated to farmers. However, the emissions trading scheme appears to outperform both other policies in realistic scenarios. Copyright © 2012 Elsevier Ltd. All rights reserved.

Modeling the sustainable development of innovation in transport construction based on the communication approach

NASA Astrophysics Data System (ADS)

Revunova, Svetlana; Vlasenko, Vyacheslav; Bukreev, Anatoly

2017-10-01

The article proposes the models of innovative activity development, which is driven by the formation of “points of innovation-driven growth”. The models are based on the analysis of the current state and dynamics of innovative development of construction enterprises in the transport sector and take into account a number of essential organizational and economic changes in management. The authors substantiate implementing such development models as an organizational innovation that has a communication genesis. The use of the communication approach to the formation of “points of innovation-driven growth” allowed the authors to apply the mathematical tools of the graph theory in order to activate the innovative activity of the transport industry in the region. As a result, the authors have proposed models that allow constructing an optimal mechanism for the formation of “points of innovation-driven growth”.

Maturation of biomass-to-biofuels conversion technology pathways for rapid expansion of biofuels production: A system dynamics perspective

DOE PAGES

Vimmerstedt, Laura J.; Bush, Brian W.; Hsu, Dave D.; ...

2014-08-12

The Biomass Scenario Model (BSM) is a system-dynamics simulation model intended to explore the potential for rapid expansion of the biofuels industry. The model is not predictive — it uses scenario assumptions based on various types of data to simulate industry development, emphasizing how incentives and technological learning-by-doing might accelerate industry growth. The BSM simulates major sectors of the biofuels industry, including feedstock production and logistics, conversion, distribution, and end uses, as well as interactions among sectors. The model represents conversion of biomass to biofuels as a set of technology pathways, each of which has allowable feedstocks, capital and operatingmore » costs, allowable products, and other defined characteristics. This study and the BSM address bioenergy modeling analytic needs that were identified in recent literature reviews. Simulations indicate that investments are most effective at expanding biofuels production through learning-by-doing when they are coordinated with respect to timing, pathway, and target sector within the biofuels industry. Effectiveness metrics include timing and magnitude of increased production, incentive cost and cost effectiveness, and avoidance of windfall profits. Investment costs and optimal investment targets have inherent risks and uncertainties, such as the relative value of investment in more-mature versus less mature pathways. These can be explored through scenarios, but cannot be precisely predicted. Dynamic competition, including competition for cellulosic feedstocks and ethanol market shares, intensifies during times of rapid growth. Ethanol production increases rapidly, even up to Renewable Fuel Standards-targeted volumes of biofuel, in simulations that allow higher blending proportions of ethanol in gasoline-fueled vehicles. Published 2014. This document is a U.S. Government work and is in the public domain in the USA. Biofuels, Bioproducts, Biorefining published by John Wiley & Sons, Ltd on behalf of Society of Chemical Industry.« less

Decomposing climate-induced temperature and water effects on the expansion and operation of the US electricity system

NASA Astrophysics Data System (ADS)

Sun, Y.; Eurek, K.; Macknick, J.; Steinberg, D. C.; Averyt, K.; Badger, A.; Livneh, B.

2017-12-01

Climate change has the potential to affect the supply and demands of the U.S. power sector. Rising air temperatures can affect the seasonal and total demand for electricity, alter the thermal efficiency of power plants, and lower the maximum capacity of electric transmission lines. Changes in hydrology can affect seasonal and total availability of water used for power plant operations. Prior studies have examined some climate impacts on the electricity sector, but there has been no systematic study quantifying and comparing the importance of these climate-induced effects in isolation and in combination. Here, we perform a systematic assessment using the Regional Energy Deployment System (ReEDS) electricity sector model in combination with downscaled climate results from four models in the CMIP5 archive that provide contrasting temperature and precipitation trends for key regions in the U.S. The ReEDS model captures dynamic climate and hydrological resource data .when choosing the cost optimal mix of generation resources necessary to balance supply and demand for electricity. We examine how different climate-induced changes in air temperature and water availability, considered in isolation and in combination, may affect energy and economic outcomes at a regional and national level from the present through 2050. Results indicate that temperature-induced impacts on electricity consumption show consistent trends nationwide across all climate scenarios. Hydrological impacts and variability differ by model and tend to have a minor effect on national electricity trends, but can be important determinants regionally. Taken together, this suggests that isolated climate change impacts on the electricity system depend on the geographic scale of interest - the effect of rising temperatures on demand, which is qualitatively robust to the choice of climate model, largely determines impacts on generation, capacity and cost at the national level, whereas other impact pathways may dominate at regional level.

Dynamic bottleneck elimination in mattress manufacturing line using theory of constraints.

PubMed

Gundogar, Emin; Sari, Murat; Kokcam, Abdullah H

2016-01-01

There is a tough competition in the furniture sector like other sectors. Along with the varying product range, production system should also be renewed on a regular basis and the production costs should be kept under control. In this study, spring mattress manufacturing line of a furniture manufacturing company is analyzed. The company wants to increase its production output with new investments. The objective is to find the bottlenecks in production line in order to balance the semi-finished material flow. These bottlenecks are investigated and several different scenarios are tested to improve the current manufacturing system. The problem with a main theme based on the elimination of the bottleneck is solved using Goldratt and Cox's theory of constraints with a simulation based heuristic method. Near optimal alternatives are determined by system models built in Arena 13.5 simulation software. Results show that approximately 46 % capacity enhancements with 2 buffer stocks have increased average production by 88.8 %.

Bridging the gap between evidence-based innovation and national health-sector reform in Ghana.

PubMed

Awoonor-Williams, John Koku; Feinglass, Ellie S; Tobey, Rachel; Vaughan-Smith, Maya N; Nyonator, Frank K; Jones, Tanya C

2004-09-01

Although experimental trials often identify optimal strategies for improving community health, transferring operational innovation from well-funded research programs to resource-constrained settings often languishes. Because research initiatives are based in institutions equipped with unique resources and staff capabilities, results are often dismissed by decisionmakers as irrelevant to large-scale operations and national health policy. This article describes an initiative undertaken in Nkwanta District, Ghana, focusing on this problem. The Nkwanta District initiative is a critical link between the experimental study conducted in Navrongo, Ghana, and a national effort to scale up the innovations developed in that study. A 2002 Nkwanta district-level survey provides the basis for assessing the likelihood that the Navrongo model is replicable elsewhere in Ghana. The effect of community-based health planning and services exposure on family planning and safe-motherhood indicators supports the hypothesis that Navrongo effects are transferable to impoverished rural settings elsewhere, confirming the need for strategies to bridge the gap between Navrongo evidence-based innovation and national health-sector reform.

Integrated modeling approach for optimal management of water, energy and food security nexus

NASA Astrophysics Data System (ADS)

Zhang, Xiaodong; Vesselinov, Velimir V.

2017-03-01

Water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-period socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. The obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.

Activities of the NASA sponsored SRI technology applications team in transferring aerospace technology to the public sector

NASA Technical Reports Server (NTRS)

Berke, J. G.

1971-01-01

The organization and functions of an interdisciplinary team for the application of aerospace generated technology to the solution of discrete technological problems within the public sector are presented. The interdisciplinary group formed at Stanford Research Institute, California is discussed. The functions of the group are to develop and conduct a program not only optimizing the match between public sector technological problems in criminalistics, transportation, and the postal services and potential solutions found in the aerospace data base, but ensuring that appropriate solutions are acutally utilized. The work accomplished during the period from July 1, 1970 to June 30, 1971 is reported.

Design search and optimization in aerospace engineering.

PubMed

Keane, A J; Scanlan, J P

2007-10-15

In this paper, we take a design-led perspective on the use of computational tools in the aerospace sector. We briefly review the current state-of-the-art in design search and optimization (DSO) as applied to problems from aerospace engineering, focusing on those problems that make heavy use of computational fluid dynamics (CFD). This ranges over issues of representation, optimization problem formulation and computational modelling. We then follow this with a multi-objective, multi-disciplinary example of DSO applied to civil aircraft wing design, an area where this kind of approach is becoming essential for companies to maintain their competitive edge. Our example considers the structure and weight of a transonic civil transport wing, its aerodynamic performance at cruise speed and its manufacturing costs. The goals are low drag and cost while holding weight and structural performance at acceptable levels. The constraints and performance metrics are modelled by a linked series of analysis codes, the most expensive of which is a CFD analysis of the aerodynamics using an Euler code with coupled boundary layer model. Structural strength and weight are assessed using semi-empirical schemes based on typical airframe company practice. Costing is carried out using a newly developed generative approach based on a hierarchical decomposition of the key structural elements of a typical machined and bolted wing-box assembly. To carry out the DSO process in the face of multiple competing goals, a recently developed multi-objective probability of improvement formulation is invoked along with stochastic process response surface models (Krigs). This approach both mitigates the significant run times involved in CFD computation and also provides an elegant way of balancing competing goals while still allowing the deployment of the whole range of single objective optimizers commonly available to design teams.

Economic and environmental costs of regulatory uncertainty for coal-fired power plants.

PubMed

Patiño-Echeverri, Dalia; Fischbeck, Paul; Kriegler, Elmar

2009-02-01

Uncertainty about the extent and timing of CO2 emissions regulations for the electricity-generating sector exacerbates the difficulty of selecting investment strategies for retrofitting or alternatively replacing existent coal-fired power plants. This may result in inefficient investments imposing economic and environmental costs to society. In this paper, we construct a multiperiod decision model with an embedded multistage stochastic dynamic program minimizing the expected total costs of plant operation, installations, and pollution allowances. We use the model to forecast optimal sequential investment decisions of a power plant operator with and without uncertainty about future CO2 allowance prices. The comparison of the two cases demonstrates that uncertainty on future CO2 emissions regulations might cause significant economic costs and higher air emissions.

A 4D-optimization concept for scanned ion beam therapy.

PubMed

Graeff, Christian; Lüchtenborg, Robert; Eley, John Gordon; Durante, Marco; Bert, Christoph

2013-12-01

Scanned carbon beam therapy offers advantageous dose distributions and an increased biological effect. Treating moving targets is complex due to sensitivity to range changes and interplay. We propose a 4D treatment planning concept that considers motion during particle number optimization. The target was subdivided into sectors, one for each motion phase of a 4D-CT. Each sector was non-rigidly transformed to its motion phase and there targeted by a dedicated raster field (RST). Therefore, the resulting 4D-RST compensated target motion and range changes. A 4D treatment control system (TCS) was needed for synchronized delivery to the measured patient motion. 4D-optimized plans were simulated for 9 NSCLC lung cancer patients and compared to static irradiation at end-exhale. A prototype TCS was implemented and successfully tested in a film experiment. The 4D-optimized treatment plan resulted in only slightly lower dose coverage of the target compared to static optimization, with V 95% of 97.9% (median, range 96.5-99.4%) vs. 99.3% (98.5-99.8%), with negligible overdose. The conformity number was comparable at 88.2% (85.1-92.5%) vs. 85.2% (79.9-91.2%) for 4D and static, respectively. We implemented and tested a 4D treatment plan optimization method resulting in highly conformal dose delivery. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Modeling water resources as a constraint in electricity capacity expansion models

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Macknick, J.; Cohen, S.; Tidwell, V. C.; Woldeyesus, T.; Martinez, A.

2013-12-01

In the United States, the electric power sector is the largest withdrawer of freshwater in the nation. The primary demand for water from the electricity sector is for thermoelectric power plant cooling. Areas likely to see the largest near-term growth in population and energy usage, the Southwest and the Southeast, are also facing freshwater scarcity and have experienced water-related power reliability issues in the past decade. Lack of water may become a barrier for new conventionally-cooled power plants, and alternative cooling systems will impact technology cost and performance. Although water is integral to electricity generation, it has long been neglected as a constraint in future electricity system projections. Assessing the impact of water resource scarcity on energy infrastructure development is critical, both for conventional and renewable energy technologies. Efficiently utilizing all water types, including wastewater and brackish sources, or utilizing dry-cooling technologies, will be essential for transitioning to a low-carbon electricity system. This work provides the first demonstration of a national electric system capacity expansion model that incorporates water resources as a constraint on the current and future U.S. electricity system. The Regional Electricity Deployment System (ReEDS) model was enhanced to represent multiple cooling technology types and limited water resource availability in its optimization of electricity sector capacity expansion to 2050. The ReEDS model has high geographic and temporal resolution, making it a suitable model for incorporating water resources, which are inherently seasonal and watershed-specific. Cooling system technologies were assigned varying costs (capital, operations and maintenance), and performance parameters, reflecting inherent tradeoffs in water impacts and operating characteristics. Water rights supply curves were developed for each of the power balancing regions in ReEDS. Supply curves include costs and availability of freshwater (surface and groundwater) and alternative water resources (municipal wastewater and brackish groundwater). In each region, a new power plant must secure sufficient water rights for operation before being built. Water rights constraints thus influence the type of power plant, cooling system, or location of new generating capacity. Results indicate that the aggregate national generating capacity by fuel type and associated carbon dioxide emissions change marginally with the inclusion of water rights. Water resource withdrawals and consumption, however, can vary considerably. Regional water resource dynamics indicate substantial differences in the location where power plant-cooling system technology combinations are built. These localized impacts highlight the importance of considering water resources as a constraint in the electricity sector when evaluating costs, transmission infrastructure needs, and externalities. Further scenario evaluations include assessments of how climate change could affect the availability of water resources, and thus the development of the electricity sector.

Building and testing models with extended Higgs sectors

NASA Astrophysics Data System (ADS)

Ivanov, Igor P.

2017-07-01

Models with non-minimal Higgs sectors represent a mainstream direction in theoretical exploration of physics opportunities beyond the Standard Model. Extended scalar sectors help alleviate difficulties of the Standard Model and lead to a rich spectrum of characteristic collider signatures and astroparticle consequences. In this review, we introduce the reader to the world of extended Higgs sectors. Not pretending to exhaustively cover the entire body of literature, we walk through a selection of the most popular examples: the two- and multi-Higgs-doublet models, as well as singlet and triplet extensions. We will show how one typically builds models with extended Higgs sectors, describe the main goals and the challenges which arise on the way, and mention some methods to overcome them. We will also describe how such models can be tested, what are the key observables one focuses on, and illustrate the general strategy with a subjective selection of results.

Climate change impact modelling needs to include cross-sectoral interactions

NASA Astrophysics Data System (ADS)

Harrison, Paula A.; Dunford, Robert W.; Holman, Ian P.; Rounsevell, Mark D. A.

2016-09-01

Climate change impact assessments often apply models of individual sectors such as agriculture, forestry and water use without considering interactions between these sectors. This is likely to lead to misrepresentation of impacts, and consequently to poor decisions about climate adaptation. However, no published research assesses the differences between impacts simulated by single-sector and integrated models. Here we compare 14 indicators derived from a set of impact models run within single-sector and integrated frameworks across a range of climate and socio-economic scenarios in Europe. We show that single-sector studies misrepresent the spatial pattern, direction and magnitude of most impacts because they omit the complex interdependencies within human and environmental systems. The discrepancies are particularly pronounced for indicators such as food production and water exploitation, which are highly influenced by other sectors through changes in demand, land suitability and resource competition. Furthermore, the discrepancies are greater under different socio-economic scenarios than different climate scenarios, and at the sub-regional rather than Europe-wide scale.

Regulatory acceptance and use of 3R models for pharmaceuticals and chemicals: expert opinions on the state of affairs and the way forward.

PubMed

Schiffelers, Marie-Jeanne W A; Blaauboer, Bas J; Bakker, Wieger E; Beken, Sonja; Hendriksen, Coenraad F M; Koëter, Herman B W M; Krul, Cyrille

2014-06-01

Pharmaceuticals and chemicals are subjected to regulatory safety testing accounting for approximately 25% of laboratory animal use in Europe. This testing meets various objections and has led to the development of a range of 3R models to Replace, Reduce or Refine the animal models. However, these models must overcome many barriers before being accepted for regulatory risk management purposes. This paper describes the barriers and drivers and options to optimize this acceptance process as identified by two expert panels, one on pharmaceuticals and one on chemicals. To untangle the complex acceptance process, the multilevel perspective on technology transitions is applied. This perspective defines influences at the micro-, meso- and macro level which need alignment to induce regulatory acceptance of a 3R model. This paper displays that there are many similar mechanisms within both sectors that prevent 3R models from becoming accepted for regulatory risk assessment and management. Shared barriers include the uncertainty about the value of the new 3R models (micro level), the lack of harmonization of regulatory requirements and acceptance criteria (meso level) and the high levels of risk aversion (macro level). In optimizing the process commitment, communication, cooperation and coordination are identified as critical drivers. Copyright © 2014 Elsevier Inc. All rights reserved.

Balancing ecosystem services with energy and food security - assessing trade-offs for reservoir operation and irrigation investment in Kenya's Tana basin

NASA Astrophysics Data System (ADS)

Hurford, A. P.; Harou, J. J.

2014-01-01

Competition for water between key economic sectors and the environment means agreeing on allocation is challenging. Managing releases from the three major dams in Kenya's Tana River basin with its 4.4 million inhabitants, 567 MW of installed hydropower capacity, 33 000 ha of irrigation and ecologically important wetlands and forests is a pertinent example. This research seeks to identify and help decision-makers visualise reservoir management strategies which result in the best possible (Pareto-optimal) allocation of benefits between sectors. Secondly we seek to show how trade-offs between achievable benefits shift with the implementation of new proposed rice, cotton and biofuel irrigation projects. To identify the Pareto-optimal trade-offs we link a water resources management model to a multi-criteria search algorithm. The decisions or "levers" of the management problem are volume dependent release rules for the three major dams and extent of investment in new irrigation schemes. These decisions are optimised for objectives covering provision of water supply and irrigation, energy generation and maintenance of ecosystem services which underpin tourism and local livelihoods. Visual analytic plots allow decision makers to assess multi-reservoir rule-sets by understanding their impacts on different beneficiaries. Results quantify how economic gains from proposed irrigation schemes trade-off against disturbance of the flow regime which supports ecosystem services. Full implementation of the proposed schemes is shown to be Pareto-optimal, but at high environmental and social cost. The clarity and comprehensiveness of "best-case" trade-off analysis is a useful vantage point from which to tackle the interdependence and complexity of water-energy-food "nexus" challenges.

Simultaneous personnel and vehicle shift scheduling in the waste management sector.

PubMed

Ghiani, Gianpaolo; Guerriero, Emanuela; Manni, Andrea; Manni, Emanuele; Potenza, Agostino

2013-07-01

Urban waste management is becoming an increasingly complex task, absorbing a huge amount of resources, and having a major environmental impact. The design of a waste management system consists in various activities, and one of these is related to the definition of shift schedules for both personnel and vehicles. This activity has a great incidence on the tactical and operational cost for companies. In this paper, we propose an integer programming model to find an optimal solution to the integrated problem. The aim is to determine optimal schedules at minimum cost. Moreover, we design a fast and effective heuristic to face large-size problems. Both approaches are tested on data from a real-world case in Southern Italy and compared to the current practice utilized by the company managing the service, showing that simultaneously solving these problems can lead to significant monetary savings. Copyright © 2013 Elsevier Ltd. All rights reserved.

Role of emerging private hospitals in a post-Soviet mixed health system: a mixed methods comparative study of private and public hospital inpatient care in Mongolia.

PubMed

Tsevelvaanchig, Uranchimeg; Gouda, Hebe; Baker, Peter; Hill, Peter S

2017-05-01

The collapse of the Soviet Union in 1990 severely impacted the health sector in Mongolia. Limited public funding for the post-Soviet model public system and a rapid growth of poorly regulated private providers have been pressing issues for a government seeking to re-establish universal health coverage. However, the evidence available on the role of private providers that would inform sector management is very limited. This study analyses the current contribution of private hospitals in Mongolia for the improvement of accessibility of health care and efficiency. We used mixed research methods. A descriptive analysis of nationally representative hospital admission records from 2013 was followed by semi-structured interviews that were carried out with purposively selected key informants (N = 45), representing the main actors in Mongolia's mixed health system. Private-for-profit hospitals are concentrated in urban areas, where their financial model is most viable. The result is the duplication of private and public inpatient services, both in terms of their geographical location and the range of services delivered. The combination of persistent inpatient-oriented care and perverse financial incentives that privilege admission over outpatient management, have created unnecessary health costs. The engagement of the private sector to improve population health outcomes is constrained by a series of issues of governance, regulation and financing and the failure of the state to manage the private sector as an integral part of its health system planning. For a mixed system like in Mongolia, a comprehensive policy and plan which defines the complementary role of private providers to optimize private public service mix is critical in the early stages of the private sector development. It further supports the importance of a system perspective that combines regulation and incentives in consistent policy, rather than an isolated approach to provide regulation. © The Author 2016. 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

Network simulation modeling of equine infectious anemia in the non-racehorse population in Japan.

PubMed

Hayama, Yoko; Kobayashi, Sota; Nishida, Takeshi; Muroga, Norihiko; Tsutsui, Toshiyuki

2012-01-01

An equine infectious anemia (EIA) transmission model was developed by constructing a network structure of horse movement patterns in a non-racehorse population. This model was then used to evaluate the effectiveness and efficiency of several EIA surveillance strategies. Because EIA had not been detected in Japan since 1993, it was appropriate to review the current surveillance strategy, which aims to eradicate EIA by intensive testing, and to consider alternative strategies suitable for the current EIA status in Japan. The non-racehorse population was divided into four sectors based on horse usage: the equestrian sector, private owner sector, exhibition sector, and fattening sector. To evaluate the risk of disease spread within and between sectors accompanied by horse movements, a stochastic individual-based network model was developed based on a previous survey of horse movement patterns. Surveillance parameters such as targeting sectors and frequency of testing were added into the model to compare surveillance strategies. The disease spread heterogeneously among sectors. Infection occurred mainly in the equestrian sector; the infection was less disseminated in other sectors. Therefore, we considered that the equestrian sector posed a higher risk of disease dissemination within and between sectors through horse movements. However, surveillance strategies targeting only the equestrian sector were not effective enough for early detection of the disease. Alternatively, targeting horses that moved permanently and those in the private owner sector in addition to the equestrian sector is recommended to achieve effectiveness equivalent to that of the current surveillance. In terms of surveillance efficacy, by increasing the testing interval (once yearly to once every 3 years), this testing scheme could reduce the number of tested horses to 44% of the current surveillance, while maintaining almost equivalent effectiveness. Intensive strategies targeting high-risk populations are considered to enhance effectiveness and efficiency of surveillance. The approach in this study may be helpful in the decision-making process that is involved in setting up strategies for risk-based surveillance. Copyright © 2011 Elsevier B.V. All rights reserved.

Empirical support for global integrated assessment modeling: Productivity trends and technological change in developing countries' agriculture and electric power sectors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sathaye, Jayant A.

2000-04-01

Integrated assessment (IA) modeling of climate policy is increasingly global in nature, with models incorporating regional disaggregation. The existing empirical basis for IA modeling, however, largely arises from research on industrialized economies. Given the growing importance of developing countries in determining long-term global energy and carbon emissions trends, filling this gap with improved statistical information on developing countries' energy and carbon-emissions characteristics is an important priority for enhancing IA modeling. Earlier research at LBNL on this topic has focused on assembling and analyzing statistical data on productivity trends and technological change in the energy-intensive manufacturing sectors of five developing countries,more » India, Brazil, Mexico, Indonesia, and South Korea. The proposed work will extend this analysis to the agriculture and electric power sectors in India, South Korea, and two other developing countries. They will also examine the impact of alternative model specifications on estimates of productivity growth and technological change for each of the three sectors, and estimate the contribution of various capital inputs--imported vs. indigenous, rigid vs. malleable-- in contributing to productivity growth and technological change. The project has already produced a data resource on the manufacturing sector which is being shared with IA modelers. This will be extended to the agriculture and electric power sectors, which would also be made accessible to IA modeling groups seeking to enhance the empirical descriptions of developing country characteristics. The project will entail basic statistical and econometric analysis of productivity and energy trends in these developing country sectors, with parameter estimates also made available to modeling groups. The parameter estimates will be developed using alternative model specifications that could be directly utilized by the existing IAMs for the manufacturing, agriculture, and electric power sectors.« less

Market Intelligence Guide

DTIC Science & Technology

2012-01-05

learn about the latest designs , trends in fashion, and scientific breakthroughs in chair ergonomics . Using this tradeshow, the Furnishings Commodity...these tools is essential to designing the optimal contract that reaps the most value from the exchange. Therefore, this market intelligence guide is...portfolio matrix) that are transferrable to the not-for-profit sector are absent. Each of these tools is essential to designing the optimal contract that

Optimizing a Query by Transformation and Expansion.

PubMed

Glocker, Katrin; Knurr, Alexander; Dieter, Julia; Dominick, Friederike; Forche, Melanie; Koch, Christian; Pascoe Pérez, Analie; Roth, Benjamin; Ückert, Frank

2017-01-01

In the biomedical sector not only the amount of information produced and uploaded into the web is enormous, but also the number of sources where these data can be found. Clinicians and researchers spend huge amounts of time on trying to access this information and to filter the most important answers to a given question. As the formulation of these queries is crucial, automated query expansion is an effective tool to optimize a query and receive the best possible results. In this paper we introduce the concept of a workflow for an optimization of queries in the medical and biological sector by using a series of tools for expansion and transformation of the query. After the definition of attributes by the user, the query string is compared to previous queries in order to add semantic co-occurring terms to the query. Additionally, the query is enlarged by an inclusion of synonyms. The translation into database specific ontologies ensures the optimal query formulation for the chosen database(s). As this process can be performed in various databases at once, the results are ranked and normalized in order to achieve a comparable list of answers for a question.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

DOE PAGES

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-24

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Hidden Sector Dark Matter and the Galactic Center Gamma-Ray Excess: A Closer Look

DOE Office of Scientific and Technical Information (OSTI.GOV)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-09-20

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

NASA Astrophysics Data System (ADS)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

2017-11-01

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case, we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. We also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.

Hidden sector dark matter and the Galactic Center gamma-ray excess: a closer look

DOE Office of Scientific and Technical Information (OSTI.GOV)

Escudero, Miguel; Witte, Samuel J.; Hooper, Dan

Stringent constraints from direct detection experiments and the Large Hadron Collider motivate us to consider models in which the dark matter does not directly couple to the Standard Model, but that instead annihilates into hidden sector particles which ultimately decay through small couplings to the Standard Model. We calculate the gamma-ray emission generated within the context of several such hidden sector models, including those in which the hidden sector couples to the Standard Model through the vector portal (kinetic mixing with Standard Model hypercharge), through the Higgs portal (mixing with the Standard Model Higgs boson), or both. In each case,more » we identify broad regions of parameter space in which the observed spectrum and intensity of the Galactic Center gamma-ray excess can easily be accommodated, while providing an acceptable thermal relic abundance and remaining consistent with all current constraints. Here, we also point out that cosmic-ray antiproton measurements could potentially discriminate some hidden sector models from more conventional dark matter scenarios.« less

Social influence, agent heterogeneity and the emergence of the urban informal sector

NASA Astrophysics Data System (ADS)

García-Díaz, César; Moreno-Monroy, Ana I.

2012-02-01

We develop an agent-based computational model in which the urban informal sector acts as a buffer where rural migrants can earn some income while queuing for higher paying modern-sector jobs. In the model, the informal sector emerges as a result of rural-urban migration decisions of heterogeneous agents subject to social influence in the form of neighboring effects of varying strengths. Besides using a multinomial logit choice model that allows for agent idiosyncrasy, explicit agent heterogeneity is introduced in the form of socio-demographic characteristics preferred by modern-sector employers. We find that different combinations of the strength of social influence and the socio-economic composition of the workforce lead to very different urbanization and urban informal sector shares. In particular, moderate levels of social influence and a large proportion of rural inhabitants with preferred socio-demographic characteristics are conducive to a higher urbanization rate and a larger informal sector.

Assessing Inter-Sectoral Climate Change Risks: The Role of ISIMIP

NASA Technical Reports Server (NTRS)

Rosenzweig, Cynthia; Arnell, Nigel W.; Ebi, Kristie L.; Lotze-Campen, Hermann; Raes, Frank; Rapley, Chris; Smith, Mark Stafford; Cramer, Wolfgang; Frieler, Katja; Reyer, Christopher P. O.;

Modeling climate change impacts on the forest sector

Treesearch

John R. Mills; Ralph Alig; Richard W. Haynes; Darius M. Adams

2000-01-01

The forest sector has had a relatively long history of applying sectorial models to estimate the effects of atmospheric issues such as acid rain, climate change, and the forestry impacts of reduced atmospheric ozone. The models of the forest sector vary in scope and complexity but share a number of common features and databases.

Modelling inflation in transportation, comunication and financial services using B-Spline time series model

NASA Astrophysics Data System (ADS)

Suparti; Prahutama, Alan; Santoso, Rukun

2018-05-01

Inflation is an increase in the price of goods and services in general where the goods and services are the basic needs of society or the decline of the selling power of a country’s currency. Significant inflationary increases occurred in 2013. This increase was contributed by a significant increase in some inflation sectors / groups i.e transportation, communication and financial services; the foodstuff sector, and the housing, water, electricity, gas and fuel sectors. However, significant contributions occurred in the transportation, communications and financial services sectors. In the model of IFIs in the transportation, communication and financial services sector use the B-Spline time series approach, where the predictor variable is Yt, whereas the predictor is a significant lag (in this case Yt-1). In modeling B-spline time series determined the order and the optimum knot point. Optimum knot determination using Generalized Cross Validation (GCV). In inflation modeling for transportation sector, communication and financial services obtained model of B-spline order 2 with 2 points knots produce MAPE less than 50%.

Integrated modeling for assessment of energy-water system resilience under changing climate

NASA Astrophysics Data System (ADS)

Yan, E.; Veselka, T.; Zhou, Z.; Koritarov, V.; Mahalik, M.; Qiu, F.; Mahat, V.; Betrie, G.; Clark, C.

2016-12-01

Energy and water systems are intrinsically interconnected. Due to an increase in climate variability and extreme weather events, interdependency between these two systems has been recently intensified resulting significant impacts on both systems and energy output. To address this challenge, an Integrated Water-Energy Systems Assessment Framework (IWESAF) is being developed to integrate multiple existing or developed models from various sectors. The IWESAF currently includes an extreme climate event generator to predict future extreme weather events, hydrologic and reservoir models, riverine temperature model, power plant water use simulator, and power grid operation and cost optimization model. The IWESAF can facilitate the interaction among the modeling systems and provide insights of the sustainability and resilience of the energy-water system under extreme climate events and economic consequence. The regional case demonstration in the Midwest region will be presented. The detailed information on some of individual modeling components will also be presented in several other abstracts submitted to AGU this year.

Balancing exploration, uncertainty and computational demands in many objective reservoir optimization

NASA Astrophysics Data System (ADS)

Zatarain Salazar, Jazmin; Reed, Patrick M.; Quinn, Julianne D.; Giuliani, Matteo; Castelletti, Andrea

2017-11-01

Reservoir operations are central to our ability to manage river basin systems serving conflicting multi-sectoral demands under increasingly uncertain futures. These challenges motivate the need for new solution strategies capable of effectively and efficiently discovering the multi-sectoral tradeoffs that are inherent to alternative reservoir operation policies. Evolutionary many-objective direct policy search (EMODPS) is gaining importance in this context due to its capability of addressing multiple objectives and its flexibility in incorporating multiple sources of uncertainties. This simulation-optimization framework has high potential for addressing the complexities of water resources management, and it can benefit from current advances in parallel computing and meta-heuristics. This study contributes a diagnostic assessment of state-of-the-art parallel strategies for the auto-adaptive Borg Multi Objective Evolutionary Algorithm (MOEA) to support EMODPS. Our analysis focuses on the Lower Susquehanna River Basin (LSRB) system where multiple sectoral demands from hydropower production, urban water supply, recreation and environmental flows need to be balanced. Using EMODPS with different parallel configurations of the Borg MOEA, we optimize operating policies over different size ensembles of synthetic streamflows and evaporation rates. As we increase the ensemble size, we increase the statistical fidelity of our objective function evaluations at the cost of higher computational demands. This study demonstrates how to overcome the mathematical and computational barriers associated with capturing uncertainties in stochastic multiobjective reservoir control optimization, where parallel algorithmic search serves to reduce the wall-clock time in discovering high quality representations of key operational tradeoffs. Our results show that emerging self-adaptive parallelization schemes exploiting cooperative search populations are crucial. Such strategies provide a promising new set of tools for effectively balancing exploration, uncertainty, and computational demands when using EMODPS.

Analyzing the Long Term Cohesive Effect of Sector Specific Driving Forces.

PubMed

Berman, Yonatan; Ben-Jacob, Eshel; Zhang, Xin; Shapira, Yoash

2016-01-01

Financial markets are partially composed of sectors dominated by external driving forces, such as commodity prices, infrastructure and other indices. We characterize the statistical properties of such sectors and present a novel model for the coupling of the stock prices and their dominating driving forces, inspired by mean reverting stochastic processes. Using the model we were able to explain the market sectors' long term behavior and estimate the coupling strength between stocks in financial markets and the sector specific driving forces. Notably, the analysis was successfully applied to the shipping market, in which the Baltic dry index (BDI), an assessment of the price of transporting the major raw materials by sea, influences the shipping financial market. We also present the analysis of other sectors-the gold mining market and the food production market, for which the model was also successfully applied. The model can serve as a general tool for characterizing the coupling between external forces and affected financial variables and therefore for estimating the risk in sectors and their vulnerability to external stress.

Materials and Waste Management Research

EPA Pesticide Factsheets

EPA is developing data and tools to reduce waste, manage risks, reuse and conserve natural materials, and optimize energy recovery. Collaboration with states facilitates assessment and utilization of technologies developed by the private sector.

Disparate British Breast Reconstruction Utilization: Is Universal Coverage Sufficient to Ensure Expanded Care?

PubMed Central

Offodile, Anaeze C.

2016-01-01

Summary: Our intent is to improve the understanding of the ability of healthcare providers to deliver high-quality care as we approach an era of universal coverage. We adopted 2 unique vantage points in this article: (1) the mandated coverage for immediate breast reconstruction (IBR) surgery as a microcosmic surrogate for universal coverage overall and (2) we then scrutinized the respective IBR utilization rates in a contemporaneous system of 2 healthcare delivery models in the United Kingdom, that is, the public National Health Service trust versus private-sector hospitals. A literature review was performed for IBR rates across public trust and private-sector hospitals in the United Kingdom. The IBR rate among public trust hospitals was 17% compared with 43% in the private sector. In the trust hospital setting, the enactment of 2 government mandates, intended to increase the access to cancer care, seemed to fall short in maximizing the ability of surgical practitioners to deliver quality care to patients. Among women who did not receive IBR, 65% felt that they had received the sufficient amount of information to appropriately inform their decision. In addition, only 46% of this same cohort reported a consultation with a reconstructive surgeon preoperatively. Private-sector hospitals delivered better IBR care because of the likely presence of infrastructure and financial incentives for physicians. These results serve as a call for a better alignment between policy initiatives designed to expand care access and the perogatives of physicians to ensure an optimized delivery of the expanded care such policy mandates. PMID:27482486

Life quality and living standards in big cities under conditions of high-rise construction development

NASA Astrophysics Data System (ADS)

Avdeeva, Elena; Averina, Tatiana; Kochetova, Larisa

2018-03-01

Modern urbanization processes occurring on a global scale inevitably lead to an increase in population density in large cities. People assess the state of life quality and living standards of megalopolises under conditions of high-rise construction development ambiguously. Using SWOT analysis, the authors distinguished positive and negative aspects of high-rise construction, highlighted threats to its development and its opportunities. The article considers the model of development of the city's industry and infrastructure, which enables determining the optimal volume of production by sectors and branches of city economy in order to increase its innovative, production and economic potential and business activity.

Exploring harmonization between integrated assessment and capacity expansion models

NASA Astrophysics Data System (ADS)

Iyer, G.; Brown, M.; Cohen, S.; Macknick, J.; Patel, P.; Wise, M. A.; Horing, J.

2017-12-01

Forward-looking quantitative models of the electric sector are extensively used to provide science-based strategic decision support to national, international and private-sector entities. Given that these models are used to inform a wide-range of stakeholders and influence policy decisions, it is vital to examine how the models' underlying data and structure influence their outcomes. We conduct several experiments harmonizing key model characteristics between ReEDS—an electric sector only model, and GCAM—an integrated assessment model—to understand how different degrees of harmonization impact model outcomes. ReEDS has high spatial, temporal, and process detail but lacks electricity demand elasticity and endogenous representations of other economic sectors, while GCAM has internally consistent representations of energy (including the electric sector), agriculture, and land-use systems but relatively aggregate representations of the factors influencing electric sector investments . We vary the degree of harmonization in electricity demand, fuel prices, technology costs and performance, and variable renewable energy resource characteristics. We then identify the prominent sources of divergence in key outputs (electricity capacity, generation, and price) across the models and study how the convergence between models can be improved with permutations of harmonized characteristics. The remaining inconsistencies help to establish how differences in the models' underlying data, construction, perspective, and methodology play into each model's outcome. There are three broad contributions of this work. First, our study provides a framework to link models with similar scope but different resolutions. Second, our work provides insight into how the harmonization of assumptions contributes to a unified and robust portrayal of the US electricity sector under various potential futures. Finally, our study enhances the understanding of the influence of structural uncertainty on consistency of outcomes.

The string prediction models as invariants of time series in the forex market

NASA Astrophysics Data System (ADS)

Pincak, R.

2013-12-01

In this paper we apply a new approach of string theory to the real financial market. The models are constructed with an idea of prediction models based on the string invariants (PMBSI). The performance of PMBSI is compared to support vector machines (SVM) and artificial neural networks (ANN) on an artificial and a financial time series. A brief overview of the results and analysis is given. The first model is based on the correlation function as invariant and the second one is an application based on the deviations from the closed string/pattern form (PMBCS). We found the difference between these two approaches. The first model cannot predict the behavior of the forex market with good efficiency in comparison with the second one which is, in addition, able to make relevant profit per year. The presented string models could be useful for portfolio creation and financial risk management in the banking sector as well as for a nonlinear statistical approach to data optimization.

Initial Systematic Investigations of the Weakly Coupled Free Fermionic Heterotic String Landscape Statistics

NASA Astrophysics Data System (ADS)

Renner, Timothy

2011-12-01

A C++ framework was constructed with the explicit purpose of systematically generating string models using the Weakly Coupled Free Fermionic Heterotic String (WCFFHS) method. The software, optimized for speed, generality, and ease of use, has been used to conduct preliminary systematic investigations of WCFFHS vacua. Documentation for this framework is provided in the Appendix. After an introduction to theoretical and computational aspects of WCFFHS model building, a study of ten-dimensional WCFFHS models is presented. Degeneracies among equivalent expressions of each of the known models are investigated and classified. A study of more phenomenologically realistic four-dimensional models based on the well known "NAHE" set is then presented, with statistics being reported on gauge content, matter representations, and space-time supersymmetries. The final study is a parallel to the NAHE study in which a variation of the NAHE set is systematically extended and examined statistically. Special attention is paid to models with "mirroring"---identical observable and hidden sector gauge groups and matter representations.

Modeling future U.S. forest sector market and trade impacts of expansion in wood energy consumption

Treesearch

Peter J. Ince; Andrew D. Kramp; Kenneth E. Skog; Do-il Yoo; V. Alaric Sample

2011-01-01

This paper describes an approach to modeling U.S. forest sector market and trade impacts of expansion in domestic wood energy consumption under hypothetical future U.S. wood biomass energy policy scenarios. The U.S. Forest Products Module (USFPM) was created to enhance the modeling of the U.S. forest sector within the Global Forest Products Model (GFPM), providing a...

Sustainability Activities In The Mining Sector: Current Status And Challenges Ahead Limestone Mining In Nusakambangan

NASA Astrophysics Data System (ADS)

Ayuningrum, Theresia Vika; Purnaweni, Hartuti

2018-02-01

Potential Karst area in Nusakambangan has an important role in maintaining the balance of nature. But with the existence of mining activities, will automatically change the environmental conditions there. In order for the utilization of resources to meet the rules of optimization between the interests of mining and sustainability of the environment so in every mining sector activities required a variety of environmental studies. The purpose of this study is to find out how the analysis of environmental management due to limestone mining activities in Nusakambangan so that it can be known the management of mining areas are optimal, wise based on ecological principles, and sustainability. In qualitative research methods, data analysis using description percentage, with the type of data collected in the form of primary data and secondary data.

Logistics in a low carbon concept: Connotation and realization way

NASA Astrophysics Data System (ADS)

Zheng, Chaocheng; Qiu, Xiaoying; Mao, Jiarong

2017-01-01

Low-carbon logistics has become a trend for the logistics industry-as a high-energy consumption industry, continuation of its previous operating mode has been significantly behind the times. So logistics industry must release lower carbon emissions. This paper sort out the literature home and abroad from three aspects, that is, the definition of low-carbon logistics, low-carbon logistics implementation mechanisms or measures, and low carbon design quantitative models. The research shows: low-carbon logistics needed to implemented both in enterprise' macro and micro level, which means the government should provide relevant policy support and micro enterprises should be actively sought from all sectors of the logistics in energy saving. In practice, low-carbon logistics optimization models are effective tools for enterprises to implement emission reduction.

A basket two-part model to analyze medical expenditure on interdependent multiple sectors.

PubMed

Sugawara, Shinya; Wu, Tianyi; Yamanishi, Kenji

2018-05-01

This study proposes a novel statistical methodology to analyze expenditure on multiple medical sectors using consumer data. Conventionally, medical expenditure has been analyzed by two-part models, which separately consider purchase decision and amount of expenditure. We extend the traditional two-part models by adding the step of basket analysis for dimension reduction. This new step enables us to analyze complicated interdependence between multiple sectors without an identification problem. As an empirical application for the proposed method, we analyze data of 13 medical sectors from the Medical Expenditure Panel Survey. In comparison with the results of previous studies that analyzed the multiple sector independently, our method provides more detailed implications of the impacts of individual socioeconomic status on the composition of joint purchases from multiple medical sectors; our method has a better prediction performance.

Wesley Cole | NREL

Science.gov Websites

. Areas of Expertise Capacity expansion modeling of the U.S. electricity sector Renewable energy models Interaction of rooftop PV deployment with the greater electricity sector Impacts of policies on the evolution of the electricity sector Interactions of the natural gas supply chain with the

Applying a private sector capitation model to the management of type 2 diabetes in the South African public sector: a cost-effectiveness analysis.

PubMed

Volmink, Heinrich C; Bertram, Melanie Y; Jina, Ruxana; Wade, Alisha N; Hofman, Karen J

2014-09-30

Diabetes mellitus contributes substantially to the non-communicable disease burden in South Africa. The proposed National Health Insurance system provides an opportunity to consider the development of a cost-effective capitation model of care for patients with type 2 diabetes. The objective of the study was to determine the potential cost-effectiveness of adapting a private sector diabetes management programme (DMP) to the South African public sector. Cost-effectiveness analysis was undertaken with a public sector model of the DMP as the intervention and a usual practice model as the comparator. Probabilistic modelling was utilized for incremental cost-effectiveness ratio analysis with life years gained selected as the outcome. Secondary data were used to design the model while cost information was obtained from various sources, taking into account public sector billing. Modelling found an incremental cost-effectiveness ratio (ICER) of ZAR 8 356 (USD 1018) per life year gained (LYG) for the DMP against the usual practice model. This fell substantially below the Willingness-to-Pay threshold with bootstrapping analysis. Furthermore, a national implementation of the intervention could potentially result in an estimated cumulative gain of 96 997 years of life (95% CI 71 073 years - 113 994 years). Probabilistic modelling found the capitation intervention to be cost-effective, with an ICER of ZAR 8 356 (USD 1018) per LYG. Piloting the service within the public sector is recommended as an initial step, as this would provide data for more accurate economic evaluation, and would also allow for qualitative analysis of the programme.

Atlantic Meridional Overturning Circulation Influence on North Atlantic Sector Surface Air Temperature and its Predictability in the Kiel Climate Model

NASA Astrophysics Data System (ADS)

Latif, M.

2017-12-01

We investigate the influence of the Atlantic Meridional Overturning Circulation (AMOC) on the North Atlantic sector surface air temperature (SAT) in two multi-millennial control integrations of the Kiel Climate Model (KCM). One model version employs a freshwater flux correction over the North Atlantic, while the other does not. A clear influence of the AMOC on North Atlantic sector SAT only is simulated in the corrected model that depicts much reduced upper ocean salinity and temperature biases in comparison to the uncorrected model. Further, the model with much reduced biases depicts significantly enhanced multiyear SAT predictability in the North Atlantic sector relative to the uncorrected model. The enhanced SAT predictability in the corrected model is due to a stronger and more variable AMOC and its enhanced influence on North Atlantic sea surface temperature (SST). Results obtained from preindustrial control integrations of models participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) support the findings obtained from the KCM: models with large North Atlantic biases tend to have a weak AMOC influence on SST and exhibit a smaller SAT predictability over the North Atlantic sector.

Recent advances in stellarator optimization

DOE PAGES

Gates, D. A.; Boozer, A. H.; Brown, T.; ...

2017-10-27

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—wasmore » written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.« less

Recent advances in stellarator optimization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gates, D. A.; Boozer, A. H.; Brown, T.

Computational optimization has revolutionized the field of stellarator design. To date, optimizations have focused primarily on optimization of neoclassical confinement and ideal MHD stability, although limited optimization of other parameters has also been performed. Here, we outline a select set of new concepts for stellarator optimization that, when taken as a group, present a significant step forward in the stellarator concept. One of the criticisms that has been leveled at existing methods of design is the complexity of the resultant field coils. Recently, a new coil optimization code—COILOPT++, which uses a spline instead of a Fourier representation of the coils,—wasmore » written and included in the STELLOPT suite of codes. The advantage of this method is that it allows the addition of real space constraints on the locations of the coils. The code has been tested by generating coil designs for optimized quasi-axisymmetric stellarator plasma configurations of different aspect ratios. As an initial exercise, a constraint that the windings be vertical was placed on large major radius half of the non-planar coils. Further constraints were also imposed that guaranteed that sector blanket modules could be removed from between the coils, enabling a sector maintenance scheme. Results of this exercise will be presented. New ideas on methods for the optimization of turbulent transport have garnered much attention since these methods have led to design concepts that are calculated to have reduced turbulent heat loss. We have explored possibilities for generating an experimental database to test whether the reduction in transport that is predicted is consistent with experimental observations. Thus, a series of equilibria that can be made in the now latent QUASAR experiment have been identified that will test the predicted transport scalings. Fast particle confinement studies aimed at developing a generalized optimization algorithm are also discussed. A new algorithm developed for the design of the scraper element on W7-X is presented along with ideas for automating the optimization approach.« less

Cross-Sector Collaboration in the High-Poverty Setting: Qualitative Results from a Community-Based Diabetes Intervention.

PubMed

Tung, Elizabeth L; Gunter, Kathryn E; Bergeron, Nyahne Q; Lindau, Stacy Tessler; Chin, Marshall H; Peek, Monica E

2018-01-22

To characterize the motivations of stakeholders from diverse sectors who engaged in cross-sector collaboration with an academic medical center. Primary qualitative data (2014-2015) were collected from 22 organizations involved in a cross-sector diabetes intervention on the South Side of Chicago. In-depth, semistructured interviews; participants included leaders from all stakeholder organization types (e.g., businesses, community development, faith-based) involved in the intervention. Data were transcribed verbatim from audio and video recordings. Analysis was conducted using the constant comparison method, derived from grounded theory. All stakeholders described collaboration as an opportunity to promote community health in vulnerable populations. Among diverse motivations across organization types, stakeholders described collaboration as an opportunity for: financial support, brand enhancement, access to specialized skills or knowledge, professional networking, and health care system involvement in community-based efforts. Based on our findings, we propose a framework for implementing a working knowledge of stakeholder motivations to facilitate effective cross-sector collaboration. We identified several factors that motivated collaboration across diverse sectors with health care systems to promote health in a high-poverty, urban setting. Understanding these motivations will be foundational to optimizing meaningful cross-sector collaboration and improving diabetes outcomes in the nation's most vulnerable communities. © Health Research and Educational Trust.

Integrated Modeling Approach for Optimal Management of Water, Energy and Food Security Nexus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

We report that water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-periodmore » socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. Lastly, the obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.« less

Integrated Modeling Approach for Optimal Management of Water, Energy and Food Security Nexus

DOE PAGES

Zhang, Xiaodong; Vesselinov, Velimir Valentinov

2016-12-28

We report that water, energy and food (WEF) are inextricably interrelated. Effective planning and management of limited WEF resources to meet current and future socioeconomic demands for sustainable development is challenging. WEF production/delivery may also produce environmental impacts; as a result, green-house-gas emission control will impact WEF nexus management as well. Nexus management for WEF security necessitates integrated tools for predictive analysis that are capable of identifying the tradeoffs among various sectors, generating cost-effective planning and management strategies and policies. To address these needs, we have developed an integrated model analysis framework and tool called WEFO. WEFO provides a multi-periodmore » socioeconomic model for predicting how to satisfy WEF demands based on model inputs representing productions costs, socioeconomic demands, and environmental controls. WEFO is applied to quantitatively analyze the interrelationships and trade-offs among system components including energy supply, electricity generation, water supply-demand, food production as well as mitigation of environmental impacts. WEFO is demonstrated to solve a hypothetical nexus management problem consistent with real-world management scenarios. Model parameters are analyzed using global sensitivity analysis and their effects on total system cost are quantified. Lastly, the obtained results demonstrate how these types of analyses can be helpful for decision-makers and stakeholders to make cost-effective decisions for optimal WEF management.« less

Bioenergy Landscape Design to Minimize the Environmental Impacts of Feedstock Cultivation

NASA Astrophysics Data System (ADS)

Field, J.; Dinh, T.; Paustian, K.

2012-12-01

The United States has adopted aggressive mandates for the use of biofuels in an attempt to improve domestic energy security, reduce greenhouse gas (GHG) emissions in the transportation sector, and stimulate rural development. The Renewable Fuel Standard requires that the environmental impact of all conventional, advanced, and cellulosic biofuels be evaluated through standardized lifecycle assessment (LCA) techniques relative to a baseline of petroleum-derived gasoline and diesel fuels. A significant fraction of the energy use, GHG emissions, and water quality impact of the production of all types of biofuel occurs during the cultivation of feedstocks (either starch- or oil-based or lignocellulosic), which requires some combination of crop switching, land use change, or cultivation intensification. Furthermore, these impacts exhibit a high degree of spatial variability with local climate, soil type, land use history, and farm management practices. Here we present a spatially-explicit LCA methodology based on the DayCent soil biogeochemistry model capable of accurately evaluating cultivation impacts for a variety of biofuel feedstocks. This methodology considers soil GHG emissions and nitrate leaching as well as the embodied emissions of agricultural inputs and fuels used for field operations and biomass transport to a centralized collection point (biorefinery or transportation hub). Model results are incorporated into a biomass production cost analysis in order to identify the impact of different system designs on production cost. Finally, the resulting multi-criteria optimization problem is solved by monetizing all environmental externalities based on figures from the non-market valuation literature and using a heuristic optimization algorithm to identify optimal cultivation areas and collection point locations to minimize overall environmental impacts at lowest possible cost. Preliminary analysis results are presented for an illustrative case study of switchgrass production to supply a commercial-scale cellulosic ethanol plant currently under construction in the Great Plains. This case study supports a larger effort to mobilize this methodology into a web-based, user-friendly tool allowing farmers, academics, and biorefinery facility owners to investigate the effects of management choices and facility siting on system environmental performance, and advancing the state-of-the-art for regulatory assessment tools in the bioenergy sector.

MULTI-OBJECTIVE ONLINE OPTIMIZATION OF BEAM LIFETIME AT APS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sun, Yipeng

In this paper, online optimization of beam lifetime at the APS (Advanced Photon Source) storage ring is presented. A general genetic algorithm (GA) is developed and employed for some online optimizations in the APS storage ring. Sextupole magnets in 40 sectors of the APS storage ring are employed as variables for the online nonlinear beam dynamics optimization. The algorithm employs several optimization objectives and is designed to run with topup mode or beam current decay mode. Up to 50\\% improvement of beam lifetime is demonstrated, without affecting the transverse beam sizes and other relevant parameters. In some cases, the top-upmore » injection efficiency is also improved.« less

Exploration risks and mineral taxation: how fiscal regimes affect exploration incentives

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stauffer, T.R.; Gault, J.C.

1985-01-01

This paper investigates the effects of taxation on exploration risk and establishes certain criteria for an optimal tax on mineral resources, such as oil and gas, where exploration risk (i.e., geological risk) is a key decision variable. The optimization is considered in the context of government ownership of the resource rights, but with an eye to the after-tax incentives perceived by private-sector explorationists. Any government that relies on the private sector for discovery and development must recognize those effects. Taxation affects not only the expected returns from mineral exploration ventures but also the riskiness of such ventures. The potential formore » misdesign is great. The authors show, however, that it is possible, in realistic cases, simultaneously to increase government revenues, improve the explorationist's return, and reduce exploration risk. The opportunity for such improvements arises because most common mineral tax schemes skew the tax burdens across fields of different sizes or qualities. A key consideration in optimizing a tax regime is designing the tax to assign the appropriate burdens to different classes of discoveries. 7 tables.« less

UNIVERSAL INDUSTRIAL SECTORS INTEGRATED SOLUTIONS MODEL FOR PULP AND PAPER MANUFACTURING INDUSTRY – UISIS-PNP

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) has developed a model for the pulp and paper sector that provides an integrated approach for investigating, developing, and evaluating strategies for reducing the emissions of interest. The Universal Industrial Sectors Integrated Sol...

Variable dose rate single-arc IMAT delivered with a constant dose rate and variable angular spacing

NASA Astrophysics Data System (ADS)

Tang, Grace; Earl, Matthew A.; Yu, Cedric X.

2009-11-01

Single-arc intensity-modulated arc therapy (IMAT) has gained worldwide interest in both research and clinical implementation due to its superior plan quality and delivery efficiency. Single-arc IMAT techniques such as the Varian RapidArc™ deliver conformal dose distributions to the target in one single gantry rotation, resulting in a delivery time in the order of 2 min. The segments in these techniques are evenly distributed within an arc and are allowed to have different monitor unit (MU) weightings. Therefore, a variable dose-rate (VDR) is required for delivery. Because the VDR requirement complicates the control hardware and software of the linear accelerators (linacs) and prevents most existing linacs from delivering IMAT, we propose an alternative planning approach for IMAT using constant dose-rate (CDR) delivery with variable angular spacing. We prove the equivalence by converting VDR-optimized RapidArc plans to CDR plans, where the evenly spaced beams in the VDR plan are redistributed to uneven spacing such that the segments with larger MU weighting occupy a greater angular interval. To minimize perturbation in the optimized dose distribution, the angular deviation of the segments was restricted to <=± 5°. This restriction requires the treatment arc to be broken into multiple sectors such that the local MU fluctuation within each sector is reduced, thereby lowering the angular deviation of the segments during redistribution. The converted CDR plans were delivered with a single gantry sweep as in the VDR plans but each sector was delivered with a different value of CDR. For four patient cases, including two head-and-neck, one brain and one prostate, all CDR plans developed with the variable spacing scheme produced similar dose distributions to the original VDR plans. For plans with complex angular MU distributions, the number of sectors increased up to four in the CDR plans in order to maintain the original plan quality. Since each sector was delivered with a different dose rate, extra mode-up time (xMOT) was needed between the transitions of the successive sectors during delivery. On average, the delivery times of the CDR plans were approximately less than 1 min longer than the treatment times of the VDR plans, with an average of about 0.33 min of xMOT per sector transition. The results have shown that VDR may not be necessary for single-arc IMAT. Using variable angular spacing, VDR RapidArc plans can be implemented into the clinics that are not equipped with the new VDR-enabled machines without compromising the plan quality or treatment efficiency. With a prospective optimization approach using variable angular spacing, CDR delivery times can be further minimized while maintaining the high delivery efficiency of single-arc IMAT treatment.

Environmental implications of carbon limits on market ...

EPA Pesticide Factsheets

Combined heat and power (CHP) is promoted as an economical, energy-efficient option for combating climate change. To fully examine the viability of CHP as a clean-technology solution, its market potential and impacts need to be analyzed as part of scenarios of the future energy system, particularly those with policies limiting greenhouse gas (GHG) emissions. This paper develops and analyzes scenarios using a bottom-up, technology rich optimization model of the U.S. energy system. Two distinct carbon reduction goals were set up for analysis. In Target 1, carbon emission reduction goals were only included for the electric sector. In Target 2, carbon emission reduction goals were set across the entire energy system with the target patterned after the U.S.’s commitment to reducing GHG emissions as part of the Paris Agreement reached at the COP21 summit. From a system-wide carbon reduction standpoint, Target 2 is significantly more stringent. In addition, these scenarios examine the implications of various CHP capacity expansion and contraction assumptions and energy prices. The largest CHP capacity expansion are observed in scenarios that included Target 1, but investments were scaled back in scenarios that incorporated Target 2. The latter scenario spurred rapid development of zero-emissions technologies within the electric sector, and purchased electricity increased dramatically in many end-use sectors. The results suggest that CHP may play a role in a carbon-c

The next 15 years: taking plant-made vaccines beyond proof of concept.

PubMed

Kirk, Dwayne D; Webb, Steven R

2005-06-01

Significant potential advantages are associated with the production of vaccines in transgenic plants; however, no commercial product has emerged. An analysis of the strengths, weaknesses, opportunities and threats for plant-made vaccine technology is provided. The use of this technology for human vaccines will require significant investment and developmental efforts that cannot be supported entirely by the academic sector and is not currently supported financially by industry. A focus on downstream aspects to define potential products, conduct of additional basic clinical testing, and the incorporation of multidisciplinary strategic planning would accelerate the potential for commercialization in this field. Estimates of production cost per dose and volume of production are highly variable for a model vaccine produced in transgenic tomato, and can be influenced by the optimization of many factors. Commercialization of plant-made vaccine technology is likely to be led by the agricultural biotechnology sector rather than the pharmaceutical sector due to the disruptive nature of the technology and the complex intellectual property landscape. The next major milestones will be conduct of a phase II human clinical trial and demonstration of protection in humans. The achievement of these milestones would be accelerated by further basic investigation into mucosal immunity, the codevelopment of oral adjuvants, and the integration of quality control standards and good manufacturing practices for the production of preclinical and clinical batch materials.

75 FR 39266 - National Protection and Programs Directorate; National Infrastructure Advisory Council

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-08

... infrastructure sectors and their information systems. Pursuant to 41 CFR 102-3.150(b), this notice was published... Critical Infrastructure Resilience Goals VI. Working Group Status: Optimization of Resources for Mitigating...

Modeling technical change in climate analysis: evidence from agricultural crop damages.

PubMed

Ahmed, Adeel; Devadason, Evelyn S; Al-Amin, Abul Quasem

2017-05-01

This study accounts for the Hicks neutral technical change in a calibrated model of climate analysis, to identify the optimum level of technical change for addressing climate changes. It demonstrates the reduction to crop damages, the costs to technical change, and the net gains for the adoption of technical change for a climate-sensitive Pakistan economy. The calibrated model assesses the net gains of technical change for the overall economy and at the agriculture-specific level. The study finds that the gains of technical change are overwhelmingly higher than the costs across the agriculture subsectors. The gains and costs following technical change differ substantially for different crops. More importantly, the study finds a cost-effective optimal level of technical change that potentially reduces crop damages to a minimum possible level. The study therefore contends that the climate policy for Pakistan should consider the role of technical change in addressing climate impacts on the agriculture sector.

Optimization of drying process and pressurized liquid extraction for recovery of bioactive compounds from avocado peel by-product.

PubMed

Figueroa, Jorge G; Borrás-Linares, Isabel; Lozano-Sánchez, Jesús; Quirantes-Piné, Rosa; Segura-Carretero, Antonio

2018-04-16

The aim of the present study was to optimize the extraction of phenolic compounds in avocado peel using pressurized liquid extraction (PLE) with GRAS solvents. Response surface methodology (RSM) based on Central Composite Design 2 2 model was used in order to optimize PLE conditions. Moreover, the effect of air drying temperature on the total polyphenol content (TPC) and individual phenolic compounds concentration were evaluated. The quantification of individual compounds was performed by HPLC-DAD-ESI-TOF-MS. The optimized extraction conditions were 200°C as extraction temperature and 1:1 v/v as ethanol/water ratio. Regarding to the effect of drying, the highest TPC was obtained with a drying temperature of 85°C. Forty seven phenolic compounds were quantified in the obtained extracts, showing that phenolic acids found to be the more stables compounds to drying process, while procyanidins were the more thermolabiles analytes. To our knowledge, this is the first available study in which phenolic compounds extraction was optimized using PLE and such amount of phenolic compounds was quantified in avocado peel. These results confirm that PLE represents a powerful tool to obtain avocado peel extracts with high concentration in bioactive compounds suitable for its use in the food, cosmetic or pharmaceutical sector. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Job Demands, Job Resources, Burnout, Work Engagement, and Their Relationships: An Analysis Across Sectors.

PubMed

Van den Broeck, Anja; Elst, Tinne Vander; Baillien, Elfi; Sercu, Maarten; Schouteden, Martijn; De Witte, Hans; Godderis, Lode

2017-04-01

The aim of this study was to gain insight in the importance of job demands and resources and the validity of the Job Demands Resources Model across sectors. We used one-way analyses of variance to examine mean differences, and multi-group Structural Equation Modeling analyses to test the strength of the relationships among job demands, resources, burnout, and work engagement across the health care, industry, service, and public sector. The four sectors differed in the experience of job demands, resources, burnout, and work engagement, but they did not vary in how (strongly) job demands and resources associated with burnout and work engagement. More attention is needed to decrease burnout and increase work engagement, particularly in industry, service, and the public sector. The Job Demands-Resources model may be helpful in this regard, as it is valid across sectors.

Simulating water markets with transaction costs

PubMed Central

Erfani, Tohid; Binions, Olga; Harou, Julien J

2014-01-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. Key Points Transaction tracking hydro-economic optimization models simulate water markets Proposed model formulation incorporates transaction costs and trading behavior Water markets benefit users with the most restricted water access PMID:25598558

Simulating water markets with transaction costs.

PubMed

Erfani, Tohid; Binions, Olga; Harou, Julien J

2014-06-01

This paper presents an optimization model to simulate short-term pair-wise spot-market trading of surface water abstraction licenses (water rights). The approach uses a node-arc multicommodity formulation that tracks individual supplier-receiver transactions in a water resource network. This enables accounting for transaction costs between individual buyer-seller pairs and abstractor-specific rules and behaviors using constraints. Trades are driven by economic demand curves that represent each abstractor's time-varying water demand. The purpose of the proposed model is to assess potential hydrologic and economic outcomes of water markets and aid policy makers in designing water market regulations. The model is applied to the Great Ouse River basin in Eastern England. The model assesses the potential weekly water trades and abstractions that could occur in a normal and a dry year. Four sectors (public water supply, energy, agriculture, and industrial) are included in the 94 active licensed water diversions. Each license's unique environmental restrictions are represented and weekly economic water demand curves are estimated. Rules encoded as constraints represent current water management realities and plausible stakeholder-informed water market behaviors. Results show buyers favor sellers who can supply large volumes to minimize transactions. The energy plant cooling and agricultural licenses, often restricted from obtaining water at times when it generates benefits, benefit most from trades. Assumptions and model limitations are discussed. Transaction tracking hydro-economic optimization models simulate water marketsProposed model formulation incorporates transaction costs and trading behaviorWater markets benefit users with the most restricted water access.

How divergent conceptions among health and education stakeholders influence the dissemination of healthy schools in Quebec.

PubMed

Deschesnes, Marthe; Couturier, Yves; Laberge, Suzanne; Campeau, Louise

2010-12-01

This paper focuses on dissemination of the healthy schools (HS) approach in the province of Quebec, Canada. Dissemination aims at raising awareness about HS and promoting its adhesion among actors concerned with youth health in school. As HS is a joint initiative based on agreement and collaboration between health and educational sectors, the positions of stakeholders that foster cooperation between these sectors were considered to be critical to optimize its dissemination. The study's objectives were to: (i) examine and contrast the stakeholders' conceptions of HS and (ii) understand how converging and diverging stakeholders' positions on HS favourably or negatively influence its dissemination in Quebec. Gray's analytical approach to collaboration and its focus on stakeholders' mindframe about a domain served as a conceptual lens to examine stakeholders' positions regarding HS. Collection methods included documentary analysis and semi-structured interviews of 34 key internal and external informants at the provincial, regional and local levels. The results showed consensual adhesion to fundamental principles of the HS approach. However, differences in conceptualization between provincial authorities of the two sectors concerning the way to disseminate HS have been observed. These differences represented a significant barrier to HS optimal dissemination. A dialogue between the two authorities appears to be essential to arrive at a negotiated and shared conceptualization of this issue in the Quebec context, thus allowing agreements for adequate support. The results may serve as the basis for a more fruitful dialogue between actors from the two sectors, at different administrative levels.

Sector-Wide Transformational Leadership--How Effectively Is the EFQM Excellence Model[R] Used in the UK FE Sector?

ERIC Educational Resources Information Center

Cartmell, Jonathan; Binsardi, Ben; McLean, Alexis

2011-01-01

This seminal study investigates the use of the EFQM Excellence Model[R] in the UK Further Education sector. Following initial interviews with Senior Managers and Quality Consultants, an online survey was sent to Principals and Senior Managers in all Colleges across the UK to critically investigate the relationship between the use of the Model and…

Technical change in forest sector models: the global forest products model approach

Treesearch

Joseph Buongiorno; Sushuai Zhu

2015-01-01

Technical change is developing rapidly in some parts of the forest sector, especially in the pulp and paper industry where wood fiber is being substituted by waste paper. In forest sector models, the processing of wood and other input into products is frequently represented by activity analysis (input–output). In this context, technical change translates in changes...

The Collective Impact Model and Its Potential for Health Promotion: Overview and Case Study of a Healthy Retail Initiative in San Francisco

ERIC Educational Resources Information Center

Flood, Johnna; Minkler, Meredith; Lavery, Susana Hennessey; Estrada, Jessica; Falbe, Jennifer

2015-01-01

As resources for health promotion become more constricted, it is increasingly important to collaborate across sectors, including the private sector. Although many excellent models for cross-sector collaboration have shown promise in the health field, collective impact (CI), an emerging model for creating larger scale change, has yet to receive…

The impact of oil price on Malaysian sector indices

NASA Astrophysics Data System (ADS)

Ismail, Mohd Tahir; Luan, Yeap Pei; Ee, Ong Joo

2015-12-01

In this paper, vector error correction model (VECM) has been utilized to model the dynamic relationships between world crude oil price and the sector indices of Malaysia. The sector indices have been collected are covering the period Jan 1998 to Dec 2013. Surprisingly, our investigations show that oil price changes do not Granger-cause any of the sectors in all of Malaysia. However, sector indices of Food Producer and Utilities are found to be the cause of the changes in world crude oil prices. Furthermore, from the results of variance decomposition, very high percentage of shocks is explained by world crude oil price itself over the 12 months and small impact from other sector indices.

On the Effectiveness of Security Countermeasures for Critical Infrastructures.

PubMed

Hausken, Kjell; He, Fei

2016-04-01

A game-theoretic model is developed where an infrastructure of N targets is protected against terrorism threats. An original threat score is determined by the terrorist's threat against each target and the government's inherent protection level and original protection. The final threat score is impacted by the government's additional protection. We investigate and verify the effectiveness of countermeasures using empirical data and two methods. The first is to estimate the model's parameter values to minimize the sum of the squared differences between the government's additional resource investment predicted by the model and the empirical data. The second is to develop a multivariate regression model where the final threat score varies approximately linearly relative to the original threat score, sectors, and threat scenarios, and depends nonlinearly on the additional resource investment. The model and method are offered as tools, and as a way of thinking, to determine optimal resource investments across vulnerable targets subject to terrorism threats. © 2014 Society for Risk Analysis.

A methodology for computing uncertainty bounds of multivariable systems based on sector stability theory concepts

NASA Technical Reports Server (NTRS)

Waszak, Martin R.

1992-01-01

The application of a sector-based stability theory approach to the formulation of useful uncertainty descriptions for linear, time-invariant, multivariable systems is explored. A review of basic sector properties and sector-based approach are presented first. The sector-based approach is then applied to several general forms of parameter uncertainty to investigate its advantages and limitations. The results indicate that the sector uncertainty bound can be used effectively to evaluate the impact of parameter uncertainties on the frequency response of the design model. Inherent conservatism is a potential limitation of the sector-based approach, especially for highly dependent uncertain parameters. In addition, the representation of the system dynamics can affect the amount of conservatism reflected in the sector bound. Careful application of the model can help to reduce this conservatism, however, and the solution approach has some degrees of freedom that may be further exploited to reduce the conservatism.

Cost Minimization for Joint Energy Management and Production Scheduling Using Particle Swarm Optimization

NASA Astrophysics Data System (ADS)

Shah, Rahul H.

Production costs account for the largest share of the overall cost of manufacturing facilities. With the U.S. industrial sector becoming more and more competitive, manufacturers are looking for more cost and resource efficient working practices. Operations management and production planning have shown their capability to dramatically reduce manufacturing costs and increase system robustness. When implementing operations related decision making and planning, two fields that have shown to be most effective are maintenance and energy. Unfortunately, the current research that integrates both is limited. Additionally, these studies fail to consider parameter domains and optimization on joint energy and maintenance driven production planning. Accordingly, production planning methodology that considers maintenance and energy is investigated. Two models are presented to achieve well-rounded operating strategy. The first is a joint energy and maintenance production scheduling model. The second is a cost per part model considering maintenance, energy, and production. The proposed methodology will involve a Time-of-Use electricity demand response program, buffer and holding capacity, station reliability, production rate, station rated power, and more. In practice, the scheduling problem can be used to determine a joint energy, maintenance, and production schedule. Meanwhile, the cost per part model can be used to: (1) test the sensitivity of the obtained optimal production schedule and its corresponding savings by varying key production system parameters; and (2) to determine optimal system parameter combinations when using the joint energy, maintenance, and production planning model. Additionally, a factor analysis on the system parameters is conducted and the corresponding performance of the production schedule under variable parameter conditions, is evaluated. Also, parameter optimization guidelines that incorporate maintenance and energy parameter decision making in the production planning framework are discussed. A modified Particle Swarm Optimization solution technique is adopted to solve the proposed scheduling problem. The algorithm is described in detail and compared to Genetic Algorithm. Case studies are presented to illustrate the benefits of using the proposed model and the effectiveness of the Particle Swarm Optimization approach. Numerical Experiments are implemented and analyzed to test the effectiveness of the proposed model. The proposed scheduling strategy can achieve savings of around 19 to 27 % in cost per part when compared to the baseline scheduling scenarios. By optimizing key production system parameters from the cost per part model, the baseline scenarios can obtain around 20 to 35 % in savings for the cost per part. These savings further increase by 42 to 55 % when system parameter optimization is integrated with the proposed scheduling problem. Using this method, the most influential parameters on the cost per part are the rated power from production, the production rate, and the initial machine reliabilities. The modified Particle Swarm Optimization algorithm adopted allows greater diversity and exploration compared to Genetic Algorithm for the proposed joint model which results in it being more computationally efficient in determining the optimal scheduling. While Genetic Algorithm could achieve a solution quality of 2,279.63 at an expense of 2,300 seconds in computational effort. In comparison, the proposed Particle Swarm Optimization algorithm achieved a solution quality of 2,167.26 in less than half the computation effort which is required by Genetic Algorithm.

Towards new business models for R&D for novel antibiotics.

PubMed

So, A D; Gupta, N; Brahmachari, S K; Chopra, I; Munos, B; Nathan, C; Outterson, K; Paccaud, J P; Payne, D J; Peeling, R W; Spigelman, M; Weigelt, J

2011-04-01

In the face of a growing global burden of resistance to existing antibiotics, a combination of scientific and economic challenges has posed significant barriers to the development of novel antibacterials over the past few decades. Yet the bottlenecks at each stage of the pharmaceutical value chain-from discovery to post-marketing-present opportunities to reengineer an innovation pipeline that has fallen short. The upstream hurdles to lead identification and optimization may be eased with greater multi-sectoral collaboration, a growing array of alternatives to high-throughput screening, and the application of open source approaches. Product development partnerships and South-South innovation platforms have shown promise in bolstering the R&D efforts to tackle neglected diseases. Strategies that delink product sales from the firms' return on investment can help ensure that the twin goals of innovation and access are met. To effect these changes, both public and private sector stakeholders must show greater commitment to an R&D agenda that will address this problem, not only for industrialized countries but also globally. Copyright © 2011 Elsevier Ltd. All rights reserved.

The Contextualized Technology Adaptation Process (CTAP): Optimizing Health Information Technology to Improve Mental Health Systems.

PubMed

Lyon, Aaron R; Wasse, Jessica Knaster; Ludwig, Kristy; Zachry, Mark; Bruns, Eric J; Unützer, Jürgen; McCauley, Elizabeth

2016-05-01

Health information technologies have become a central fixture in the mental healthcare landscape, but few frameworks exist to guide their adaptation to novel settings. This paper introduces the contextualized technology adaptation process (CTAP) and presents data collected during Phase 1 of its application to measurement feedback system development in school mental health. The CTAP is built on models of human-centered design and implementation science and incorporates repeated mixed methods assessments to guide the design of technologies to ensure high compatibility with a destination setting. CTAP phases include: (1) Contextual evaluation, (2) Evaluation of the unadapted technology, (3) Trialing and evaluation of the adapted technology, (4) Refinement and larger-scale implementation, and (5) Sustainment through ongoing evaluation and system revision. Qualitative findings from school-based practitioner focus groups are presented, which provided information for CTAP Phase 1, contextual evaluation, surrounding education sector clinicians' workflows, types of technologies currently available, and influences on technology use. Discussion focuses on how findings will inform subsequent CTAP phases, as well as their implications for future technology adaptation across content domains and service sectors.

Heidelberg retina tomograph measurements of the optic disc and parapapillary retina for detecting glaucoma analyzed by machine learning classifiers.

PubMed

Zangwill, Linda M; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N; Sejnowski, Terrence J; Goldbaum, Michael H

2004-09-01

To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240 degrees and 300 degrees, had the largest area under the ROC curve (0.85-0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. Copyright Association for Research in Vision and Ophthalmology

Heidelberg Retina Tomograph Measurements of the Optic Disc and Parapapillary Retina for Detecting Glaucoma Analyzed by Machine Learning Classifiers

PubMed Central

Zangwill, Linda M.; Chan, Kwokleung; Bowd, Christopher; Hao, Jicuang; Lee, Te-Won; Weinreb, Robert N.; Sejnowski, Terrence J.; Goldbaum, Michael H.

2010-01-01

Purpose To determine whether topographical measurements of the parapapillary region analyzed by machine learning classifiers can detect early to moderate glaucoma better than similarly processed measurements obtained within the disc margin and to improve methods for optimization of machine learning classifier feature selection. Methods One eye of each of 95 patients with early to moderate glaucomatous visual field damage and of each of 135 normal subjects older than 40 years participating in the longitudinal Diagnostic Innovations in Glaucoma Study (DIGS) were included. Heidelberg Retina Tomograph (HRT; Heidelberg Engineering, Dossenheim, Germany) mean height contour was measured in 36 equal sectors, both along the disc margin and in the parapapillary region (at a mean contour line radius of 1.7 mm). Each sector was evaluated individually and in combination with other sectors. Gaussian support vector machine (SVM) learning classifiers were used to interpret HRT sector measurements along the disc margin and in the parapapillary region, to differentiate between eyes with normal and glaucomatous visual fields and to compare the results with global and regional HRT parameter measurements. The area under the receiver operating characteristic (ROC) curve was used to measure diagnostic performance of the HRT parameters and to evaluate the cross-validation strategies and forward selection and backward elimination optimization techniques that were used to generate the reduced feature sets. Results The area under the ROC curve for mean height contour of the 36 sectors along the disc margin was larger than that for the mean height contour in the parapapillary region (0.97 and 0.85, respectively). Of the 36 individual sectors along the disc margin, those in the inferior region between 240° and 300°, had the largest area under the ROC curve (0.85–0.91). With SVM Gaussian techniques, the regional parameters showed the best ability to discriminate between normal eyes and eyes with glaucomatous visual field damage, followed by the global parameters, mean height contour measures along the disc margin, and mean height contour measures in the parapapillary region. The area under the ROC curve was 0.98, 0.94, 0.93, and 0.85, respectively. Cross-validation and optimization techniques demonstrated that good discrimination (99% of peak area under the ROC curve) can be obtained with a reduced number of HRT parameters. Conclusions Mean height contour measurements along the disc margin discriminated between normal and glaucomatous eyes better than measurements obtained in the parapapillary region. PMID:15326133

Financial fluctuations anchored to economic fundamentals: A mesoscopic network approach.

PubMed

Sharma, Kiran; Gopalakrishnan, Balagopal; Chakrabarti, Anindya S; Chakraborti, Anirban

2017-08-14

We demonstrate the existence of an empirical linkage between nominal financial networks and the underlying economic fundamentals, across countries. We construct the nominal return correlation networks from daily data to encapsulate sector-level dynamics and infer the relative importance of the sectors in the nominal network through measures of centrality and clustering algorithms. Eigenvector centrality robustly identifies the backbone of the minimum spanning tree defined on the return networks as well as the primary cluster in the multidimensional scaling map. We show that the sectors that are relatively large in size, defined with three metrics, viz., market capitalization, revenue and number of employees, constitute the core of the return networks, whereas the periphery is mostly populated by relatively smaller sectors. Therefore, sector-level nominal return dynamics are anchored to the real size effect, which ultimately shapes the optimal portfolios for risk management. Our results are reasonably robust across 27 countries of varying degrees of prosperity and across periods of market turbulence (2008-09) as well as periods of relative calmness (2012-13 and 2015-16).

Managing risk selection incentives in health sector reforms.

PubMed

Puig-Junoy, J

1999-01-01

The object of the paper is to review theoretical and empirical contributions to the optimal management of risk selection incentives ('cream skimming') in health sector reforms. The trade-off between efficiency and risk selection is fostered in health sector reforms by the introduction of competitive mechanisms such as price competition or prospective payment systems. The effects of two main forms of competition in health sector reforms are observed when health insurance is mandatory: competition in the market for health insurance, and in the market for health services. Market and government failures contribute to the assessment of the different forms of risk selection employed by insurers and providers, as the effects of selection incentives on efficiency and their proposed remedies to reduce the impact of these perverse incentives. Two European (Netherlands and Spain) and two Latin American (Chile and Colombia) case studies of health sector reforms are examined in order to observe selection incentives, their effects on efficiency and costs in the health system, and regulation policies implemented in each country to mitigate incentives to 'cream skim' good risks.

Optimization of Game Formats in U-10 Soccer Using Logistic Regression Analysis

PubMed Central

Amatria, Mario; Arana, Javier; Anguera, M. Teresa; Garzón, Belén

2016-01-01

Abstract Small-sided games provide young soccer players with better opportunities to develop their skills and progress as individual and team players. There is, however, little evidence on the effectiveness of different game formats in different age groups, and furthermore, these formats can vary between and even within countries. The Royal Spanish Soccer Association replaced the traditional grassroots 7-a-side format (F-7) with the 8-a-side format (F-8) in the 2011-12 season and the country’s regional federations gradually followed suit. The aim of this observational methodology study was to investigate which of these formats best suited the learning needs of U-10 players transitioning from 5-aside futsal. We built a multiple logistic regression model to predict the success of offensive moves depending on the game format and the area of the pitch in which the move was initiated. Success was defined as a shot at the goal. We also built two simple logistic regression models to evaluate how the game format influenced the acquisition of technicaltactical skills. It was found that the probability of a shot at the goal was higher in F-7 than in F-8 for moves initiated in the Creation Sector-Own Half (0.08 vs 0.07) and the Creation Sector-Opponent's Half (0.18 vs 0.16). The probability was the same (0.04) in the Safety Sector. Children also had more opportunities to control the ball and pass or take a shot in the F-7 format (0.24 vs 0.20), and these were also more likely to be successful in this format (0.28 vs 0.19). PMID:28031768

The Army’s Local Economic Effects

DTIC Science & Technology

2015-01-01

region. An I/O model is a representation of the linkages between major sectors of a regional economy in which each sector of the regional economy is...assumed to require inputs from the other sectors to produce output. These inputs can come from local sources within the region, from other domestic...ment of the Army in a congressional district. An I/O model is a representation of the linkages between major sectors of a regional economy (and, to a

Climate services in the tourism sector - examples and market research

NASA Astrophysics Data System (ADS)

Damm, Andrea; Köberl, Judith; Prettenthaler, Franz; Kortschak, Dominik; Hofer, Marianne; Winkler, Claudia

2017-04-01

Tourism is one of the most weather-sensitive sectors. Hence, dealing with weather and climate risks is an important part of operational risk management. WEDDA® (WEather Driven Demand Analysis), developed by Joanneum Research, represents a comprehensive and flexible toolbox for managing weather and climate risks. Modelling the demand for products or services of a particular economic sector or company and its weather and climate sensitivity usually forms the starting and central point of WEDDA®. Coupling the calibrated demand models to either long-term climate scenarios or short-term weather forecasts enables the use of WEDDA® for the following areas of application: (i) implementing short-term forecasting systems for the prediction of the considered indicator; (ii) quantifying the weather risk of a particular economic sector or company using parameters from finance (e.g. Value-at-Risk); (iii) assessing the potential impacts of changing climatic conditions on a particular economic sector or company. WEDDA® for short-term forecasts on the demand for products or services is currently used by various tourism businesses, such as open-air swimming pools, ski areas, and restaurants. It supports tourism and recreation facilities to better cope with (increasing) weather variability by optimizing the disposability of staff, resources and merchandise according to expected demand. Since coping with increasing weather variability forms one of the challenges with respect to climate change, WEDDA® may become an important component within a whole pool of weather and climate services designed to support tourism and recreation facilities to adapt to climate change. Climate change impact assessments at European scale, as conducted in the EU-FP7 project IMPACT2C, provide basic information of climate change impacts on tourism demand not only for individual tourism businesses, but also for regional and national tourism planners and policy makers interested in benchmarks for the vulnerability of their tourism destination. In this project we analysed the impacts of +2 °C global warming on winter tourism demand in ski tourism related regions in Europe. In order to achieve the climate targets, tailored climate information services - for individual businesses as well as at the regional and national level - play an important role. The current market, however, is still in the early stages. In the ongoing H2020 projects EU-MACS (www.eu-macs.eu) and MARCO (www.marco-h2020.eu) (Nov 2016 - Oct 2018) Joanneum Research explores the climate services market in the tourism sector. The current use of climate services is reviewed in detail and in an interactive process key market barriers and enablers will be identified in close collaboration with stakeholders from the tourism industry. The analysis and co-development of new climate services concepts for the tourism sector aims to reduce the gaps between climate services supply and demand.

Forestry sector analysis for developing countries: issues and methods.

Treesearch

R.W. Haynes

1993-01-01

A satellite meeting of the 10th Forestry World Congress focused on the methods used for forest sector analysis and their applications in both developed and developing countries. The results of that meeting are summarized, and a general approach for forest sector modeling is proposed. The approach includes models derived from the existing...

General structure of democratic mass matrix of quark sector in E6 model

NASA Astrophysics Data System (ADS)

Ciftci, R.; ćiftci, A. K.

2016-03-01

An extension of the Standard Model (SM) fermion sector, which is inspired by the E6 Grand Unified Theory (GUT) model, might be a good candidate to explain a number of unanswered questions in SM. Existence of the isosinglet quarks might explain great mass difference of bottom and top quarks. Also, democracy on mass matrix elements is a natural approach in SM. In this study, we have given general structure of Democratic Mass Matrix (DMM) of quark sector in E6 model.

Implant strategies for endocervical and interstitial ultrasound hyperthermia adjunct to HDR brachytherapy for the treatment of cervical cancer

NASA Astrophysics Data System (ADS)

Wootton, Jeffery H.; Prakash, Punit; Hsu, I.-Chow Joe; Diederich, Chris J.

2011-07-01

Catheter-based ultrasound devices provide a method to deliver 3D conformable heating integrated with HDR brachytherapy delivery. Theoretical characterization of heating patterns was performed to identify implant strategies for these devices which can best be used to apply hyperthermia to cervical cancer. A constrained optimization-based hyperthermia treatment planning platform was used for the analysis. The proportion of tissue >=41 °C in a hyperthermia treatment volume was maximized with constraints Tmax <= 47 °C, Trectum <= 41.5 °C, and Tbladder <= 42.5 °C. Hyperthermia treatment was modeled for generalized implant configurations and complex configurations from a database of patients (n = 14) treated with HDR brachytherapy. Various combinations of endocervical (360° or 2 × 180° output; 6 mm OD) and interstitial (180°, 270°, or 360° output; 2.4 mm OD) applicators within catheter locations from brachytherapy implants were modeled, with perfusion constant (1 or 3 kg m-3 s-1) or varying with location or temperature. Device positioning, sectoring, active length and aiming were empirically optimized to maximize thermal coverage. Conformable heating of appreciable volumes (>200 cm3) is possible using multiple sectored interstitial and endocervical ultrasound devices. The endocervical device can heat >41 °C to 4.6 cm diameter compared to 3.6 cm for the interstitial. Sectored applicators afford tight control of heating that is robust to perfusion changes in most regularly spaced configurations. T90 in example patient cases was 40.5-42.7 °C (1.9-39.6 EM43 °C) at 1 kg m-3 s-1 with 10/14 patients >=41 °C. Guidelines are presented for positioning of implant catheters during the initial surgery, selection of ultrasound applicator configurations, and tailored power schemes for achieving T90 >= 41 °C in clinically practical implant configurations. Catheter-based ultrasound devices, when adhering to the guidelines, show potential to generate conformal therapeutic heating ranging from a single endocervical device targeting small volumes local to the cervix (<2 cm radial) to a combination of a 2 × 180° endocervical and directional interstitial applicators in the lateral periphery to target much larger volumes (6 cm radial), while preferentially limiting heating of the bladder and rectum.

Model documentation report: Residential sector demand module of the national energy modeling system

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies,more » market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.« less

System integration of wind and solar power in integrated assessment models: A cross-model evaluation of new approaches

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pietzcker, Robert C.; Ueckerdt, Falko; Carrara, Samuel

Mitigation-Process Integrated Assessment Models (MP-IAMs) are used to analyze long-term transformation pathways of the energy system required to achieve stringent climate change mitigation targets. Due to their substantial temporal and spatial aggregation, IAMs cannot explicitly represent all detailed challenges of integrating the variable renewable energies (VRE) wind and solar in power systems, but rather rely on parameterized modeling approaches. In the ADVANCE project, six international modeling teams have developed new approaches to improve the representation of power sector dynamics and VRE integration in IAMs. In this study, we qualitatively and quantitatively evaluate the last years' modeling progress and study themore » impact of VRE integration modeling on VRE deployment in IAM scenarios. For a comprehensive and transparent qualitative evaluation, we first develop a framework of 18 features of power sector dynamics and VRE integration. We then apply this framework to the newly-developed modeling approaches to derive a detailed map of strengths and limitations of the different approaches. For the quantitative evaluation, we compare the IAMs to the detailed hourly-resolution power sector model REMIX. We find that the new modeling approaches manage to represent a large number of features of the power sector, and the numerical results are in reasonable agreement with those derived from the detailed power sector model. Updating the power sector representation and the cost and resources of wind and solar substantially increased wind and solar shares across models: Under a carbon price of 30$/tCO2 in 2020 (increasing by 5% per year), the model-average cost-minimizing VRE share over the period 2050-2100 is 62% of electricity generation, 24%-points higher than with the old model version.« less

An effective and optimal quality control approach for green energy manufacturing using design of experiments framework and evolutionary algorithm

NASA Astrophysics Data System (ADS)

Saavedra, Juan Alejandro

Quality Control (QC) and Quality Assurance (QA) strategies vary significantly across industries in the manufacturing sector depending on the product being built. Such strategies range from simple statistical analysis and process controls, decision-making process of reworking, repairing, or scraping defective product. This study proposes an optimal QC methodology in order to include rework stations during the manufacturing process by identifying the amount and location of these workstations. The factors that are considered to optimize these stations are cost, cycle time, reworkability and rework benefit. The goal is to minimize the cost and cycle time of the process, but increase the reworkability and rework benefit. The specific objectives of this study are: (1) to propose a cost estimation model that includes energy consumption, and (2) to propose an optimal QC methodology to identify quantity and location of rework workstations. The cost estimation model includes energy consumption as part of the product direct cost. The cost estimation model developed allows the user to calculate product direct cost as the quality sigma level of the process changes. This provides a benefit because a complete cost estimation calculation does not need to be performed every time the processes yield changes. This cost estimation model is then used for the QC strategy optimization process. In order to propose a methodology that provides an optimal QC strategy, the possible factors that affect QC were evaluated. A screening Design of Experiments (DOE) was performed on seven initial factors and identified 3 significant factors. It reflected that one response variable was not required for the optimization process. A full factorial DOE was estimated in order to verify the significant factors obtained previously. The QC strategy optimization is performed through a Genetic Algorithm (GA) which allows the evaluation of several solutions in order to obtain feasible optimal solutions. The GA evaluates possible solutions based on cost, cycle time, reworkability and rework benefit. Finally it provides several possible solutions because this is a multi-objective optimization problem. The solutions are presented as chromosomes that clearly state the amount and location of the rework stations. The user analyzes these solutions in order to select one by deciding which of the four factors considered is most important depending on the product being manufactured or the company's objective. The major contribution of this study is to provide the user with a methodology used to identify an effective and optimal QC strategy that incorporates the number and location of rework substations in order to minimize direct product cost, and cycle time, and maximize reworkability, and rework benefit.

Characterizing the emission implications of future natural gas production and use in the U.S. and Rocky Mountain region: A scenario-based energy system modeling approach

NASA Astrophysics Data System (ADS)

McLeod, Jeffrey

The recent increase in U.S. natural gas production made possible through advancements in extraction techniques including hydraulic fracturing has transformed the U.S. energy supply landscape while raising questions regarding the balance of environmental impacts associated with natural gas production and use. Impact areas at issue include emissions of methane and criteria pollutants from natural gas production, alongside changes in emissions from increased use of natural gas in place of coal for electricity generation. In the Rocky Mountain region, these impact areas have been subject to additional scrutiny due to the high level of regional oil and gas production activity and concerns over its links to air quality. Here, the MARKAL (MArket ALlocation) least-cost energy system optimization model in conjunction with the EPA-MARKAL nine-region database has been used to characterize future regional and national emissions of CO 2, CH4, VOC, and NOx attributed to natural gas production and use in several sectors of the economy. The analysis is informed by comparing and contrasting a base case, business-as-usual scenario with scenarios featuring variations in future natural gas supply characteristics, constraints affecting the electricity generation mix, carbon emission reduction strategies and increased demand for natural gas in the transportation sector. Emission trends and their associated sensitivities are identified and contrasted between the Rocky Mountain region and the U.S. as a whole. The modeling results of this study illustrate the resilience of the short term greenhouse gas emission benefits associated with fuel switching from coal to gas in the electric sector, but also call attention to the long term implications of increasing natural gas production and use for emissions of methane and VOCs, especially in the Rocky Mountain region. This analysis can help to inform the broader discussion of the potential environmental impacts of future natural gas production and use by illustrating links between relevant economic and environmental variables.

A Dynamic Information Framework (DIF): A Portal for the Changing Biogeochemistry of Aquatic Systems

NASA Astrophysics Data System (ADS)

Richey, J. E.; Fernandes, E. C. M.

2014-12-01

The ability of societies to adapt to climate and landuse change in aquatic systems is functionally and practically expressed by how regional stakeholders are able to address complex management issues. These targets represent a very complex set of intersecting issues of scale, cross-sector science and technology, education, politics, and economics. Implications transcend individual projects and ministries. An immediate challenge is to incorporate the realities of changing environmental conditions in these sectors into the policies and projects of the Ministries nominally responsible. Ideally this would be done on the basis of the absolute best understanding of the issues involved, and done in a way that optimizes a multi-stakeholder return. Central to a response is "actionable information-" the synthesis and "bringing to life" of the key information that integrates the end-to-end knowledge required to provide the high-level decision support to make the most informed decisions. But, in practice, the information necessary and even perspectives are virtually absent, in much of especially the developing world. To meet this challenge, we have been developing a Dynamic Information Framework (DIF), primarily through collaborations with the World Bank in Asia, Africa, and Brazil. The DIF is, essentially a decision support structure, built around "earth system" models. The environment is built on progressive information layers that are fed through hydrological and geospatial landscape models to produce outputs that address specific science questions related to water resources management of the region. Information layers from diverse sources are assembled, according to the principles of how the landscape is organized, and computer models are used to bring the information "to life." A fundamental aspect to a DIF is not only the convergence of multi-sector information, but how that information can be conveyed, in the most compelling, and visual, manner. Deployment of the environment in the Cloud facilitates access for stakeholders.

A proposed approach to monitor private-sector policies and practices related to food environments, obesity and non-communicable disease prevention.

PubMed

Sacks, G; Swinburn, B; Kraak, V; Downs, S; Walker, C; Barquera, S; Friel, S; Hawkes, C; Kelly, B; Kumanyika, S; L'Abbé, M; Lee, A; Lobstein, T; Ma, J; Macmullan, J; Mohan, S; Monteiro, C; Neal, B; Rayner, M; Sanders, D; Snowdon, W; Vandevijvere, S

2013-10-01

Private-sector organizations play a critical role in shaping the food environments of individuals and populations. However, there is currently very limited independent monitoring of private-sector actions related to food environments. This paper reviews previous efforts to monitor the private sector in this area, and outlines a proposed approach to monitor private-sector policies and practices related to food environments, and their influence on obesity and non-communicable disease (NCD) prevention. A step-wise approach to data collection is recommended, in which the first ('minimal') step is the collation of publicly available food and nutrition-related policies of selected private-sector organizations. The second ('expanded') step assesses the nutritional composition of each organization's products, their promotions to children, their labelling practices, and the accessibility, availability and affordability of their products. The third ('optimal') step includes data on other commercial activities that may influence food environments, such as political lobbying and corporate philanthropy. The proposed approach will be further developed and piloted in countries of varying size and income levels. There is potential for this approach to enable national and international benchmarking of private-sector policies and practices, and to inform efforts to hold the private sector to account for their role in obesity and NCD prevention. © 2013 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of the International Association for the Study of Obesity.

Ecosystem service tradeoff analysis reveals the value of marine spatial planning for multiple ocean uses

PubMed Central

White, Crow; Halpern, Benjamin S.; Kappel, Carrie V.

2012-01-01

Marine spatial planning (MSP) is an emerging responsibility of resource managers around the United States and elsewhere. A key proposed advantage of MSP is that it makes tradeoffs in resource use and sector (stakeholder group) values explicit, but doing so requires tools to assess tradeoffs. We extended tradeoff analyses from economics to simultaneously assess multiple ecosystem services and the values they provide to sectors using a robust, quantitative, and transparent framework. We used the framework to assess potential conflicts among offshore wind energy, commercial fishing, and whale-watching sectors in Massachusetts and identify and quantify the value from choosing optimal wind farm designs that minimize conflicts among these sectors. Most notably, we show that using MSP over conventional planning could prevent >$1 million dollars in losses to the incumbent fishery and whale-watching sectors and could generate >$10 billion in extra value to the energy sector. The value of MSP increased with the greater the number of sectors considered and the larger the area under management. Importantly, the framework can be applied even when sectors are not measured in dollars (e.g., conservation). Making tradeoffs explicit improves transparency in decision-making, helps avoid unnecessary conflicts attributable to perceived but weak tradeoffs, and focuses debate on finding the most efficient solutions to mitigate real tradeoffs and maximize sector values. Our analysis demonstrates the utility, feasibility, and value of MSP and provides timely support for the management transitions needed for society to address the challenges of an increasingly crowded ocean environment. PMID:22392996

Three essays on monetary policy responses to oil price shocks

NASA Astrophysics Data System (ADS)

Plante, Michael

This dissertation contains three chapters which explore the question of how monetary policy should respond to changes in the price of oil. Each chapter explores the question from the perspective of a different economic environment. The first chapter examines welfare maximizing optimal monetary policy in a closed economy New Keynesian model that is extended to include household and firm demand for oil products, sticky wages, and capital accumulation. When households and firms demand oil products a natural difference arises between the Consumer Price Index (CPI), the core CPI, and the GDP deflator. I show that when nominal wages are flexible then the optimal policy places a heavy emphasis on stabilizing the inflation rate of the core CPI. If aggregate nominal wages are sticky then the central bank should focus on stabilizing some combination of core inflation and nominal wage inflation. Under no case examined is it optimal to stabilize either GDP deflator or CPI inflation. The second chapter examines monetary policy responses to oil price shocks in a small open economy with traded and non-traded goods. Oil and labor are used to produce the traded and non-traded goods and prices are sticky in the non-traded sector. I show analytically that the ratio of the oil and labor cost shares in the traded and non-traded sectors is crucial for determining the dynamic behavior of many macroeconomic variables after a rise in the price of oil. A policy of fixed exchange rates can produce higher or lower inflation in the non-traded sector depending upon the ratio. Likewise, a policy that stabilizes the inflation rate of prices in the non-traded sector can cause the nominal exchange rate to appreciate or depreciate. For the proper calibration, a policy that stabilizes core inflation produces results very close to the one that stabilizes non-traded inflation. Analytical results show that the fixed exchange rate always produces a unique solution. The policy of stabilizing non-traded inflation produces a unique solution so long as the nominal interest rate is raised more than one for one with increases in non-traded inflation. A policy of stabilizing core inflation, however, produces a unique solution only if the response is greater than one for one and less then one divided by one minus the share of the non-traded good in the CPI. In the third chapter I consider monetary and fiscal policy responses to oil price shocks in a low income oil importing country. The model used in this chapter differs from the model in the second chapter in that there is currency substitution, household demand for oil products, and a potential subsidy on the purchase of oil products by households. I examine the dynamic properties and the welfare implications of a set of inflation targeting policies and a group of policies that subsidize the price of oil and finance the subsidy through a combination of raising lump sum taxes and printing money. The dynamic properties of the inflation targeting policies are similar in many regards to those in the second chapter as the key assumptions driving the results are the same in the two models. For the policies which subsidize the price of oil I show that both the choice to have the subsidy and how to finance it matter a great deal for the behavior of the macroeconomic variables. In terms of welfare, for most calibrations there are only minor differences between the inflation targeting polices, the policy with a subsidy funded by lump sum taxes, and the baseline policy with no subsidy. The policy with a subsidy financed by the inflation tax generally causes significant welfare losses compared to the policy with no pass through.

[Evaluation of rational prescribing and dispensing of medicines in Mali].

PubMed

Maiga, D; Diawara, A; Maiga, M D

2006-12-01

Pharmaceutical policy in Mali is based on the concept of essential medicines and procurement of generic medicines. Unfortunately, increasing availability of generic medicines via different promotional programs can often be accompanied by their irrational use. This survey was thus designed to evaluate rational prescribing and dispensing of medicines in Mali. A cross-sectional survey was conducted from 1998 to 2005 in 30 primary health centers and 30 private dispensaries; in Bamako and in 6 of the 8 other regions of the country. In each of the visited facilities, 20 prescriptions dispensed at the time of the survey were collected. The average number of medicines per prescription was 3.2+/-1.3 and 2.8+/-1.2 respectively in the public and private sectors. Medicines were prescribed under generic name in 88.2% of the public sector prescriptions and in 30.9% of the private sector ones. Antibiotics were prescribed in 70.4% of the public sector prescriptions and in 50.0% of the private sector prescriptions. In the public sector 33.2% of the prescriptions had injections compared with 14.3% in the private sector (p<0.001). The median price per prescription was lower in the public sector (1575.0 CFA F, or 2.4 Euros, of which 91.3% were actually purchased by the patient) than in the private sector (5317.5 CFA F, or 8.1 Euros, of which 84.6% were purchased). Generic medicines are being used in the public sector but less frequently than in private practice. As therapeutic guidelines are already available, it would be useful to institute interactive information for practitioners through intensive visits by more experienced supervisors. The quality of the prescriptions could thus be optimized.

Business grants

NASA Astrophysics Data System (ADS)

Twelve small businesses who are developing equipment and computer programs for geophysics have won Small Business Innovative Research (SBIR) grants from the National Science Foundation for their 1989 proposals. The SBIR program was set up to encourage the private sector to undertake costly, advanced experimental work that has potential for great benefit.The geophysical research projects are a long-path intracavity laser spectrometer for measuring atmospheric trace gases, optimizing a local weather forecast model, a new platform for high-altitude atmospheric science, an advanced density logging tool, a deep-Earth sampling system, superconducting seismometers, a phased-array Doppler current profiler, monitoring mesoscale surface features of the ocean through automated analysis, krypton-81 dating in polar ice samples, discrete stochastic modeling of thunderstorm winds, a layered soil-synthetic liner base system to isolate buildings from earthquakes, and a low-cost continuous on-line organic-content monitor for water-quality determination.

Sectoral transitions - modeling the development from agrarian to service economies

NASA Astrophysics Data System (ADS)

Lutz, Raphael; Spies, Michael; Reusser, Dominik E.; Kropp, Jürgen P.; Rybski, Diego

2013-04-01

We consider the sectoral composition of a country's GDP, i.e the partitioning into agrarian, industrial, and service sectors. Exploring a simple system of differential equations we characterise the transfer of GDP shares between the sectors in the course of economic development. The model fits for the majority of countries providing 4 country-specific parameters. Relating the agrarian with the industrial sector, a data collapse over all countries and all years supports the applicability of our approach. Depending on the parameter ranges, country development exhibits different transfer properties. Most countries follow 3 of 8 characteristic paths. The types are not random but show distinct geographic and development patterns.

Thermal-economic optimisation of a CHP gas turbine system by applying a fit-problem genetic algorithm

NASA Astrophysics Data System (ADS)

Ferreira, Ana C. M.; Teixeira, Senhorinha F. C. F.; Silva, Rui G.; Silva, Ângela M.

2018-04-01

Cogeneration allows the optimal use of the primary energy sources and significant reductions in carbon emissions. Its use has great potential for applications in the residential sector. This study aims to develop a methodology for thermal-economic optimisation of small-scale micro-gas turbine for cogeneration purposes, able to fulfil domestic energy needs with a thermal power out of 125 kW. A constrained non-linear optimisation model was built. The objective function is the maximisation of the annual worth from the combined heat and power, representing the balance between the annual incomes and the expenditures subject to physical and economic constraints. A genetic algorithm coded in the java programming language was developed. An optimal micro-gas turbine able to produce 103.5 kW of electrical power with a positive annual profit (i.e. 11,925 €/year) was disclosed. The investment can be recovered in 4 years and 9 months, which is less than half of system lifetime expectancy.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies.

PubMed

Azadeh, Ali; Sheikhalishahi, Mohammad

2015-06-01

A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors.

The climate impacts of bioenergy systems depend on market and regulatory policy contexts.

PubMed

Lemoine, Derek M; Plevin, Richard J; Cohn, Avery S; Jones, Andrew D; Brandt, Adam R; Vergara, Sintana E; Kammen, Daniel M

2010-10-01

Biomass can help reduce greenhouse gas (GHG) emissions by displacing petroleum in the transportation sector, by displacing fossil-based electricity, and by sequestering atmospheric carbon. Which use mitigates the most emissions depends on market and regulatory contexts outside the scope of attributional life cycle assessments. We show that bioelectricity's advantage over liquid biofuels depends on the GHG intensity of the electricity displaced. Bioelectricity that displaces coal-fired electricity could reduce GHG emissions, but bioelectricity that displaces wind electricity could increase GHG emissions. The electricity displaced depends upon existing infrastructure and policies affecting the electric grid. These findings demonstrate how model assumptions about whether the vehicle fleet and bioenergy use are fixed or free parameters constrain the policy questions an analysis can inform. Our bioenergy life cycle assessment can inform questions about a bioenergy mandate's optimal allocation between liquid fuels and electricity generation, but questions about the optimal level of bioenergy use require analyses with different assumptions about fixed and free parameters.

Potential impact of a transatlantic trade and Investment partnership on the global forest sector

Treesearch

Joseph Buongiorno; Paul Rougieux; Ahmed Barkaoui; Shushuai Zhu; Patrice Harou

2014-01-01

The effects of a transatlantic trade agreement on the global forest sector were assessed with the Global Forest Products Model, conditional on previous macroeconomic impacts predicted with a general equilibrium model. Comprehensive tariff elimination per se had little effect on the forest sector. However, with deeper reforms and integration consumption would increase...

Modeling uncertainties in workforce disruptions from influenza pandemics using dynamic input-output analysis.

PubMed

El Haimar, Amine; Santos, Joost R

2014-03-01

Influenza pandemic is a serious disaster that can pose significant disruptions to the workforce and associated economic sectors. This article examines the impact of influenza pandemic on workforce availability within an interdependent set of economic sectors. We introduce a simulation model based on the dynamic input-output model to capture the propagation of pandemic consequences through the National Capital Region (NCR). The analysis conducted in this article is based on the 2009 H1N1 pandemic data. Two metrics were used to assess the impacts of the influenza pandemic on the economic sectors: (i) inoperability, which measures the percentage gap between the as-planned output and the actual output of a sector, and (ii) economic loss, which quantifies the associated monetary value of the degraded output. The inoperability and economic loss metrics generate two different rankings of the critical economic sectors. Results show that most of the critical sectors in terms of inoperability are sectors that are related to hospitals and health-care providers. On the other hand, most of the sectors that are critically ranked in terms of economic loss are sectors with significant total production outputs in the NCR such as federal government agencies. Therefore, policy recommendations relating to potential mitigation and recovery strategies should take into account the balance between the inoperability and economic loss metrics. © 2013 Society for Risk Analysis.

Child and Adolescent Obesity and Employment Sector in Urban China

PubMed Central

Li, Yi; Zimmer, Zachary

2013-01-01

Despite its importance as a part of the economic reform in China, sectoral employment has been overlooked as a potential determinant of child and adolescent obesity (CAO). Using large-scale longitudinal data from surveys conducted from 1989 to 2006, this paper examines the relationship between the sector in which a parent is employed and CAO, with the sector being based on ownership and categorised as either state or non-state. Analyses of over 1,700 children and adolescents show that children and adolescents whose parents work in the state sector are less likely to be obese. Patterns of sectoral employment's effect are robust across time periods, in fixed-effects models, and across multiple measures of obesity. Additionally, the paper shows that socioeconomic characteristics of the parent, such as income, education, and occupation, typically thought to be important predictors of CAO, are not as important when the parental working sector is included in the models. PMID:24298293

Child and Adolescent Obesity and Employment Sector in Urban China.

PubMed

Li, Yi; Zimmer, Zachary

2013-01-01

Despite its importance as a part of the economic reform in China, sectoral employment has been overlooked as a potential determinant of child and adolescent obesity (CAO). Using large-scale longitudinal data from surveys conducted from 1989 to 2006, this paper examines the relationship between the sector in which a parent is employed and CAO, with the sector being based on ownership and categorised as either state or non-state. Analyses of over 1,700 children and adolescents show that children and adolescents whose parents work in the state sector are less likely to be obese. Patterns of sectoral employment's effect are robust across time periods, in fixed-effects models, and across multiple measures of obesity. Additionally, the paper shows that socioeconomic characteristics of the parent, such as income, education, and occupation, typically thought to be important predictors of CAO, are not as important when the parental working sector is included in the models.

Evaluation on the efficiency of the construction sector companies in Malaysia with data envelopment analysis model

NASA Astrophysics Data System (ADS)

Weng Hoe, Lam; Jinn, Lim Shun; Weng Siew, Lam; Hai, Tey Kim

2018-04-01

In Malaysia, construction sector is essential parts in driving the development of the Malaysian economy. Construction industry is an economic investment and its relationship with economic development is well posited. However, the evaluation on the efficiency of the construction sectors companies listed in Kuala Lumpur Stock Exchange (KLSE) with Data Analysis Envelopment (DEA) model have not been actively studied by the past researchers. Hence the purpose of this study is to examine the financial performance the listed construction sectors companies in Malaysia in the year of 2015. The results of this study show that the efficiency of construction sectors companies can be obtained by using DEA model through ratio analysis which defined as the ratio of total outputs to total inputs. This study is significant because the inefficient companies are identified for potential improvement.

A Multi-Scale Energy Food Systems Modeling Framework For Climate Adaptation

NASA Astrophysics Data System (ADS)

Siddiqui, S.; Bakker, C.; Zaitchik, B. F.; Hobbs, B. F.; Broaddus, E.; Neff, R.; Haskett, J.; Parker, C.

2016-12-01

Our goal is to understand coupled system dynamics across scales in a manner that allows us to quantify the sensitivity of critical human outcomes (nutritional satisfaction, household economic well-being) to development strategies and to climate or market induced shocks in sub-Saharan Africa. We adopt both bottom-up and top-down multi-scale modeling approaches focusing our efforts on food, energy, water (FEW) dynamics to define, parameterize, and evaluate modeled processes nationally as well as across climate zones and communities. Our framework comprises three complementary modeling techniques spanning local, sub-national and national scales to capture interdependencies between sectors, across time scales, and on multiple levels of geographic aggregation. At the center is a multi-player micro-economic (MME) partial equilibrium model for the production, consumption, storage, and transportation of food, energy, and fuels, which is the focus of this presentation. We show why such models can be very useful for linking and integrating across time and spatial scales, as well as a wide variety of models including an agent-based model applied to rural villages and larger population centers, an optimization-based electricity infrastructure model at a regional scale, and a computable general equilibrium model, which is applied to understand FEW resources and economic patterns at national scale. The MME is based on aggregating individual optimization problems for relevant players in an energy, electricity, or food market and captures important food supply chain components of trade and food distribution accounting for infrastructure and geography. Second, our model considers food access and utilization by modeling food waste and disaggregating consumption by income and age. Third, the model is set up to evaluate the effects of seasonality and system shocks on supply, demand, infrastructure, and transportation in both energy and food.

Parametric sensitivity analysis of an agro-economic model of management of irrigation water

NASA Astrophysics Data System (ADS)

El Ouadi, Ihssan; Ouazar, Driss; El Menyari, Younesse

2015-04-01

The current work aims to build an analysis and decision support tool for policy options concerning the optimal allocation of water resources, while allowing a better reflection on the issue of valuation of water by the agricultural sector in particular. Thus, a model disaggregated by farm type was developed for the rural town of Ait Ben Yacoub located in the east Morocco. This model integrates economic, agronomic and hydraulic data and simulates agricultural gross margin across in this area taking into consideration changes in public policy and climatic conditions, taking into account the competition for collective resources. To identify the model input parameters that influence over the results of the model, a parametric sensitivity analysis is performed by the "One-Factor-At-A-Time" approach within the "Screening Designs" method. Preliminary results of this analysis show that among the 10 parameters analyzed, 6 parameters affect significantly the objective function of the model, it is in order of influence: i) Coefficient of crop yield response to water, ii) Average daily gain in weight of livestock, iii) Exchange of livestock reproduction, iv) maximum yield of crops, v) Supply of irrigation water and vi) precipitation. These 6 parameters register sensitivity indexes ranging between 0.22 and 1.28. Those results show high uncertainties on these parameters that can dramatically skew the results of the model or the need to pay particular attention to their estimates. Keywords: water, agriculture, modeling, optimal allocation, parametric sensitivity analysis, Screening Designs, One-Factor-At-A-Time, agricultural policy, climate change.

Tree-based flood damage modeling of companies: Damage processes and model performance

NASA Astrophysics Data System (ADS)

Sieg, Tobias; Vogel, Kristin; Merz, Bruno; Kreibich, Heidi

2017-07-01

Reliable flood risk analyses, including the estimation of damage, are an important prerequisite for efficient risk management. However, not much is known about flood damage processes affecting companies. Thus, we conduct a flood damage assessment of companies in Germany with regard to two aspects. First, we identify relevant damage-influencing variables. Second, we assess the prediction performance of the developed damage models with respect to the gain by using an increasing amount of training data and a sector-specific evaluation of the data. Random forests are trained with data from two postevent surveys after flood events occurring in the years 2002 and 2013. For a sector-specific consideration, the data set is split into four subsets corresponding to the manufacturing, commercial, financial, and service sectors. Further, separate models are derived for three different company assets: buildings, equipment, and goods and stock. Calculated variable importance values reveal different variable sets relevant for the damage estimation, indicating significant differences in the damage process for various company sectors and assets. With an increasing number of data used to build the models, prediction errors decrease. Yet the effect is rather small and seems to saturate for a data set size of several hundred observations. In contrast, the prediction improvement achieved by a sector-specific consideration is more distinct, especially for damage to equipment and goods and stock. Consequently, sector-specific data acquisition and a consideration of sector-specific company characteristics in future flood damage assessments is expected to improve the model performance more than a mere increase in data.

ISI-MIP: The Inter-Sectoral Impact Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Huber, V.; Dahlemann, S.; Frieler, K.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

2013-12-01

The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. The unique cross-sectoral scope of the project provides the opportunity to study cascading effects of impacts in interacting sectors and to identify regional 'hot spots' where multiple sectors experience extreme impacts. Another emphasis lies on the development of novel metrics to describe societal impacts of a warmer climate. We briefly outline the methodological framework, and then present selected results of the first, fast-tracked phase of ISI-MIP. The fast track brought together 35 global impact models internationally, spanning five sectors across human society and the natural world (agriculture, water, natural ecosystems, health and coastal infrastructure), and using the latest generation of global climate simulations (RCP projections from the CMIP5 archive) and socioeconomic drivers provided within the SSP process. We also introduce the second phase of the project, which will enlarge the scope of ISI-MIP by encompassing further impact sectors (e.g., forestry, fisheries, permafrost) and regional modeling approaches. The focus for the next round of simulations will be the validation and improvement of models based on historical observations and the analysis of variability and extreme events. Last but not least, we discuss the longer-term objective of ISI-MIP to initiate a coordinated, ongoing impact assessment process, driven by the entire impact community and in parallel with well-established climate model intercomparisons (CMIP).

Assessing the impacts of 1.5°C of global warming - The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) approach

NASA Astrophysics Data System (ADS)

Zhao, F.; Frieler, K.; Warszawski, L.; Lange, S.; Schewe, J.; Reyer, C.; Ostberg, S.; Piontek, F.; Betts, R. A.; Burke, E.; Ciais, P.; Deryng, D.; Ebi, K. L.; Emanuel, K.; Elliott, J. W.; Galbraith, E. D.; Gosling, S.; Hickler, T.; Hinkel, J.; Jones, C.; Krysanova, V.; Lotze-Campen, H.; Mouratiadou, I.; Popp, A.; Tian, H.; Tittensor, D.; Vautard, R.; van Vliet, M. T. H.; Eddy, T.; Hattermann, F.; Huber, V.; Mengel, M.; Stevanovic, M.; Kirsten, T.; Mueller Schmied, H.; Denvil, S.; Halladay, K.; Suzuki, T.; Lotze, H. K.

2016-12-01

In Paris, France, December 2015 the Conference of Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the IPCC to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016 the IPCC panel accepted the invitation. Here we describe the model simulations planned within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to address the request by providing tailored cross-sectoral consistent impacts projections. The protocol is designed to allow for 1) a separation of the impacts of the historical warming starting from pre-industrial conditions from other human drivers such as historical land use changes (based on pre-industrial and historical impact model simulations), 2) a quantification of the effects of an additional warming to 1.5°C including a potential overshoot and long term effects up to 2300 in comparison to a no-mitigation scenario (based on the low emissions Representative Concentration Pathway RCP2.6 and a no-mitigation scenario RCP6.0) keeping socio-economic conditions fixed at year 2005 levels, and 3) an assessment of the climate effects based on the same climate scenarios but accounting for parallel changes in socio-economic conditions following the middle of the road Shared Socioeconomic Pathway (SSP2) and differential bio-energy requirements associated with the transformation of the energy system to reach RCP2.6 compared to RCP6.0. To provide the scientific basis for an aggregation of impacts across sectors and an analysis of cross-sectoral interactions potentially damping or amplifying sectoral impacts the protocol is designed to provide consistent impacts projections across a range of impact models from different sectors (global and regional hydrological models, global gridded crop models, global vegetation models, regional forestry models, global and regional marine ecosystem and fisheries models, global and regional coastal infrastructure models, energy models, health models, and agro-economic models).

Assessing the impacts of 1.5°C of global warming - The Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) approach

NASA Astrophysics Data System (ADS)

Frieler, Katja; Warszawski, Lila; Zhao, Fang

2017-04-01

In Paris, France, December 2015 the Conference of Parties (COP) to the United Nations Framework Convention on Climate Change (UNFCCC) invited the IPCC to provide a "special report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways". In Nairobi, Kenya, April 2016 the IPCC panel accepted the invitation. Here we describe the model simulations planned within the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) to address the request by providing tailored cross-sectoral consistent impacts projections. The protocol is designed to allow for 1) a separation of the impacts of the historical warming starting from pre-industrial conditions from other human drivers such as historical land use changes (based on pre-industrial and historical impact model simulations), 2) a quantification of the effects of an additional warming to 1.5°C including a potential overshoot and long term effects up to 2300 in comparison to a no-mitigation scenario (based on the low emissions Representative Concentration Pathway RCP2.6 and a no-mitigation scenario RCP6.0) keeping socio-economic conditions fixed at year 2005 levels, and 3) an assessment of the climate effects based on the same climate scenarios but accounting for parallel changes in socio-economic conditions following the middle of the road Shared Socioeconomic Pathway (SSP2) and differential bio-energy requirements associated with the transformation of the energy system to reach RCP2.6 compared to RCP6.0. To provide the scientific basis for an aggregation of impacts across sectors and an analysis of cross-sectoral interactions potentially damping or amplifying sectoral impacts the protocol is designed to provide consistent impacts projections across a range of impact models from different sectors (global and regional hydrological models, global gridded crop models, global vegetation models, regional forestry models, global and regional marine ecosystem and fisheries models, global and regional coastal infrastructure models, energy models, health models, and agro-economic models).

Top-down NOx and SO2 emissions simultaneously estimated from different OMI retrievals and inversion frameworks

NASA Astrophysics Data System (ADS)

Qu, Z.; Henze, D. K.; Wang, J.; Xu, X.; Wang, Y.

2017-12-01

Quantifying emissions trends of nitrogen oxides (NOx) and sulfur dioxide (SO2) is important for improving understanding of air pollution and the effectiveness of emission control strategies. We estimate long-term (2005-2016) global (2° x 2.5° resolution) and regional (North America and East Asia at 0.5° x 0.667° resolution) NOx emissions using a recently developed hybrid (mass-balance / 4D-Var) method with GEOS-Chem. NASA standard product and DOMINO retrievals of NO2 column are both used to constrain emissions; comparison of these results provides insight into regions where trends are most robust with respect to retrieval uncertainties, and highlights regions where seemingly significant trends are retrieval-specific. To incorporate chemical interactions among species, we extend our hybrid method to assimilate NO2 and SO2 observations and optimize NOx and SO2 emissions simultaneously. Due to chemical interactions, inclusion of SO2 observations leads to 30% grid-scale differences in posterior NOx emissions compared to those constrained only by NO2 observations. When assimilating and optimizing both species in pseudo observation tests, the sum of the normalized mean squared error (compared to the true emissions) of NOx and SO2 posterior emissions are 54-63% smaller than when observing/constraining a single species. NOx and SO2 emissions are also correlated through the amount of fuel combustion. To incorporate this correlation into the inversion, we optimize seven sector-specific emission scaling factors, including industry, energy, residential, aviation, transportation, shipping and agriculture. We compare posterior emissions from inversions optimizing only species' emissions, only sector-based emissions, and both species' and sector-based emissions. In situ measurements of NOx and SO2 are applied to evaluate the performance of these inversions. The impacts of the inversion on PM2.5 and O3 concentrations and premature deaths are also evaluated.

On domain symmetry and its use in homogenization

DOE PAGES

Barbarosie, Cristian A.; Tortorelli, Daniel A.; Watts, Seth E.

2017-03-08

The present study focuses on solving partial differential equations in domains exhibiting symmetries and periodic boundary conditions for the purpose of homogenization. We show in a systematic manner how the symmetry can be exploited to significantly reduce the complexity of the problem and the computational burden. This is especially relevant in inverse problems, when one needs to solve the partial differential equation (the primal problem) many times in an optimization algorithm. The main motivation of our study is inverse homogenization used to design architected composite materials with novel properties which are being fabricated at ever increasing rates thanks to recentmore » advances in additive manufacturing. For example, one may optimize the morphology of a two-phase composite unit cell to achieve isotropic homogenized properties with maximal bulk modulus and minimal Poisson ratio. Typically, the isotropy is enforced by applying constraints to the optimization problem. However, in two dimensions, one can alternatively optimize the morphology of an equilateral triangle and then rotate and reflect the triangle to form a space filling D 3 symmetric hexagonal unit cell that necessarily exhibits isotropic homogenized properties. One can further use this D 3 symmetry to reduce the computational expense by performing the “unit strain” periodic boundary condition simulations on the single triangle symmetry sector rather than the six fold larger hexagon. In this paper we use group representation theory to derive the necessary periodic boundary conditions on the symmetry sectors of unit cells. The developments are done in a general setting, and specialized to the two-dimensional dihedral symmetries of the abelian D 2, i.e. orthotropic, square unit cell and nonabelian D 3, i.e. trigonal, hexagon unit cell. We then demonstrate how this theory can be applied by evaluating the homogenized properties of a two-phase planar composite over the triangle symmetry sector of a D 3 symmetric hexagonal unit cell.« less

General structure of democratic mass matrix of quark sector in E{sub 6} model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ciftci, R., E-mail: rciftci@cern.ch; Çiftci, A. K., E-mail: abbas.kenan.ciftci@cern.ch

2016-03-25

An extension of the Standard Model (SM) fermion sector, which is inspired by the E{sub 6} Grand Unified Theory (GUT) model, might be a good candidate to explain a number of unanswered questions in SM. Existence of the isosinglet quarks might explain great mass difference of bottom and top quarks. Also, democracy on mass matrix elements is a natural approach in SM. In this study, we have given general structure of Democratic Mass Matrix (DMM) of quark sector in E6 model.

Exposing the dark sector with future Z factories

NASA Astrophysics Data System (ADS)

Liu, Jia; Wang, Lian-Tao; Wang, Xiao-Ping; Xue, Wei

2018-05-01

We investigate the prospects of searching dark sector models via exotic Z -boson decay at future e+e- colliders with Giga Z and Tera Z options. Four general categories of dark sector models, Higgs portal dark matter, vector-portal dark matter, inelastic dark matter, and axionlike particles, are considered. Focusing on channels motivated by the dark sector models, we carry out a model-independent study of the sensitivities of Z factories in probing exotic decays. The limits on branching ratios of the exotic Z decay are typically O (10-6- 10-8.5) for the Giga Z and O (10-7.5- 10-11) for the Tera Z , and they are compared with the projection for the high luminosity LHC. We demonstrate that future Z factories can provide its unique and leading sensitivity and highlight the complementarity with other experiments, including the indirect and direct dark matter search limits and the existing collider limits. Future Z factories will play a leading role in uncovering the hidden sector of the Universe in the future.

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Cost-effectiveness of interventions to prevent alcohol-related disease and injury in Australia.

PubMed

Cobiac, Linda; Vos, Theo; Doran, Christopher; Wallace, Angela

2009-10-01

To evaluate cost-effectiveness of eight interventions for reducing alcohol-attributable harm and determine the optimal intervention mix. Interventions include volumetric taxation, advertising bans, an increase in minimum legal drinking age, licensing controls on operating hours, brief intervention (with and without general practitioner telemarketing and support), drink driving campaigns, random breath testing and residential treatment for alcohol dependence (with and without naltrexone). Cost-effectiveness is modelled over the life-time of the Australian population in 2003, with all costs and health outcomes evaluated from an Australian health sector perspective. Each intervention is compared with current practice, and the most cost-effective options are then combined to determine the optimal intervention mix. Cost-effectiveness is measured in 2003 Australian dollars per disability adjusted life year averted. Although current alcohol intervention in Australia (random breath testing) is cost-effective, if the current spending of $71 million could be invested in a more cost-effective combination of interventions, more than 10 times the amount of health gain could be achieved. Taken as a package of interventions, all seven preventive interventions would be a cost-effective investment that could lead to substantial improvement in population health; only residential treatment is not cost-effective. Based on current evidence, interventions to reduce harm from alcohol are highly recommended. The potential reduction in costs of treating alcohol-related diseases and injuries mean that substantial improvements in population health can be achieved at a relatively low cost to the health sector. © 2009 The Authors. Journal compilation © 2009 Society for the Study of Addiction.

Simulating the Water Use of Thermoelectric Power Plants in the United States: Model Development and Verification

NASA Astrophysics Data System (ADS)

Betrie, G.; Yan, E.; Clark, C.

2016-12-01

Thermoelectric power plants use the highest amount of freshwater second to the agriculture sector. However, there is scarcity of information that characterizes the freshwater use of these plants in the United States. This could be attributed to the lack of model and data that are required to conduct analysis and gain insights. The competition for freshwater among sectors will increase in the future as the amount of freshwater gets limited due climate change and population growth. A model that makes use of less data is urgently needed to conduct analysis and identify adaptation strategies. The objectives of this study are to develop a model and simulate the water use of thermoelectric power plants in the United States. The developed model has heat-balance, climate, cooling system, and optimization modules. It computes the amount of heat rejected to the environment, estimates the quantity of heat exchanged through latent and sensible heat to the environment, and computes the amount of water required per unit generation of electricity. To verify the model, we simulated a total of 876 fossil-fired, nuclear and gas-turbine power plants with different cooling systems (CS) using 2010-2014 data obtained from Energy Information Administration. The CS includes once-through with cooling pond, once-through without cooling ponds, recirculating with induced draft and recirculating with induced draft natural draft. The results show that the model reproduced the observed water use per unit generation of electricity for the most of the power plants. It is also noticed that the model slightly overestimates the water use during the summer period when the input water temperatures are higher. We are investigating the possible reasons for the overestimation and address it in the future work. The model could be used individually or coupled to regional models to analyze various adaptation strategies and improve the water use efficiency of thermoelectric power plants.

Assessment of the Efficiency of Hospitals Before and After the Implementation of Health Sector Evolution Plan in Iran Based on Pabon Lasso Model

PubMed Central

MORADI, Ghobad; PIROOZI, Bakhtiar; SAFARI, Hossein; ESMAIL NASAB, Nader; MOHAMADI BOLBANABAD, Amjad; YARI, Arezoo

2017-01-01

Background: Pabon Lasso model was applied to assess the relative performance of hospitals affiliated to Kurdistan University of Medical Sciences (KUMS) before and after the implementation of Health Sector Evolution Plan (HSEP) in Iran. Methods: This cross-sectional study was carried out in 11 public hospitals affiliated to KUMS in 2015. Twelve months before and after the implementation of the first phase of HSEP, a checklist was used to collect data from computerized databases within the hospitals’ admission and discharge units. Pabon Lasso model includes three indices: bed turnover, bed occupancy ratio, and average length of stay. Results: Analysis of hospital performance showed an increase in mean of bed occupancy and turnover ratio, which changed from 65.40% and 86.22 times/year during 12 months before to 69.97% and 90.98 times/year during 12 months after HSEP, respectively. In line with Pabon Lasso model, before the implementation of HSEP, 27.27% and 36.36% of the hospitals were entirely efficient and inefficient, respectively, whilst after the implementation of HSEP, their condition changed to 18.18% and 27.27%, in order. Conclusion: Indicators of bed occupancy and turnover ratio had a 4% increase in the studied hospitals after the implementation of HSEP. Number of the hospitals in the efficient zone reduced because of the relative measurement of efficiency by Pabon Lasso model. Since more than 50% of the hospitals in the studied province have not yet reached their optimal bed occupancy ratio (more than 70%), short-term and suitable strategy for improving the efficiency is to stop further expansion of hospitals as well as developing the number of hospital beds. PMID:28435825

Outcomes of a nurse-managed service for stable HIV-positive patients in a large South African public sector antiretroviral therapy programme.

PubMed

Grimsrud, Anna; Kaplan, Richard; Bekker, Linda-Gail; Myer, Landon

2014-09-01

Models of care utilizing task shifting and decentralization are needed to support growing ART programmes. We compared patient outcomes between a doctor-managed clinic and a nurse-managed down-referral site in Cape Town, South Africa. Analysis included all adults who initiated ART between 2002 and 2011 within a large public sector ART service. Stable patients were eligible for down-referral. Outcomes [mortality, loss to follow-up (LTFU), virologic failure] were compared under different models of care using proportional hazards models with time-dependent covariates. Five thousand seven hundred and forty-six patients initiated ART and over 5 years 41% (n = 2341) were down-referred; the median time on ART before down-referral was 1.6 years (interquartile range, 0.9-2.6). The nurse-managed down-referral site reported lower crude rates of mortality, LTFU and virologic failure compared with the doctor-managed clinic. After adjustment, there was no difference in the risk of mortality or virologic failure by model of care. However, patients who were down-referred were more likely to be LTFU than those retained at the doctor-managed site (adjusted hazard ratio, 1.36; 95% CI, 1.09-1.69). Increased levels of LTFU in the nurse-managed vs. doctor-managed service were observed in subgroups of male patients, those with advanced disease at initiation and those who started ART in the early years of the programme. Reorganization of ART maintenance by down-referral to nurse-managed services is associated with programme outcomes similar to those achieved using doctor-driven primary care services. Further research is necessary to identify optimal models of care to support long-term retention of patients on ART in resource-limited settings. © 2014 John Wiley & Sons Ltd.

Promoting inclusive water governance and forecasting the structure of water consumption based on compositional data: A case study of Beijing.

PubMed

Wei, Yigang; Wang, Zhichao; Wang, Huiwen; Yao, Tang; Li, Yan

2018-09-01

Water is centrally important for agricultural security, environment, people's livelihoods, and socio-economic development, particularly in the face of extreme climate changes. Due to water shortages in many cities, the conflicts between various stakeholders and sectors over water use and allocation are becoming more common and intense. Effective inclusive governance of water use is critical for relieving water use conflicts. In addition, reliable forecasting of the structure of water usage among different sectors is a basic need for effective water governance planning. Although a large number of studies have attempted to forecast water use, little is known about the forecasted structure and trends of water use in the future. This paper aims to develop a forecasting model for the structure of water usage based on compositional data. Compositional data analysis is an effective approach for investigating the internal structure of a system. A host of data transformation methods and forecasting models were adopted and compared in order to derive the best-performing model. According to mean absolute percent error for compositional data (CoMAPE), a hyperspherical-transformation-based vector autoregression model for compositional data (VAR-DRHT) is the best-performing model. The proportions of the agricultural, industrial, domestic and environmental water will be 6.11%, 5.01%, 37.48% and 51.4% by 2020. Several recommendations for water inclusive development are provided to give a better account for the optimization of the water use structure, alleviation of water shortages, and improving stake holders' wellbeing. Overall, although we focus on groundwater, this study presents a powerful framework broadly applicable to resource management. Copyright © 2018 Elsevier B.V. All rights reserved.

A Multi-Sector Assessment of the Effects of Climate Change at the Energy-Water-Land Nexus in the US

NASA Astrophysics Data System (ADS)

McFarland, J.; Sarofim, M. C.; Martinich, J.

2017-12-01

Rising temperatures and changing precipitation patterns due to climate change are projected to alter many sectors of the US economy. A growing body of research has examined these effects in the energy, water, and agricultural sectors. Rising summer temperatures increase the demand for electricity. Changing precipitation patterns effect the availability of water for hydropower generation, thermo-electric cooling, irrigation, and municipal and industrial consumption. A combination of changes to temperature and precipitation alter crop yields and cost-effective farming practices. Although a significant body of research exists on analyzing impacts to individual sectors, fewer studies examine the effects using a common set of assumptions (e.g., climatic and socio-economic) within a coupled modeling framework. The present analysis uses a multi-sector, multi-model framework with common input assumptions to assess the projected effects of climate change on energy, water, and land-use in the United States. The analysis assesses the climate impacts for across 5 global circulation models for representative concentration pathways (RCP) of 8.5 and 4.5 W/m2. The energy sector models - Pacific Northwest National Lab's Global Change Assessment Model (GCAM) and the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) - show the effects of rising temperature on energy and electricity demand. Electricity supply in ReEDS is also affected by the availability of water for hydropower and thermo-electric cooling. Water availability is calculated from the GCM's precipitation using the US Basins model. The effects on agriculture are estimated using both a process-based crop model (EPIC) and an agricultural economic model (FASOM-GHG), which adjusts water supply curves based on information from US Basins. The sectoral models show higher economic costs of climate change under RCP 8.5 than RCP 4.5 averaged across the country and across GCM's.

Environmental pollution as engine of industrialization

NASA Astrophysics Data System (ADS)

Antoci, Angelo; Galeotti, Marcello; Sordi, Serena

2018-05-01

This paper analyzes the dynamics of a small open economy with two sectors (a farming sector and an industrial one), heterogeneous agents (workers and entrepreneurs) and free inter-sectoral labor mobility. Labor productivity in the first sector is negatively affected by environmental pollution generated by both sectors, whereas in the second sector it is positively affected by physical capital accumulated by entrepreneurs. Through a global analysis of the non-linear three-dimensional dynamic system of the model we derive conditions under which industrialization generates a decline in workers' revenues in both sectors.

Impacts of Rising Air Temperatures and Emissions Mitigation on Electricity Demand and Supply in the United States. A Multi-Model Comparison

DOE PAGES

McFarland, James; Zhou, Yuyu; Clarke, Leon; ...

2015-06-10

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Fewer studies have explored the physical impacts of climate change on the power sector. Our present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effectsmore » of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. Moreover, the increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.« less

Productivity growth, case mix and optimal size of hospitals. A 16-year study of the Norwegian hospital sector.

PubMed

Anthun, Kjartan Sarheim; Kittelsen, Sverre Andreas Campbell; Magnussen, Jon

2017-04-01

This paper analyses productivity growth in the Norwegian hospital sector over a period of 16 years, 1999-2014. This period was characterized by a large ownership reform with subsequent hospital reorganizations and mergers. We describe how technological change, technical productivity, scale efficiency and the estimated optimal size of hospitals have evolved during this period. Hospital admissions were grouped into diagnosis-related groups using a fixed-grouper logic. Four composite outputs were defined and inputs were measured as operating costs. Productivity and efficiency were estimated with bootstrapped data envelopment analyses. Mean productivity increased by 24.6% points from 1999 to 2014, an average annual change of 1.5%. There was a substantial growth in productivity and hospital size following the ownership reform. After the reform (2003-2014), average annual growth was <0.5%. There was no evidence of technical change. Estimated optimal size was smaller than the actual size of most hospitals, yet scale efficiency was high even after hospital mergers. However, the later hospital mergers have not been followed by similar productivity growth as around time of the reform. This study addresses the issues of both cross-sectional and longitudinal comparability of case mix between hospitals, and thus provides a framework for future studies. The study adds to the discussion on optimal hospital size. Copyright © 2017 Elsevier B.V. All rights reserved.

A participatory model for improving occupational health and safety: improving informal sector working conditions in Thailand.

PubMed

Manothum, Aniruth; Rukijkanpanich, Jittra; Thawesaengskulthai, Damrong; Thampitakkul, Boonwa; Chaikittiporn, Chalermchai; Arphorn, Sara

2009-01-01

The purpose of this study was to evaluate the implementation of an Occupational Health and Safety Management Model for informal sector workers in Thailand. The studied model was characterized by participatory approaches to preliminary assessment, observation of informal business practices, group discussion and participation, and the use of environmental measurements and samples. This model consisted of four processes: capacity building, risk analysis, problem solving, and monitoring and control. The participants consisted of four local labor groups from different regions, including wood carving, hand-weaving, artificial flower making, and batik processing workers. The results demonstrated that, as a result of applying the model, the working conditions of the informal sector workers had improved to meet necessary standards. This model encouraged the use of local networks, which led to cooperation within the groups to create appropriate technologies to solve their problems. The authors suggest that this model could effectively be applied elsewhere to improve informal sector working conditions on a broader scale.

A comprehensive framework to assess, model, and enhance the human role in conserving energy in commercial buildings

NASA Astrophysics Data System (ADS)

Azar, Elie

Energy conservation and sustainability are subjects of great interest today, especially in the commercial building sector which is witnessing a very high and growing demand for energy. Traditionally, efforts to reduce energy consumption in this sector consisted of researching and developing energy efficient building technologies and systems. On the other hand, recent studies indicate that human actions are major determinants of building energy performance and can lead to excessive energy use even in advanced low-energy buildings. As a result, it is essential to determine if the approach to future energy reduction initiatives should remain solely technology-focused, or if a human-focused approach is also needed to complement advancements in technology and improve building operation and performance. In practice, while technology-focused solutions have been extensively researched, promoted, and adopted in commercial buildings, research efforts on the role of human actions and energy use behaviors in energy conservation remain very limited. This study fills the missing gap in literature by presenting a comprehensive framework to (1) understand and quantify the influence of human actions on building energy performance, (2) model building occupants' energy use behaviors and account for potential changes in these behaviors over time, and (3) test and optimize different human-focused energy reduction interventions to increase their adoption in commercial buildings. Results are significant and prove that human actions have a major role to play in reducing the energy intensity of the commercial building sector. This sheds the light on the need for a shift in how people currently use and control different buildings systems, as this is crucial to ensure efficient building operation and to maximize the return on investment in energy-efficient technologies. Furthermore, this study proposes methods and tools that can be applied on any individual or groups of commercial buildings to evaluate the human impact on their energy performance. This is expected to boost research on the topic and promote the integration of human-focused interventions in large-scale energy reduction initiatives and policies. Finally, this dissertation presents a roadmap for the future challenges to energy conservation and the steps to take towards a more sustainable building sector and society.

Using learning curves on energy-efficient technologies to estimate future energy savings and emission reduction potentials in the U.S. iron and steel industry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Park, Won Young; McNeil, Michael A.

Increasing concerns on non-sustainable energy use and climate change spur a growing research interest in energy efficiency potentials in various critical areas such as industrial production. This paper focuses on learning curve aspects of energy efficiency measures in the U.S iron and steel sector. A number of early-stage efficient technologies (i.e., emerging or demonstration technologies) are technically feasible and have the potential to make a significant contribution to energy saving and CO 2 emissions reduction, but fall short economically to be included. However, they may also have the cost effective potential for significant cost reduction and/or performance improvement in themore » future under learning effects such as ‘learning-by-doing’. The investigation is carried out using ISEEM, a technology oriented, linear optimization model. We investigated how steel demand is balanced with/without the availability learning curve, compared to a Reference scenario. The retrofit (or investment in some cases) costs of energy efficient technologies decline in the scenario where learning curve is applied. The analysis also addresses market penetration of energy efficient technologies, energy saving, and CO 2 emissions in the U.S. iron and steel sector with/without learning impact. Accordingly, the study helps those who use energy models better manage the price barriers preventing unrealistic diffusion of energy-efficiency technologies, better understand the market and learning system involved, predict future achievable learning rates more accurately, and project future savings via energy-efficiency technologies with presence of learning. We conclude from our analysis that, most of the existing energy efficiency technologies that are currently used in the U.S. iron and steel sector are cost effective. Penetration levels increases through the years, even though there is no price reduction. However, demonstration technologies are not economically feasible in the U.S. iron and steel sector with the current cost structure. In contrast, some of the demonstration technologies are adapted in the mid-term and their penetration levels increase as the prices go down with learning curve. We also observe large penetration of 225kg pulverized coal injection with the presence of learning.« less

Optimizing desalinated sea water blending with other sources to meet magnesium requirements for potable and irrigation waters.

PubMed

Avni, Noa; Eben-Chaime, Moshe; Oron, Gideon

2013-05-01

Sea water desalination provides fresh water that typically lacks minerals essential to human health and to agricultural productivity. Thus the rising proportion of desalinated sea water consumed by both the domestic and agricultural sectors constitutes a public health risk. Research on low-magnesium water irrigation showed that crops developed magnesium deficiency symptoms that could lead to plant death, and tomato yields were reduced by 10-15%. The World Health Organization (WHO) reported on a relationship between sudden cardiac death rates and magnesium intake deficits. An optimization model, developed and tested to provide recommendations for Water Distribution System (WDS) quality control in terms of meeting optimal water quality requirements, was run in computational experiments based on an actual regional WDS. The expected magnesium deficit due to the operation of a large Sea Water Desalination Plant (SWDP) was simulated, and an optimal operation policy, in which remineralization at the SWDP was combined with blending desalinated and natural water to achieve the required quality, was generated. The effects of remineralization costs and WDS physical layout on the optimal policy were examined by sensitivity analysis. As part of the sensitivity blending natural and desalinated water near the treatment plants will be feasible up to 16.2 US cents/m(3), considering all expenses. Additional chemical injection was used to meet quality criteria when blending was not feasible. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

Integrating water use into Southern California's power dispatch: an evaluation of the potential for cost-effective water conservation

NASA Astrophysics Data System (ADS)

Bolorinos, J.; Ajami, N.; Yu, Y.; Rajagopal, R.

2016-12-01

Urban water supply and energy systems in the arid Southwestern United States are closely linked. Freshwater use by the electricity sector in particular represents a sizable portion of total water consumption in the region. Nonetheless, the dispatch of water and energy resources is managed separately, and no research to-date has examined the water conservation potential presented by the electricity sector. This study gauges the potential water savings that could be achieved including water use in the power dispatch process in Southern California by simulating a DC Optimal Power Flow for a simplified model of the region's power network. The simulation uses historical power consumption data, historical power production data and water use data from the US Geological Survey, the California Energy Commission and the US Energy Information Administration to estimate freshwater consumption by the region's thermoelectric power generation fleet. Preliminary results indicate that power system freshwater consumption could be reduced by as much as 20% at a minimal cost penalty, with potential for even greater savings. Model results show that Southern California's power system has the ability to competitively shift the use of some of the region's water resources from electricity to urban consumption, and suggests that water use should be incorporated into the policy-making process to enhance the efficient use of the state's interconnected water and energy resources.

Falls From Agricultural Machinery: Risk Factors Related to Work Experience, Worked Hours, and Operators' Behavior.

PubMed

Caffaro, Federica; Roccato, Michele; Micheletti Cremasco, Margherita; Cavallo, Eugenio

2018-02-01

Objective We investigated the risk factors for falls when egressing from agricultural tractors, analyzing the role played by worked hours, work experience, operators' behavior, and near misses. Background Many accidents occur within the agricultural sector each year. Among them, falls while dismounting the tractor represent a major source of injuries. Previous studies pointed out frequent hazardous movements and incorrect behaviors adopted by operators to exit the tractor cab. However, less is known about the determinants of such behaviors. In addition, near misses are known to be important predictors of accidents, but they have been under-investigated in the agricultural sector in general and as concerns falls in particular. Method A questionnaire assessing dismounting behaviors, previous accidents and near misses, and participants' relation with work was administered to a sample of Italian tractor operators ( n = 286). Results A mediated model showed that worked hours increase unsafe behaviors, whereas work experience decreases them. Unsafe behaviors in turn show a positive association with accidents, via the mediation of near misses. Conclusions We gave a novel contribution to the knowledge of the chain of events leading to fall accidents in the agricultural sector, which is one of the most hazardous industries. Applications Besides tractor design improvements, preventive training interventions may focus on the redesign of the actual working strategies and the adoption of engaging training methods in the use of machinery to optimize the learning of safety practices and safe behaviors.

Modeling the Value of Integrated Canadian and U.S. Power Sector Expansion

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cole, Wesley, Beiter, Philipp; Steinberg, Daniel

2016-09-08

The United States and Canada power systems are not isolated. Cross-border transmission and coordination of system operation create an interconnected power system, which results in combined imports and exports of electricity of greater than 70 TWh per year [1]. Currently, over 5 GW of new international transmission lines are in various stages of permitting and development. These lines may enable greater integration and coordination of the U.S. and Canada systems, which can in turn reduce challenges associated with integration of high penetrations of variable renewables. Furthermore, low-cost Canadian resources, such as wind and hydro, could contribute to compliance with themore » EPA's recently released Clean Power Plan. Improving integration and coordination internationally will reduce the costs of accessing these resources. This analysis work build on previous work by Ibanez and Zinaman [2]. In this work we seek to better understand the value of additional interconnection between the U.S. and Canadian power systems. Specifically, we quantify the value of additional interconnection and coordination within the Canadian-US integrated power system under scenarios in which large reductions (>80%) in power sector CO2 emissions are achieved. We explore how the ability to add additional cross-border transmission impacts capacity investment, the generation mix, system costs, and the ability of the system to integrate variable renewable energy into the power system. This analysis uses the Regional Energy Deployment System (ReEDS) capacity expansion model [3], [4] to quantify the value of the integrated power system expansion of the United States and Canada. ReEDS is an optimization model that assesses the deployment and operation (including transmission) of the electricity sector of the contiguous United States and Canadian provinces from 2016 through 2050. It has the ability to model the integration of renewable energy technologies into the grid. ReEDS captures renewable energy resources through the use of 356 individual resource regions and 134 balancing areas across the U.S. and is able to handle renewable energy issues such as variability in wind and solar output, transmission costs and constraints, and ancillary services requirements.« less

Scalable multi-objective control for large scale water resources systems under uncertainty

NASA Astrophysics Data System (ADS)

Giuliani, Matteo; Quinn, Julianne; Herman, Jonathan; Castelletti, Andrea; Reed, Patrick

2016-04-01

The use of mathematical models to support the optimal management of environmental systems is rapidly expanding over the last years due to advances in scientific knowledge of the natural processes, efficiency of the optimization techniques, and availability of computational resources. However, undergoing changes in climate and society introduce additional challenges for controlling these systems, ultimately motivating the emergence of complex models to explore key causal relationships and dependencies on uncontrolled sources of variability. In this work, we contribute a novel implementation of the evolutionary multi-objective direct policy search (EMODPS) method for controlling environmental systems under uncertainty. The proposed approach combines direct policy search (DPS) with hierarchical parallelization of multi-objective evolutionary algorithms (MOEAs) and offers a threefold advantage: the DPS simulation-based optimization can be combined with any simulation model and does not add any constraint on modeled information, allowing the use of exogenous information in conditioning the decisions. Moreover, the combination of DPS and MOEAs prompts the generation or Pareto approximate set of solutions for up to 10 objectives, thus overcoming the decision biases produced by cognitive myopia, where narrow or restrictive definitions of optimality strongly limit the discovery of decision relevant alternatives. Finally, the use of large-scale MOEAs parallelization improves the ability of the designed solutions in handling the uncertainty due to severe natural variability. The proposed approach is demonstrated on a challenging water resources management problem represented by the optimal control of a network of four multipurpose water reservoirs in the Red River basin (Vietnam). As part of the medium-long term energy and food security national strategy, four large reservoirs have been constructed on the Red River tributaries, which are mainly operated for hydropower production, flood control, and water supply. Numerical results under historical as well as synthetically generated hydrologic conditions show that our approach is able to discover key system tradeoffs in the operations of the system. The ability of the algorithm to find near-optimal solutions increases with the number of islands in the adopted hierarchical parallelization scheme. In addition, although significant performance degradation is observed when the solutions designed over history are re-evaluated over synthetically generated inflows, we successfully reduced these vulnerabilities by identifying alternative solutions that are more robust to hydrologic uncertainties, while also addressing the tradeoffs across the Red River multi-sector services.

An optimal renewable energy mix for Indonesia

NASA Astrophysics Data System (ADS)

Leduc, Sylvain; Patrizio, Piera; Yowargana, Ping; Kraxner, Florian

2016-04-01

Indonesia has experienced a constant increase of the use of petroleum and coal in the power sector, while the share of renewable sources has remained stable at 6% of the total energy production during the last decade. As its domestic energy demand undeniably continues to grow, Indonesia is committed to increase the production of renewable energy. Mainly to decrease its dependency on fossil fuel-based resources, and to decrease the anthropogenic emissions, the government of Indonesia has established a 23 percent target for renewable energy by 2025, along with a 100 percent electrification target by 2020 (the current rate is 80.4 percent). In that respect, Indonesia has abundant resources to meet these targets, but there is - inter alia - a lack of proper integrated planning, regulatory support, investment, distribution in remote areas of the Archipelago, and missing data to back the planning. To support the government of Indonesia in its sustainable energy system planning, a geographic explicit energy modeling approach is applied. This approach is based on the energy systems optimization model BeWhere, which identifies the optimal location of energy conversion sites based on the minimization of the costs of the supply chain. The model will incorporate the existing fossil fuel-based infrastructures, and evaluate the optimal costs, potentials and locations for the development of renewable energy technologies (i.e., wind, solar, hydro, biomass and geothermal based technologies), as well as the development of biomass co-firing in existing coal plants. With the help of the model, an optimally adapted renewable energy mix - vis-à-vis the competing fossil fuel based resources and applicable policies in order to promote the development of those renewable energy technologies - will be identified. The development of the optimal renewable energy technologies is carried out with special focus on nature protection and cultural heritage areas, where feedstock (e.g., biomass harvesting) and green-field power plant sites will be limited - depending on the protection type and renewable energy technology. The results of the study provide indications to the policy makers on where, how and which technologies should be implemented, and what kind of policy support would be needed in order to increase and meet the Indonesian renewable energy target and to increase the energy access for all.

Source-sector contributions to European ozone and fine PM in 2010 using AQMEII modeling data

NASA Astrophysics Data System (ADS)

Karamchandani, Prakash; Long, Yoann; Pirovano, Guido; Balzarini, Alessandra; Yarwood, Greg

2017-05-01

Source apportionment modeling provides valuable information on the contributions of different source sectors and/or source regions to ozone (O3) or fine particulate matter (PM2.5) concentrations. This information can be useful in designing air quality management strategies and in understanding the potential benefits of reducing emissions from a particular source category. The Comprehensive Air quality Model with Extensions (CAMx) offers unique source attribution tools, called the Ozone and Particulate Source Apportionment Technology (OSAT/PSAT), which track source contributions. We present results from a CAMx source attribution modeling study for a summer month and a winter month using a recently evaluated European CAMx modeling database developed for Phase 3 of the Air Quality Model Evaluation International Initiative (AQMEII). The contributions of several source sectors (including model boundary conditions of chemical species representing transport of emissions from outside the modeling domain as well as initial conditions of these species) to O3 or PM2.5 concentrations in Europe were calculated using OSAT and PSAT, respectively. A 1-week spin-up period was used to reduce the influence of initial conditions. Evaluation focused on 16 major cities and on identifying source sectors that contributed above 5 %. Boundary conditions have a large impact on summer and winter ozone in Europe and on summer PM2.5, but they are only a minor contributor to winter PM2.5. Biogenic emissions are important for summer ozone and PM2.5. The important anthropogenic sectors for summer ozone are transportation (both on-road and non-road), energy production and conversion, and industry. In two of the 16 cities, solvent and product also contributed above 5 % to summertime ozone. For summertime PM2.5, the important anthropogenic source sectors are energy, transportation, industry, and agriculture. Residential wood combustion is an important anthropogenic sector in winter for PM2.5 over most of Europe, with larger contributions in central and eastern Europe and the Nordic cities. Other anthropogenic sectors with large contributions to wintertime PM2.5 include energy, transportation, and agriculture.

Convective Weather Forecast Accuracy Analysis at Center and Sector Levels

NASA Technical Reports Server (NTRS)

Wang, Yao; Sridhar, Banavar

2010-01-01

This paper presents a detailed convective forecast accuracy analysis at center and sector levels. The study is aimed to provide more meaningful forecast verification measures to aviation community, as well as to obtain useful information leading to the improvements in the weather translation capacity models. In general, the vast majority of forecast verification efforts over past decades have been on the calculation of traditional standard verification measure scores over forecast and observation data analyses onto grids. These verification measures based on the binary classification have been applied in quality assurance of weather forecast products at the national level for many years. Our research focuses on the forecast at the center and sector levels. We calculate the standard forecast verification measure scores for en-route air traffic centers and sectors first, followed by conducting the forecast validation analysis and related verification measures for weather intensities and locations at centers and sectors levels. An approach to improve the prediction of sector weather coverage by multiple sector forecasts is then developed. The weather severe intensity assessment was carried out by using the correlations between forecast and actual weather observation airspace coverage. The weather forecast accuracy on horizontal location was assessed by examining the forecast errors. The improvement in prediction of weather coverage was determined by the correlation between actual sector weather coverage and prediction. observed and forecasted Convective Weather Avoidance Model (CWAM) data collected from June to September in 2007. CWAM zero-minute forecast data with aircraft avoidance probability of 60% and 80% are used as the actual weather observation. All forecast measurements are based on 30-minute, 60- minute, 90-minute, and 120-minute forecasts with the same avoidance probabilities. The forecast accuracy analysis for times under one-hour showed that the errors in intensity and location for center forecast are relatively low. For example, 1-hour forecast intensity and horizontal location errors for ZDC center were about 0.12 and 0.13. However, the correlation between sector 1-hour forecast and actual weather coverage was weak, for sector ZDC32, about 32% of the total variation of observation weather intensity was unexplained by forecast; the sector horizontal location error was about 0.10. The paper also introduces an approach to estimate the sector three-dimensional actual weather coverage by using multiple sector forecasts, which turned out to produce better predictions. Using Multiple Linear Regression (MLR) model for this approach, the correlations between actual observation and the multiple sector forecast model prediction improved by several percents at 95% confidence level in comparison with single sector forecast.

A framework for linking cybersecurity metrics to the modeling of macroeconomic interdependencies.

PubMed

Santos, Joost R; Haimes, Yacov Y; Lian, Chenyang

2007-10-01

Hierarchical decision making is a multidimensional process involving management of multiple objectives (with associated metrics and tradeoffs in terms of costs, benefits, and risks), which span various levels of a large-scale system. The nation is a hierarchical system as it consists multiple classes of decisionmakers and stakeholders ranging from national policymakers to operators of specific critical infrastructure subsystems. Critical infrastructures (e.g., transportation, telecommunications, power, banking, etc.) are highly complex and interconnected. These interconnections take the form of flows of information, shared security, and physical flows of commodities, among others. In recent years, economic and infrastructure sectors have become increasingly dependent on networked information systems for efficient operations and timely delivery of products and services. In order to ensure the stability, sustainability, and operability of our critical economic and infrastructure sectors, it is imperative to understand their inherent physical and economic linkages, in addition to their cyber interdependencies. An interdependency model based on a transformation of the Leontief input-output (I-O) model can be used for modeling: (1) the steady-state economic effects triggered by a consumption shift in a given sector (or set of sectors); and (2) the resulting ripple effects to other sectors. The inoperability metric is calculated for each sector; this is achieved by converting the economic impact (typically in monetary units) into a percentage value relative to the size of the sector. Disruptive events such as terrorist attacks, natural disasters, and large-scale accidents have historically shown cascading effects on both consumption and production. Hence, a dynamic model extension is necessary to demonstrate the interplay between combined demand and supply effects. The result is a foundational framework for modeling cybersecurity scenarios for the oil and gas sector. A hypothetical case study examines a cyber attack that causes a 5-week shortfall in the crude oil supply in the Gulf Coast area.

Implications of Preference and Problem Formulation on the Operating Policies of Complex Multi-Reservoir Systems

NASA Astrophysics Data System (ADS)

Quinn, J.; Reed, P. M.; Giuliani, M.; Castelletti, A.

2016-12-01

Optimizing the operations of multi-reservoir systems poses several challenges: 1) the high dimension of the problem's states and controls, 2) the need to balance conflicting multi-sector objectives, and 3) understanding how uncertainties impact system performance. These difficulties motivated the development of the Evolutionary Multi-Objective Direct Policy Search (EMODPS) framework, in which multi-reservoir operating policies are parameterized in a given family of functions and then optimized for multiple objectives through simulation over a set of stochastic inputs. However, properly framing these objectives remains a severe challenge and a neglected source of uncertainty. Here, we use EMODPS to optimize operating policies for a 4-reservoir system in the Red River Basin in Vietnam, exploring the consequences of optimizing to different sets of objectives related to 1) hydropower production, 2) meeting multi-sector water demands, and 3) providing flood protection to the capital city of Hanoi. We show how coordinated operation of the reservoirs can differ markedly depending on how decision makers weigh these concerns. Moreover, we illustrate how formulation choices that emphasize the mean, tail, or variability of performance across objective combinations must be evaluated carefully. Our results show that these choices can significantly improve attainable system performance, or yield severe unintended consequences. Finally, we show that satisfactory validation of the operating policies on a set of out-of-sample stochastic inputs depends as much or more on the formulation of the objectives as on effective optimization of the policies. These observations highlight the importance of carefully considering how we abstract stakeholders' objectives and of iteratively optimizing and visualizing multiple problem formulation hypotheses to ensure that we capture the most important tradeoffs that emerge from different stakeholder preferences.

An examination of a voluntary policy model to effect ...

EPA Pesticide Factsheets

An examination of a voluntary policy model to effect behavioral change and influence interactions and decision-making in the freight sector An examination of a voluntary policy model to effect behavioral change and influence interactions and decision-making in the freight sector

The management and design of economic development projects: A case study of World Bank electricity projects in Egypt

DOE Office of Scientific and Technical Information (OSTI.GOV)

El Sabaa, S.M.

1992-01-01

This study is concerned with the efficiency of World Bank projects in Egypt. The study seeks improvements in the methods of evaluating public sector projects in Egypt. To approaches are employed: (1) project identification to optimally allocate Egypt's and World Bank's resources; (2) project appraisal to assess the economic viability and efficiency of investments. The electricity sector is compared with the agriculture sector as a means of employing project identification for priority ordering of investment for development in Egypt. The key criteria for evaluation are the impacts of developments of each sector upon Egypt's national objectives and needs. These includemore » employment opportunities, growth, alleviation of poverty, cross comparison of per capita consumption in each sector, economic rate of return, national security, balance of payments and foreign debt. The allocation of scarce investments would have been more efficient in agriculture than in electricity in meeting Egypt's national objectives and needs. World Bank lending programs in Egypt reveal a priority ordering of electricity over agriculture and rural development. World Bank development projects in Egypt have not been optimally identified, and its programs have not followed an efficient allocation of World Bank's and Egypt's resources. The key parameters in evaluating economic viability and efficiency of development projects are: (1) the discount rate (the opportunity cost of public funds); (2) the exchange rate; and (3) the cost of major inputs, as approximated by shadow prices of labor, water, electricity, and transportation for development projects. Alternative approaches to estimating the opportunity cost of public funds are made. The parameters in evaluating the efficiency of projects have not been accurately estimated in the appraisal stage of the World Bank projects in Egypt, resulting in false or misleading information concerning the economic viability and efficiency of the projects.« less

Patterns of case management and chemoprevention for malaria-in-pregnancy by public and private sector health providers in Enugu state, Nigeria.

PubMed

Onwujekwe, Ogochukwu C; Soremekun, Rebecca O; Uzochukwu, Benjamin; Shu, Elvis; Onwujekwe, Obinna

2012-07-06

Malaria in pregnancy (MIP) is a major disease burden in Nigeria and has adverse consequences on the health of the mother, the foetus and the newborn. Information is required on how to improve its prevention and treatment from both the providers' and consumers' perspectives. The study sites were two public and two private hospitals in Enugu, southeast Nigeria. Data was collected using a pre-tested structured questionnaire. The respondents were healthcare providers (doctors, pharmacists and nurses) providing ante-natal care (ANC) services. They consisted of 32 respondents from the public facilities and 20 from the private facilities. The questionnaire elicited information on their: knowledge about malaria, attitude, chemotherapy and chemoprophylaxis using pyrimethamine, chloroquine proguanil as well as IPTp with sulphadoxine-pyrimethamine (SP). The data was collected from May to June 2010. Not many providers recognized maternal and neonatal deaths as potential consequences of MIP. The public sector providers provided more appropriate treatment for the pregnant women, but the private sector providers found IPTp more acceptable and provided it more rationally than public sector providers (p < 0.05). It was found that 50 % of private sector providers and 25 % of public sector providers prescribed chemoprophylaxis using pyrimethamine, chloroquine and proguanil to pregnant women. There is sub-optimal level of knowledge about current best practices for treatment and chemoprophylaxis for MIP especially in the private sector. Also, IPTp was hardly used in the public sector. Interventions are required to improve providers' knowledge and practices with regards to management of MIP.

Tuberculosis Notification by Private Sector' Physicians in Tehran.

PubMed

Ahmadi, Ayat; Nedjat, Saharnaz; Gholami, Jaleh; Majdzadeh, Reza

2015-01-01

A small proportion of physicians adhere to tuberculosis (TB) notification regulations, particularly in the private sector. In most developing countries, the private sector has dominance over delivering services in big cities. In such circumstances deviation from the TB treatment protocol is frequently happening. This study sought to estimate TB notification in the private sector and settle on determinants of TB notification by private sector physicians. A population-based study has been conducted; private physicians at their clinics were interviewed. The total number of 443 private sectors' physicians has been chosen by the stratified random sampling method. Appropriate descriptive analysis was used to describe the study's participants. Logistic regression was used for bivariable and multivariable analysis. The response rate of the study was 90.06 (399%). Among responders, who had stated that they were suspicious of TB over the recent year, 62 (16.45%) stated that they reported cases of TB at least once during the same period. Having reporting requirements and the number of visited patients was significantly related to TB suspicious (odds ratio = 2.84, confidence interval: 1.62-5, P < 0.01). Workplace and access to relevant resources are associated with TB notification (P < 0.05). In poor resource settings with a high burden of TB, the public health administration can promote notification activities in the private sector by simple and quick interventions. It seems that a considerable fraction of private sector physicians, not all of them, will notify TB if they are provided with primary information and primary resources. To optimize the TB notification, however, intersectoral interventions are more likely to be successful.

Development and Performance of Alternative Electricity Sector Pathways Subject to Multiple Climate and Water Projections

NASA Astrophysics Data System (ADS)

Newmark, R. L.; Vorosmarty, C. J.; Miara, A.; Cohen, S.; Macknick, J.; Sun, Y.; Corsi, F.; Fekete, B. M.; Tidwell, V. C.

2017-12-01

Climate change impacts on air temperatures and water availability have the potential to alter future electricity sector investment decisions as well as the reliability and performance of the power sector. Different electricity sector configurations are more or less vulnerable to climate-induced changes. For example, once-through cooled thermal facilities are the most cost-effective and efficient technologies under cooler and wetter conditions, but can be substantially affected by and vulnerable to warmer and drier conditions. Non-thermal renewable technologies, such as PV and wind, are essentially "drought-proof" but have other integration and reliability challenges. Prior efforts have explored the impacts of climate change on electric sector development for a limited set of climate and electricity scenarios. Here, we provide a comprehensive suite of scenarios that evaluate how different electricity sector pathways could be affected by a range of climate and water resource conditions. We use four representative concentration pathway (RCP) scenarios under five global circulation models (GCM) as climate drivers to a Water Balance Model (WBM), to provide twenty separate future climate-water conditions. These climate-water conditions influence electricity sector development from present day to 2050 as determined using the Regional Energy Deployment Systems (ReEDS) model. Four unique electricity sector pathways will be considered, including business-as-usual, carbon cap, high renewable energy technology costs, and coal reliance scenarios. The combination of climate-water and electricity sector pathway scenarios leads to 80 potential future cases resulting in different national and regional electricity infrastructure configurations. The vulnerability of these configurations in relation to climate change (including in-stream thermal pollution impacts and environmental regulations) is evaluated using the Thermoelectric Power and Thermal Pollution (TP2M) model, providing quantitative estimates of the power sector's ability to meet loads, given changes in air temperature, water temperature, and water availability.

Development of energy consumption and energy efficiency potential in the Brazilian industrial sector according to the Integrated Energy Planning Model (IEPM)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tolmasquim, M.T.; Szklo, A.S.; Cohen, C.

This paper presents the development of energy consumption in the Brazilian industrial sector and energy efficiency potential based on the analysis undertaken through a model developed in the Energy Planning Program at COPPE/UFRJ, known as the Integrated Energy Planning Model (IEPM). The study starts by presenting the IEPM, which is a technical and economic parameter-based model designed to forecast energy supplies and consumption for all economic sectors in Brazil, within three scenarios. Outlines of all three scenarios are presented, as they were constructed according to certain specific assumptions. The industrial sector was broken down into eleven sub-sectors: food and beverages,more » ceramics, cement, iron and steel, mining and pelletizing, ferroalloys, non-ferrous metals and others (metallurgy), chemicals, pulp and paper, textiles and other industries (MME, 1998). All these sub-sectors will also be presented as well as the results of the scenario forecasts. Results deriving from these forecasts come from very specific studies that analyze all process steps in each sub-sector in order to propose energy replacements, efficiency improvements of structural production alterations that result in major potential energy consumption reductions. Last but not least, this paper gives the development forecasts deriving from the three scenarios over ten years, with their contributions to energy efficiency in the Brazilian industrial sector, showing that the authors can reduce energy consumption in the Brazilian industrial sector by: substituting less efficient processes by more efficient ones, through the conversion of final energy into usable energy, basically, in the cement and aluminum industries; replacing equipment and energy sources; modifying product mix of several industries (pulp and paper), assigning top priority to producing goods with higher added value that are less energy intensive, and, finally, reducing the share held by some energy intensive sectors in the industrial output.« less

Dave Bielen | NREL

Science.gov Websites

Dave Bielen Photo of Dave Bielen Dave Bielen Energy and Environmental Policy Analyst David.Bielen Energy Analysis Center. Areas of Expertise Environmental policy design Dynamic programming Time series energy policy GHG emissions mitigation in the electricity and transportation sectors Optimal control of

Assimilation of satellite altimeter data into an open ocean model

NASA Astrophysics Data System (ADS)

Vogeler, Armin; SchröTer, Jens

1995-08-01

Geosat sea surface height data are assimilated into an eddy-resolving quasi-geostrophic open ocean model using the adjoint technique. The method adjusts the initial conditions for all layers and is successful on the timescale of a few weeks. Time-varying values for the open boundaries are prescribed by a much larger quasi-geostrophic model of the Antarctic Circumpolar Current (ACC). Both models have the same resolution of approximately 20×20 km (1/3°×1/6°), have three layers, and include realistic bottom topography and coastlines. The open model box is embedded in the African sector of the ACC. For continuous assimilation of satellite data into the larger model the nudging technique is applied. These results are used for the adjoint optimization procedure as boundary conditions and as a first guess for the initial condition. For the open model box the difference between model and satellite sea surface height that remains after the nudging experiment amounts to a 19-cm root-mean-square error (rmse). By assimilation into the regional model this value can be reduced to a 6-cm rmse for an assimilation period of 20 days. Several experiments which attempt to improve the convergence of the iterative optimization method are reported. Scaling and regularization by smoothing have to be applied carefully. Especially during the first 10 iterations, the convergence can be improved considerably by low-pass filtering of the cost function gradient. The result of a perturbation experiment shows that for longer assimilation periods the influence of the boundary values becomes dominant and they should be determined inversely by data assimilation into the open ocean model.

Development of water allocation Model Based on ET-Control and Its Application in Haihe River Basin

NASA Astrophysics Data System (ADS)

You, Jinjun; Gan, Hong; Gan, Zhiguo; Wang, Lin

2010-05-01

Traditionally, water allocation is to distribute water to different regions and sectors, without enough consideration on amount of water consumed after water distribution. Water allocation based on ET (evaporation and Transpiration) control changes this idea and emphasizes the absolute amount of evaporation and transpiration in specific area. With this ideology, the amount of ET involved the water allocation includes not only water consumed from the sectors, but the natural ET. Therefore, the water allocation consist of two steps, the first step is to estimate reasonable ET quantum in regions, then allocate water to more detailed regions and various sectors with the ET quantum according with the operational rules. To make qualified ET distribution and water allocation in various regions, a framework is put forward in this paper, in which two models are applied to analyze the different scenarios with predefined economic growth and ecological objective. The first model figures out rational ET objective with multi-objective analysis for compromised solution in economic growth and ecological maintenance. Food security and environmental protection are also taken as constraints in the optimization in the first model. The second one provides hydraulic simulation and water balance to allocate the ET objective to corresponding regions under operational rules. These two models are combined into an integrated ET-Control water allocation. Scenario analysis through the ET-Control Model could discover the relations between economy and ecology, farther to give suggestion on measures to control water use with condition of changing socio-economic growth and ecological objectives. To confirm the methodology, Haihe River is taken as a case to study. Rational water allocation is important branch of decision making on water planning and management in Haihe River Basin since water scarcity and deteriorating environment fights for water in this basin dramatically and reasonable water allocation between economy and ecology is a focus. Considering condition of water scarcity in Haihe River Basin, ET quota is taken as objective for water allocation in provinces to realize the requirement of water inflow into the Bohai Sea. Scenario analysis provides the results of water evaporation from natural water cycle and artificial use. A trade-off curve based on fulfilment of ecological and economic objectives in different scenarios discovers the competitive relation between human activities and nature.

Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation

NASA Astrophysics Data System (ADS)

Cheng, C. L.

2015-12-01

Investigation on Reservoir Operation of Agricultural Water Resources Management for Drought Mitigation Chung-Lien Cheng, Wen-Ping Tsai, Fi-John Chang* Department of Bioenvironmental Systems Engineering, National Taiwan University, Da-An District, Taipei 10617, Taiwan, ROC.Corresponding author: Fi-John Chang (changfj@ntu.edu.tw) AbstractIn Taiwan, the population growth and economic development has led to considerable and increasing demands for natural water resources in the last decades. Under such condition, water shortage problems have frequently occurred in northern Taiwan in recent years such that water is usually transferred from irrigation sectors to public sectors during drought periods. Facing the uneven spatial and temporal distribution of water resources and the problems of increasing water shortages, it is a primary and critical issue to simultaneously satisfy multiple water uses through adequate reservoir operations for sustainable water resources management. Therefore, we intend to build an intelligent reservoir operation system for the assessment of agricultural water resources management strategy in response to food security during drought periods. This study first uses the grey system to forecast the agricultural water demand during February and April for assessing future agricultural water demands. In the second part, we build an intelligent water resources system by using the non-dominated sorting genetic algorithm-II (NSGA-II), an optimization tool, for searching the water allocation series based on different water demand scenarios created from the first part to optimize the water supply operation for different water sectors. The results can be a reference guide for adequate agricultural water resources management during drought periods. Keywords: Non-dominated sorting genetic algorithm-II (NSGA-II); Grey System; Optimization; Agricultural Water Resources Management.

Cardiac imaging with multi-sector data acquisition in volumetric CT: variation of effective temporal resolution and its potential clinical consequences

NASA Astrophysics Data System (ADS)

Tang, Xiangyang; Hsieh, Jiang; Taha, Basel H.; Vass, Melissa L.; Seamans, John L.; Okerlund, Darin R.

2009-02-01

With increasing longitudinal detector dimension available in diagnostic volumetric CT, step-and-shoot scan is becoming popular for cardiac imaging. In comparison to helical scan, step-and-shoot scan decouples patient table movement from cardiac gating/triggering, which facilitates the cardiac imaging via multi-sector data acquisition, as well as the administration of inter-cycle heart beat variation (arrhythmia) and radiation dose efficiency. Ideally, a multi-sector data acquisition can improve temporal resolution at a factor the same as the number of sectors (best scenario). In reality, however, the effective temporal resolution is jointly determined by gantry rotation speed and patient heart beat rate, which may significantly lower than the ideal or no improvement (worst scenario). Hence, it is clinically relevant to investigate the behavior of effective temporal resolution in cardiac imaging with multi-sector data acquisition. In this study, a 5-second cine scan of a porcine heart, which cascades 6 porcine cardiac cycles, is acquired. In addition to theoretical analysis and motion phantom study, the clinical consequences due to the effective temporal resolution variation are evaluated qualitative or quantitatively. By employing a 2-sector image reconstruction strategy, a total of 15 (the permutation of P(6, 2)) cases between the best and worst scenarios are studied, providing informative guidance for the design and optimization of CT cardiac imaging in volumetric CT with multi-sector data acquisition.

Optimal Electric Vehicle Scheduling: A Co-Optimized System and Customer Perspective

NASA Astrophysics Data System (ADS)

Maigha

Electric vehicles provide a two pronged solution to the problems faced by the electricity and transportation sectors. They provide a green, highly efficient alternative to the internal combustion engine vehicles, thus reducing our dependence on fossil fuels. Secondly, they bear the potential of supporting the grid as energy storage devices while incentivising the customers through their participation in energy markets. Despite these advantages, widespread adoption of electric vehicles faces socio-technical and economic bottleneck. This dissertation seeks to provide solutions that balance system and customer objectives under present technological capabilities. The research uses electric vehicles as controllable loads and resources. The idea is to provide the customers with required tools to make an informed decision while considering the system conditions. First, a genetic algorithm based optimal charging strategy to reduce the impact of aggregated electric vehicle load has been presented. A Monte Carlo based solution strategy studies change in the solution under different objective functions. This day-ahead scheduling is then extended to real-time coordination using a moving-horizon approach. Further, battery degradation costs have been explored with vehicle-to-grid implementations, thus accounting for customer net-revenue and vehicle utility for grid support. A Pareto front, thus obtained, provides the nexus between customer and system desired operating points. Finally, we propose a transactive business model for a smart airport parking facility. This model identifies various revenue streams and satisfaction indices that benefit the parking lot owner and the customer, thus adding value to the electric vehicle.

Public sector energy management: A strategy for catalyzing energy efficiency in Malaysia

NASA Astrophysics Data System (ADS)

Roy, Anish Kumar

To date the public sector role in facilitating the transition to a sustainable energy future has been envisaged mainly from a regulatory perspective. In such a role, the public sector provides the push factors---enforcing regulations and providing incentives---to correct market imperfections that impede energy transitions. An alternative and complementary role of the public sector that is now gaining increasing attention is that of catalyzing energy transitions through public sector energy management initiatives. This dissertation offers a conceptual framework to rationalize such a role for the public sector by combining recent theories of sustainable energy transition and public management. In particular, the framework identifies innovative public management strategies (such as performance contracting and procurement) for effectively implementing sustainable energy projects in government facilities. The dissertation evaluates a model of sustainable public sector energy management for promoting energy efficiency in Malaysia. The public sector in Malaysia can be a major player in leading and catalyzing energy efficiency efforts as it is not only the largest and one of the most influential energy consumers, but it also plays a central role in setting national development strategy. The dissertation makes several recommendations on how a public sector energy management strategy can be implemented in Malaysia. The US Federal Energy Management Program (FEMP) is used as a practical model. The analysis, however, shows that in applying the FEMP model to the Malaysian context, there are a number of limitations that will have to be taken into consideration to enable a public sector energy management strategy to be effectively implemented. Overall the analysis of this dissertation contributes to a rethinking of the public sector role in sustainable energy development that can strengthen the sector's credibility both in terms of governance and institutional performance. In addition, it links theory with practice by offering a strategy that can effectively address critical issues arising from the energy-development-policy nexus of the sustainable energy development debate.

Evaluating digital libraries in the health sector. Part 1: measuring inputs and outputs.

PubMed

Cullen, Rowena

2003-12-01

This is the first part of a two-part paper which explores methods that can be used to evaluate digital libraries in the health sector. In this first part, some approaches to evaluation that have been proposed for mainstream digital information services are examined for their suitability to provide models for the health sector. The paper summarizes some major national and collaborative initiatives to develop measures for digital libraries, and analyses these approaches in terms of their relationship to traditional measures of library performance, which are focused on inputs and outputs, and their relevance to current debates among health information specialists. The second part* looks more specifically at evaluative models based on outcomes, and models being developed in the health sector.

A national econometric forecasting model of the dental sector.

PubMed Central

Feldstein, P J; Roehrig, C S

1980-01-01

The Econometric Model of the the Dental Sector forecasts a broad range of dental sector variables, including dental care prices; the amount of care produced and consumed; employment of hygienists, dental assistants, and clericals; hours worked by dentists; dental incomes; and number of dentists. These forecasts are based upon values specified by the user for the various factors which help determine the supply an demand for dental care, such as the size of the population, per capita income, the proportion of the population covered by private dental insurance, the cost of hiring clericals and dental assistants, and relevant government policies. In a test of its reliability, the model forecast dental sector behavior quite accurately for the period 1971 through 1977. PMID:7461974

Econometrics and data of the 9 sector Dynamic General Equilibrium Model. Volume III. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berndt, E.R.; Fraumeni, B.M.; Hudson, E.A.

1981-03-01

This report presents the econometrics and data of the 9 sector Dynamic General Equilibrium Model. There are two key components of 9DGEM - the model of household behavior and the model of produconcrneer behavior. The household model is concerned with decisions on consumption, saving, labor supply and the composition of consumption. The producer model is concerned with output price formation and determination of input patterns and purchases for each of the nine producing sectors. These components form the behavioral basis of DGEM. The remaining components are concerned with constraints, balance conditions, accounting, and government revenues and expenditures (these elements aremore » developed in the report on the model specification).« less

Forecasting urban water demand: A meta-regression analysis.

PubMed

Sebri, Maamar

2016-12-01

Water managers and planners require accurate water demand forecasts over the short-, medium- and long-term for many purposes. These range from assessing water supply needs over spatial and temporal patterns to optimizing future investments and planning future allocations across competing sectors. This study surveys the empirical literature on the urban water demand forecasting using the meta-analytical approach. Specifically, using more than 600 estimates, a meta-regression analysis is conducted to identify explanations of cross-studies variation in accuracy of urban water demand forecasting. Our study finds that accuracy depends significantly on study characteristics, including demand periodicity, modeling method, forecasting horizon, model specification and sample size. The meta-regression results remain robust to different estimators employed as well as to a series of sensitivity checks performed. The importance of these findings lies in the conclusions and implications drawn out for regulators and policymakers and for academics alike. Copyright © 2016. Published by Elsevier Ltd.

Economic impacts of a transition to higher oil prices

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tessmer, Jr, R. G.; Carhart, S. C.; Marcuse, W.

1978-06-01

Economic impacts of sharply higher oil and gas prices in the eighties are estimated using a combination of optimization and input-output models. A 1985 Base Case is compared with a High Case in which crude oil and crude natural gas are, respectively, 2.1 and 1.4 times as expensive as in the Base Case. Impacts examined include delivered energy prices and demands, resource consumption, emission levels and costs, aggregate and compositional changes in gross national product, balance of payments, output, employment, and sectoral prices. Methodology is developed for linking models in both quantity and price space for energy service--specific fuel demands.more » A set of energy demand elasticities is derived which is consistent between alternative 1985 cases and between the 1985 cases and an historical year (1967). A framework and methodology are also presented for allocating portions of the DOE Conservation budget according to broad policy objectives and allocation rules.« less

Optimizing your options: Extracting the full economic value of transmission when planning under uncertainty

DOE PAGES

Munoz, Francisco D.; Watson, Jean -Paul; Hobbs, Benjamin F.

2015-06-04

In this study, the anticipated magnitude of needed investments in new transmission infrastructure in the U.S. requires that these be allocated in a way that maximizes the likelihood of achieving society's goals for power system operation. The use of state-of-the-art optimization tools can identify cost-effective investment alternatives, extract more benefits out of transmission expansion portfolios, and account for the huge economic, technology, and policy uncertainties that the power sector faces over the next several decades.

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System

DOE Office of Scientific and Technical Information (OSTI.GOV)

NONE

1998-01-01

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas,more » and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.« less

An overview of methods to identify and manage uncertainty for modelling problems in the water-environment-agriculture cross-sector

DOE PAGES

Jakeman, Anthony J.; Jakeman, John Davis

2018-03-14

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclecticmore » treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.« less

An overview of methods to identify and manage uncertainty for modelling problems in the water-environment-agriculture cross-sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jakeman, Anthony J.; Jakeman, John Davis

Uncertainty pervades the representation of systems in the water–environment–agriculture cross-sector. Successful methods to address uncertainties have largely focused on standard mathematical formulations of biophysical processes in a single sector, such as partial or ordinary differential equations. More attention to integrated models of such systems is warranted. Model components representing the different sectors of an integrated model can have less standard, and different, formulations to one another, as well as different levels of epistemic knowledge and data informativeness. Thus, uncertainty is not only pervasive but also crosses boundaries and propagates between system components. Uncertainty assessment (UA) cries out for more eclecticmore » treatment in these circumstances, some of it being more qualitative and empirical. Here in this paper, we discuss the various sources of uncertainty in such a cross-sectoral setting and ways to assess and manage them. We have outlined a fast-growing set of methodologies, particularly in the computational mathematics literature on uncertainty quantification (UQ), that seem highly pertinent for uncertainty assessment. There appears to be considerable scope for advancing UA by integrating relevant UQ techniques into cross-sectoral problem applications. Of course this will entail considerable collaboration between domain specialists who often take first ownership of the problem and computational methods experts.« less

Multifractal detrended cross-correlations between crude oil market and Chinese ten sector stock markets

NASA Astrophysics Data System (ADS)

Yang, Liansheng; Zhu, Yingming; Wang, Yudong; Wang, Yiqi

2016-11-01

Based on the daily price data of spot prices of West Texas Intermediate (WTI) crude oil and ten CSI300 sector indices in China, we apply multifractal detrended cross-correlation analysis (MF-DCCA) method to investigate the cross-correlations between crude oil and Chinese sector stock markets. We find that the strength of multifractality between WTI crude oil and energy sector stock market is the highest, followed by the strength of multifractality between WTI crude oil and financial sector market, which reflects a close connection between energy and financial market. Then we do vector autoregression (VAR) analysis to capture the interdependencies among the multiple time series. By comparing the strength of multifractality for original data and residual errors of VAR model, we get a conclusion that vector auto-regression (VAR) model could not be used to describe the dynamics of the cross-correlations between WTI crude oil and the ten sector stock markets.

Optimal Defaults in the Prevention of Pediatric Obesity: From Platform to Practice

PubMed Central

Radnitz, Cynthia; Loeb, Katharine L; DiMatteo, Julie; Keller, Kathleen L.; Zucker, Nancy; Schwartz, Marlene B.

2014-01-01

The term “optimal defaults” refers to imparting pre-selected choices which are designed to produce a desired behavior change. The concept is attractive to policymakers because it steers people toward desirable behaviors while preserving free choice through the ability to opt out. It has been found to be a powerful behavioral determinant in areas such as pension plan enrollment, organ donation, and green energy utilization. We discuss how optimal defaults can be applied to pediatric obesity prevention in several domains including public policy, institutional, private sector, and home environment. Although there are obstacles to overcome in implementing optimal defaults, it is a promising component to incorporate in a multi-level strategy for preventing pediatric obesity. PMID:25328903

Robust Control of Uncertain Systems via Dissipative LQG-Type Controllers

NASA Technical Reports Server (NTRS)

Joshi, Suresh M.

2000-01-01

Optimal controller design is addressed for a class of linear, time-invariant systems which are dissipative with respect to a quadratic power function. The system matrices are assumed to be affine functions of uncertain parameters confined to a convex polytopic region in the parameter space. For such systems, a method is developed for designing a controller which is dissipative with respect to a given power function, and is simultaneously optimal in the linear-quadratic-Gaussian (LQG) sense. The resulting controller provides robust stability as well as optimal performance. Three important special cases, namely, passive, norm-bounded, and sector-bounded controllers, which are also LQG-optimal, are presented. The results give new methods for robust controller design in the presence of parametric uncertainties.

Decision support system for health care resources allocation

PubMed Central

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-01-01

Background A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. Aim The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. Methods To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. Results A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. Conclusion In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff. PMID:28848645

Primary Health Care and Public Health: Foundations of Universal Health Systems

PubMed Central

White, Franklin

2015-01-01

The aim of this review is to advocate for more integrated and universally accessible health systems, built on a foundation of primary health care and public health. The perspective outlined identified health systems as the frame of reference, clarified terminology and examined complementary perspectives on health. It explored the prospects for universal and integrated health systems from a global perspective, the role of healthy public policy in achieving population health and the value of the social-ecological model in guiding how best to align the components of an integrated health service. The importance of an ethical private sector in partnership with the public sector is recognized. Most health systems around the world, still heavily focused on illness, are doing relatively little to optimize health and minimize illness burdens, especially for vulnerable groups. This failure to improve the underlying conditions for health is compounded by insufficient allocation of resources to address priority needs with equity (universality, accessibility and affordability). Finally, public health and primary health care are the cornerstones of sustainable health systems, and this should be reflected in the health policies and professional education systems of all nations wishing to achieve a health system that is effective, equitable, efficient and affordable. PMID:25591411

Decision support system for health care resources allocation.

PubMed

Sebaa, Abderrazak; Nouicer, Amina; Tari, AbdelKamel; Tarik, Ramtani; Abdellah, Ouhab

2017-06-01

A study about healthcare resources can improve decisions regarding the allotment and mobilization of medical resources and to better guide future investment in the health sector. The aim of this work was to design and implement a decision support system to improve medical resources allocation of Bejaia region. To achieve the retrospective cohort study, we integrated existing clinical databases from different Bejaia department health sector institutions (an Algerian department) to collect information about patients from January 2015 through December 2015. Data integration was performed in a data warehouse using the multi-dimensional model and OLAP cube. During implementation, we used Microsoft SQL server 2012 and Microsoft Excel 2010. A medical decision support platform was introduced, and was implemented during the planning stages allowing the management of different medical orientations, it provides better apportionment and allotment of medical resources, and ensures that the allocation of health care resources has optimal effects on improving health. In this study, we designed and implemented a decision support system which would improve health care in Bejaia department to especially assist in the selection of the optimum location of health center and hospital, the specialty of the health center, the medical equipment and the medical staff.

Modeling of policies for reduction of GHG emissions in energy sector using ANN: case study-Croatia (EU).

PubMed

Bolanča, Tomislav; Strahovnik, Tomislav; Ukić, Šime; Stankov, Mirjana Novak; Rogošić, Marko

2017-07-01

This study describes the development of tool for testing different policies for reduction of greenhouse gas (GHG) emissions in energy sector using artificial neural networks (ANNs). The case study of Croatia was elaborated. Two different energy consumption scenarios were used as a base for calculations and predictions of GHG emissions: the business as usual (BAU) scenario and sustainable scenario. Both of them are based on predicted energy consumption using different growth rates; the growth rates within the second scenario resulted from the implementation of corresponding energy efficiency measures in final energy consumption and increasing share of renewable energy sources. Both ANN architecture and training methodology were optimized to produce network that was able to successfully describe the existing data and to achieve reliable prediction of emissions in a forward time sense. The BAU scenario was found to produce continuously increasing emissions of all GHGs. The sustainable scenario was found to decrease the GHG emission levels of all gases with respect to BAU. The observed decrease was attributed to the group of measures termed the reduction of final energy consumption through energy efficiency measures.

A Fast Evaluation Method for Energy Building Consumption Based on the Design of Experiments

NASA Astrophysics Data System (ADS)

Belahya, Hocine; Boubekri, Abdelghani; Kriker, Abdelouahed

2017-08-01

Building sector is one of the effective consumer energy by 42% in Algeria. The need for energy has continued to grow, in inordinate way, due to lack of legislation on energy performance in this large consumer sector. Another reason is the simultaneous change of users’ requirements to maintain their comfort, especially summer in dry lands and parts of southern Algeria, where the town of Ouargla presents a typical example which leads to a large amount of electricity consumption through the use of air conditioning. In order to achieve a high performance envelope of the building, an optimization of major parameters building envelope is required, using design of experiments (DOE), can determine the most effective parameters and eliminate the less importance. The study building is often complex and time consuming due to the large number of parameters to consider. This study focuses on reducing the computing time and determines the major parameters of building energy consumption, such as area of building, factor shape, orientation, ration walls to windows …etc to make some proposal models in order to minimize the seasonal energy consumption due to air conditioning needs.

Can modeling of HIV treatment processes improve outcomes? Capitalizing on an operations research approach to the global pandemic

PubMed Central

Xiong, Wei; Hupert, Nathaniel; Hollingsworth, Eric B; O'Brien, Megan E; Fast, Jessica; Rodriguez, William R

2008-01-01

Background Mathematical modeling has been applied to a range of policy-level decisions on resource allocation for HIV care and treatment. We describe the application of classic operations research (OR) techniques to address logistical and resource management challenges in HIV treatment scale-up activities in resource-limited countries. Methods We review and categorize several of the major logistical and operational problems encountered over the last decade in the global scale-up of HIV care and antiretroviral treatment for people with AIDS. While there are unique features of HIV care and treatment that pose significant challenges to effective modeling and service improvement, we identify several analogous OR-based solutions that have been developed in the service, industrial, and health sectors. Results HIV treatment scale-up includes many processes that are amenable to mathematical and simulation modeling, including forecasting future demand for services; locating and sizing facilities for maximal efficiency; and determining optimal staffing levels at clinical centers. Optimization of clinical and logistical processes through modeling may improve outcomes, but successful OR-based interventions will require contextualization of response strategies, including appreciation of both existing health care systems and limitations in local health workforces. Conclusion The modeling techniques developed in the engineering field of operations research have wide potential application to the variety of logistical problems encountered in HIV treatment scale-up in resource-limited settings. Increasing the number of cross-disciplinary collaborations between engineering and public health will help speed the appropriate development and application of these tools. PMID:18680594

Analyzing the Long Term Cohesive Effect of Sector Specific Driving Forces

PubMed Central

Berman, Yonatan; Zhang, Xin; Shapira, Yoash

2016-01-01

Financial markets are partially composed of sectors dominated by external driving forces, such as commodity prices, infrastructure and other indices. We characterize the statistical properties of such sectors and present a novel model for the coupling of the stock prices and their dominating driving forces, inspired by mean reverting stochastic processes. Using the model we were able to explain the market sectors’ long term behavior and estimate the coupling strength between stocks in financial markets and the sector specific driving forces. Notably, the analysis was successfully applied to the shipping market, in which the Baltic dry index (BDI), an assessment of the price of transporting the major raw materials by sea, influences the shipping financial market. We also present the analysis of other sectors—the gold mining market and the food production market, for which the model was also successfully applied. The model can serve as a general tool for characterizing the coupling between external forces and affected financial variables and therefore for estimating the risk in sectors and their vulnerability to external stress. PMID:27031230

Strategic responses to CO2 emission reduction targets drive shift in U.S. electric sector water use

EPA Science Inventory

The reliance of the U.S. electric sector on water makes this sector vulnerable to climate change and variability. We use the EPAUS9r MARKAL model to investigate changes in U.S. electric sector water withdrawal and consumption through 2055 under alternative energy system-wide CO2...

Optimal Decision Model for Sustainable Hospital Building Renovation—A Case Study of a Vacant School Building Converting into a Community Public Hospital

PubMed Central

Juan, Yi-Kai; Cheng, Yu-Ching; Perng, Yeng-Horng; Castro-Lacouture, Daniel

2016-01-01

Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient. PMID:27347986

Optimal Decision Model for Sustainable Hospital Building Renovation-A Case Study of a Vacant School Building Converting into a Community Public Hospital.

PubMed

Juan, Yi-Kai; Cheng, Yu-Ching; Perng, Yeng-Horng; Castro-Lacouture, Daniel

2016-06-24

Much attention has been paid to hospitals environments since modern pandemics have emerged. The building sector is considered to be the largest world energy consumer, so many global organizations are attempting to create a sustainable environment in building construction by reducing energy consumption. Therefore, maintaining high standards of hygiene while reducing energy consumption has become a major task for hospitals. This study develops a decision model based on genetic algorithms and A* graph search algorithms to evaluate existing hospital environmental conditions and to recommend an optimal scheme of sustainable renovation strategies, considering trade-offs among minimal renovation cost, maximum quality improvement, and low environmental impact. Reusing vacant buildings is a global and sustainable trend. In Taiwan, for example, more and more school space will be unoccupied due to a rapidly declining birth rate. Integrating medical care with local community elder-care efforts becomes important because of the aging population. This research introduces a model that converts a simulated vacant school building into a community public hospital renovation project in order to validate the solutions made by hospital managers and suggested by the system. The result reveals that the system performs well and its solutions are more successful than the actions undertaken by decision-makers. This system can improve traditional hospital building condition assessment while making it more effective and efficient.

Numerical investigation for formability of aluminum 6016 alloy under non-isothermal warm forming process

NASA Astrophysics Data System (ADS)

Hu, P.; Dai, M. H.; Ying, L.; Shi, D. Y.; Zhao, K. M.; Lu, J. D.

2013-05-01

The warm forming technology of aluminum alloy has attracted attention from worldwide automotive engineering sector in recent years, with which the complex geometry parts can be realized at elevated temperature. A non-isothermal warm forming process for the heat treatable aluminum can quickly carry out its application on traditional production line by adding a furnace to heat up the aluminum alloy sheet. The 6000 aluminum alloy was investigated by numerical simulation and experiment using the Nakajima test model in this paper. A modified Fields-Backofen model was introduced into numerical simulation process to describe the thermo-mechanical flow behavior of a 6000 series aluminum alloy. The experimental data was obtained by conducting thermal-mechanical uniaxial tensile experiment in temperatures range of 25˜400°C to guarantee the numerical simulation more accurate. The numerical simulation was implemented with LS_DYNA software in terms of coupled dynamic explicit method for investigating the effect of initial forming temperature and the Binder Holder Force (BHF), which are critical process parameters in non-isothermal warm forming. The results showed that the optimal initial forming temperature range was 300°C˜350°C. By means of conducting numerical simulation in deep drawing box model, the forming window of BHF and temperature around the optimal initial forming temperature (275°, 300° and 325°) are investigated, which can provide guidance to actual experiment.

Decision-theoretic approach to data acquisition for transit operations planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ritchie, S.G.

The most costly element of transportation planning and modeling activities in the past has usually been that of data acquisition. This is even truer today when the unit costs of data collection are increasing rapidly and at the same time budgets are severely limited by continuing policies of fiscal austerity in the public sector. The overall objectives of this research were to improve the decisions and decision-making capabilities of transit operators or planners in short-range transit planning, and to improve the quality and cost-effectiveness of associated route or corridor-level data collection and service monitoring activities. A new approach was presentedmore » for sequentially updating the parameters of both simple and multiple linear regression models with stochastic regressors, and for determining the expected value of sample information and expected net gain of sampling for associated sample designs. A new approach was also presented for estimating and updating (both spatially and temporally) the parameters of multinomial logit discrete choice models, and for determining associated optimal sample designs for attribute-based and choice-based sampling methods. The approach provides an effective framework for addressing the issue of optimal sampling method and sample size, which to date have been largely unresolved. The application of these methodologies and the feasibility of the decision-theoretic approach was illustrated with a hypothetical case study example.« less

Government Investment and Follow-on Private Sector Investment in Pakistan, 1972-1995

DTIC Science & Technology

1997-06-01

private sector investment has long been suggested. Until recently, an appropriate model to test for the relationship in developing countries has been absent. In 1984, Blejer and Khan developed and estimated a model for 24 developing countries between 1971 and 1979. They found that higher rates of investment took place when the private sector took a large role in capital formation. This paper estimates a similar model for one developing country, Pakistan, for the period 1972 to 1995. Our results are broadly similar to those obtained by Blejer and Khan

Analysis of Costs and Time Frame for Reducing CO2 Emissions by 70% in the U.S. Auto and Energy Sectors by 2050.

PubMed

Supekar, Sarang D; Skerlos, Steven J

2017-10-03

Using a least-cost optimization framework, it is shown that unless emissions reductions beyond those already in place begin at the latest by 2025 (±2 years) for the U.S. automotive sector, and by 2026 (-3 years) for the U.S. electric sector, 2050 targets to achieve necessary within-sector preventative CO 2 emissions reductions of 70% or more relative to 2010 will be infeasible. The analysis finds no evidence to justify delaying climate action in the name of reducing technological costs. Even without considering social and environmental damage costs, delaying aggressive climate action does not reduce CO 2 abatement costs even under the most optimistic trajectories for improvements in fuel efficiencies, demand, and technology costs in the U.S. auto and electric sectors. In fact, the abatement cost for both sectors is found to increase sharply with every year of delay beyond 2020. When further considering reasonable limits to technology turnover, retirements, and new capacity additions, these costs would be higher, and the feasible time frame for initiating successful climate action on the 70% by 2050 target would be shorter, perhaps having passed already. The analysis also reveals that optimistic business-as-usual scenarios in the U.S. will, conservatively, release 79-108 billion metric tons of CO 2 . This could represent up to 13% of humanity's remaining carbon budget through 2050.

Impacts of Energy Sector Emissions on PM2.5 Air Quality in Northern India

NASA Astrophysics Data System (ADS)

Karambelas, A. N.; Kiesewetter, G.; Heyes, C.; Holloway, T.

2015-12-01

India experiences high concentrations of fine particulate matter (PM2.5), and several Indian cities currently rank among the world's most polluted cities. With ongoing urbanization and a growing economy, emissions from different energy sectors remain major contributors to air pollution in India. Emission sectors impact ambient air quality differently due to spatial distribution (typical urban vs. typical rural sources) as well as source height characteristics (low-level vs. high stack sources). This study aims to assess the impacts of emissions from three distinct energy sectors—transportation, domestic, and electricity—on ambient PM2.5­­ in northern India using an advanced air quality analysis framework based on the U.S. EPA Community Multi-Scale Air Quality (CMAQ) model. Present air quality conditions are simulated using 2010 emissions from the Greenhouse Gas-Air Pollution Interaction and Synergies (GAINS) model. Modeled PM2.5 concentrations are compared with satellite observations of aerosol optical depth (AOD) from the Moderate Imaging Spectroradiometer (MODIS) for 2010. Energy sector emissions impacts on future (2030) PM2.5 are evaluated with three sensitivity simulations, assuming maximum feasible reduction technologies for either transportation, domestic, or electricity sectors. These simulations are compared with a business as usual 2030 simulation to assess relative sectoral impacts spatially and temporally. CMAQ is modeled at 12km by 12km and include biogenic emissions from the Community Land Model coupled with the Model of Emissions of Gases and Aerosols in Nature (CLM-MEGAN), biomass burning emissions from the Global Fires Emissions Database (GFED), and ERA-Interim meteorology generated with the Weather Research and Forecasting (WRF) model for 2010 to quantify the impact of modified anthropogenic emissions on ambient PM2.5 concentrations. Energy sector emissions analysis supports decision-making to improve future air quality and public health in India.

Seeking Energy System Pathways to Reduce Ozone Damage to Ecosystems through Adjoint-based Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Capps, S. L.; Pinder, R. W.; Loughlin, D. H.; Bash, J. O.; Turner, M. D.; Henze, D. K.; Percell, P.; Zhao, S.; Russell, M. G.; Hakami, A.

2014-12-01

Tropospheric ozone (O3) affects the productivity of ecosystems in addition to degrading human health. Concentrations of this pollutant are significantly influenced by precursor gas emissions, many of which emanate from energy production and use processes. Energy system optimization models could inform policy decisions that are intended to reduce these harmful effects if the contribution of precursor gas emissions to human health and ecosystem degradation could be elucidated. Nevertheless, determining the degree to which precursor gas emissions harm ecosystems and human health is challenging because of the photochemical production of ozone and the distinct mechanisms by which ozone causes harm to different crops, tree species, and humans. Here, the adjoint of a regional chemical transport model is employed to efficiently calculate the relative influences of ozone precursor gas emissions on ecosystem and human health degradation, which informs an energy system optimization. Specifically, for the summer of 2007 the Community Multiscale Air Quality (CMAQ) model adjoint is used to calculate the location- and sector-specific influences of precursor gas emissions on potential productivity losses for the major crops and sensitive tree species as well as human mortality attributable to chronic ozone exposure in the continental U.S. The atmospheric concentrations are evaluated with 12-km horizontal resolution with crop production and timber biomass data gridded similarly. These location-specific factors inform the energy production and use technologies selected in the MARKet ALlocation (MARKAL) model.

A spatially explicit whole-system model of the lignocellulosic bioethanol supply chain: an assessment of decentralised processing potential

PubMed Central

Dunnett, Alex J; Adjiman, Claire S; Shah, Nilay

2008-01-01

Background Lignocellulosic bioethanol technologies exhibit significant capacity for performance improvement across the supply chain through the development of high-yielding energy crops, integrated pretreatment, hydrolysis and fermentation technologies and the application of dedicated ethanol pipelines. The impact of such developments on cost-optimal plant location, scale and process composition within multiple plant infrastructures is poorly understood. A combined production and logistics model has been developed to investigate cost-optimal system configurations for a range of technological, system scale, biomass supply and ethanol demand distribution scenarios specific to European agricultural land and population densities. Results Ethanol production costs for current technologies decrease significantly from $0.71 to $0.58 per litre with increasing economies of scale, up to a maximum single-plant capacity of 550 × 106 l year-1. The development of high-yielding energy crops and consolidated bio-processing realises significant cost reductions, with production costs ranging from $0.33 to $0.36 per litre. Increased feedstock yields result in systems of eight fully integrated plants operating within a 500 × 500 km2 region, each producing between 1.24 and 2.38 × 109 l year-1 of pure ethanol. A limited potential for distributed processing and centralised purification systems is identified, requiring developments in modular, ambient pretreatment and fermentation technologies and the pipeline transport of pure ethanol. Conclusion The conceptual and mathematical modelling framework developed provides a valuable tool for the assessment and optimisation of the lignocellulosic bioethanol supply chain. In particular, it can provide insight into the optimal configuration of multiple plant systems. This information is invaluable in ensuring (near-)cost-optimal strategic development within the sector at the regional and national scale. The framework is flexible and can thus accommodate a range of processing tasks, logistical modes, by-product markets and impacting policy constraints. Significant scope for application to real-world case studies through dynamic extensions of the formulation has been identified. PMID:18662392

Development and Implementation of a Telecommuting Evaluation Framework, and Modeling the Executive Telecommuting Adoption Process

NASA Astrophysics Data System (ADS)

Vora, V. P.; Mahmassani, H. S.

2002-02-01

This work proposes and implements a comprehensive evaluation framework to document the telecommuter, organizational, and societal impacts of telecommuting through telecommuting programs. Evaluation processes and materials within the outlined framework are also proposed and implemented. As the first component of the evaluation process, the executive survey is administered within a public sector agency. The survey data is examined through exploratory analysis and is compared to a previous survey of private sector executives. The ordinal probit, dynamic probit, and dynamic generalized ordinal probit (DGOP) models of telecommuting adoption are calibrated to identify factors which significantly influence executive adoption preferences and to test the robustness of such factors. The public sector DGOP model of executive willingness to support telecommuting under different program scenarios is compared with an equivalent private sector DGOP model. Through the telecommuting program, a case study of telecommuting travel impacts is performed to further substantiate research.

Non-perturbative reheating and Nnaturalness

NASA Astrophysics Data System (ADS)

Hardy, Edward

2017-11-01

We study models in which reheating happens only through non-perturbative processes. The energy transferred can be exponentially suppressed unless the inflaton is coupled to a particle with a parametrically small mass. Additionally, in some models a light scalar with a negative mass squared parameter leads to much more efficient reheating than one with a positive mass squared of the same magnitude. If a theory contains many sectors similar to the Standard Model coupled to the inflaton via their Higgses, such dynamics can realise the Nnaturalness solution to the hierarchy problem. A sector containing a light Higgs with a non-zero vacuum expectation value is dominantly reheated and there is little energy transferred to the other sectors, consistent with cosmological constraints. The inflaton must decouple from other particles and have a flat potential at large field values, in which case the visible sector UV cutoff can be raised to 10 TeV in a simple model.

Source Sector and Region Contributions to BC and PM2.5 in Central Asia

EPA Science Inventory

Particulate matter (PM) mass concentrations, seasonal cycles, source sector and source region contributions in Central Asia (CA) are analyzed for the period April 2008-July 2009 using the STEM chemical transport model and modeled meteorology from the WRF model. Predicted AOD valu...

Industrial Sector Energy Efficiency Modeling (ISEEM) Framework Documentation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Karali, Nihan; Xu, Tengfang; Sathaye, Jayant

2012-12-12

The goal of this study is to develop a new bottom-up industry sector energy-modeling framework with an agenda of addressing least cost regional and global carbon reduction strategies, improving the capabilities and limitations of the existing models that allows trading across regions and countries as an alternative.

Basin Economic Allocation Model (BEAM): An economic model of water use developed for the Aral Sea Basin

NASA Astrophysics Data System (ADS)

Riegels, Niels; Kromann, Mikkel; Karup Pedersen, Jesper; Lindgaard-Jørgensen, Palle; Sokolov, Vadim; Sorokin, Anatoly

2013-04-01

The water resources of the Aral Sea basin are under increasing pressure, particularly from the conflict over whether hydropower or irrigation water use should take priority. The purpose of the BEAM model is to explore the impact of changes to water allocation and investments in water management infrastructure on the overall welfare of the Aral Sea basin. The BEAM model estimates welfare changes associated with changes to how water is allocated between the five countries in the basin (Kazakhstan, Kyrgyz Republic, Tajikistan, Turkmenistan and Uzbekistan; water use in Afghanistan is assumed to be fixed). Water is allocated according to economic optimization criteria; in other words, the BEAM model allocates water across time and space so that the economic welfare associated with water use is maximized. The model is programmed in GAMS. The model addresses the Aral Sea Basin as a whole - that is, the rivers Syr Darya, Amu Darya, Kashkadarya, and Zarafshan, as well as the Aral Sea. The model representation includes water resources, including 14 river sections, 6 terminal lakes, 28 reservoirs and 19 catchment runoff nodes, as well as land resources (i.e., irrigated croplands). The model covers 5 sectors: agriculture (crops: wheat, cotton, alfalfa, rice, fruit, vegetables and others), hydropower, nature, households and industry. The focus of the model is on welfare impacts associated with changes to water use in the agriculture and hydropower sectors. The model aims at addressing the following issues of relevance for economic management of water resources: • Physical efficiency (estimating how investments in irrigation efficiency affect economic welfare). • Economic efficiency (estimating how changes in how water is allocated affect welfare). • Equity (who will gain from changes in allocation of water from one sector to another and who will lose?). Stakeholders in the region have been involved in the development of the model, and about 10 national experts, including staff from the International Fund for Saving the Aral Sea (IFAS), have been trained in using the model. The model is publicly accessible through a web-based user interface that allows users to investigate scenarios and perform sensitivity analyses. Preliminary results suggest that: 1. At the margin, hydropower water use increases basin-wide welfare more than irrigation water use. 2. Under normal or average hydrological conditions, water scarcity is not a significant problem in the basin. 3. Under dry hydrological conditions, water scarcity is significant. Under these conditions, preliminary results suggest that cotton irrigation is less effective than other uses, particularly in Turkmenistan. 4. Investments in irrigation efficiency can have a significant impact on the effectiveness of water use for irrigation, thereby increasing the welfare of irrigation regions during dry periods.

Dark matter freeze-out in a nonrelativistic sector

NASA Astrophysics Data System (ADS)

Pappadopulo, Duccio; Ruderman, Joshua T.; Trevisan, Gabriele

2016-08-01

A thermally decoupled hidden sector of particles, with a mass gap, generically enters a phase of cannibalism in the early Universe. The Standard Model sector becomes exponentially colder than the hidden sector. We propose the cannibal dark matter framework, where dark matter resides in a cannibalizing sector with a relic density set by 2-to-2 annihilations. Observable signals of cannibal dark matter include a boosted rate for indirect detection, new relativistic degrees of freedom, and warm dark matter.

Organizational factors influencing successful primary care and public health collaboration.

PubMed

Valaitis, Ruta; Meagher-Stewart, Donna; Martin-Misener, Ruth; Wong, Sabrina T; MacDonald, Marjorie; O'Mara, Linda

2018-06-07

Public health and primary care are distinct sectors within western health care systems. Within each sector, work is carried out in the context of organizations, for example, public health units and primary care clinics. Building on a scoping literature review, our study aimed to identify the influencing factors within these organizations that affect the ability of these health care sectors to collaborate with one another in the Canadian context. Relationships between these factors were also explored. We conducted an interpretive descriptive qualitative study involving in-depth interviews with 74 key informants from three provinces, one each in western, central and eastern Canada, and others representing national organizations, government, or associations. The sample included policy makers, managers, and direct service providers in public health and primary care. Seven major organizational influencing factors on collaboration were identified: 1) Clear Mandates, Vision, and Goals; 2) Strategic Coordination and Communication Mechanisms between Partners; 3) Formal Organizational Leaders as Collaborative Champions; 4) Collaborative Organizational Culture; 5) Optimal Use of Resources; 6) Optimal Use of Human Resources; and 7) Collaborative Approaches to Programs and Services Delivery. While each influencing factor was distinct, the many interactions among these influences are indicative of the complex nature of public health and primary care collaboration. These results can be useful for those working to set up new or maintain existing collaborations with public health and primary care which may or may not include other organizations.

Comprehensive asymmetric dark matter model

NASA Astrophysics Data System (ADS)

Lonsdale, Stephen J.; Volkas, Raymond R.

2018-05-01

Asymmetric dark matter (ADM) is motivated by the similar cosmological mass densities measured for ordinary and dark matter. We present a comprehensive theory for ADM that addresses the mass density similarity, going beyond the usual ADM explanations of similar number densities. It features an explicit matter-antimatter asymmetry generation mechanism, has one fully worked out thermal history and suggestions for other possibilities, and meets all phenomenological, cosmological and astrophysical constraints. Importantly, it incorporates a deep reason for why the dark matter mass scale is related to the proton mass, a key consideration in ADM models. Our starting point is the idea of mirror matter, which offers an explanation for dark matter by duplicating the standard model with a dark sector related by a Z2 parity symmetry. However, the dark sector need not manifest as a symmetric copy of the standard model in the present day. By utilizing the mechanism of "asymmetric symmetry breaking" with two Higgs doublets in each sector, we develop a model of ADM where the mirror symmetry is spontaneously broken, leading to an electroweak scale in the dark sector that is significantly larger than that of the visible sector. The weak sensitivity of the ordinary and dark QCD confinement scales to their respective electroweak scales leads to the necessary connection between the dark matter and proton masses. The dark matter is composed of either dark neutrons or a mixture of dark neutrons and metastable dark hydrogen atoms. Lepton asymmetries are generated by the C P -violating decays of heavy Majorana neutrinos in both sectors. These are then converted by sphaleron processes to produce the observed ratio of visible to dark matter in the universe. The dynamics responsible for the kinetic decoupling of the two sectors emerges as an important issue that we only partially solve.

China's transportation energy consumption and CO2 emissions from a global perspective

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yin, Xiang; Chen, Wenying; Eom, Jiyong

2015-07-01

ABSTRACT Rapidly growing energy demand from China's transportation sector in the last two decades have raised concerns over national energy security, local air pollution, and carbon dioxide (CO2) emissions, and there is broad consensus that China's transportation sector will continue to grow in the coming decades. This paper explores the future development of China's transportation sector in terms of service demands, final energy consumption, and CO2 emissions, and their interactions with global climate policy. This study develops a detailed China transportation energy model that is nested in an integrated assessment model—Global Change Assessment Model (GCAM)—to evaluate the long-term energy consumptionmore » and CO2 emissions of China's transportation sector from a global perspective. The analysis suggests that, without major policy intervention, future transportation energy consumption and CO2 emissions will continue to rapidly increase and the transportation sector will remain heavily reliant on fossil fuels. Although carbon price policies may significantly reduce the sector's energy consumption and CO2 emissions, the associated changes in service demands and modal split will be modest, particularly in the passenger transport sector. The analysis also suggests that it is more difficult to decarbonize the transportation sector than other sectors of the economy, primarily owing to its heavy reliance on petroleum products.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

LHC searches for dark sector showers

NASA Astrophysics Data System (ADS)

Cohen, Timothy; Lisanti, Mariangela; Lou, Hou Keong; Mishra-Sharma, Siddharth

2017-11-01

This paper proposes a new search program for dark sector parton showers at the Large Hadron Collider (LHC). These signatures arise in theories characterized by strong dynamics in a hidden sector, such as Hidden Valley models. A dark parton shower can be composed of both invisible dark matter particles as well as dark sector states that decay to Standard Model particles via a portal. The focus here is on the specific case of `semi-visible jets,' jet-like collider objects where the visible states in the shower are Standard Model hadrons. We present a Simplified Model-like parametrization for the LHC observables and propose targeted search strategies for regions of parameter space that are not covered by existing analyses. Following the `mono- X' literature, the portal is modeled using either an effective field theoretic contact operator approach or with one of two ultraviolet completions; sensitivity projections are provided for all three cases. We additionally highlight that the LHC has a unique advantage over direct detection experiments in the search for this class of dark matter theories.

Optimizing freight routes and modes to minimize environmental impacts : integrating truck emissions cost in traffic assignment.

DOT National Transportation Integrated Search

2014-10-01

Adverse impacts of greenhouse gasses (GHG) and the imperative for reducing the production are well established. The : transportation sector accounts for 28% of all U.S. GHG production. Heavy-duty vehicles (e.g., large freight trucks) account for : ne...

Rois Langner | NREL

Science.gov Websites

engineer in the Commercial Buildings Research Group at NREL since 2010. Her research efforts have focused optimize building design and performance for military and large commercial buildings. She has also worked continual energy improvement, and more recently is working to support the small commercial building sector

Implementation of CFD modeling in the performance assessment and optimization of secondary clarifiers: the PVSC case study.

PubMed

Xanthos, S; Ramalingam, K; Lipke, S; McKenna, B; Fillos, J

2013-01-01

The water industry and especially the wastewater treatment sector has come under steadily increasing pressure to optimize their existing and new facilities to meet their discharge limits and reduce overall cost. Gravity separation of solids, producing clarified overflow and thickened solids underflow has long been one of the principal separation processes used in treating secondary effluent. Final settling tanks (FSTs) are a central link in the treatment process and often times act as the limiting step to the maximum solids handling capacity when high throughput requirements need to be met. The Passaic Valley Sewerage Commission (PVSC) is interested in using a computational fluid dynamics (CFD) modeling approach to explore any further FST retrofit alternatives to sustain significantly higher plant influent flows, especially under wet weather conditions. In detail there is an interest in modifying and/or upgrading/optimizing the existing FSTs to handle flows in the range of 280-720 million gallons per day (MGD) (12.25-31.55 m(3)/s) in compliance with the plant's effluent discharge limits for total suspended solids (TSS). The CFD model development for this specific plant will be discussed, 2D and 3D simulation results will be presented and initial results of a sensitivity study between two FST effluent weir structure designs will be reviewed at a flow of 550 MGD (∼24 m(3)/s) and 1,800 mg/L MLSS (mixed liquor suspended solids). The latter will provide useful information in determining whether the existing retrofit of one of the FSTs would enable compliance under wet weather conditions and warrants further consideration for implementing it in the remaining FSTs.

T.R.I.C.K.-Tire/Road Interaction Characterization & Knowledge - A tool for the evaluation of tire and vehicle performances in outdoor test sessions

NASA Astrophysics Data System (ADS)

Farroni, Flavio

2016-05-01

The most powerful engine, the most sophisticated aerodynamic devices or the most complex control systems will not improve vehicle performances if the forces exchanged with the road are not optimized by proper employment and knowledge of tires. The vehicle interface with the ground is constituted by the sum of small surfaces, wide about as one of our palms, in which tire/road interaction forces are exchanged. From this it is clear to see how the optimization of tire behavior represents a key-factor in the definition of the best setup of the whole vehicle. Nowadays, people and companies playing a role in automotive sector are looking for the optimal solution to model and understand tire's behavior both in experimental and simulation environments. The studies carried out and the tool developed herein demonstrate a new approach in tire characterization and in vehicle simulation procedures. This enables the reproduction of the dynamic response of a tire through the use of specific track sessions, carried out with the aim to employ the vehicle as a moving lab. The final product, named TRICK tool (Tire/Road Interaction Characterization and Knowledge), comprises of a vehicle model which processes experimental signals acquired from vehicle CAN bus and from sideslip angle estimation additional instrumentation. The output of the tool is several extra "virtual telemetry" channels, based on the time history of the acquired signals and containing force and slip estimations, useful to provide tire interaction characteristics. TRICK results can be integrated with the physical models developed by the Vehicle Dynamics UniNa research group, providing a multitude of working solutions and constituting an ideal instrument for the prediction and the simulation of the real tire dynamics.

Electric power and the global economy: Advances in database construction and sector representation

NASA Astrophysics Data System (ADS)

Peters, Jeffrey C.

The electricity sector plays a crucial role in the global economy. The sector is a major consumer of fossil fuel resources, producer of greenhouse gas emissions, and an important indicator and correlate of economic development. As such, the sector is a primary target for policy-makers seeking to address these issues. The sector is also experiencing rapid technological change in generation (e.g. renewables), primary inputs (e.g. horizontal drilling and hydraulic fracturing), and end-use efficiency. This dissertation seeks to further our understanding of the role of the electricity sector as part of the dynamic global energy-economy, which requires significant research advances in both database construction and modeling techniques. Chapter 2 identifies useful engineering-level data and presents a novel matrix balancing method for integrating these data in global economic databases. Chapter 3 demonstrates the relationship between matrix balancing method and modeling results, and Chapter 4 presents the full construction methodology for GTAP-Power, the foremost, publicly-available global computable general equilibrium database. Chapter 5 presents an electricity-detailed computational equilibrium model that explicitly and endogenously captures capacity utilization, capacity expansion, and their interdependency - important aspects of technological substitution in the electricity sector. The individual, but interrelated, research contributions to database construction and electricity modeling in computational equilibrium are placed in the context of analyzing the US EPA Clean Power Plan (CPP) CO 2 target of 32 percent reduction of CO2 emissions in the US electricity sector from a 2005 baseline by 2030. Assuming current fuel prices, the model predicts an almost 28 percent CO2 reduction without further policy intervention. Next, a carbon tax and investment subsidies for renewable technologies to meet the CPP full targets are imposed and compared (Chapter 6). The carbon tax achieves the target via both utilization and expansion, while the renewable investment subsidies lead to over-expansion and compromises some of the possibilities via utilization. In doing so, this dissertation furthers our understanding of the role of the electricity sector as part of the dynamic global energy-economy.

What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference? Results from ISI-MIP the first Inter-Sectoral Impact Model Intercomparison Project

NASA Astrophysics Data System (ADS)

Frieler, K.; Huber, V.; Piontek, F.; Schewe, J.; Serdeczny, O.; Warszawski, L.

2012-12-01

The Inter-sectoral Impact Model Intercomparison Project (ISI-MIP) aims to synthesize the state-of-the-art knowledge of climate change impacts at different levels of global warming. Over 25 climate impact modelling teams from around the world, working within the agriculture, water, biomes, infrastructure and health sectors, are collaborating to find answers to the question "What is the difference between a 2, 3, 4, or 5 °C world and how good are we at telling this difference?". The analysis is based on common, bias-corrected climate projections, and socio-economic pathways. The first, fast-tracked phase of the ISI-MIP has a focus on global impact models. The project's experimental design is formulated to distinguish the uncertainty introduced by the impact models themselves, from the inherent uncertainty in the climate projections and the variety of plausible socio-economic futures. Novel metrics, developed to emphasize societal impacts, will be used to identify regional 'hot-spots' of climate change impacts, as well as to quantify the cross-sectoral impact of the increasing frequency of extreme events in future climates. We present here first results from the Fast-Track phase of the project covering impact simulations in the biomes, agriculture and water sectors, in which the societal impacts of climate change are quantified for different levels of global warming. We also discuss the design of the scenario set-up and impact indicators chosen to suit the unique cross-sectoral, multi-model nature of the project.

Review of indicators for cross-sectoral optimization of nosocomial infection prophylaxis – a perspective from structurally- and process-oriented hygiene

PubMed Central

Hübner, Nils-Olaf; Fleßa, Steffen; Jakisch, Ralf; Assadian, Ojan; Kramer, Axel

2012-01-01

In the care of patients, the prevention of nosocomial infections is crucial. For it to be successful, cross-sectoral, interface-oriented hygiene quality management is necessary. The goal is to apply the HACCP (Hazard Assessment and Critical Control Points) concept to hospital hygiene, in order to create a multi-dimensional hygiene control system based on hygiene indicators that will overcome the limitations of a procedurally non-integrated and non-cross-sectoral view of hygiene. Three critical risk dimensions can be identified for the implementation of three-dimensional quality control of hygiene in clinical routine: the constitution of the person concerned, the surrounding physical structures and technical equipment, and the medical procedures. In these dimensions, the establishment of indicators and threshold values enables a comprehensive assessment of hygiene quality. Thus, the cross-sectoral evaluation of the quality of structure, processes and results is decisive for the success of integrated infection prophylaxis. This study lays the foundation for hygiene indicator requirements and develops initial concepts for evaluating quality management in hygiene. PMID:22558049

A Wideband Circularly Polarized Antenna with a Multiple-Circular-Sector Dielectric Resonator.

PubMed

Trinh-Van, Son; Yang, Youngoo; Lee, Kang-Yoon; Hwang, Keum Cheol

2016-11-03

This paper presents the design of a wideband circularly polarized antenna using a multiple-circular-sector dielectric resonator (DR). The DR is composed of twelve circular-sector DRs with identical central angles of 30 ∘ but with different radii. A genetic algorithm is utilized to optimize the radii of the twelve circular-sector DRs to realize wideband circular polarization. The proposed antenna is excited using an aperture-coupled feeding technique through a narrow rectangular slot etched onto the ground plane. An antenna prototype is experimentally verified. The measured -10 dB reflection and 3 dB axial ratio (AR) bandwidths are 31.39% (1.88-2.58 GHz) and 19.30% (2.06-2.50 GHz), respectively, covering the operating bands of the following systems: UMTS-2100 (2.145 GHz), WiMAX (2.3 GHz), and Wi-Fi (2.445 GHz). A measured peak gain of 7.65 dBic at 2.225 GHz and gain variation of less than 2.70 dBic within the measured 3 dB AR bandwidth are achieved. In addition, the radiation patterns of the proposed antenna are presented and discussed.

Closing the access barrier for effective anti-malarials in the private sector in rural Uganda: consortium for ACT private sector subsidy (CAPSS) pilot study.

PubMed

Talisuna, Ambrose O; Daumerie, Penny Grewal; Balyeku, Andrew; Egan, Timothy; Piot, Bram; Coghlan, Renia; Lugand, Maud; Bwire, Godfrey; Rwakimari, John Bosco; Ndyomugyenyi, Richard; Kato, Fred; Byangire, Maria; Kagwa, Paul; Sebisubi, Fred; Nahamya, David; Bonabana, Angela; Mpanga-Mukasa, Susan; Buyungo, Peter; Lukwago, Julius; Batte, Allan; Nakanwagi, Grace; Tibenderana, James; Nayer, Kinny; Reddy, Kishore; Dokwal, Nilesh; Rugumambaju, Sylvester; Kidde, Saul; Banerji, Jaya; Jagoe, George

2012-10-29

Artemisinin-based combination therapy (ACT), the treatment of choice for uncomplicated falciparum malaria, is unaffordable and generally inaccessible in the private sector, the first port of call for most malaria treatment across rural Africa. Between August 2007 and May 2010, the Uganda Ministry of Health and the Medicines for Malaria Venture conducted the Consortium for ACT Private Sector Subsidy (CAPSS) pilot study to test whether access to ACT in the private sector could be improved through the provision of a high level supply chain subsidy. Four intervention districts were purposefully selected to receive branded subsidized medicines - "ACT with a leaf", while the fifth district acted as the control. Baseline and evaluation outlet exit surveys and retail audits were conducted at licensed and unlicensed drug outlets in the intervention and control districts. A survey-adjusted, multivariate logistic regression model was used to analyse the intervention's impact on: ACT uptake and price; purchase of ACT within 24 hours of symptom onset; ACT availability and displacement of sub-optimal anti-malarial. At baseline, ACT accounted for less than 1% of anti-malarials purchased from licensed drug shops for children less than five years old. However, at evaluation, "ACT with a leaf" accounted for 69% of anti-malarial purchased in the interventions districts. Purchase of ACT within 24 hours of symptom onset for children under five years rose from 0.8% at baseline to 26.2% (95% CI: 23.2-29.2%) at evaluation in the intervention districts. In the control district, it rose modestly from 1.8% to 5.6% (95% CI: 4.0-7.3%). The odds of purchasing ACT within 24 hours in the intervention districts compared to the control was 0.46 (95% CI: 0.08-2.68, p=0.4) at baseline and significant increased to 6.11 (95% CI: 4.32-8.62, p<0.0001) at evaluation. Children less than five years of age had "ACT with a leaf" purchased for them more often than those aged above five years. There was no evidence of price gouging. These data demonstrate that a supply-side subsidy and an intensive communications campaign significantly increased the uptake and use of ACT in the private sector in Uganda.

Closing the access barrier for effective anti-malarials in the private sector in rural Uganda: consortium for ACT private sector subsidy (CAPSS) pilot study

PubMed Central

2012-01-01

Background Artemisinin-based combination therapy (ACT), the treatment of choice for uncomplicated falciparum malaria, is unaffordable and generally inaccessible in the private sector, the first port of call for most malaria treatment across rural Africa. Between August 2007 and May 2010, the Uganda Ministry of Health and the Medicines for Malaria Venture conducted the Consortium for ACT Private Sector Subsidy (CAPSS) pilot study to test whether access to ACT in the private sector could be improved through the provision of a high level supply chain subsidy. Methods Four intervention districts were purposefully selected to receive branded subsidized medicines - “ACT with a leaf”, while the fifth district acted as the control. Baseline and evaluation outlet exit surveys and retail audits were conducted at licensed and unlicensed drug outlets in the intervention and control districts. A survey-adjusted, multivariate logistic regression model was used to analyse the intervention’s impact on: ACT uptake and price; purchase of ACT within 24 hours of symptom onset; ACT availability and displacement of sub-optimal anti-malarial. Results At baseline, ACT accounted for less than 1% of anti-malarials purchased from licensed drug shops for children less than five years old. However, at evaluation, “ACT with a leaf” accounted for 69% of anti-malarial purchased in the interventions districts. Purchase of ACT within 24 hours of symptom onset for children under five years rose from 0.8% at baseline to 26.2% (95% CI: 23.2-29.2%) at evaluation in the intervention districts. In the control district, it rose modestly from 1.8% to 5.6% (95% CI: 4.0-7.3%). The odds of purchasing ACT within 24 hours in the intervention districts compared to the control was 0.46 (95% CI: 0.08-2.68, p=0.4) at baseline and significant increased to 6.11 (95% CI: 4.32-8.62, p<0.0001) at evaluation. Children less than five years of age had “ACT with a leaf” purchased for them more often than those aged above five years. There was no evidence of price gouging. Conclusions These data demonstrate that a supply-side subsidy and an intensive communications campaign significantly increased the uptake and use of ACT in the private sector in Uganda. PMID:23107021

Fermion masses and mixings and dark matter constraints in a model with radiative seesaw mechanism

NASA Astrophysics Data System (ADS)

Bernal, Nicolás; Cárcamo Hernández, A. E.; de Medeiros Varzielas, Ivo; Kovalenko, Sergey

2018-05-01

We formulate a predictive model of fermion masses and mixings based on a Δ(27) family symmetry. In the quark sector the model leads to the viable mixing inspired texture where the Cabibbo angle comes from the down quark sector and the other angles come from both up and down quark sectors. In the lepton sector the model generates a predictive structure for charged leptons and, after radiative seesaw, an effective neutrino mass matrix with only one real and one complex parameter. We carry out a detailed analysis of the predictions in the lepton sector, where the model is only viable for inverted neutrino mass hierarchy, predicting a strict correlation between θ 23 and θ 13. We show a benchmark point that leads to the best-fit values of θ 12, θ 13, predicting a specific sin2 θ 23 ≃ 0.51 (within the 3 σ range), a leptonic CP-violating Dirac phase δ ≃ 281.6° and for neutrinoless double-beta decay m ee ≃ 41.3 meV. We turn then to an analysis of the dark matter candidates in the model, which are stabilized by an unbroken ℤ2 symmetry. We discuss the possibility of scalar dark matter, which can generate the observed abundance through the Higgs portal by the standard WIMP mechanism. An interesting possibility arises if the lightest heavy Majorana neutrino is the lightest ℤ2-odd particle. The model can produce a viable fermionic dark matter candidate, but only as a feebly interacting massive particle (FIMP), with the smallness of the coupling to the visible sector protected by a symmetry and directly related to the smallness of the light neutrino masses.

Thermal dark matter from a highly decoupled sector

DOE PAGES

Berlin, Asher; Hooper, Dan; Krnjaic, Gordan

2016-11-17

It has recently been shown that if the dark matter is in thermal equilibrium with a sector that is highly decoupled from the Standard Model, it can freeze out with an acceptable relic abundance, even if the dark matter is as heavy as ~1–100 PeV. In such scenarios, both the dark and visible sectors are populated after inflation, but with independent temperatures. The lightest particle in the dark sector will be generically long-lived and can come to dominate the energy density of the Universe. Upon decaying, these particles can significantly reheat the visible sector, diluting the abundance of dark mattermore » and thus allowing for dark matter particles that are much heavier than conventional WIMPs. In this study, we present a systematic and pedagogical treatment of the cosmological history in this class of models, emphasizing the simplest scenarios in which a dark matter candidate annihilates into hidden sector particles which then decay into visible matter through the vector, Higgs, or lepton portals. In each case, we find ample parameter space in which very heavy dark matter particles can provide an acceptable thermal relic abundance. We also discuss possible extensions of models featuring these dynamics.« less

Thermal dark matter from a highly decoupled sector

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berlin, Asher; Hooper, Dan; Krnjaic, Gordan

It has recently been shown that if the dark matter is in thermal equilibrium with a sector that is highly decoupled from the Standard Model, it can freeze out with an acceptable relic abundance, even if the dark matter is as heavy as ~1–100 PeV. In such scenarios, both the dark and visible sectors are populated after inflation, but with independent temperatures. The lightest particle in the dark sector will be generically long-lived and can come to dominate the energy density of the Universe. Upon decaying, these particles can significantly reheat the visible sector, diluting the abundance of dark mattermore » and thus allowing for dark matter particles that are much heavier than conventional WIMPs. In this study, we present a systematic and pedagogical treatment of the cosmological history in this class of models, emphasizing the simplest scenarios in which a dark matter candidate annihilates into hidden sector particles which then decay into visible matter through the vector, Higgs, or lepton portals. In each case, we find ample parameter space in which very heavy dark matter particles can provide an acceptable thermal relic abundance. We also discuss possible extensions of models featuring these dynamics.« less

TreePOD: Sensitivity-Aware Selection of Pareto-Optimal Decision Trees.

PubMed

Muhlbacher, Thomas; Linhardt, Lorenz; Moller, Torsten; Piringer, Harald

2018-01-01

Balancing accuracy gains with other objectives such as interpretability is a key challenge when building decision trees. However, this process is difficult to automate because it involves know-how about the domain as well as the purpose of the model. This paper presents TreePOD, a new approach for sensitivity-aware model selection along trade-offs. TreePOD is based on exploring a large set of candidate trees generated by sampling the parameters of tree construction algorithms. Based on this set, visualizations of quantitative and qualitative tree aspects provide a comprehensive overview of possible tree characteristics. Along trade-offs between two objectives, TreePOD provides efficient selection guidance by focusing on Pareto-optimal tree candidates. TreePOD also conveys the sensitivities of tree characteristics on variations of selected parameters by extending the tree generation process with a full-factorial sampling. We demonstrate how TreePOD supports a variety of tasks involved in decision tree selection and describe its integration in a holistic workflow for building and selecting decision trees. For evaluation, we illustrate a case study for predicting critical power grid states, and we report qualitative feedback from domain experts in the energy sector. This feedback suggests that TreePOD enables users with and without statistical background a confident and efficient identification of suitable decision trees.

Coverage of private sector community midwife services in rural Punjab, Pakistan: development and demand.

PubMed

Mumtaz, Zubia; Levay, Adrienne V; Jhangri, Gian S; Bhatti, Afshan

2015-11-25

In 2007, the Government of Pakistan introduced a new cadre of community midwives (CMWs) to address low skilled birth attendance rates in rural areas; this workforce is located in the private-sector. There are concerns about the effectiveness of the programme for increasing skilled birth attendance as previous experience from private-sector programmes has been sub-optimal. Indonesia first promoted private sector midwifery care, but the initiative failed to provide universal coverage and reduce maternal mortality rates. A clustered, stratified survey was conducted in the districts of Jhelum and Layyah, Punjab. A total of 1,457 women who gave birth in the 2 years prior to the survey were interviewed. χ(2) analyses were performed to assess variation in coverage of maternal health services between the two districts. Logistic regression models were developed to explore whether differentials in coverage between the two districts could be explained by differential levels of development and demand for skilled birth attendance. Mean cost of childbirth care by type of provider was also calculated. Overall, 7.9% of women surveyed reported a CMW-attended birth. Women in Jhelum were six times more likely to report a CMW-attended birth than women in Layyah. The mean cost of a CMW-attended birth compared favourably with a dai-attended birth. The CMWs were, however, having difficulty garnering community trust. The majority of women, when asked why they had not sought care from their neighbourhood CMW, cited a lack of trust in CMWs' competency and that they wanted a different provider. The CMWs have yet to emerge as a significant maternity care provider in rural Punjab. Levels of overall community development determined uptake and hence coverage of CMW care. The CMWs were able to insert themselves into the maternal health marketplace in Jhelum because of an existing demand. A lower demand in Layyah meant there was less 'space' for the CMWs to enter the market. To ensure universal coverage, there is a need to revisit the strategy of introducing a new midwifery workforce in the private sector in contexts of low demand and marketing the benefits of skilled birth attendance.

Optimizing adherence to antiretroviral therapy

PubMed Central

Sahay, Seema; Reddy, K. Srikanth; Dhayarkar, Sampada

2011-01-01

HIV has now become a manageable chronic disease. However, the treatment outcomes may get hampered by suboptimal adherence to ART. Adherence optimization is a concrete reality in the wake of ‘universal access’ and it is imperative to learn lessons from various studies and programmes. This review examines current literature on ART scale up, treatment outcomes of the large scale programmes and the role of adherence therein. Social, behavioural, biological and programme related factors arise in the context of ART adherence optimization. While emphasis is laid on adherence, retention of patients under the care umbrella emerges as a major challenge. An in-depth understanding of patients’ health seeking behaviour and health care delivery system may be useful in improving adherence and retention of patients in care continuum and programme. A theoretical framework to address the barriers and facilitators has been articulated to identify problematic areas in order to intervene with specific strategies. Empirically tested objective adherence measurement tools and approaches to assess adherence in clinical/ programme settings are required. Strengthening of ART programmes would include appropriate policies for manpower and task sharing, integrating traditional health sector, innovations in counselling and community support. Implications for the use of theoretical model to guide research, clinical practice, community involvement and policy as part of a human rights approach to HIV disease is suggested. PMID:22310817

Early Probe and Drug Discovery in Academia: A Minireview.

PubMed

Roy, Anuradha

2018-02-09

Drug discovery encompasses processes ranging from target selection and validation to the selection of a development candidate. While comprehensive drug discovery work flows are implemented predominantly in the big pharma domain, early discovery focus in academia serves to identify probe molecules that can serve as tools to study targets or pathways. Despite differences in the ultimate goals of the private and academic sectors, the same basic principles define the best practices in early discovery research. A successful early discovery program is built on strong target definition and validation using a diverse set of biochemical and cell-based assays with functional relevance to the biological system being studied. The chemicals identified as hits undergo extensive scaffold optimization and are characterized for their target specificity and off-target effects in in vitro and in animal models. While the active compounds from screening campaigns pass through highly stringent chemical and Absorption, Distribution, Metabolism, and Excretion (ADME) filters for lead identification, the probe discovery involves limited medicinal chemistry optimization. The goal of probe discovery is identification of a compound with sub-µM activity and reasonable selectivity in the context of the target being studied. The compounds identified from probe discovery can also serve as starting scaffolds for lead optimization studies.

The Impact of Military Training on Veterans’ Earnings in the Private Sector: Is there Complimentarity Between Military and Private Training for Veterans

DTIC Science & Technology

1994-03-01

thesis analyzed the complimentarity between military and post-military private sector training and the effect of military training on private sector wages...of data. The results of the thesis indicate that military training increases post-military private sector earnings of Veterans by 0.18 percent per...between military and post-service private sector training. When type of occupation is included in the models, the wage effect of military training fell to

Promoting Evidence-Based Practice: Models and Mechanisms from Cross-Sector Review

ERIC Educational Resources Information Center

Nutley, Sandra; Walter, Isabel; Davies, Huw T. O.

2009-01-01

This article draws on both a cross-sector literature review of mechanisms to promote evidence-based practice and a specific review of ways of improving research use in social care. At the heart of the article is a discussion of three models of evidence-based practice: the research-based practitioner model, the embedded research model, and the…

Multi-model Effort Highlights Progress, Future Needs in Renewable Energy

Science.gov Websites

January 9, 2018 Models of the U.S. electricity sector are relied upon by sector stakeholders and decision of VRE technologies. The report also documents differences in modeling methodologies and shows how long-term planning and decision-making, both for the respective agencies and for other electricity

Balancing ecosystem services with energy and food security - Assessing trade-offs from reservoir operation and irrigation investments in Kenya's Tana Basin

NASA Astrophysics Data System (ADS)

Hurford, A. P.; Harou, J. J.

2014-08-01

Competition for water between key economic sectors and the environment means agreeing allocations is challenging. Managing releases from the three major dams in Kenya's Tana River basin with its 4.4 million inhabitants, 567 MW of installed hydropower capacity, 33 000 ha of irrigation and ecologically important wetlands and forests is a pertinent example. This research seeks firstly to identify and help decision-makers visualise reservoir management strategies which result in the best possible (Pareto-optimal) allocation of benefits between sectors. Secondly, it seeks to show how trade-offs between achievable benefits shift with the implementation of proposed new rice, cotton and biofuel irrigation projects. To approximate the Pareto-optimal trade-offs we link a water resources management simulation model to a multi-criteria search algorithm. The decisions or "levers" of the management problem are volume-dependent release rules for the three major dams and extent of investment in new irrigation schemes. These decisions are optimised for eight objectives covering the provision of water supply and irrigation, energy generation and maintenance of ecosystem services. Trade-off plots allow decision-makers to assess multi-reservoir rule-sets and irrigation investment options by visualising their impacts on different beneficiaries. Results quantify how economic gains from proposed irrigation schemes trade-off against the disturbance of ecosystems and local livelihoods that depend on them. Full implementation of the proposed schemes is shown to come at a high environmental and social cost. The clarity and comprehensiveness of "best-case" trade-off analysis is a useful vantage point from which to tackle the interdependence and complexity of "water-energy-food nexus" resource security issues.

Still serving hot soup? Two hundred years of a charitable food sector in Australia: a narrative review.

PubMed

Lindberg, Rebecca; Whelan, Jillian; Lawrence, Mark; Gold, Lisa; Friel, Sharon

2015-08-01

Despite the importance of the charitable food sector for a proportion of the Australian population, there is uncertainty about its present and future contributions to wellbeing. This paper describes its nature and examines its scope for improving health and food security. The review, using systematic methods for public health research, identified peer-reviewed and grey literature relevant to Australian charitable food programs (2002 to 2012). Seventy publications met the criteria and informed this paper. The sector includes food banks, more than 3,000 community agencies and 800 school breakfast programs. It provides food for up to two million people annually. The scope extends beyond emergency food relief and includes case management, advocacy and other support. Weaknesses include a food supply that is sub-optimal, resource limitations and lack of evidence to evaluate or support their work towards food security. The sector supports people experiencing disadvantage and involves multiple organisations, working in a variety of settings, to provide food for up to 8% of the population. The limits on the sector's capacity to address food insecurity by itself must be acknowledged so that civil society, government and the food industry can support sufficient, nutritious and affordable food for all. © 2015 Public Health Association of Australia.

Medical imaging technology shock and volatility of macro economics: Analysis using a three-sector dynamical stochastic general equilibrium REC model.

PubMed

Han, Shurong; Huang, Yeqing

2017-07-07

The study analysed the medical imaging technology business cycle from 1981 to 2009 and found that the volatility of consumption in Chinese medical imaging business was higher than that of the developed countries. The volatility of gross domestic product (GDP) and the correlation between consumption and GDP is also higher than that of the developed countries. Prior to the early 1990s the volatility of consumption is even higher than GDP. This fact makes it difficult to explain the volatile market using the standard one sector real economic cycle (REC) model. Contrary to the other domestic studies, this study considers a three-sector dynamical stochastic general equilibrium REC model. In this model there are two consumption sectors, whereby one is labour intensive and another is capital intensive. The more capital intensive investment sector only introduces technology shocks in the medical imaging market. Our response functions and Monte-Carlo simulation results show that the model can explain 90% of the volatility of consummation relative to GDP, and explain the correlation between consumption and GDP. The results demonstrated the significant correlation between the technological reform in medical imaging and volatility in the labour market on Chinese macro economy development.

Control of water distribution networks with dynamic DMA topology using strictly feasible sequential convex programming

NASA Astrophysics Data System (ADS)

Wright, Robert; Abraham, Edo; Parpas, Panos; Stoianov, Ivan

2015-12-01

The operation of water distribution networks (WDN) with a dynamic topology is a recently pioneered approach for the advanced management of District Metered Areas (DMAs) that integrates novel developments in hydraulic modeling, monitoring, optimization, and control. A common practice for leakage management is the sectorization of WDNs into small zones, called DMAs, by permanently closing isolation valves. This facilitates water companies to identify bursts and estimate leakage levels by measuring the inlet flow for each DMA. However, by permanently closing valves, a number of problems have been created including reduced resilience to failure and suboptimal pressure management. By introducing a dynamic topology to these zones, these disadvantages can be eliminated while still retaining the DMA structure for leakage monitoring. In this paper, a novel optimization method based on sequential convex programming (SCP) is outlined for the control of a dynamic topology with the objective of reducing average zone pressure (AZP). A key attribute for control optimization is reliable convergence. To achieve this, the SCP method we propose guarantees that each optimization step is strictly feasible, resulting in improved convergence properties. By using a null space algorithm for hydraulic analyses, the computations required are also significantly reduced. The optimized control is actuated on a real WDN operated with a dynamic topology. This unique experimental program incorporates a number of technologies set up with the objective of investigating pioneering developments in WDN management. Preliminary results indicate AZP reductions for a dynamic topology of up to 6.5% over optimally controlled fixed topology DMAs. This article was corrected on 12 JAN 2016. See the end of the full text for details.

Educational Connoisseurship and Criticism: Evaluation of a Cooperation Model between University and the Sector on Vocational Education

ERIC Educational Resources Information Center

Kaysi, Feyzi; Bavli, Bunyamin; Gurol, Aysun

2017-01-01

Vocational schools which were opened to raise intermediate staff for the sector must update their functions to fulfill the intermediate staff need emerging as a result of the developments and changes in the sector through the time. Considering the needs of the sector, updating content of the courses and opening new lessons or programs will fulfill…

A Marginal Cost Based "Social Cost of Carbon" Provides Inappropriate Guidance in a World That Needs Rapid and Deep Decarbonization

NASA Astrophysics Data System (ADS)

Morgan, M. G.; Vaishnav, P.; Azevedo, I. L.; Dowlatabadi, H.

2016-12-01

Rising temperatures and changing precipitation patterns due to climate change are projected to alter many sectors of the US economy. A growing body of research has examined these effects in the energy, water, and agricultural sectors. Rising summer temperatures increase the demand for electricity. Changing precipitation patterns effect the availability of water for hydropower generation, thermo-electric cooling, irrigation, and municipal and industrial consumption. A combination of changes to temperature and precipitation alter crop yields and cost-effective farming practices. Although a significant body of research exists on analyzing impacts to individual sectors, fewer studies examine the effects using a common set of assumptions (e.g., climatic and socio-economic) within a coupled modeling framework. The present analysis uses a multi-sector, multi-model framework with common input assumptions to assess the projected effects of climate change on energy, water, and land-use in the United States. The analysis assesses the climate impacts for across 5 global circulation models for representative concentration pathways (RCP) of 8.5 and 4.5 W/m2. The energy sector models - Pacific Northwest National Lab's Global Change Assessment Model (GCAM) and the National Renewable Energy Laboratory's Regional Energy Deployment System (ReEDS) - show the effects of rising temperature on energy and electricity demand. Electricity supply in ReEDS is also affected by the availability of water for hydropower and thermo-electric cooling. Water availability is calculated from the GCM's precipitation using the US Basins model. The effects on agriculture are estimated using both a process-based crop model (EPIC) and an agricultural economic model (FASOM-GHG), which adjusts water supply curves based on information from US Basins. The sectoral models show higher economic costs of climate change under RCP 8.5 than RCP 4.5 averaged across the country and across GCM's.

Product Mix Selection Using AN Evolutionary Technique

NASA Astrophysics Data System (ADS)

Tsoulos, Ioannis G.; Vasant, Pandian

2009-08-01

This paper proposes an evolutionary technique for the solution of a real—life industrial problem and particular for the product mix selection problem. The evolutionary technique is a combination of a genetic algorithm that preserves the feasibility of the trial solutions with penalties and some local optimization method. The goal of this paper has been achieved in finding the best near optimal solution for the profit fitness function respect to vagueness factor and level of satisfaction. The findings of the profit values will be very useful for the decision makers in the industrial engineering sector for the implementation purpose. It's possible to improve the solutions obtained in this study by employing other meta-heuristic methods such as simulated annealing, tabu Search, ant colony optimization, particle swarm optimization and artificial immune systems.

Hazardous waste management system design under population and environmental impact considerations.

PubMed

Yilmaz, Ozge; Kara, Bahar Y; Yetis, Ulku

2017-12-01

This paper presents a multi objective mixed integer location/routing model that aims to minimize transportation cost and risks for large-scale hazardous waste management systems (HWMSs). Risks induced by hazardous wastes (HWs) on both public and the environment are addressed. For this purpose, a new environmental impact definition is proposed that considers the environmentally vulnerable elements including water bodies, agricultural areas, coastal regions and forestlands located within a certain bandwidth around transportation routes. The solution procedure yields to Pareto optimal curve for two conflicting objectives. The conceptual model developed prior to mathematical formulation addresses waste-to-technology compatibility and HW processing residues to assure applicability of the model to real-life HWMSs. The suggested model was used in a case study targeting HWMS in Turkey. Based on the proposed solution, it was possible to identify not only the transportation routes but also a set of information on HW handling facilities including the types, locations, capacities, and investment/operational cost. The HWMS of this study can be utilized both by public authorities and private sector investors for planning purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Thick electrodes for Li-ion batteries: A model based analysis

NASA Astrophysics Data System (ADS)

Danner, Timo; Singh, Madhav; Hein, Simon; Kaiser, Jörg; Hahn, Horst; Latz, Arnulf

2016-12-01

Li-ion batteries are commonly used in portable electronic devices due to their outstanding energy and power density. A remaining issue which hinders the breakthrough e.g. in the automotive sector is the high production cost. For low power applications, such as stationary storage, batteries with electrodes thicker than 300 μm were suggested. High energy densities can be attained with only a few electrode layers which reduces production time and cost. However, mass and charge transport limitations can be severe at already small C-rates due to long transport pathways. In this article we use a detailed 3D micro-structure resolved model to investigate limiting factors for battery performance. The model is parametrized with data from the literature and dedicated experiments and shows good qualitative agreement with experimental discharge curves of thick NMC-graphite Li-ion batteries. The model is used to assess the effect of inhomogeneities in carbon black distribution and gives answers to the possible occurrence of lithium plating during battery charge. Based on our simulations we can predict optimal operation strategies and improved design concepts for future Li-ion batteries employing thick electrodes.

An Efficient Taguchi Approach for the Performance Optimization of Health, Safety, Environment and Ergonomics in Generation Companies

PubMed Central

Azadeh, Ali; Sheikhalishahi, Mohammad

2014-01-01

Background A unique framework for performance optimization of generation companies (GENCOs) based on health, safety, environment, and ergonomics (HSEE) indicators is presented. Methods To rank this sector of industry, the combination of data envelopment analysis (DEA), principal component analysis (PCA), and Taguchi are used for all branches of GENCOs. These methods are applied in an integrated manner to measure the performance of GENCO. The preferred model between DEA, PCA, and Taguchi is selected based on sensitivity analysis and maximum correlation between rankings. To achieve the stated objectives, noise is introduced into input data. Results The results show that Taguchi outperforms other methods. Moreover, a comprehensive experiment is carried out to identify the most influential factor for ranking GENCOs. Conclusion The approach developed in this study could be used for continuous assessment and improvement of GENCO's performance in supplying energy with respect to HSEE factors. The results of such studies would help managers to have better understanding of weak and strong points in terms of HSEE factors. PMID:26106505

A reservoir optimization study--El Bunduq Field, Abu Dhabi, Qatar

DOE Office of Scientific and Technical Information (OSTI.GOV)

Blashbush, J.L.; Nagai, R.B.; Ogimoto, T.

El Bunduq reservoir is located in the offshore area of Abu Dhabi and Qatar. The field was shut-in in July 1979 due to production with high gas-oil ratios. Pressure differences of 200-400 psi between the flanks and the central part of the reservoir were still present almost four years after the field was shut-in. A comprehensive reservoir engineering study determined that the reasons for this behavior were the deteriorating qualities of the reservoir rock downstructure and the presence of a tar mat around the field. After the field behavior was history matched, model studies of a representative sector of themore » field indicated that peripheral waterflooding would recover less than 15 percent of the OOIP in a period of 30 years. However, pattern injection recoveries were calculated to be at least twice as high. Several full field alternatives were investigated to optimize the development of the reservoir under a pattern waterflood. This paper summarizes the various studies that led to the acceptance of the idea of pattern development over peripheral injection, as a result of the unique characteristics of this field.« less

Consequence and Resilience Modeling for Chemical Supply Chains

NASA Technical Reports Server (NTRS)

Stamber, Kevin L.; Vugrin, Eric D.; Ehlen, Mark A.; Sun, Amy C.; Warren, Drake E.; Welk, Margaret E.

2011-01-01

The U.S. chemical sector produces more than 70,000 chemicals that are essential material inputs to critical infrastructure systems, such as the energy, public health, and food and agriculture sectors. Disruptions to the chemical sector can potentially cascade to other dependent sectors, resulting in serious national consequences. To address this concern, the U.S. Department of Homeland Security (DHS) tasked Sandia National Laboratories to develop a predictive consequence modeling and simulation capability for global chemical supply chains. This paper describes that capability , which includes a dynamic supply chain simulation platform called N_ABLE(tm). The paper also presents results from a case study that simulates the consequences of a Gulf Coast hurricane on selected segments of the U.S. chemical sector. The case study identified consequences that include impacted chemical facilities, cascading impacts to other parts of the chemical sector. and estimates of the lengths of chemical shortages and recovery . Overall. these simulation results can DHS prepare for and respond to actual disruptions.

On the LHC sensitivity for non-thermalised hidden sectors

NASA Astrophysics Data System (ADS)

Kahlhoefer, Felix

2018-04-01

We show under rather general assumptions that hidden sectors that never reach thermal equilibrium in the early Universe are also inaccessible for the LHC. In other words, any particle that can be produced at the LHC must either have been in thermal equilibrium with the Standard Model at some point or must be produced via the decays of another hidden sector particle that has been in thermal equilibrium. To reach this conclusion, we parametrise the cross section connecting the Standard Model to the hidden sector in a very general way and use methods from linear programming to calculate the largest possible number of LHC events compatible with the requirement of non-thermalisation. We find that even the HL-LHC cannot possibly produce more than a few events with energy above 10 GeV involving states from a non-thermalised hidden sector.

Principles of proteome allocation are revealed using proteomic data and genome-scale models

PubMed Central

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; Ebrahim, Ali; Saunders, Michael A.; Palsson, Bernhard O.

2016-01-01

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thus represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. This flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models. PMID:27857205

Principles of proteome allocation are revealed using proteomic data and genome-scale models

DOE PAGES

Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.; ...

2016-11-18

Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the “generalist” (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions, prediction errors for growth rate and metabolic fluxes were 69% and 14% lower, respectively. The sector-constrained ME model thusmore » represents a generalist ME model reflecting both growth rate maximization and “hedging” against uncertain environments and stresses, as indicated by significant enrichment of these sectors for the general stress response sigma factor σS. Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally-related protein groups) as demonstrated here. Furthermore, this flexible formalism provides an accessible approach for narrowing the gap between the complexity captured by omics data and governing principles of proteome allocation described by systems-level models.« less

Impact of Climate Change on Energy Production, Distribution, and Consumption in Russia

NASA Astrophysics Data System (ADS)

Klimenko, V. V.; Klimenko, A. V.; Tereshin, A. G.; Fedotova, E. V.

2018-05-01

An assessment of the overall impact of the observed and expected climatic changes on energy production, distribution, and consumption in Russia is presented. Climate model results of various complexity and evaluation data on the vulnerability of various energy production sectors to climate change are presented. It is shown that, due to the increase of air temperature, the efficiency of electricity production at thermal and nuclear power plants declines. According to the climate model results, the production of electricity at TPPs and NPPs by 2050 could be reduced by 6 billion kW h due to the temperature increase. At the same time, as a result of simulation, the expected increase in the rainfall amount and river runoff in Russia by 2050 could lead to an increase in the output of HPP by 4-6% as compared with the current level, i.e., by 8 billion kW h. For energy transmission and distribution, the climate warming will mean an increase in transmission losses, which, according to estimates, may amount to approximately 1 billion kW h by 2050. The increase of air temperature in summer will require higher energy consumption for air conditioning, which will increase by approximately 6 billion kW h by 2050. However, in total, the optimal energy consumption in Russia, corresponding to the postindustrial level, will decrease by 2050 by approximately 150 billion kW h as a result of climate- induced changes. The maximum global warming impact is focused on the heat demand sector. As a result of a decrease in the heating degree-days by 2050, the need for space heating is expected to fall by 10-15%, which will cause a fuel conservation sufficient for generating approximately 140 billion kW h of electricity. Hence, a conclusion about the positive direct impact of climate change on the Russia's energy sector follows, which is constituted in the additional available energy resource of approximately 300 billion kW h per year.

Endocavity Ultrasound Hyperthermia for Locally Advanced Cervical Cancer: Patient-specific Modeling, Experimental Verification, and Combination with HDR Brachytherapy

NASA Astrophysics Data System (ADS)

Wootton, Jeffery; Chen, Xin; Prakash, Punit; Juang, Titania; Diederich, Chris

2010-03-01

The feasibility of targeted hyperthermia delivery by an intrauterine ultrasound applicator to patient-specific treatment volumes in conjunction with HDR brachytherapy was investigated using theory and experiment. 30 HDR brachytherapy treatment plans were inspected to define hyperthermia treatment volumes (HTVs) based on tumor and radiation target volumes. Several typical cases were imported into a patient-specific treatment planning platform that optimized acoustic output power from an endocavity multisectored tubular array to conform temperature and thermal dose to HTVs. Perfusion was within a clinical range of 0.5-3 kg m-3 s-1. Applicators were constructed with 1-3 elements at 6.5-8 MHz with 90°-360° sectoring and 25-35 mm heating length housed in a water-cooled PET catheter. Acoustic output was compared to heating in ex vivo tissue assessed with implanted thermometry. Radiation attenuation through the device was measured in an ionization chamber. The HTV extends 2-4 cm in diameter and 2-4 cm in length. The bladder and rectum can be within 10-12 mm. HTV targets can be covered with temperature clouds >41° and thermal dose t43>5 min with 45° C maximum temperature and rectal temperature <41.5° C. Sectored applicators preferentially direct energy laterally into the parametrium to limit heating of rectum and bladder. Interstitial brachytherapy catheters within the HTV could be used for thermal feedback during HT treatment. Temperature distributions in phantom show preferential heating within sectors and align well with acoustic output. Heating control along the device length and in angle is evident. A 4-6% reduction in radiation transmission through the transducers was observed, which could likely be compensated for in planning. Patient-specific modeling and experimental heating demonstrated 3-D conformal heating capabilities of endocavity ultrasound applicators.

Partially composite particle physics with and without supersymmetry

NASA Astrophysics Data System (ADS)

Kramer, Thomas A.

Theories in which the Standard Model fields are partially compositeness provide elegant and phenomenologically viable solutions to the Hierarchy Problem. In this thesis we will study types of models from two different perspectives. We first derive an effective field theory describing the interactions of the Standard Models fields with their lightest composite partners based on two weakly coupled sectors. Technically, via the AdS/CFT correspondence, our model is dual to a highly deconstructed theory with a single warped extra-dimension. This two sector theory provides a simplified approach to the phenomenology of this important class of theories. We then use this effective field theoretic approach to study models with weak scale accidental supersymmetry. Particularly, we will investigate the possibility that the Standard Model Higgs field is a member of a composite supersymmetric sector interacting weakly with the known Standard Model fields.

A model for water discharge based on energy consumption data (WATEN).

NASA Astrophysics Data System (ADS)

Moyano, María Carmen; Tornos, Lucía; Juana, Luis

2014-05-01

As the need for water conservation is becoming a major water concern, a lumped model entitled WATEN has been proposed to analyse the water balance in the B-XII Irrigation Sector of the Lower Guadalquivir Irrigated Area, one of the largest irrigated areas in Spain. The aim of this work is to approach the hydrological study of an irrigation district lacking of robust data in such a manner that the water balance is performed from less to more process complexity. WATEN parameters are the total and readily available moisture in the soil, a fix percentage for effective precipitation, and the irrigation efficiency. The Sector presents six different drainage pumping stations, with particular pumping groups and with no water flow measurement devices. Energy consumption depends on the working pumping stations and groups, and on the variable water level to discharge. Energy consumed in the drainage pumping stations has been used for calibration The study has relied on two monthly series of data: the volume of drainage obtained from the model and the energy consumed in the pumping stations. A double mass analysis has permitted the detection of data tendencies. The two resulting series of data have been compared to assess model performance, particularly the Pearson's product moment correlation coefficient and the Nash-Sutcliffe coefficient of efficiency, e2, determined for monthly data and for annual and monthly average data. For model calibration, we have followed a classical approach based on objective functions optimization, and a robust approach based on Markov chain Monte Carlo simulation process, driven in a similar manner to genetic algorithms, entitled Parameters Estimation on Driven Trials (PEDT), and aiming to reduce computational requirements. WATEN has been parameterised maintaining its physical and conceptual rationality. The study approach is outlined as a progressive introduction of data. In this manner, we can observe its effect on the studied objective functions, and visualize if new data adds significant improvements to model results. The model attained an average Nash-Sutcliffe coefficient e2~= 0.90 between based on energy drainage observations and estimated drainage discharge. The study has shown that the Sector crop evapotranspiration, is lower than the expected value in pristine conditions. This reduction would be more noticeable at the end of the summer months, attaining as far as a 40% reduction. Average drainage in the studied period, is about 3700 m3/ha/year. This methodology is thought to be the basis for similar worldwide studies comprising scarce-data irrigation districts with drainage discharge to receiving water bodies, and serve as a guide for future alike applications.

Spin-1 Kitaev model in one dimension

NASA Astrophysics Data System (ADS)

Sen, Diptiman; Shankar, R.; Dhar, Deepak; Ramola, Kabir

2010-11-01

We study a one-dimensional version of the Kitaev model on a ring of size N , in which there is a spin S>1/2 on each site and the Hamiltonian is J∑nSnxSn+1y . The cases where S is integer and half-odd integer are qualitatively different. We show that there is a Z2 -valued conserved quantity Wn for each bond (n,n+1) of the system. For integer S , the Hilbert space can be decomposed into 2N sectors, of unequal sizes. The number of states in most of the sectors grows as dN , where d depends on the sector. The largest sector contains the ground state, and for this sector, for S=1 , d=(5+1)/2 . We carry out exact diagonalization for small systems. The extrapolation of our results to large N indicates that the energy gap remains finite in this limit. In the ground-state sector, the system can be mapped to a spin-1/2 model. We develop variational wave functions to study the lowest energy states in the ground state and other sectors. The first excited state of the system is the lowest energy state of a different sector and we estimate its excitation energy. We consider a more general Hamiltonian, adding a term λ∑nWn , and show that this has gapless excitations in the range λ1c≤λ≤λ2c . We use the variational wave functions to study how the ground-state energy and the defect density vary near the two critical points λ1c and λ2c .

The Long-Term Cost to the UK NHS and Social Services of Different Durations of IV Thiamine (Vitamin B1) for Chronic Alcohol Misusers with Symptoms of Wernicke's Encephalopathy Presenting at the Emergency Department.

PubMed

Wilson, Edward C F; Stanley, George; Mirza, Zulfiquar

2016-04-01

Wernicke's encephalopathy (WE) is an acute neuropsychiatric condition caused by depleted intracellular thiamine, most commonly arising in chronic alcohol misusers, who may present to emergency departments (EDs) for a variety of reasons. Guidelines recommend a minimum 5-day course of intravenous (IV) thiamine in at-risk patients unless WE can be excluded. To estimate the cost impact on the UK public sector (NHS and social services) of a 5-day course of IV thiamine, vs a 2- and 10-day course, in harmful or dependent drinkers presenting to EDs. A Markov chain model compared expected prognosis of patients under alternative admission strategies over 35 years. Model inputs were derived from a prospective cohort study, expert opinion via structured elicitation and NHS costing databases. Costs (2012/2013 price year) were discounted at 3.5 %. Increasing treatment from 2 to 5 days increased acute care costs but reduced the probability of disease progression and thus reduced the expected net costs by GBP87,000 per patient (95 % confidence interval GBP19,300 to GBP172,300) over 35 years. Increasing length of stay to optimize IV thiamine replacement will place additional strain on acute care but has potential UK public sector cost savings. Social services and the NHS should explore collaborations to realise both the health benefits to patients and savings to the public purse.

Agricultural Water Use under Global Change

NASA Astrophysics Data System (ADS)

Zhu, T.; Ringler, C.; Rosegrant, M. W.

2008-12-01

Irrigation is by far the single largest user of water in the world and is projected to remain so in the foreseeable future. Globally, irrigated agricultural land comprises less than twenty percent of total cropland but produces about forty percent of the world's food. Increasing world population will require more food and this will lead to more irrigation in many areas. As demands increase and water becomes an increasingly scarce resource, agriculture's competition for water with other economic sectors will be intensified. This water picture is expected to become even more complex as climate change will impose substantial impacts on water availability and demand, in particular for agriculture. To better understand future water demand and supply under global change, including changes in demographic, economic and technological dimensions, the water simulation module of IMPACT, a global water and food projection model developed at the International Food Policy Research Institute, is used to analyze future water demand and supply in agricultural and several non-agricultural sectors using downscaled GCM scenarios, based on water availability simulation done with a recently developed semi-distributed global hydrological model. Risk analysis is conducted to identify countries and regions where future water supply reliability for irrigation is low, and food security may be threatened in the presence of climate change. Gridded shadow values of irrigation water are derived for global cropland based on an optimization framework, and they are used to illustrate potential irrigation development by incorporating gridded water availability and existing global map of irrigation areas.

AdS and stabilized extra dimensions in multi-dimensional gravitational models with nonlinear scalar curvature terms R-1 and R4

NASA Astrophysics Data System (ADS)

Günther, Uwe; Zhuk, Alexander; Bezerra, Valdir B.; Romero, Carlos

2005-08-01

We study multi-dimensional gravitational models with scalar curvature nonlinearities of types R-1 and R4. It is assumed that the corresponding higher dimensional spacetime manifolds undergo a spontaneous compactification to manifolds with a warped product structure. Special attention has been paid to the stability of the extra-dimensional factor spaces. It is shown that for certain parameter regions the systems allow for a freezing stabilization of these spaces. In particular, we find for the R-1 model that configurations with stabilized extra dimensions do not provide a late-time acceleration (they are AdS), whereas the solution branch which allows for accelerated expansion (the dS branch) is incompatible with stabilized factor spaces. In the case of the R4 model, we obtain that the stability region in parameter space depends on the total dimension D = dim(M) of the higher dimensional spacetime M. For D > 8 the stability region consists of a single (absolutely stable) sector which is shielded from a conformal singularity (and an antigravity sector beyond it) by a potential barrier of infinite height and width. This sector is smoothly connected with the stability region of a curvature-linear model. For D < 8 an additional (metastable) sector exists which is separated from the conformal singularity by a potential barrier of finite height and width so that systems in this sector are prone to collapse into the conformal singularity. This second sector is not smoothly connected with the first (absolutely stable) one. Several limiting cases and the possibility of inflation are discussed for the R4 model.

Neogene-Quaternary evolution of the offshore sector of the Southern Apennines accretionary wedge, Gulf of Taranto, Italy

NASA Astrophysics Data System (ADS)

Teofilo, G.; Antoncecchi, I.; Caputo, R.

2018-07-01

Southern Apennines represent a collisional orogenic belt whose compressional regime is commonly assumed to have ceased during Middle Quaternary. On the other hand, to the south the Calabria Arc is still characterized by subduction and the principal aim of the present research is to shed some light on the space and time transition from the ceased collision to the active subduction. Accordingly, we investigated the offshore sector of the Southern Apennines accretionary wedge, corresponding to the Taranto Gulf. To gain insights into the offshore accretionary wedge, we reconstructed a 3D geological and tectonic model by interpreting a grid of 40 seismic reflection lines (1100 km, 80 intersections), within an area of ca. 104 km2, calibrated with 17 wells. The geometric and chronological constraints allow documenting a systematic Messinian-Quaternary thrust migration from internal towards external sectors of the wedge. The migrating deformational process was essentially associated with a leading-imbricate thrust system with a general NE-younging direction, where we could recognize and distinguish some major advancing phases characterized by alternating fast thrust propagation events and strain accumulation periods within the wedge. This process is well emphasized by the jump of the foredeep and piggy-back basins. The NE-wards wedge migration was also associated with a lithospheric-scale flexural folding that generated a set of normal faults striking parallel to the coeval thrusts, likely reactivating optimally oriented structures inherited from Mesozoic events. Finally, a persisting thrust activity up to the latest Quaternary and possibly up to Present in correspondence of the externalmost sector of the accretionary wedge has been documented and explained in terms of strain partitioning in the frame of a recent oblique convergence. The results of this research have possible implications for the seismic hazard assessment of the broader region which is possibly greater than previously assumed.

Using morbidity and income data to forecast the variation of growth and employment in the oral healthcare sector.

PubMed

Ostwald, Dennis A; Klingenberger, David

2016-12-01

The perception of the health sector from an economic policy point of view is changing. In the past, health expenditure was mostly seen as a "cost" item, probably because many medical treatments are covered by public health insurance. However, policymakers are increasingly realizing that a growing health sector may be quite beneficial for an economy. It creates employment opportunities and it is relatively resistant to the fluctuations of the business cycle. Input-output analysis could be a useful tool to study the structural change resulting from the growth of the health sector. This paper quantifies for the first time the economic significance of the oral healthcare sector as a component of the German healthcare sector as a whole. The current data for the healthcare sector comes from Health Satellite Accounts, which while comprehensive do fail to answer important questions due to not incorporating certain sectors such as the oral healthcare sector. Therefore on the basis of the Health Satellite Account a specific Satellite Account for the oral healthcare sector is created by using billing data as well as epidemiological data, provided by several dental associations and the Institute of German Dentists. Based on this added information, gross value added data and the number of employees in the oral healthcare sector are computed. Gross value added in 2010 amounted to €13.4 billion, with around €4 billion being attributable to the secondary oral healthcare market; the market for solely out-of-pocket payments. In a second step the paper develops a model to forecast oral healthcare sector growth based on various explanatory variables such as demographic change, take-up behaviour, medical-technical progress, oral morbidity, aggregated supply (collective dental treatment times) as well as income levels and distribution, where the latter two are considered to be of particular importance. According to this model, by 2030 gross value added in the oral healthcare sector will amount to €15.9 million, which corresponds to a 19.2 % increase. The secondary oral healthcare market will be the key to this increase since the model predicts a disproportionately high growth of 60.3 % bringing the total to €6.3 million gross value added in 2030.

Environmental tipping points significantly affect the cost-benefit assessment of climate policies.

PubMed

Cai, Yongyang; Judd, Kenneth L; Lenton, Timothy M; Lontzek, Thomas S; Narita, Daiju

2015-04-14

Most current cost-benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost-benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost-benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost-benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.

Environmental tipping points significantly affect the cost−benefit assessment of climate policies

PubMed Central

Cai, Yongyang; Judd, Kenneth L.; Lenton, Timothy M.; Lontzek, Thomas S.; Narita, Daiju

2015-01-01

Most current cost−benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost−benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost−benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost−benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change. PMID:25825719

Improved Weather and Power Forecasts for Energy Operations - the German Research Project EWeLiNE

NASA Astrophysics Data System (ADS)

Lundgren, Kristina; Siefert, Malte; Hagedorn, Renate; Majewski, Detlev

2014-05-01

The German energy system is going through a fundamental change. Based on the energy plans of the German federal government, the share of electrical power production from renewables should increase to 35% by 2020. This means that, in the near future at certain times renewable energies will provide a major part of Germany's power production. Operating a power supply system with a large share of weather-dependent power sources in a secure way requires improved power forecasts. One of the most promising strategies to improve the existing wind power and PV power forecasts is to optimize the underlying weather forecasts and to enhance the collaboration between the meteorology and energy sectors. Deutscher Wetterdienst addresses these challenges in collaboration with Fraunhofer IWES within the research project EWeLiNE. The overarching goal of the project is to improve the wind and PV power forecasts by combining improved power forecast models and optimized weather forecasts. During the project, the numerical weather prediction models COSMO-DE and COSMO-DE-EPS (Ensemble Prediction System) by Deutscher Wetterdienst will be generally optimized towards improved wind power and PV forecasts. For instance, it will be investigated whether the assimilation of new types of data, e.g. power production data, can lead to improved weather forecasts. With regard to the probabilistic forecasts, the focus is on the generation of ensembles and ensemble calibration. One important aspect of the project is to integrate the probabilistic information into decision making processes by developing user-specified products. In this paper we give an overview of the project and present first results.

Does the Wage Gap between Private and Public Sectors Encourage Political Corruption?

PubMed Central

Podobnik, Boris; Vukovic, Vuk; Stanley, H. Eugene

2015-01-01

We present a dynamic network model of corrupt and noncorrupt employees representing two states in the public and private sector. Corrupt employees are more connected to one another and are less willing to change their attitudes regarding corruption than noncorrupt employees. This behavior enables them to prevail and become the majority in the workforce through a first-order phase transition even though they initially represented a minority. In the model, democracy—understood as the principle of majority rule—does not create corruption, but it serves as a mechanism that preserves corruption in the long run. The motivation for our network model is a paradox that exists on the labor market. Although economic theory indicates that higher risk investments should lead to larger rewards, in many developed and developing countries workers in lower-risk public sector jobs are paid more than workers in higher-risk private sector jobs. To determine the long-run sustainability of this economic paradox, we study data from 28 EU countries and find that the public sector wage premium increases with the level of corruption. PMID:26495847

Does the Wage Gap between Private and Public Sectors Encourage Political Corruption?

PubMed

Podobnik, Boris; Vukovic, Vuk; Stanley, H Eugene

2015-01-01

We present a dynamic network model of corrupt and noncorrupt employees representing two states in the public and private sector. Corrupt employees are more connected to one another and are less willing to change their attitudes regarding corruption than noncorrupt employees. This behavior enables them to prevail and become the majority in the workforce through a first-order phase transition even though they initially represented a minority. In the model, democracy-understood as the principle of majority rule-does not create corruption, but it serves as a mechanism that preserves corruption in the long run. The motivation for our network model is a paradox that exists on the labor market. Although economic theory indicates that higher risk investments should lead to larger rewards, in many developed and developing countries workers in lower-risk public sector jobs are paid more than workers in higher-risk private sector jobs. To determine the long-run sustainability of this economic paradox, we study data from 28 EU countries and find that the public sector wage premium increases with the level of corruption.

Universal industrial sectors integrated solutions module for the pulp and paper industry.

PubMed

Bhander, Gurbakhash; Jozewicz, Wojciech

2017-09-01

The U.S. is the world's second-leading producer of pulp and paper products after China. Boilers, recovery furnaces, and lime kilns are the dominant sources of emissions from pulp and paper mills, collectively accounting for more than 99 % of the SO 2 , almost 96 % of the NO X , and more than 85 % of the particulate matter (PM) emitted to the air from this sector in the U.S. The process of developing industrial strategies for managing emissions can be made efficient, and the resulting strategies more cost-effective, through the application of modeling that accounts for relevant technical, environmental and economic factors. Accordingly, the United States Environmental Protection Agency is developing the Universal Industrial Sectors Integrated Solutions module for the Pulp and Paper Industry (UISIS-PNP). It can be applied to evaluate emissions and economic performance of pulp and paper mills separately under user-defined pollution control strategies. In this paper, we discuss the UISIS-PNP module, the pulp and paper market and associated air emissions from the pulp and paper sector. After illustrating the sector-based multi-product modeling structure, a hypothetical example is presented to show the engineering and economic considerations involved in the emission-reduction modeling of the pulp and paper sector in the U.S.

Raising Public Awareness: The Role of the Household Sector in Mitigating Climate Change

PubMed Central

Lin, Shis-Ping

2015-01-01

In addition to greenhouse gas emissions from the industrial, transportation and commercial sectors, emissions from the household sector also contribute to global warming. By examining residents of Taiwan (N = 236), this study aims to reveal the factors that influence households’ intention to purchase energy-efficient appliances. The assessment in this study is based on the theory of planned behavior (TPB), and perceived benefit or cost (BOC) is introduced as an independent variable in the proposed efficiency action toward climate change (ECC) model. According to structural equation modeling, most of the indicators presented a good fit to the corresponding ECC model constructs. The analysis indicated that BOC is a good complementary variable to the TPB, as the ECC model explained 61.9% of the variation in intention to purchase energy-efficient appliances, which was higher than that explained by the TPB (58.4%). This result indicates that the ECC model is superior to the TPB. Thus, the strategy of promoting energy-efficient appliances in the household sector should emphasize global warming and include the concept of BOC. PMID:26492262

Raising Public Awareness: The Role of the Household Sector in Mitigating Climate Change.

PubMed

Lin, Shis-Ping

2015-10-20

In addition to greenhouse gas emissions from the industrial, transportation and commercial sectors, emissions from the household sector also contribute to global warming. By examining residents of Taiwan (N = 236), this study aims to reveal the factors that influence households' intention to purchase energy-efficient appliances. The assessment in this study is based on the theory of planned behavior (TPB), and perceived benefit or cost (BOC) is introduced as an independent variable in the proposed efficiency action toward climate change (ECC) model. According to structural equation modeling, most of the indicators presented a good fit to the corresponding ECC model constructs. The analysis indicated that BOC is a good complementary variable to the TPB, as the ECC model explained 61.9% of the variation in intention to purchase energy-efficient appliances, which was higher than that explained by the TPB (58.4%). This result indicates that the ECC model is superior to the TPB. Thus, the strategy of promoting energy-efficient appliances in the household sector should emphasize global warming and include the concept of BOC.

Water resources planning and management : A stochastic dual dynamic programming approach

NASA Astrophysics Data System (ADS)

Goor, Q.; Pinte, D.; Tilmant, A.

2008-12-01

Allocating water between different users and uses, including the environment, is one of the most challenging task facing water resources managers and has always been at the heart of Integrated Water Resources Management (IWRM). As water scarcity is expected to increase over time, allocation decisions among the different uses will have to be found taking into account the complex interactions between water and the economy. Hydro-economic optimization models can capture those interactions while prescribing efficient allocation policies. Many hydro-economic models found in the literature are formulated as large-scale non linear optimization problems (NLP), seeking to maximize net benefits from the system operation while meeting operational and/or institutional constraints, and describing the main hydrological processes. However, those models rarely incorporate the uncertainty inherent to the availability of water, essentially because of the computational difficulties associated stochastic formulations. The purpose of this presentation is to present a stochastic programming model that can identify economically efficient allocation policies in large-scale multipurpose multireservoir systems. The model is based on stochastic dual dynamic programming (SDDP), an extension of traditional SDP that is not affected by the curse of dimensionality. SDDP identify efficient allocation policies while considering the hydrologic uncertainty. The objective function includes the net benefits from the hydropower and irrigation sectors, as well as penalties for not meeting operational and/or institutional constraints. To be able to implement the efficient decomposition scheme that remove the computational burden, the one-stage SDDP problem has to be a linear program. Recent developments improve the representation of the non-linear and mildly non- convex hydropower function through a convex hull approximation of the true hydropower function. This model is illustrated on a cascade of 14 reservoirs on the Nile river basin.

European scale climate information services for water use sectors

NASA Astrophysics Data System (ADS)

van Vliet, Michelle T. H.; Donnelly, Chantal; Strömbäck, Lena; Capell, René; Ludwig, Fulco

2015-09-01

This study demonstrates a climate information service for pan-European water use sectors that are vulnerable to climate change induced hydrological changes, including risk and safety (disaster preparedness), agriculture, energy (hydropower and cooling water use for thermoelectric power) and environment (water quality). To study the climate change impacts we used two different hydrological models forced with an ensemble of bias-corrected general circulation model (GCM) output for both the lowest (2.6) and highest (8.5) representative concentration pathways (RCP). Selected indicators of water related vulnerability for each sector were then calculated from the hydrological model results. Our results show a distinct north-south divide in terms of climate change impacts; in the south the water availability will reduce while in the north water availability will increase. Across different climate models precipitation and streamflow increase in northern Europe and decrease in southern Europe, but the latitude at which this change occurs varies depending on the GCM. Hydrological extremes are increasing over large parts of Europe. The agricultural sector will be affected by reduced water availability (in the south) and increased drought. Both streamflow and soil moistures droughts are projected to increase in most parts of Europe except in northern Scandinavia and the Alps. The energy sector will be affected by lower hydropower potential in most European countries and reduced cooling water availability due to higher water temperatures and reduced summer river flows. Our results show that in particular in the Mediterranean the pressures are high because of increasing drought which will have large impacts on both the agriculture and energy sectors. In France and Italy this is combined with increased flood hazards. Our results show important impacts of climate change on European water use sectors indicating a clear need for adaptation.

Higgs boson from the metastable supersymmetric breaking sector

NASA Astrophysics Data System (ADS)

Bai, Yang; Fan, Jiji; Han, Zhenyu

2007-09-01

We construct a calculable model of electroweak symmetry breaking in which the Higgs doublet emerges from the metastable SUSY breaking sector as a pseudo Nambu-Goldstone boson. The Higgs boson mass is further protected by the little Higgs mechanism, and naturally suppressed by a two-loop factor from the SUSY breaking scale of 10 TeV. Gaugino and sfermion masses arise from standard gauge mediation, but the Higgsino obtains a tree-level mass at the SUSY breaking scale. At 1 TeV, aside from new gauge bosons and fermions similar to other little Higgs models and their superpartners, our model predicts additional electroweak triplets and doublets from the SUSY breaking sector.

The dual economy in long-run development

PubMed Central

2013-01-01

A salient feature of developing economies is the coexistence of a modern commercial sector alongside a traditional subsistence sector—the dual economy. The apparent differences in productivity between sectors imply substantial losses in aggregate productivity. Existing theories of the dual economy rely on exogenous price distortions, and cannot explain why or if these distortions evolve over the course of development. This paper provides a model of the dual economy in which the productivity differences arise endogenously because of a non-separability between the value of market and non-market time in the traditional sector. Incorporating endogenous fertility, the model then demonstrates how a dual economy will originate, persist, and eventually disappear within a unified growth framework. An implication is that traditional sector productivity growth will exacerbate the inefficiencies of a dual economy and produce slower overall growth than will modern sector productivity improvements. PMID:23946556

One Health: a perspective from the human health sector.

PubMed

Kakkar, M; Hossain, S S; Abbas, S S

2014-08-01

Despite emerging consensus that the One Health concept involves multiple stakeholders, the human health sector has continued to view it from a predominantly human health security perspective. It has often ignored the concerns of other sectors, e.g. concerns that relate to trade, commerce, livelihoods and sustainable development, all of which are important contributors to societal well-being. In the absence of a culture of collaboration, clear One Health goals, conceptual clarity and operating frameworks, this disconnect between human health and One Health efforts has often impeded the translation of One Health from concept to reality, other than during emergency situations. If there are to be effective and sustainable One Health partnerships we must identify clear operating principles that allow flexible approaches to intersectoral collaborations. To convince technical experts and political leaders in the human health sector of the importance of intersectoral cooperation, and to make the necessary structural adjustments, we need examples of best practice models and trans-sectoral methods for measuring the risks, burden and costs across sectors. Informal collaborations between researchers and technical experts will play a decisive role in developing these methods and models and instilling societal well-being into the human health sector's view of One Health.

Mining Deployment Optimization

NASA Astrophysics Data System (ADS)

Čech, Jozef

2016-09-01

The deployment problem, researched primarily in the military sector, is emerging in some other industries, mining included. The principal decision is how to deploy some activities in space and time to achieve desired outcome while complying with certain requirements or limits. Requirements and limits are on the side constraints, while minimizing costs or maximizing some benefits are on the side of objectives. A model with application to mining of polymetallic deposit is presented. To obtain quick and immediate decision solutions for a mining engineer with experimental possibilities is the main intention of a computer-based tool. The task is to determine strategic deployment of mining activities on a deposit, meeting planned output from the mine and at the same time complying with limited reserves and haulage capacities. Priorities and benefits can be formulated by the planner.

Dark matter cosmic string in the gravitational field of a black hole

NASA Astrophysics Data System (ADS)

Nakonieczny, Łukasz; Nakonieczna, Anna; Rogatko, Marek

2018-03-01

We examined analytically and proposed a numerical model of an Abelian Higgs dark matter vortex in the spacetime of a stationary axisymmetric Kerr black hole. In analytical calculations the dark matter sector was modeled by an addition of a U(1)-gauge field coupled to the visible sector. The backreaction analysis revealed that the impact of the dark vortex presence is far more complicated than causing only a deficit angle. The vortex causes an ergosphere shift and the event horizon velocity is also influenced by its presence. These phenomena are more significant than in the case of a visible vortex sector. The area of the event horizon of a black hole is diminished and this decline is larger in comparison to the Kerr black hole with an Abelian Higgs vortex case. After analyzing the gravitational properties for the general setup, we focused on the subset of models that are motivated by particle physics. We retained the Abelian Higgs model as a description of the dark matter sector (this sector contained a heavy dark photon and an additional complex scalar) and added a real scalar representing the real component of the Higgs doublet in the unitary gauge, as well as an additional U(1)-gauge field representing an ordinary electromagnetic field. Moreover, we considered two coupling channels between the visible and dark sectors, which were the kinetic mixing between the gauge fields and a quartic coupling between the scalar fields. After solving the equations of motion for the matter fields numerically we analyzed properties of the cosmic string in the dark matter sector and its influence on the visible sector fields that are directly coupled to it. We found out that the presence of the cosmic string induced spatial variation in the vacuum expectation value of the Higgs field and a nonzero electromagnetic field around the black hole.

Dark matter phenomenology of SM and enlarged Higgs sectors extended with vector-like leptons

NASA Astrophysics Data System (ADS)

Angelescu, Andrei; Arcadi, Giorgio

2017-07-01

We will investigate the scenario in which the Standard Model (SM) Higgs sector and its two-doublet extension (called the Two Higgs Doublet Model or 2HDM) are the "portal" for the interactions between the Standard Model and a fermionic Dark Matter (DM) candidate. The latter is the lightest stable neutral particle of a family of vector-like leptons (VLLs). We will provide an extensive overview of this scenario combining the constraints coming purely from DM phenomenology with more general constraints like Electroweak Precision Test (EWPT) as well as with collider searches. In the case that the new fermionic sector interacts with the SM Higgs sector, constraints from DM phenomenology force the new states to lie above the TeV scale. This requirement is relaxed in the case of 2HDM. Nevertheless, strong constraints coming from EWPTs and the Renormalization Group Equations (RGEs) limit the impact of VLFs on collider phenomenology.

Dark matter phenomenology of SM and enlarged Higgs sectors extended with vector-like leptons.

PubMed

Angelescu, Andrei; Arcadi, Giorgio

2017-01-01

We will investigate the scenario in which the Standard Model (SM) Higgs sector and its two-doublet extension (called the Two Higgs Doublet Model or 2HDM) are the "portal" for the interactions between the Standard Model and a fermionic Dark Matter (DM) candidate. The latter is the lightest stable neutral particle of a family of vector-like leptons (VLLs). We will provide an extensive overview of this scenario combining the constraints coming purely from DM phenomenology with more general constraints like Electroweak Precision Test (EWPT) as well as with collider searches. In the case that the new fermionic sector interacts with the SM Higgs sector, constraints from DM phenomenology force the new states to lie above the TeV scale. This requirement is relaxed in the case of 2HDM. Nevertheless, strong constraints coming from EWPTs and the Renormalization Group Equations (RGEs) limit the impact of VLFs on collider phenomenology.

Large scale hydro-economic modelling for policy support

NASA Astrophysics Data System (ADS)

de Roo, Ad; Burek, Peter; Bouraoui, Faycal; Reynaud, Arnaud; Udias, Angel; Pistocchi, Alberto; Lanzanova, Denis; Trichakis, Ioannis; Beck, Hylke; Bernhard, Jeroen

2014-05-01

To support European Union water policy making and policy monitoring, a hydro-economic modelling environment has been developed to assess optimum combinations of water retention measures, water savings measures, and nutrient reduction measures for continental Europe. This modelling environment consists of linking the agricultural CAPRI model, the LUMP land use model, the LISFLOOD water quantity model, the EPIC water quality model, the LISQUAL combined water quantity, quality and hydro-economic model, and a multi-criteria optimisation routine. With this modelling environment, river basin scale simulations are carried out to assess the effects of water-retention measures, water-saving measures, and nutrient-reduction measures on several hydro-chemical indicators, such as the Water Exploitation Index (WEI), Nitrate and Phosphate concentrations in rivers, the 50-year return period river discharge as an indicator for flooding, and economic losses due to water scarcity for the agricultural sector, the manufacturing-industry sector, the energy-production sector and the domestic sector, as well as the economic loss due to flood damage. Recently, this model environment is being extended with a groundwater model to evaluate the effects of measures on the average groundwater table and available resources. Also, water allocation rules are addressed, while having environmental flow included as a minimum requirement for the environment. Economic functions are currently being updated as well. Recent development and examples will be shown and discussed, as well as open challenges.

The Impact of Individual Anthropogenic Emissions Sectors on the Global Burden of Human Mortality due to Ambient Air Pollution.

PubMed

Silva, Raquel A; Adelman, Zachariah; Fry, Meridith M; West, J Jason

2016-11-01

Exposure to ozone and fine particulate matter (PM2.5) can cause adverse health effects, including premature mortality due to cardiopulmonary diseases and lung cancer. Recent studies quantify global air pollution mortality but not the contribution of different emissions sectors, or they focus on a specific sector. We estimated the global mortality burden of anthropogenic ozone and PM2.5, and the impact of five emissions sectors, using a global chemical transport model at a finer horizontal resolution (0.67° × 0.5°) than previous studies. We performed simulations for 2005 using the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), zeroing out all anthropogenic emissions and emissions from specific sectors (All Transportation, Land Transportation, Energy, Industry, and Residential and Commercial). We estimated premature mortality using a log-linear concentration-response function for ozone and an integrated exposure-response model for PM2.5. We estimated 2.23 (95% CI: 1.04, 3.33) million deaths/year related to anthropogenic PM2.5, with the highest mortality in East Asia (48%). The Residential and Commercial sector had the greatest impact globally-675 (95% CI: 428, 899) thousand deaths/year-and in most regions. Land Transportation dominated in North America (32% of total anthropogenic PM2.5 mortality), and it had nearly the same impact (24%) as Residential and Commercial (27%) in Europe. Anthropogenic ozone was associated with 493 (95% CI: 122, 989) thousand deaths/year, with the Land Transportation sector having the greatest impact globally (16%). The contributions of emissions sectors to ambient air pollution-related mortality differ among regions, suggesting region-specific air pollution control strategies. Global sector-specific actions targeting Land Transportation (ozone) and Residential and Commercial (PM2.5) sectors would particularly benefit human health. Citation: Silva RA, Adelman Z, Fry MM, West JJ. 2016. The impact of individual anthropogenic emissions sectors on the global burden of human mortality due to ambient air pollution. Environ Health Perspect 124:1776-1784; http://dx.doi.org/10.1289/EHP177.

The Impact of Individual Anthropogenic Emissions Sectors on the Global Burden of Human Mortality due to Ambient Air Pollution

PubMed Central

Silva, Raquel A.; Adelman, Zachariah; Fry, Meridith M.; West, J. Jason

2016-01-01

Background: Exposure to ozone and fine particulate matter (PM2.5) can cause adverse health effects, including premature mortality due to cardiopulmonary diseases and lung cancer. Recent studies quantify global air pollution mortality but not the contribution of different emissions sectors, or they focus on a specific sector. Objectives: We estimated the global mortality burden of anthropogenic ozone and PM2.5, and the impact of five emissions sectors, using a global chemical transport model at a finer horizontal resolution (0.67° × 0.5°) than previous studies. Methods: We performed simulations for 2005 using the Model for Ozone and Related Chemical Tracers, version 4 (MOZART-4), zeroing out all anthropogenic emissions and emissions from specific sectors (All Transportation, Land Transportation, Energy, Industry, and Residential and Commercial). We estimated premature mortality using a log-linear concentration–response function for ozone and an integrated exposure–response model for PM2.5. Results: We estimated 2.23 (95% CI: 1.04, 3.33) million deaths/year related to anthropogenic PM2.5, with the highest mortality in East Asia (48%). The Residential and Commercial sector had the greatest impact globally—675 (95% CI: 428, 899) thousand deaths/year—and in most regions. Land Transportation dominated in North America (32% of total anthropogenic PM2.5 mortality), and it had nearly the same impact (24%) as Residential and Commercial (27%) in Europe. Anthropogenic ozone was associated with 493 (95% CI: 122, 989) thousand deaths/year, with the Land Transportation sector having the greatest impact globally (16%). Conclusions: The contributions of emissions sectors to ambient air pollution–related mortality differ among regions, suggesting region-specific air pollution control strategies. Global sector-specific actions targeting Land Transportation (ozone) and Residential and Commercial (PM2.5) sectors would particularly benefit human health. Citation: Silva RA, Adelman Z, Fry MM, West JJ. 2016. The impact of individual anthropogenic emissions sectors on the global burden of human mortality due to ambient air pollution. Environ Health Perspect 124:1776–1784; http://dx.doi.org/10.1289/EHP177 PMID:27177206

COMPUTER MODEL TECHNOLOGY TRANSFER IN THE UNITED STATES

EPA Science Inventory

Computer-based mathematical models for urban water resources planning, management and design are widely used by engineers and planners in both the public and private sectors. In the United States, the majority of the users are in the private (consulting) sector, yet most of the m...

[Demographic pressure, "informal sector" and technological choices in Third World countries].

PubMed

Hugon, P

1983-01-01

Trisectorial models of economic functioning have been proposed to replace the dualistic models that proved incapable of illuminating postwar employment trends in developing countries. The new models propose 3 sectors: the subsistence sector, where average productivity corresponds to the subsistence minimum and which is thus incapable of generating a surplus for savings; the intermediate sector, weakly capitalistic, characterized by the absence of a permanent salaried work force or codified labor relations, in which precariousness of employment and the exploitation of specific social relations allow a low wage rate, with a concommitant mode of regulation that largely escapes state control; and the intensely capitalistic sector, with a salaried work force, codified labor relations, existence of administered prices, various state subventions and protections and a monopolistic type of regulation. The 3 sectors are described in greater detail and represented graphically, along with a critique of the limitations of most studies employing a trisectorial perspective. A study of the impact of demographic pressure at different levels of technology embedded in specific sociohistoric systems follows. The final section contains an analysis of 3 types of effects which may mediate the role of demographic pressure in the choice of technologies: effects of demographic pressure on structures of production and consumption, on segments of the labor force, and on involutive and evolutive processes. It is argued that the links between demographic pressure, technologic choices, and the productive sector can only be analyzed in specific social systems.

U.S. electric power sector transitions required to achieve 80% reductions in economy-wide greenhouse gas emissions: Results based on a state-level model of the U.S. energy system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Iyer, Gokul C.; Clarke, Leon E.; Edmonds, James A.

The United States has articulated a deep decarbonization strategy for achieving a reduction in economy-wide greenhouse gas (GHG) emissions of 80% below 2005 levels by 2050. Achieving such deep emissions reductions will entail a major transformation of the energy system and of the electric power sector in particular. , This study uses a detailed state-level model of the U.S. energy system embedded within a global integrated assessment model (GCAM-USA) to demonstrate pathways for the evolution of the U.S. electric power sector that achieve 80% economy-wide reductions in GHG emissions by 2050. The pathways presented in this report are based onmore » feedback received during a workshop of experts organized by the U.S. Department of Energy’s Office of Energy Policy and Systems Analysis. Our analysis demonstrates that achieving deep decarbonization by 2050 will require substantial decarbonization of the electric power sector resulting in an increase in the deployment of zero-carbon and low-carbon technologies such as renewables and carbon capture utilization and storage. The present results also show that the degree to which the electric power sector will need to decarbonize and low-carbon technologies will need to deploy depends on the nature of technological advances in the energy sector, the ability of end-use sectors to electrify and level of electricity demand.« less

Decision support for the management of water resources at Sub-middle of the São Francisco river basin in Brazil using integrated hydro-economic modeling and scenarios for land use changes

NASA Astrophysics Data System (ADS)

Moraes, M. G. A.; Souza da Silva, G.

2016-12-01

Hydro-economic models can measure the economic effects of different operating rules, environmental restrictions, ecosystems services, technical constraints and institutional constraints. Furthermore, water allocation can be improved by considering economical criteria's. Likewise, climate and land use change can be analyzed to provide resilience. We developed and applied a hydro-economic optimization model to determine the optimal water allocation of main users in the Lower-middle São Francisco River Basin in Northeast (NE) Brazil. The model uses demand curves for the irrigation projects, small farmers and human supply, rather than fixed requirements for water resources. This study analyzed various constraints and operating alternatives for the installed hydropower dams in economic terms. A seven-year period (2000-2006) with water scarcity in the past has been selected to analyze the water availability and the associated optimal economic water allocation. The used constraints are technical, socioeconomic and environmental. The economically impacts of scenarios like prioritizing human consumption, impacts of the implementation of the São Francisco river transposition, human supply without high distribution losses, environmental hydrographs, forced reservoir level control, forced reduced reservoir capacity, alteration of lower flow restriction were analyzed. The results in this period show that scarcity costs related ecosystem service and environmental constraints are significant, and have major impacts (increase of scarcity cost) for consumptive users like irrigation projects. In addition, institutional constraints such as prioritizing human supply, minimum release limits downstream of the reservoirs and the implementation of the transposition project impact the costs and benefits of the two main economic sectors (irrigation and power generation) in the region of the Lower-middle of the São Francisco river basin. Scarcity costs for irrigation users generally increase more (in percentage terms) than the other users associated to environmental and institutional constraints.

Optimization modeling of U.S. renewable electricity deployment using local input variables

NASA Astrophysics Data System (ADS)

Bernstein, Adam

For the past five years, state Renewable Portfolio Standard (RPS) laws have been a primary driver of renewable electricity (RE) deployments in the United States. However, four key trends currently developing: (i) lower natural gas prices, (ii) slower growth in electricity demand, (iii) challenges of system balancing intermittent RE within the U.S. transmission regions, and (iv) fewer economical sites for RE development, may limit the efficacy of RPS laws over the remainder of the current RPS statutes' lifetime. An outsized proportion of U.S. RE build occurs in a small number of favorable locations, increasing the effects of these variables on marginal RE capacity additions. A state-by-state analysis is necessary to study the U.S. electric sector and to generate technology specific generation forecasts. We used LP optimization modeling similar to the National Renewable Energy Laboratory (NREL) Renewable Energy Development System (ReEDS) to forecast RE deployment across the 8 U.S. states with the largest electricity load, and found state-level RE projections to Year 2031 significantly lower than thoseimplied in the Energy Information Administration (EIA) 2013 Annual Energy Outlook forecast. Additionally, the majority of states do not achieve their RPS targets in our forecast. Combined with the tendency of prior research and RE forecasts to focus on larger national and global scale models, we posit that further bottom-up state and local analysis is needed for more accurate policy assessment, forecasting, and ongoing revision of variables as parameter values evolve through time. Current optimization software eliminates much of the need for algorithm coding and programming, allowing for rapid model construction and updating across many customized state and local RE parameters. Further, our results can be tested against the empirical outcomes that will be observed over the coming years, and the forecast deviation from the actuals can be attributed to discrete parameter variances.

Enterprise Funds: Evolving Models for Private Sector Development in Central and Eastern Europe

DTIC Science & Technology

1994-03-01

and Hungary to help private sector development in those countries. Enterprise funds for the former Czech and Slovak Federal Republic were created in...institutions are reluctant to invest. The enterprise funds are also to provide technical assistance for private sector development in the host country...Strategies of loan programs developed. Poland and Hungary had taken some steps toward the creation of a private sector before the collapse of communism

Economic base determination and influence of several variables against contributions percentage of the GDRP in Aceh Besar district

NASA Astrophysics Data System (ADS)

Andayani, Keumala; Miftahuddin

2018-05-01

The percentage contribution of Gross Regional Domestic Product (GRDP) in Aceh Besar district is influenced by several leading sectors, such as agriculture, building sector, trade, hotel and restaurant sector, transport and communications, financial sector, leasing and business services, and services sector. Based on the use of Location Quotient (LQ) method and multiple regression model, the effect of labor variables and population to Gross Regional Domestic Product by 2000 constant prices for agriculture and trade. For each addition of one workforce in the trading sector, the trade sector contribution will increase by 0.000014157%. Thus, the trade sector contribution will increase by 0.0000013786% in every addition of one soul of the population. Whereas, for every addition of one human resource in the agricultural sector will be reduced by 0.0002%. In other words, for each addition of one soul of the population will reduce the contribution of the agricultural sector by 0.00008611%.

Simulating the Impacts of Climate Extremes Across Sectors: The Case of the 2003 European Heat Wave

NASA Astrophysics Data System (ADS)

Schewe, J.; Zhao, F.; Reyer, C.; Breuer, L.; Coll, M.; Deryng, D.; Eddy, T.; Elliott, J. W.; Francois, L. M.; Friend, A. D.; Gerten, D.; Gosling, S.; Gudmundsson, L.; Huber, V.; Kim, H.; Lotze, H. K.; Orth, R.; Seneviratne, S. I.; Tittensor, D.; Vautard, R.; van Vliet, M. T. H.; Wada, Y.

2017-12-01

Increased occurrence of extreme climate or weather events is one of the most damaging consequences of global climate change today and in the future. Estimating the impacts of such extreme events across different human and natural systems is crucial for quantifying overall risks from climate change. Are current models fit for this task? Here we use the 2003 European heat wave and drought (EHW) as a historical analogue for comparable events in the future, and evaluate how accurately its impacts are reproduced by a multi-sectoral "super-ensemble" of state-of-the-art impacts models. Our study combines, for the first time, impacts on agriculture, freshwater resources, terrestrial and marine ecosystems, energy, and human health in a consistent multi-model framework. We identify key impacts of the 2003 EHW reported in the literature and/or recorded in publicly available databases, and examine how closely the models reproduce those impacts, applying the same measure of impact magnitude across different sectors. Preliminary results are mixed: While the EHW's impacts on water resources (streamflow) are reproduced well by most global hydrological models, not all crop and natural vegetation models reproduce the magnitude of impacts on agriculture and ecosystem productivity, respectively, and their performance varies by country or region. A hydropower capacity model matches reported hydropower generation anomalies only in some countries, and estimates of heat-related excess mortality from a set of statistical models are consistent with literature reports only for some of the cities investigated. We present a synthesis of simulated and observed impacts across sectors, and reflect on potential improvements in modeling and analyzing cross-sectoral impacts.

Providing an Optimal School Context for Talent Development: An Extended Curriculum Program in Practice

ERIC Educational Resources Information Center

Kronborg, Leonie; Plunkett, Margaret

2015-01-01

Developing the talents of academically able students in government secondary schools in Victoria, Australia, has recently gained support through the expansion of Select Entry Accelerated Learning (SEAL) Programs. In the private sector, a similar expansion of interest in talent development has occurred through the development and implementation of…

The Fourth Way of Technology and Change

ERIC Educational Resources Information Center

Shirley, Dennis

2011-01-01

Recent social policy reforms have sought to overcome the limitations of "First Way" strategies emphasizing the welfare state and "Second Way" approaches advocating markets. Scholars and policymakers instead have begun to explore optimal synthesis of the public and private sector in a new "Third Way" of leadership and change. According to one line…

Meeting Students' Special Needs in Catholic Schools: A Report from the USA

ERIC Educational Resources Information Center

Scanlan, Martin

2017-01-01

Students experience a wide array of special needs, from diagnosed disabilities to cultural and linguistic barriers to traumas. Schools around the world and across public and private sectors struggle to provide optimal opportunities to learn for students experiencing special needs. Moreover, schools typically engage in these efforts in isolation…

Optimizing Mexico’s Water Distribution Services

DTIC Science & Technology

2011-10-28

government pursued a decentralization policy in the water distribution infrastructure sector.5 This is evident in Article 115 of the Mexican Constitution ...infrastructure, monitoring water 5 Ibid, 47. 6 Mexican Constitution . http://www.oas.org/juridico...54 Apogee Research International, Ltd., Innovative Financing of Water and Wastewater Infrastructure in the NAFTA Partners: A Focus on

Advanced helium purge seals for Liquid Oxygen (LOX) turbopumps

NASA Technical Reports Server (NTRS)

Shapiro, Wilbur; Lee, Chester C.

1989-01-01

Program objectives were to determine three advanced configurations of helium buffer seals capable of providing improved performance in a space shuttle main engine (SSME), high-pressure liquid oxygen (LOX) turbopump environment, and to provide NASA with the analytical tools to determine performance of a variety of seal configurations. The three seal designs included solid-ring fluid-film seals often referred to as floating ring seals, back-to-back fluid-film face seals, and a circumferential sectored seal that incorporated inherent clearance adjustment capabilities. Of the three seals designed, the sectored seal is favored because the self-adjusting clearance features accommodate the variations in clearance that will occur because of thermal and centrifugal distortions without compromising performance. Moreover, leakage can be contained well below the maximum target values; minimizing leakage is important on the SSME since helium is provided by an external tank. A reduction in tank size translates to an increase in payload that can be carried on board the shuttle. The computer codes supplied under this program included a code for analyzing a variety of gas-lubricated, floating ring, and sector seals; a code for analyzing gas-lubricated face seals; a code for optimizing and analyzing gas-lubricated spiral-groove face seals; and a code for determining fluid-film face seal response to runner excitations in as many as five degrees of freedom. These codes proved invaluable for optimizing designs and estimating final performance of the seals described.

Analytical optimization of demand management strategies across all urban water use sectors

NASA Astrophysics Data System (ADS)

Friedman, Kenneth; Heaney, James P.; Morales, Miguel; Palenchar, John

2014-07-01

An effective urban water demand management program can greatly influence both peak and average demand and therefore long-term water supply and infrastructure planning. Although a theoretical framework for evaluating residential indoor demand management has been well established, little has been done to evaluate other water use sectors such as residential irrigation in a compatible manner for integrating these results into an overall solution. This paper presents a systematic procedure to evaluate the optimal blend of single family residential irrigation demand management strategies to achieve a specified goal based on performance functions derived from parcel level tax assessor's data linked to customer level monthly water billing data. This framework is then generalized to apply to any urban water sector, as exponential functions can be fit to all resulting cumulative water savings functions. Two alternative formulations are presented: maximize net benefits, or minimize total costs subject to satisfying a target water savings. Explicit analytical solutions are presented for both formulations based on appropriate exponential best fits of performance functions. A direct result of this solution is the dual variable which represents the marginal cost of water saved at a specified target water savings goal. A case study of 16,303 single family irrigators in Gainesville Regional Utilities utilizing high quality tax assessor and monthly billing data along with parcel level GIS data provide an illustrative example of these techniques. Spatial clustering of targeted homes can be easily performed in GIS to identify priority demand management areas.

Neural Network Analysis of Different Segmentation Strategies of Nerve Fiber Layer Assessment for Glaucoma Diagnosis.

PubMed

Larrosa, Jose M; Polo, Vicente; Ferreras, Antonio; García-Martín, Elena; Calvo, Pilar; Pablo, Luis E

2015-12-01

To compare the diagnostic performance of different segmentations of the nerve fiber layer (NFL) thickness measurements using an artificial neural network and to define the optimal number of sectors with best diagnostic ability for glaucoma diagnosis. A total of 117 glaucoma patients and 123 normal subjects were included in the study. NFL thickness measurements were performed using the Spectralis-OCT (Heidelberg Engineering) to obtain the NFL thickness average; measurements from 2 semicircles, 4 quadrants, and 6, 8, 12, 16, 24, 32, and 64 sectors; and 768 uniformly divided locations around the peripapillary NFL. An artificial neural network evaluation was performed to compare the influence of sector analysis on the diagnostic performance of optical coherence tomography. Receiver operating characteristic curves were used to compare the diagnostic ability of the different segmentation analyses. The 6 sectors divided by the horizontal division of the nasal and temporal quadrants were better than the 6 sectors divided by the vertical line through the superior and inferior quadrants [areas under curve, 0.778; 95% confidence interval (CI), 0.720-0.829 and 0.814; 95% CI, 0.759-0.861, respectively]. In the case of quadrants, clock quadrants (area under curve 0.770; 95% CI, 0.712-0.822) were better than the ISNT (inferior-superior-nasal-temporal) quadrants (area under curve, 0.770; 95% CI, 0.712-0.822; P=0.003). The first segmentation strategy that improved the diagnostic value of 4 ISNT quadrants was the 12-sector analysis (area under curve, 0.845; 95% CI, 0.793-0.889; P=0.001). The 2 best candidate strategies for the OCT report were the 12-sector analysis and the 4 planimetric quadrant (alternatively, the 4 clock quadrants) analysis.

Is health care infected by Baumol's cost disease? Test of a new model.

PubMed

Atanda, Akinwande; Menclova, Andrea Kutinova; Reed, W Robert

2018-05-01

Rising health care costs are a policy concern across the Organisation for Economic Co-operation and Development, and relatively little consensus exists concerning their causes. One explanation that has received revived attention is Baumol's cost disease (BCD). However, developing a theoretically appropriate test of BCD has been a challenge. In this paper, we construct a 2-sector model firmly based on Baumol's axioms. We then derive several testable propositions. In particular, the model predicts that (a) the share of total labor employed in the health care sector and (b) the relative price index of the health and non-health care sectors should both be positively related to economy-wide productivity. The model also predicts that (c) the share of labor in the health sector will be negatively related and (d) the ratio of prices in the health and non-health sectors unrelated, to the demand for non-health services. Using annual data from 28 Organisation for Economic Co-operation and Development countries over the years 1995-2016 and from 14 U.S. industry groups over the years 1947-2015, we find little evidence to support the predictions of BCD once we address spurious correlation due to coincident trending and other econometric issues. Copyright © 2018 John Wiley & Sons, Ltd.

A Microeconomic Model of the Personnel Shortage in Public Rehabilitation Agencies

ERIC Educational Resources Information Center

Schultz, Jared C.; Millington, Michael J.

2007-01-01

There is a well-documented, growing shortage of rehabilitation counseling professionals in the public sector. Using microeconomics principles, a theoretical model is offered to account for the personnel shortage and propose potential solutions to recruit and retain rehabilitation counselors in the public sector. Suggestions for rehabilitation…

Renewing the model employer. Changing employment relations and "partnership" in the health and private sectors.

PubMed

Stuart, M; Martinez Lucio, M

2000-01-01

Drawing from original empirical data this paper compares the changing nature of employment relations in the health and private sectors. A key concern is to assess the extent to which the emergence of partnership-type arrangements between employers and trade unions lays the basis for the "renewal" of the traditional public sector concept of the model employer. Empirically, the paper draws on a survey of trade union representatives from 238 workplaces and a case study of a hospital trust. The data reveal that employment relations in the NHS are more collectivist when compared with the private sector. However, the development of partnership in the NHS is hamstrung by ongoing training and involvement gaps and widespread work intensification.

Who are more responsive? Mixed-methods comparison of public and private sector physicians in rural Bangladesh.

PubMed

Joarder, Taufique; George, Asha; Sarker, Malabika; Ahmed, Saifuddin; Peters, David H

2017-11-01

Responsiveness of physicians (ROPs) reflects the social actions by physicians to meet the legitimate expectations of health care users. Responsiveness is important since it improves understanding and care seeking by users, as well as fostering trust in health systems rather than replicating discrimination and entrenching inequality. Given widespread public and private sector health care provision in Bangladesh, we undertook a mixed-methods study comparing responsiveness of public and private physicians in rural Bangladesh. The study included in-depth interviews with physicians (n = 12, seven public, five private) and patients (n = 7, three male, four female); focus group discussions with users (four sessions, two male and two female); and observations in consultation rooms of public and private sector physicians (1 week in each setting). This was followed by structured observation of patient consultations with 195 public and 198 private physicians using the ROPs Scale, consisting of five domains (Friendliness; Respecting; Informing and guiding; Gaining trust; and Financial sensitivity). Qualitative data were analysed by framework analysis and quantitative data were analyzed using two-sample t-test, multiple linear regression, multivariate analysis of variance, and descriptive discriminant analyses. The mean responsiveness score of public sector physicians was statistically different from private sector physicians: -0.29 vs 0.29, i.e. a difference of - 0.58 (P-value < 0.01; 95% CI - 0.77, -0.39) on a normalized scale. Despite relatively higher level of responsiveness of private sector, according to qualitative findings, neither of the sectors performed optimally. Private physicians scored higher in Friendliness, Respecting and Informing and guiding; while public sector physicians scored higher in other domains. 'Respecting' domain was found as the most important. Unlike findings from other studies in Bangladesh, instead of seeing one sector as better than the other, this study identified areas of responsiveness where each sector needs improvements. © 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.

[Application of extended exergy method in driving mechanism and efficiency of regional eco-economy].

PubMed

Fan, Xin Gang; Mi, Wen Bao; Hou, Jing Wei

2017-01-01

To analyze social-economic causes of the regional ecological degradation, and avoid such problems as the complex circulation network and difficulty to identify laws caused by extended exergy analysis (EEA) previously applied at the national scale, this paper reduced spatial scale to the county scale and took Pengyang County in Ningxia as an example. Eco-economic system in Peng-yang County was divided into seven interrelated sectors. The exergy value of circulations in the eco-economic system including materials, labor and capital were calculated respectively to analyze the extended exergy characteristics of the driving sectors, factors and paths and evaluate their ecological efficiency. The results showed that agriculture and households were the main driving sectors of the eco-economic system in Pengyang County. The average exergy value of 31 flow paths among the sectors was 0.80 PJ. There were only 8 flow paths whose exergy values were higher than the average value. Eco-economic system in Pengyang County development was driven by two continuous flow paths, labor output of the households sector and demands of the households sector supported by other sectors. The mineral resources were massively exploited, and then directly exported to the outside, which could not promote the local development from the inside, but, on the contrary, increase the ecological environment pressure because of the over-exploitation. The eco-efficiency of Pengyang County in 2014 was 68.1%, almost equivalent to the by-level of the national scale at home and abroad ten years ago, mainly because of the lower eco-efficiencies of the service sector and households sector. EEA had the advantage of networking and structuring, could specify the sectors, factors and driven paths, and break through the bottleneck of driving mechanism research of the eco-economic system. EEA had certain adaptability to explore the operational principle and optimal pattern of the regional eco-economic system. Compared with the national scale, EEA at the regional scale could more easily identify the driving mechanism of eco-economic system, and could clearly guide the regional administrative department to reduce the ecological environment pressure.

Ebola Preparedness in the Netherlands: The Need for Coordination Between the Public Health and the Curative Sector.

PubMed

Swaan, Corien M; Öry, Alexander V; Schol, Lianne G C; Jacobi, André; Richardus, Jan Hendrik; Timen, Aura

During the Ebola outbreak in West Africa in 2014-2015, close cooperation between the curative sector and the public health sector in the Netherlands was necessary for timely identification, referral, and investigation of patients with suspected Ebola virus disease (EVD). In this study, we evaluated experiences in preparedness among stakeholders of both curative and public health sectors to formulate recommendations for optimizing preparedness protocols. Timeliness of referred patients with suspected EVD was used as indicator for preparedness. In focus group sessions and semistructured interviews, experiences of curative and public health stakeholders about the regional and national process of preparedness and response were listed. Timeliness recordings of all referred patients with suspected EVD (13) were collected from first date of illness until arrival in the referral academic hospital. Ebola preparedness was considered extensive compared with the risk of an actual patient, however necessary. Regional coordination varied between regions. More standardization of regional preparation and operational guidelines was requested, as well as nationally standardized contingency criteria, and the National Centre for Infectious Disease Control was expected to coordinate the development of these guidelines. For the timeliness of referred patients with suspected EVD, the median delay between first date of illness until triage was 2.0 days (range: 0-10 days), and between triage and arrival in the referral hospital, it was 5.0 hours (range: 2-7.5 hours). In none of these patients Ebola infection was confirmed. Coordination between the public health sector and the curative sector needs improvement to reduce delay in patient management in emerging infectious diseases. Standardization of preparedness and response practices, through guidelines for institutional preparedness and blueprints for regional and national coordination, is necessary, as preparedness for emerging infectious diseases needs a multidisciplinary approach overarching both the public health sector and the curative sector. In the Netherlands a national platform for preparedness is established, in which both the curative sector and public health sector participate, in order to implement the outcomes of this study.

A theoretical approach to dual practice regulations in the health sector.

PubMed

González, Paula; Macho-Stadler, Inés

2013-01-01

Internationally, there is wide cross-country heterogeneity in government responses to dual practice in the health sector. This paper provides a uniform theoretical framework to analyze and compare some of the most common regulations. We focus on three interventions: banning dual practice, offering rewarding contracts to public physicians, and limiting dual practice (including both limits to private earnings of dual providers and limits to involvement in private activities). An ancillary objective of the paper is to investigate whether regulations that are optimal for developed countries are adequate for developing countries as well. Our results offer theoretical support for the desirability of different regulations in different economic environments. Copyright © 2012 Elsevier B.V. All rights reserved.

Advancing Articulation: Models of College-University Collaboration in Canadian Higher

ERIC Educational Resources Information Center

Kirby, Dale

2008-01-01

This paper reports on the results of an analysis of program articulation between the college and university sectors in Canada. The Canadian post-secondary system is best described as a binary system with discrete university and non-university sectors. While there are complex sectoral differences between the two institutional types in terms of…

TRACKING THE EMISSION OF CARBON DIOXIDE BY NATION, SECTOR, AND FUEL TYPE: A TRACE GAS ACCOUNTING SYSTEM (TGAS)

EPA Science Inventory

The paper describes a new way to estimate an efficient econometric model of global emissions of carbon dioxide (CO2) by nation, sector, and fuel type. Equations for fuel intensity are estimated for coal, oil, natural gas, electricity, and heat for six sectors: agricultural, indus...

2010 Staff Organization for Optimum C2: A Private Sector Analysis

DTIC Science & Technology

1998-02-13

control over business operations. Warfighting CINCs can benefit from the lessons learned in the private sector by adapting those lessons to future military... private sector analysis. Through the use of a networked command and control system and a "matrix" staff structure, the model consolidates the JFC staff

Preparing Rehabilitation Counselors for Private Sector Practice within a CORE Accredited Generalist Educational Model

ERIC Educational Resources Information Center

Zanskas, Stephen; Leahy, Michael

2007-01-01

As private sector rehabilitation has matured as a field of practice, the issue of how rehabilitation counselor educators can effectively prepare rehabilitation counselors for practice in this setting remains. This article reviews the literature regarding the training needs of rehabilitation counselors entering private sector practice, and proposes…

Dynamics of Private Sector Support for Education: Experiences in Latin America

ERIC Educational Resources Information Center

Brady, Kristin; Galisson, Kirsten

2008-01-01

Recognizing the diversity of models and strategies for private sector participation in education that have emerged in Latin America, the United States Agency for International Development (USAID) requested the Academy for Educational Development (AED) to conduct research with leaders in the public and private sectors in several countries. While…

Implementing the WorkAdvance Model: Lessons for Practitioners. Policy Brief

ERIC Educational Resources Information Center

Kazis, Richard; Molina, Frieda

2016-01-01

WorkAdvance is a sectoral workforce development program designed to meet the needs of workers and employers alike. For unemployed and low-wage working adults, the program provides skills training in targeted sectors that have good-quality job openings with room for advancement within established career pathways. For employers in those sectors,…

A Wideband Circularly Polarized Antenna with a Multiple-Circular-Sector Dielectric Resonator

PubMed Central

Trinh-Van, Son; Yang, Youngoo; Lee, Kang-Yoon; Hwang, Keum Cheol

2016-01-01

This paper presents the design of a wideband circularly polarized antenna using a multiple-circular-sector dielectric resonator (DR). The DR is composed of twelve circular-sector DRs with identical central angles of 30∘ but with different radii. A genetic algorithm is utilized to optimize the radii of the twelve circular-sector DRs to realize wideband circular polarization. The proposed antenna is excited using an aperture-coupled feeding technique through a narrow rectangular slot etched onto the ground plane. An antenna prototype is experimentally verified. The measured −10 dB reflection and 3 dB axial ratio (AR) bandwidths are 31.39% (1.88–2.58 GHz) and 19.30% (2.06–2.50 GHz), respectively, covering the operating bands of the following systems: UMTS-2100 (2.145 GHz), WiMAX (2.3 GHz), and Wi-Fi (2.445 GHz). A measured peak gain of 7.65 dBic at 2.225 GHz and gain variation of less than 2.70 dBic within the measured 3 dB AR bandwidth are achieved. In addition, the radiation patterns of the proposed antenna are presented and discussed. PMID:27827881

Economic constraints - the growing challenge for Western breast cancer centers.

PubMed

Seidel, Rene P; Lux, Michael P; Hoellthaler, Josef; Beckmann, Matthias W; Voigt, Wieland

2013-03-01

Breast cancer care in Western countries has reached a considerable level of quality and standardization, which has contributed to the decline in breast cancer mortality. Certified Breast Cancer Centers (BCC) represent an important element of this development. Related to changes in reimbursement and growing costs, BCC face economic constraints which ultimately could endanger the achievements of the past. Thus, BCC have to optimize their care strategies from an economic perspective, particularly by increasing efficiency but also by adapting their service portfolio. This could result in competitive advantages and additional revenue by increasing case numbers and extra charges to patients. Furthermore, an intensification of collaboration with the outpatient sector resulting in an integrated and managed 'trans-sectoral' care approach which could allow to shift unprofitable procedures to the outpatient sector - in the sense of a win-win situation for both sectors and without loss of care quality - seems reasonable. Structured and specialized consulting approaches can further be a lever to fulfill economic requirements in order to avoid cuts in medical care quality for the sake of a balanced budget. In this review, economic constraints of BCC with a focus on the German healthcare system and potential approaches to ameliorate these financial burdens are being discussed.

Deep carbon reductions in California require electrification and integration across economic sectors

NASA Astrophysics Data System (ADS)

Wei, Max; Nelson, James H.; Greenblatt, Jeffery B.; Mileva, Ana; Johnston, Josiah; Ting, Michael; Yang, Christopher; Jones, Chris; McMahon, James E.; Kammen, Daniel M.

2013-03-01

Meeting a greenhouse gas (GHG) reduction target of 80% below 1990 levels in the year 2050 requires detailed long-term planning due to complexity, inertia, and path dependency in the energy system. A detailed investigation of supply and demand alternatives is conducted to assess requirements for future California energy systems that can meet the 2050 GHG target. Two components are developed here that build novel analytic capacity and extend previous studies: (1) detailed bottom-up projections of energy demand across the building, industry and transportation sectors; and (2) a high-resolution variable renewable resource capacity planning model (SWITCH) that minimizes the cost of electricity while meeting GHG policy goals in the 2050 timeframe. Multiple pathways exist to a low-GHG future, all involving increased efficiency, electrification, and a dramatic shift from fossil fuels to low-GHG energy. The electricity system is found to have a diverse, cost-effective set of options that meet aggressive GHG reduction targets. This conclusion holds even with increased demand from transportation and heating, but the optimal levels of wind and solar deployment depend on the temporal characteristics of the resulting load profile. Long-term policy support is found to be a key missing element for the successful attainment of the 2050 GHG target in California.

Emissions implications of future natural gas production and use in the U.S. and in the Rocky Mountain region.

PubMed

McLeod, Jeffrey D; Brinkman, Gregory L; Milford, Jana B

2014-11-18

Enhanced prospects for natural gas production raise questions about the balance of impacts on air quality, as increased emissions from production activities are considered alongside the reductions expected when natural gas is burned in place of other fossil fuels. This study explores how trends in natural gas production over the coming decades might affect emissions of greenhouse gases (GHG), volatile organic compounds (VOCs) and nitrogen oxides (NOx) for the United States and its Rocky Mountain region. The MARKAL (MARKet ALlocation) energy system optimization model is used with the U.S. Environmental Protection Agency's nine-region database to compare scenarios for natural gas supply and demand, constraints on the electricity generation mix, and GHG emissions fees. Through 2050, total energy system GHG emissions show little response to natural gas supply assumptions, due to offsetting changes across sectors. Policy-driven constraints or emissions fees are needed to achieve net reductions. In most scenarios, wind is a less expensive source of new electricity supplies in the Rocky Mountain region than natural gas. U.S. NOx emissions decline in all the scenarios considered. Increased VOC emissions from natural gas production offset part of the anticipated reductions from the transportation sector, especially in the Rocky Mountain region.

Primary health care and public health: foundations of universal health systems.

PubMed

White, Franklin

2015-01-01

The aim of this review is to advocate for more integrated and universally accessible health systems, built on a foundation of primary health care and public health. The perspective outlined identified health systems as the frame of reference, clarified terminology and examined complementary perspectives on health. It explored the prospects for universal and integrated health systems from a global perspective, the role of healthy public policy in achieving population health and the value of the social-ecological model in guiding how best to align the components of an integrated health service. The importance of an ethical private sector in partnership with the public sector is recognized. Most health systems around the world, still heavily focused on illness, are doing relatively little to optimize health and minimize illness burdens, especially for vulnerable groups. This failure to improve the underlying conditions for health is compounded by insufficient allocation of resources to address priority needs with equity (universality, accessibility and affordability). Finally, public health and primary health care are the cornerstones of sustainable health systems, and this should be reflected in the health policies and professional education systems of all nations wishing to achieve a health system that is effective, equitable, efficient and affordable. © 2015 S. Karger AG, Basel.

Essays on economic development, energy demand, and the environment

NASA Astrophysics Data System (ADS)

Medlock, Kenneth Barry, III

2000-10-01

The rapid expansion of industry at the outset of economic development and the subsequent growth of the transportation and residential and commercial sectors dictate both the rate at which energy demand increases and the composition of primary fuel sources used to meet secondary requirements. Each of these factors each has an impact on the pollution problems that nations may face. Growth in consumer wealth, however, appears to eventually lead to a shift in priorities. In particular, the importance of the environment begins to take precedent over the acquisition of goods. Accordingly, cleaner energy alternatives are sought out. The approach taken here is to determine the energy profile of an average nation, and apply those results to a model of economic growth. Dematerialization of production and saturation of consumer bundles results in declining rates of growth of energy demand in broadly defined end-use sectors. The effects of technological change in fossil fuel efficiency, fossil fuel recovery, and 'backstop' energy resources on economic growth and the emissions of carbon dioxide are then analyzed. A central planner is assumed to optimize the consumption of goods and services subject to capital and resource constraints. Slight perturbations in the parameters are used to determine their local elasticities with respect to different endogenous variables, and give an indication of the effects of changes in the various assumptions.

Hidden Sector Dark Matter Models for the Galactic Center Gamma-Ray Excess

DOE Office of Scientific and Technical Information (OSTI.GOV)

Berlin, Asher; Gratia, Pierre; Hooper, Dan

2014-07-24

The gamma-ray excess observed from the Galactic Center can be interpreted as dark matter particles annihilating into Standard Model fermions with a cross section near that expected for a thermal relic. Although many particle physics models have been shown to be able to account for this signal, the fact that this particle has not yet been observed in direct detection experiments somewhat restricts the nature of its interactions. One way to suppress the dark matter's elastic scattering cross section with nuclei is to consider models in which the dark matter is part of a hidden sector. In such models, themore » dark matter can annihilate into other hidden sector particles, which then decay into Standard Model fermions through a small degree of mixing with the photon, Z, or Higgs bosons. After discussing the gamma-ray signal from hidden sector dark matter in general terms, we consider two concrete realizations: a hidden photon model in which the dark matter annihilates into a pair of vector gauge bosons that decay through kinetic mixing with the photon, and a scenario within the generalized NMSSM in which the dark matter is a singlino-like neutralino that annihilates into a pair of singlet Higgs bosons, which decay through their mixing with the Higgs bosons of the MSSM.« less

The mineral sector and economic development in Ghana: A computable general equilibrium analysis

NASA Astrophysics Data System (ADS)

Addy, Samuel N.

A computable general equilibrium model (CGE) model is formulated for conducting mineral policy analysis in the context of national economic development for Ghana. The model, called GHANAMIN, places strong emphasis on production, trade, and investment. It can be used to examine both micro and macro economic impacts of policies associated with mineral investment, taxation, and terms of trade changes, as well as mineral sector performance impacts due to technological change or the discovery of new deposits. Its economywide structure enables the study of broader development policy with a focus on individual or multiple sectors, simultaneously. After going through a period of contraction for about two decades, mining in Ghana has rebounded significantly and is currently the main foreign exchange earner. Gold alone contributed 44.7 percent of 1994 total export earnings. GHANAMIN is used to investigate the economywide impacts of mineral tax policies, world market mineral prices changes, mining investment, and increased mineral exports. It is also used for identifying key sectors for economic development. Various simulations were undertaken with the following results: Recently implemented mineral tax policies are welfare increasing, but have an accompanying decrease in the output of other export sectors. World mineral price rises stimulate an increase in real GDP; however, this increase is less than real GDP decreases associated with price declines. Investment in the non-gold mining sector increases real GDP more than investment in gold mining, because of the former's stronger linkages to the rest of the economy. Increased mineral exports are very beneficial to the overall economy. Foreign direct investment (FDI) in mining increases welfare more so than domestic capital, which is very limited. Mining investment and the increased mineral exports since 1986 have contributed significantly to the country's economic recovery, with gold mining accounting for 95 percent of the mineral sector's contribution. The mining sector in general is identified as a leading sector for economic development.

Physician and nurse supply in Serbia using time-series data

PubMed Central

2013-01-01

Background Unemployment among health professionals in Serbia has risen in the recent past and continues to increase. This highlights the need to understand how to change policies to meet real and projected needs. This study identified variables that were significantly related to physician and nurse employment rates in the public healthcare sector in Serbia from 1961 to 2008 and used these to develop parameters to model physician and nurse supply in the public healthcare sector through to 2015. Methods The relationships among six variables used for planning physician and nurse employment in public healthcare sector in Serbia were identified for two periods: 1961 to 1982 and 1983 to 2008. Those variables included: the annual total national population; gross domestic product adjusted to 1994 prices; inpatient care discharges; outpatient care visits; students enrolled in the first year of medical studies at public universities; and the annual number of graduated physicians. Based on historic trends, physician supply and nurse supply in the public healthcare sector by 2015 (with corresponding 95% confidence level) have been modeled using Autoregressive Integrated Moving Average (ARIMA) / Transfer function (TF) models. Results The ARIMA/TF modeling yielded stable and significant forecasts of physician supply (stationary R2 squared = 0.71) and nurse supply (stationary R2 squared = 0.92) in the public healthcare sector in Serbia through to 2015. The most significant predictors for physician employment were the population and GDP. The supply of nursing staff was, in turn, related to the number of physicians. Physician and nurse rates per 100,000 population increased by 13%. The model predicts a seven-year mismatch between the supply of graduates and vacancies in the public healthcare sector is forecasted at 8,698 physicians - a net surplus. Conclusion The ARIMA model can be used to project trends, especially those that identify significant mismatches between forecasted supply of physicians and vacancies and can be used to guide decision-making for enrollment planning for the medical schools in Serbia. Serbia needs an inter-sectoral strategy for HRH development that is more coherent with healthcare objectives and more accountable in terms of professional mobility. PMID:23773678

Physician and nurse supply in Serbia using time-series data.

PubMed

Santric-Milicevic, Milena; Vasic, Vladimir; Marinkovic, Jelena

2013-06-17

Unemployment among health professionals in Serbia has risen in the recent past and continues to increase. This highlights the need to understand how to change policies to meet real and projected needs. This study identified variables that were significantly related to physician and nurse employment rates in the public healthcare sector in Serbia from 1961 to 2008 and used these to develop parameters to model physician and nurse supply in the public healthcare sector through to 2015. The relationships among six variables used for planning physician and nurse employment in public healthcare sector in Serbia were identified for two periods: 1961 to 1982 and 1983 to 2008. Those variables included: the annual total national population; gross domestic product adjusted to 1994 prices; inpatient care discharges; outpatient care visits; students enrolled in the first year of medical studies at public universities; and the annual number of graduated physicians. Based on historic trends, physician supply and nurse supply in the public healthcare sector by 2015 (with corresponding 95% confidence level) have been modeled using Autoregressive Integrated Moving Average (ARIMA) / Transfer function (TF) models. The ARIMA/TF modeling yielded stable and significant forecasts of physician supply (stationary R2 squared = 0.71) and nurse supply (stationary R2 squared = 0.92) in the public healthcare sector in Serbia through to 2015. The most significant predictors for physician employment were the population and GDP. The supply of nursing staff was, in turn, related to the number of physicians. Physician and nurse rates per 100,000 population increased by 13%. The model predicts a seven-year mismatch between the supply of graduates and vacancies in the public healthcare sector is forecasted at 8,698 physicians - a net surplus. The ARIMA model can be used to project trends, especially those that identify significant mismatches between forecasted supply of physicians and vacancies and can be used to guide decision-making for enrollment planning for the medical schools in Serbia. Serbia needs an inter-sectoral strategy for HRH development that is more coherent with healthcare objectives and more accountable in terms of professional mobility.

Digital Transformation and Disruption of the Health Care Sector: Internet-Based Observational Study.

PubMed

Herrmann, Maximilian; Boehme, Philip; Mondritzki, Thomas; Ehlers, Jan P; Kavadias, Stylianos; Truebel, Hubert

2018-03-27

Digital innovation, introduced across many industries, is a strong force of transformation. Some industries have seen faster transformation, whereas the health care sector only recently came into focus. A context where digital corporations move into health care, payers strive to keep rising costs at bay, and longer-living patients desire continuously improved quality of care points to a digital and value-based transformation with drastic implications for the health care sector. We tried to operationalize the discussion within the health care sector around digital and disruptive innovation to identify what type of technological enablers, business models, and value networks seem to be emerging from different groups of innovators with respect to their digital transformational efforts. From the Forbes 2000 and CBinsights databases, we identified 100 leading technology, life science, and start-up companies active in the health care sector. Further analysis identified projects from these companies within a digital context that were subsequently evaluated using the following criteria: delivery of patient value, presence of a comprehensive and distinctive underlying business model, solutions provided, and customer needs addressed. Our methodological approach recorded more than 400 projects and collaborations. We identified patterns that show established corporations rely more on incremental innovation that supports their current business models, while start-ups engage their flexibility to explore new market segments with notable transformations of established business models. Thereby, start-ups offer higher promises of disruptive innovation. Additionally, start-ups offer more diversified value propositions addressing broader areas of the health care sector. Digital transformation is an opportunity to accelerate health care performance by lowering cost and improving quality of care. At an economic scale, business models can be strengthened and disruptive innovation models enabled. Corporations should look for collaborations with start-up companies to keep investment costs at bay and off the balance sheet. At the same time, the regulatory knowledge of established corporations might help start-ups to kick off digital disruption in the health care sector. ©Maximilian Herrmann, Philip Boehme, Thomas Mondritzki, Jan P Ehlers, Stylianos Kavadias, Hubert Truebel. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 27.03.2018.

Digital Transformation and Disruption of the Health Care Sector: Internet-Based Observational Study

PubMed Central

Mondritzki, Thomas; Ehlers, Jan P; Kavadias, Stylianos

2018-01-01

Background Digital innovation, introduced across many industries, is a strong force of transformation. Some industries have seen faster transformation, whereas the health care sector only recently came into focus. A context where digital corporations move into health care, payers strive to keep rising costs at bay, and longer-living patients desire continuously improved quality of care points to a digital and value-based transformation with drastic implications for the health care sector. Objective We tried to operationalize the discussion within the health care sector around digital and disruptive innovation to identify what type of technological enablers, business models, and value networks seem to be emerging from different groups of innovators with respect to their digital transformational efforts. Methods From the Forbes 2000 and CBinsights databases, we identified 100 leading technology, life science, and start-up companies active in the health care sector. Further analysis identified projects from these companies within a digital context that were subsequently evaluated using the following criteria: delivery of patient value, presence of a comprehensive and distinctive underlying business model, solutions provided, and customer needs addressed. Results Our methodological approach recorded more than 400 projects and collaborations. We identified patterns that show established corporations rely more on incremental innovation that supports their current business models, while start-ups engage their flexibility to explore new market segments with notable transformations of established business models. Thereby, start-ups offer higher promises of disruptive innovation. Additionally, start-ups offer more diversified value propositions addressing broader areas of the health care sector. Conclusions Digital transformation is an opportunity to accelerate health care performance by lowering cost and improving quality of care. At an economic scale, business models can be strengthened and disruptive innovation models enabled. Corporations should look for collaborations with start-up companies to keep investment costs at bay and off the balance sheet. At the same time, the regulatory knowledge of established corporations might help start-ups to kick off digital disruption in the health care sector. PMID:29588274

Exotic quarks in Twin Higgs models

DOE PAGES

Cheng, Hsin -Chia; Jung, Sunghoon; Salvioni, Ennio; ...

2016-03-14

The Twin Higgs model provides a natural theory for the electroweak symmetry breaking without the need of new particles carrying the standard model gauge charges below a few TeV. In the low energy theory, the only probe comes from the mixing of the Higgs fields in the standard model and twin sectors. However, an ultraviolet completion is required below ~ 10 TeV to remove residual logarithmic divergences. In non-supersymmetric completions, new exotic fermions charged under both the standard model and twin gauge symmetries have to be present to accompany the top quark, thus providing a high energy probe of themore » model. Some of them carry standard model color, and may therefore be copiously produced at current or future hadron colliders. Once produced, these exotic quarks can decay into a top together with twin sector particles. If the twin sector particles escape the detection, we have the irreducible stop-like signals. On the other hand, some twin sector particles may decay back into the standard model particles with long lifetimes, giving spectacular displaced vertex signals in combination with the prompt top quarks. This happens in the Fraternal Twin Higgs scenario with typical parameters, and sometimes is even necessary for cosmological reasons. We study the potential displaced vertex signals from the decays of the twin bottomonia, twin glueballs, and twin leptons in the Fraternal Twin Higgs scenario. As a result, depending on the details of the twin sector, the exotic quarks may be probed up to ~ 2.5 TeV at the LHC and beyond 10 TeV at a future 100 TeV collider, providing a strong test of this class of ultraviolet completions.« less

Patterns of tropical Pacific convection anomalies and associated extratropical wave trains in AMIP5

NASA Astrophysics Data System (ADS)

Ding, Shuoyi; Chen, Wen; Graf, Hans-F.; Guo, Yuanyuan

2018-05-01

In this paper, the performance of 18 Coupled Model Intercomparison Project Phase 5 (CMIP5) models forced by observational SSTs in simulating the tropical Pacific convective variation and the atmospheric responses in the extratropics are assessed. The multi-model ensemble mean results of 18 CMIP5 models show that five major patterns of tropical Pacific convection anomaly in winter can indeed be well reproduced, however, the simulation of the corresponding extratropical responses for each pattern exists some deficiency except for the La Niña pattern compared with observations. We defined an optimized subset of well performing models (ACCESS1.0, CanAM4, CCSM4, CMCC-CM, HadGEM2-A, MPI-ESM-MR) in tropical Pacific deep convection according to the ranking of model skill score. These models exhibit approximately identical convection anomaly patterns in both amplitude and spatial structure to the observation, which potentially might improve the representation of extratropical teleconnections with the tropical Pacific, especially for the CP El Niño (CPEN), EP El Niño (EPEN) and western CP (W-CP) patterns. Both evident atmospheric anomalies of CPEN and EPEN patterns over the NA/E sector and the northeastward propagating wave trains of W-CP pattern can be quite well simulated in the high-skilled models.

Cyclical absenteeism among private sector, public sector and self-employed workers.

PubMed

Pfeifer, Christian

2013-03-01

This research note analyzes differences in the number of absent working days and doctor visits and in their cyclicality between private sector, public sector and self-employed workers. For this purpose, I used large-scale German survey data for the years 1995 to 2007 to estimate random effects negative binomial (count data) models. The main findings are as follows. (i) Public sector workers have on average more absent working days than private sector and self-employed workers. Self-employed workers have fewer absent working days and doctor visits than dependent employed workers. (ii) The regional unemployment rate is on average negatively correlated with the number of absent working days among private and public sector workers as well as among self-employed men. The correlations between regional unemployment rate and doctor visits are only significantly negative among private sector workers. Copyright © 2012 John Wiley & Sons, Ltd.

Application of lean manufacturing concepts to drug discovery: rapid analogue library synthesis.

PubMed

Weller, Harold N; Nirschl, David S; Petrillo, Edward W; Poss, Michael A; Andres, Charles J; Cavallaro, Cullen L; Echols, Martin M; Grant-Young, Katherine A; Houston, John G; Miller, Arthur V; Swann, R Thomas

2006-01-01

The application of parallel synthesis to lead optimization programs in drug discovery has been an ongoing challenge since the first reports of library synthesis. A number of approaches to the application of parallel array synthesis to lead optimization have been attempted over the years, ranging from widespread deployment by (and support of) individual medicinal chemists to centralization as a service by an expert core team. This manuscript describes our experience with the latter approach, which was undertaken as part of a larger initiative to optimize drug discovery. In particular, we highlight how concepts taken from the manufacturing sector can be applied to drug discovery and parallel synthesis to improve the timeliness and thus the impact of arrays on drug discovery.

Improvement of radiology services based on the process management approach.

PubMed

Amaral, Creusa Sayuri Tahara; Rozenfeld, Henrique; Costa, Janaina Mascarenhas Hornos; Magon, Maria de Fátima de Andrade; Mascarenhas, Yvone Maria

2011-06-01

The health sector requires continuous investments to ensure the improvement of products and services from a technological standpoint, the use of new materials, equipment and tools, and the application of process management methods. Methods associated with the process management approach, such as the development of reference models of business processes, can provide significant innovations in the health sector and respond to the current market trend for modern management in this sector (Gunderman et al. (2008) [4]). This article proposes a process model for diagnostic medical X-ray imaging, from which it derives a primary reference model and describes how this information leads to gains in quality and improvements. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Recommendations for Modeling Disaster Responses in Public Health and Medicine: A Position Paper of The Society for Medical Decision Making

PubMed Central

Brandeau, Margaret L.; McCoy, Jessica H.; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M.

2013-01-01

Purpose Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. We examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. Methods We reviewed a spectrum of published disaster response models addressing public health or healthcare delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. We developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. Results We propose six recommendations for model construction and reporting, inspired by the most exemplary models: Health sector disaster response models should address real-world problems; be designed for maximum usability by response planners; strike the appropriate balance between simplicity and complexity; include appropriate outcomes, which extend beyond those considered in traditional cost-effectiveness analyses; and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. Conclusions Quantitative models are critical tools for planning effective health sector responses to disasters. The recommendations we propose can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response. PMID:19605887

Recommendations for modeling disaster responses in public health and medicine: a position paper of the society for medical decision making.

PubMed

Brandeau, Margaret L; McCoy, Jessica H; Hupert, Nathaniel; Holty, Jon-Erik; Bravata, Dena M

2009-01-01

Mathematical and simulation models are increasingly used to plan for and evaluate health sector responses to disasters, yet no clear consensus exists regarding best practices for the design, conduct, and reporting of such models. The authors examined a large selection of published health sector disaster response models to generate a set of best practice guidelines for such models. . The authors reviewed a spectrum of published disaster response models addressing public health or health care delivery, focusing in particular on the type of disaster and response decisions considered, decision makers targeted, choice of outcomes evaluated, modeling methodology, and reporting format. They developed initial recommendations for best practices for creating and reporting such models and refined these guidelines after soliciting feedback from response modeling experts and from members of the Society for Medical Decision Making. . The authors propose 6 recommendations for model construction and reporting, inspired by the most exemplary models: health sector disaster response models should address real-world problems, be designed for maximum usability by response planners, strike the appropriate balance between simplicity and complexity, include appropriate outcomes that extend beyond those considered in traditional cost-effectiveness analyses, and be designed to evaluate the many uncertainties inherent in disaster response. Finally, good model reporting is particularly critical for disaster response models. . Quantitative models are critical tools for planning effective health sector responses to disasters. The proposed recommendations can increase the applicability and interpretability of future models, thereby improving strategic, tactical, and operational aspects of preparedness planning and response.

Financial Structure and Economic Welfare: Applied General Equilibrium Development Economics.

PubMed

Townsend, Robert

2010-09-01

This review provides a common framework for researchers thinking about the next generation of micro-founded macro models of growth, inequality, and financial deepening, as well as direction for policy makers targeting microfinance programs to alleviate poverty. Topics include treatment of financial structure general equilibrium models: testing for as-if-complete markets or other financial underpinnings; examining dual-sector models with both a perfectly intermediated sector and a sector in financial autarky, as well as a second generation of these models that embeds information problems and other obstacles to trade; designing surveys to capture measures of income, investment/savings, and flow of funds; and aggregating individuals and households to the level of network, village, or national economy. The review concludes with new directions that overcome conceptual and computational limitations.

Financial Structure and Economic Welfare: Applied General Equilibrium Development Economics

PubMed Central

Townsend, Robert

2010-01-01

This review provides a common framework for researchers thinking about the next generation of micro-founded macro models of growth, inequality, and financial deepening, as well as direction for policy makers targeting microfinance programs to alleviate poverty. Topics include treatment of financial structure general equilibrium models: testing for as-if-complete markets or other financial underpinnings; examining dual-sector models with both a perfectly intermediated sector and a sector in financial autarky, as well as a second generation of these models that embeds information problems and other obstacles to trade; designing surveys to capture measures of income, investment/savings, and flow of funds; and aggregating individuals and households to the level of network, village, or national economy. The review concludes with new directions that overcome conceptual and computational limitations. PMID:21037939

Indonesia’s Electricity Demand Dynamic Modelling

NASA Astrophysics Data System (ADS)

Sulistio, J.; Wirabhuana, A.; Wiratama, M. G.

2017-06-01

Electricity Systems modelling is one of the emerging area in the Global Energy policy studies recently. System Dynamics approach and Computer Simulation has become one the common methods used in energy systems planning and evaluation in many conditions. On the other hand, Indonesia experiencing several major issues in Electricity system such as fossil fuel domination, demand - supply imbalances, distribution inefficiency, and bio-devastation. This paper aims to explain the development of System Dynamics modelling approaches and computer simulation techniques in representing and predicting electricity demand in Indonesia. In addition, this paper also described the typical characteristics and relationship of commercial business sector, industrial sector, and family / domestic sector as electricity subsystems in Indonesia. Moreover, it will be also present direct structure, behavioural, and statistical test as model validation approach and ended by conclusions.

Generating community-built tools for data sharing and analysis in environmental networks

USGS Publications Warehouse

Read, Jordan S.; Gries, Corinna; Read, Emily K.; Klug, Jennifer; Hanson, Paul C.; Hipsey, Matthew R.; Jennings, Eleanor; O'Reilley, Catherine; Winslow, Luke A.; Pierson, Don; McBride, Christopher G.; Hamilton, David

2016-01-01

Rapid data growth in many environmental sectors has necessitated tools to manage and analyze these data. The development of tools often lags behind the proliferation of data, however, which may slow exploratory opportunities and scientific progress. The Global Lake Ecological Observatory Network (GLEON) collaborative model supports an efficient and comprehensive data–analysis–insight life cycle, including implementations of data quality control checks, statistical calculations/derivations, models, and data visualizations. These tools are community-built and openly shared. We discuss the network structure that enables tool development and a culture of sharing, leading to optimized output from limited resources. Specifically, data sharing and a flat collaborative structure encourage the development of tools that enable scientific insights from these data. Here we provide a cross-section of scientific advances derived from global-scale analyses in GLEON. We document enhancements to science capabilities made possible by the development of analytical tools and highlight opportunities to expand this framework to benefit other environmental networks.

Settlement of the alien mollusc Brachidontes pharaonis in a Mediterranean industrial plant: bioassays for antifouling treatment optimization and management.

PubMed

Garaventa, F; Corrà, C; Piazza, V; Giacco, E; Greco, G; Pane, L; Faimali, M

2012-05-01

In this work, we investigated the efficacy of three new biocides (77351, 73532, 73503--NALCO®) as specific antifouling products against adult organisms of the bivalve Brachidontes pharaonis (Fischer P., 1870), a Lessepsian species introduced in the Mediterranean Sea by sea transport (ballast water), and which has recently shown invasive behaviour in an industrial plant in Southern Italy (Sicily). These biocides were tested to verify their efficacy, as well as their environmental compatibility at discharge point, using the crustacean belonging to the genus Artemia (Leach, 1819) as model organism, according to Government Decree (D. Lgs) No. 152/06. Biocides were also tested using alternative crustaceans, Amphibalanus amphitrite (Darwin, 1854), and Tigriopus fulvus (Fischer, 1860), in order to check whether their introduction as model species in the national regulation could affect discharge limit concentrations (DLC) due to their different sensitivity, with likely economic and technical repercussions in the industrial water treatment sector. Copyright © 2011 Elsevier Ltd. All rights reserved.

Commercial Capaciflector

NASA Technical Reports Server (NTRS)

Vranish, John M.

1991-01-01

A capacitive proximity/tactile sensor with unique performance capabilities ('capaciflector' or capacitive reflector) is being developed by NASA/Goddard Space Flight Center (GSFC) for use on robots and payloads in space in the interests of safety, efficiency, and ease of operation. Specifically, this sensor will permit robots and their attached payloads to avoid collisions in space with humans and other objects and to dock these payloads in a cluttered environment. The sensor is simple, robust, and inexpensive to manufacture with obvious and recognized commercial possibilities. Accordingly, NASA/GSFC, in conjunction with industry, is embarking on an effort to 'spin' this technology off into the private sector. This effort includes prototypes aimed at commercial applications. The principles of operation of these prototypes are described along with hardware, software, modelling, and test results. The hardware description includes both the physical sensor in terms of a flexible printed circuit board and the electronic circuitry. The software description will include filtering and detection techniques. The modelling will involve finite element electric field analysis and will underline techniques used for design optimization.

Practical example of the infrastructure protection against rock fall

NASA Astrophysics Data System (ADS)

Jirásko, Daniel; Vaníček, Ivan

2017-09-01

The protection of transport infrastructures against rock falls represents for the Czech Republic one of the sensitive questions. Rock falls, similarly as other typical geo-hazards for the Czech Republic, as landslides and floods, can have negative impact on safety and security of these infrastructures. One practical example how to reduce risk of rock fall is described in the paper. Great care is devoted to the visual inspection enabling to indicate places with high potential to failure. With the help of numerical modelling the range of rock fall negative impact is estimated. Protection measures are dealing with two basic ways. The first one utilize the results of numerical modelling for the optimal design of protection measures and the second one is focused on the monitoring of the rock blocks with high potential of instability together with wire-less transfer of measured results. After quick evaluation, e.g. comparison with warning values, some protection measures, mostly connected with closure of the potential sector, can be recommended.

Re-treatment decisions for failed posterior fillings by Finnish general practitioners.

PubMed

Heinikainen, Mia; Vehkalahti, Miira; Murtomaa, Heikki

2002-06-01

To evaluate treatment decisions of general dental practitioners (GDPs) in the private and public sector in cases of re-treatment of failed posterior fillings. A questionnaire on six cases from 400 GDPs, selected by stratified randomisation by gender, and main occupation (public vs. private sector). Others were all full-time dental teachers (DTs; n=47) representing clinical disciplines other than surgery and orthodontics. Restorative cases were described in detail, including figures drawn on four subcases involving the first permanent upper molar where the filling to be replaced increased in size from occlusal filling to the entire clinical crown. For each case, respondents chose the optimal treatment from eight alternatives, later re-classified as amalgam restoration, direct composite restoration, prosthetic restoration (indirect composite, cast gold inlay/onlay, ceramic inlay/onlay, ceramic crown, or bridge construction following tooth extraction). For re-treatment of the occlusal filling, composite restoration was preferred both by GDPs (92%) and DTs (83%). For three-surface fillings, prosthetic restorations were dominant in the private sector (OR=2.3; 95% CI: 1.4, 3.8; P<0.001). In total loss of the clinical crown, prosthetic restoration was chosen by all the DTs, public-sector dentists, and 95% of private-sector dentists. No more than 10% of GDPs chose amalgam and 2% gold; the rest chose composites. Treatment decisions were similar in public and private sectors for cases with the smallest and largest fillings. Wide variation in cases of medium-sized restorations indicated a lack of generally accepted guidelines of good clinical practice and of evidence-based treatment practice.

Economic planning and equilibrium growth of human resources and capital in health-care sector: Case study of Iran.

PubMed

Mahboobi-Ardakan, Payman; Kazemian, Mahmood; Mehraban, Sattar

2017-01-01

During different planning periods, human resources factor has been considerably increased in the health-care sector. The main goal is to determine economic planning conditions and equilibrium growth for services level and specialized workforce resources in health-care sector and also to determine the gap between levels of health-care services and specialized workforce resources in the equilibrium growth conditions and their available levels during the periods of the first to fourth development plansin Iran. In the study after data collection, econometric methods and EViews version 8.0 were used for data processing. The used model was based on neoclassical economic growth model. The results indicated that during the former planning periods, although specialized workforce has been increased significantly in health-care sector, lack of attention to equilibrium growth conditions caused imbalance conditions for product level and specialized workforce in health-care sector. In the past development plans for health services, equilibrium conditions based on the full employment in the capital stock, and specialized labor are not considered. The government could act by choosing policies determined by the growth model to achieve equilibrium level in the field of human resources and services during the next planning periods.

Ionospheric disturbances in low- and middle-latitudes induced by neutral winds and vertical ExB drift during the 2015 St. Patrick's Day storm

NASA Astrophysics Data System (ADS)

Lee, W. K.; Kil, H.; Krall, J.

2016-12-01

Significant longitudinal and latitudinal modulations in plasma density were observed by satellites during the 17 March 2015 storm. Pronounced equatorial ionization anomaly (EIA) and ionization trough developed in the Indian sector (60°-90°E), whereas those features did not appear in the African sector (20°-40°E). Significant ionospheric uplift was observed in the Indian sector, but the uplift was ignorable in the African sector. The vertical ExB drift is an important factor for the longitudinal variation of the ionospheric morphology, but the observed latitudinal density profiles are not explained satisfactorily by the effect of the vertical ExB drift alone. In this study, we investigate the combined effect of vertical ExB drift and meridional winds by conducting SAMI2 (Sam2 is Another Model of the Ionosphere) model simulations. By comparing the model results with satellite observations, we will assess the ionospheric conditions in the Indian and African sectors. The observations of Defense Meteorological satellite Program, Swarm, and Communication/Navigation Outage Forecasting System satellites will be analyzed for this purpose.

Drops of energy: conserving urban water to reduce greenhouse gas emissions.

PubMed

Zhou, Yuanchun; Zhang, Bing; Wang, Haikun; Bi, Jun

2013-10-01

Water and energy are two essential resources of modern civilization and are inherently linked. Indeed, the optimization of the water supply system would reduce energy demands and greenhouse gas emissions in the municipal water sector. This research measured the climatic cobenefit of water conservation based on a water flow analysis. The results showed that the estimated energy consumption of the total water system in Changzhou, China, reached approximately 10% of the city's total energy consumption, whereas the industrial sector was found to be more energy intensive than other sectors within the entire water system, accounting for nearly 70% of the total energy use of the water system. In addition, four sustainable water management scenarios would bring the cobenefit of reducing the total energy use of the water system by 13.9%, and 77% of the energy savings through water conservation was indirect. To promote sustainable water management and reduce greenhouse gas emissions, China would require its water price system, both for freshwater and recycled water, to be reformed.

Exotic Gauge Bosons in the 331 Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Romero, D.; Ravinez, O.; Diaz, H.

We analize the bosonic sector of the 331 model which contains exotic leptons, quarks and bosons (E,J,U,V) in order to satisfy the weak gauge SU(3){sub L} invariance. We develop the Feynman rules of the entire kinetic bosonic sector which will let us to compute some of the Z(0)' decays modes.

Assessment of Projected Temperature Impacts from Climate Change on the U.S. Electric Power Sector Using the Integrated Planning Model

EPA Science Inventory

The energy sector is considered to be one of the most vulnerable to climate change. This study is a first-order analysis of the potential climate change impacts on the U.S. electric power sector, measuring the energy, environmental, and economic impacts of power system changes du...

Developing Future University Structures: New Funding and Legal Models. Policy Commentary

ERIC Educational Resources Information Center

Stanfield, Glynne

2009-01-01

The last decade has seen significant changes in the interaction between publicly funded higher education institutions and the private sector. This has led not only to collaborations between the public and the private sectors but also to the public higher education sector seeking to learn from and, in some instances, to replicate the private…

Distributed Leadership: A Collaborative Framework for Academics, Executives and Professionals in Higher Education

ERIC Educational Resources Information Center

Jones, Sandra; Lefoe, Geraldine; Harvey, Marina; Ryland, Kevin

2012-01-01

New models of leadership are needed for the higher education sector to continue to graduate students with leading edge capabilities. While multiple theories of leadership exist, the higher education sector requires a less hierarchical approach that takes account of its specialised and professional context. Over the last decade the sector has…

Dark spectroscopy at lepton colliders

NASA Astrophysics Data System (ADS)

Hochberg, Yonit; Kuflik, Eric; Murayama, Hitoshi

2018-03-01

Rich and complex dark sectors are abundant in particle physics theories. Here, we propose performing spectroscopy of the mass structure of dark sectors via mono-photon searches at lepton colliders. The energy of the mono-photon tracks the invariant mass of the invisible system it recoils against, which enables studying the resonance structure of the dark sector. We demonstrate this idea with several well-motivated models of dark sectors. Such spectroscopy measurements could potentially be performed at Belle II, BES-III and future low-energy lepton colliders.

Third degree waiting time discrimination: optimal allocation of a public sector healthcare treatment under rationing by waiting.

PubMed

Gravelle, Hugh; Siciliani, Luigi

2009-08-01

In many public healthcare systems treatments are rationed by waiting time. We examine the optimal allocation of a fixed supply of a given treatment between different groups of patients. Even in the absence of any distributional aims, welfare is increased by third degree waiting time discrimination: setting different waiting times for different groups waiting for the same treatment. Because waiting time imposes dead weight losses on patients, lower waiting times should be offered to groups with higher marginal waiting time costs and with less elastic demand for the treatment.

U.S. Energy Sector Impacts of Technology Innovation, Fuel Price, and Electric Sector CO 2 Policy: Results from the EMF 32 Model Intercomparison Study

DOE PAGES

Hodson, Elke L.; Brown, Maxwell; Cohen, Stuart; ...

2018-03-22

We study the impact of fuel prices, technology innovation, and a CO 2 emissions reduction policy on both the electric power and end-use sectors by comparing outputs from four U.S. energyeconomic models through the year 2050. Achieving innovation goals decreases CO 2 emissions in all models, regardless of natural gas price, due to increased energy efficiency and low-carbon generation becoming more cost competitive. For the models that include domestic natural gas markets, achieving innovation goals lowers wholesale electricity prices, but this effect diminishes as projected natural gas prices increase. Higher natural gas prices lead to higher wholesale electricity prices butmore » fewer coal capacity retirements. A CO 2 electric power sector emissions cap influences electric sector evolution under reference technology assumptions but has little to no incremental influence when added to innovation goals. Long-term, meeting innovation goals achieves a generation mix with similar CO 2 emissions compared to the CO 2 policy but with smaller increases to wholesale electricity prices. In the short-term, the relative effect on wholesale prices differs by model. Finally, higher natural gas prices, achieving innovation goals, and the combination of the two, increases the amount of renewable generation that is cost-effective to build and operate while slowing the growth of natural-gas fired generation, which is the predominant generation type in 2050 under reference conditions.« less

U.S. Energy Sector Impacts of Technology Innovation, Fuel Price, and Electric Sector CO 2 Policy: Results from the EMF 32 Model Intercomparison Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodson, Elke L.; Brown, Maxwell; Cohen, Stuart

We study the impact of fuel prices, technology innovation, and a CO 2 emissions reduction policy on both the electric power and end-use sectors by comparing outputs from four U.S. energyeconomic models through the year 2050. Achieving innovation goals decreases CO 2 emissions in all models, regardless of natural gas price, due to increased energy efficiency and low-carbon generation becoming more cost competitive. For the models that include domestic natural gas markets, achieving innovation goals lowers wholesale electricity prices, but this effect diminishes as projected natural gas prices increase. Higher natural gas prices lead to higher wholesale electricity prices butmore » fewer coal capacity retirements. A CO 2 electric power sector emissions cap influences electric sector evolution under reference technology assumptions but has little to no incremental influence when added to innovation goals. Long-term, meeting innovation goals achieves a generation mix with similar CO 2 emissions compared to the CO 2 policy but with smaller increases to wholesale electricity prices. In the short-term, the relative effect on wholesale prices differs by model. Finally, higher natural gas prices, achieving innovation goals, and the combination of the two, increases the amount of renewable generation that is cost-effective to build and operate while slowing the growth of natural-gas fired generation, which is the predominant generation type in 2050 under reference conditions.« less

Overview of the Special Issue: A Multi-Model Framework to ...

EPA Pesticide Factsheets

The Climate Change Impacts and Risk Analysis (CIRA) project establishes a new multi-model framework to systematically assess the impacts, economic damages, and risks from climate change in the United States. The primary goal of this framework to estimate how climate change impacts and damages in the United States are avoided or reduced due to global greenhouse gas (GHG) emissions mitigation scenarios. Scenarios are designed to explore key uncertainties around the measurement of these changes. The modeling exercise presented in this Special Issue includes two integrated assessment models and 15 sectoral models encompassing six broad impacts sectors - water resources, electric power, infrastructure, human health, ecosystems, and forests. Three consistent emissions scenarios are used to analyze the benefits of global GHG mitigation targets: a reference and two policy scenarios, with total radiative forcing in 2100 of 10.0W/m2, 4.5W/m2, and 3.7W/m2. A range of climate sensitivities, climate models, natural variability measures, and structural uncertainties of sectoral models are examined to explore the implications of key uncertainties. This overview paper describes the motivations, goals, design, and academic contribution of the CIRA modeling exercise and briefly summarizes the subsequent papers in this Special Issue. A summary of results across impact sectors is provided showing that: GHG mitigation provides benefits to the United States that increase over

Future Water Management in the South Platte River Basin: Impacts of Hydraulic Fracturing, Population, Agriculture, and Climate Change in a Semi-Arid Region.

NASA Astrophysics Data System (ADS)

Walker, E. L.; Hogue, T. S.; Anderson, A. M.; Read, L.

2015-12-01

In semi-arid basins across the world, the gap between water supply and demand is growing due to climate change, population growth, and shifts in agriculture and unconventional energy development. Water conservation efforts among residential and industrial water users, recycling and reuse techniques and innovative regulatory frameworks for water management strive to mitigate this gap, however, the extent of these strategies are often difficult to quantify and not included in modeling water allocations. Decision support systems (DSS) are purposeful for supporting water managers in making informed decisions when competing demands create the need to optimize water allocation between sectors. One region of particular interest is the semi-arid region of the South Platte River basin in northeastern Colorado, where anthropogenic and climatic effects are expected to increase the gap between water supply and demand in the near future. Specifically, water use in the South Platte is impacted by several high-intensity activities, including unconventional energy development, i.e. hydraulic fracturing, and large withdrawals for agriculture; these demands are in addition to a projected population increase of 100% by 2050. The current work describes the development of a DSS for the South Platte River basin, using the Water Evaluation and Planning system software (WEAP) to explore scenarios of how variation in future water use in the energy, agriculture, and municipal sectors will impact water allocation decisions. Detailed data collected on oil and gas water use in the Niobrara shale play will be utilized to predict future sector use. We also employ downscaled climate projections for the region to quantify the potential range of water availability in the basin under each scenario, and observe whether or not, and to what extent, climate may impact management decisions at the basin level.

U.S. energy sector impacts of technology innovation, fuel price, and electric sector CO 2 policy: Results from the EMF 32 model intercomparison study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hodson, Elke L.; Brown, Maxwell; Cohen, Stuart

We study the impact of achieving technology innovation goals, representing significant technology cost reductions and performance improvements, in both the electric power and end-use sectors by comparing outputs from four energy-economic models through the year 2050. We harmonize model input assumptions and then compare results in scenarios that vary natural gas prices, technology cost and performance metrics, and the implementation of a representative national electricity sector carbon dioxide (CO 2) policy. Achieving the representative technology innovation goals decreases CO 2 emissions in all models, regardless of natural gas price, due to increased energy efficiency and low-carbon generation becoming more costmore » competitive. For the models that include domestic natural gas markets, achieving the technology innovation goals lowers wholesale electricity prices, but this effect diminishes as projected natural gas prices increase. Higher natural gas prices lead to higher wholesale electricity prices but fewer coal capacity retirements. Some of the models include energy efficiency improvements as part of achieving the high-technology goals. Absent these energy efficiency improvements, low-cost electricity facilitates greater electricity consumption. The effect of implementing a representative electricity sector CO 2 policy differs considerably depending on the cost and performance of generating and end-use technologies. The CO 2 policy influences electric sector evolution in the cases with reference technology assumptions but has little to no influence in the cases that achieve the technology innovation goals. This outcome implies that meeting the representative technology innovation goals achieves a generation mix with similar CO 2 emissions to the representative CO 2 policy but with smaller increases to wholesale electricity prices. Finally, higher natural gas prices, achieving the representative technology innovation goals, and the combination of the two, increases the amount of renewable generation that is cost-effective to build and operate while slowing the growth of natural-gas fired generation, which is the predominant generation type in 2050 under reference conditions.« less

A Parameterized Pattern-Error Objective for Large-Scale Phase-Only Array Pattern Design

DTIC Science & Technology

2016-03-21

12 4.4 Example 3: Sector Beam w/ Nonuniform Amplitude...fixed uniform amplitude illumination, phase-only optimization can also find application to arrays with fixed but nonuniform tapers. Such fixed tapers...arbitrary element locations nonuniform FFT algorithms exist [43–45] that have the same asymptotic complexity as the conventional FFT, although the

Modern Languages and Interculturality in the Primary Sector in England, Greece, Italy and Spain.

ERIC Educational Resources Information Center

Cerezal, Fernando

1997-01-01

Addresses concerns and issues regarding modern language teaching and learning at primary schools in Greece, Italy, Spain, and England. It focuses on the optimal age for learning and acquiring languages and to the educational reforms which have been undertaken in each country relating to early modern language teaching and learning and…

Throughput analysis for the National Airspace System

NASA Astrophysics Data System (ADS)

Sureshkumar, Chandrasekar

The United States National Airspace System (NAS) network performance is currently measured using a variety of metrics based on delay. Developments in the fields of wireless communication, manufacturing and other modes of transportation like road, freight, etc. have explored various metrics that complement the delay metric. In this work, we develop a throughput concept for both the terminal and en-route phases of flight inspired by studies in the above areas and explore the applications of throughput metrics for the en-route airspace of the NAS. These metrics can be applied to the NAS performance at each hierarchical level—the sector, center, regional and national and will consist of multiple layers of networks with the bottom level comprising the traffic pattern modelled as a network of individual sectors acting as nodes. This hierarchical approach is especially suited for executive level decision making as it gives an overall picture of not just the inefficiencies but also the aspects where the NAS has performed well in a given situation from which specific information about the effects of a policy change on the NAS performance at each level can be determined. These metrics are further validated with real traffic data using the Future Air Traffic Management Concepts Evaluation Tool (FACET) for three en-route sectors and an Air Route Traffic Control Center (ARTCC). Further, this work proposes a framework to compute the minimum makespan and the capacity of a runway system in any configuration. Towards this, an algorithm for optimal arrival and departure flight sequencing is proposed. The proposed algorithm is based on a branch-and-bound technique and allows for the efficient computation of the best runway assignment and sequencing of arrival and departure operations that minimize the makespan at a given airport. The lower and upper bounds of the cost of each branch for the best first search in the branch-and-bound algorithm are computed based on the minimum separation standards between arrival and departure operations set by the Federal Aviation Administration. The optimal objective value is mathematically proved to lie between these bounds and the algorithm uses these bounds to efficiently find promising branches and discard all others and terminate with atleast one sequence with the minimal makespan. The proposed algorithm is analyzed and validated through real traffic operations data at the Hartsfield-Jackson Atlanta international airport.

Assessing HIV risk in workplaces for prioritizing HIV preventive interventions in Karnataka State, India.

PubMed

Halli, Shiva S; Buzdugan, Raluca; Ramesh, B M; Gurnani, Vandana; Sharma, Vivek; Moses, Stephen; Blanchard, James F

2009-09-01

To develop a model for prioritizing economic sectors for HIV preventive intervention programs in the workplace. This study was undertaken in Karnataka state, India. A 3-stage survey process was undertaken. In the first stage, we reviewed secondary data available from various government departments, identified industries in the private sector with large workforces, and mapped their geographical distribution. In the second stage, an initial rapid risk assessment of industrial sectors was undertaken, using key-informant interviews conducted in relation to a number of enterprises, and in consultation with stakeholders. In the third stage, we used both quantitative (polling booth survey) and qualitative methods (key informant interviews, in-depth interviews, focus group discussions) to study high-risk sectors in-depth, and assessed the need and feasibility of HIV workplace intervention programs. The highest risk sectors were found to be mining, garment/textile, sugar, construction/infrastructure, and fishing industries. Workers in all sectors had at best partial knowledge about HIV/AIDS, coupled with common misconceptions about HIV transmission. There were intersector and intrasector variations in risk and vulnerability across different geographical locations and across different categories of workers. This has implications for the design and implementation of workplace intervention programs. There is tremendous scope for HIV preventive interventions in workplaces in India. Given the variation in HIV risk across economic sectors and limited available resources, there will be increased pressure to prioritize intervention efforts towards high-risk sectors. This study offers a model for rapidly assessing the risk level of economic sectors for HIV intervention programs.

Environmental sub models for a macroeconomic model: agricultural contribution to climate change and acidification in Denmark.

PubMed

Jensen, Trine S; Jensen, Jørgen D; Hasler, Berit; Illerup, Jytte B; Andersen, Frits M

2007-01-01

Integrated modelling of the interaction between environmental pressure and economic development is a useful tool to evaluate environmental consequences of policy initiatives. However, the usefulness of such models is often restricted by the fact that these models only include a limited set of environmental impacts, which are often energy-related emissions. In order to evaluate the development in the overall environmental pressure correctly, these model systems must be extended. In this article an integrated macroeconomic model system of the Danish economy with environmental modules of energy related emissions is extended to include the agricultural contribution to climate change and acidification. Next to the energy sector, the agricultural sector is the most important contributor to these environmental themes and subsequently the extended model complex calculates more than 99% of the contribution to both climate change and acidification. Environmental sub-models are developed for agriculture-related emissions of CH(4), N(2)O and NH(3). Agricultural emission sources related to the production specific activity variables are mapped and emission dependent parameters are identified in order to calculate emission coefficients. The emission coefficients are linked to the economic activity variables of the Danish agricultural production. The model system is demonstrated by projections of agriculture-related emissions in Denmark under two alternative sets of assumptions: a baseline projection of the general economic development and a policy scenario for changes in the husbandry sector within the agricultural sector.

High-Fidelity Aerostructural Optimization of Nonplanar Wings for Commercial Transport Aircraft

NASA Astrophysics Data System (ADS)

Khosravi, Shahriar

Although the aerospace sector is currently responsible for a relatively small portion of global anthropogenic greenhouse gas emissions, the growth of the airline industry raises serious concerns about the future of commercial aviation. As a result, the development of new aircraft design concepts with the potential to improve fuel efficiency remains an important priority. Numerical optimization based on high-fidelity physics has become an increasingly attractive tool over the past fifteen years in the search for environmentally friendly aircraft designs that reduce fuel consumption. This approach is able to discover novel design concepts and features that may never be considered without optimization. This can help reduce the economic costs and risks associated with developing new aircraft concepts by providing a more realistic assessment early in the design process. This thesis provides an assessment of the potential efficiency improvements obtained from nonplanar wings through the application of fully coupled high-fidelity aerostructural optimization. In this work, we conduct aerostructural optimization using the Euler equations to model the flow along with a viscous drag estimate based on the surface area. A major focus of the thesis is on finding the optimal shape and performance benefits of nonplanar wingtip devices. Two winglet configurations are considered: winglet-up and winglet-down. These are compared to optimized planar wings of the same projected span in order to quantify the possible drag reductions offered by winglets. In addition, the drooped wing is studied in the context of exploratory optimization. The main results show that the winglet-down configuration is the most efficient winglet shape, reducing the drag by approximately 2% at the same weight in comparison to a planar wing. There are two reasons for the superior performance of this design. First, this configuration moves the tip vortex further away from the wing. Second, the winglet-down concept has a higher projected span at the deflected state due to the structural deflections. Finally, the exploratory optimization studies lead to a drooped wing with the potential to increase range by 4.9% relative to a planar wing.

Distributed and Centralized Conflict Management Under Traffic Flow Management Constraints

NASA Technical Reports Server (NTRS)

Feron, Eric; Bilimoria, Karl (Technical Monitor)

2001-01-01

The past year's activity has concentrated on the following two activities: (1) Refining and completing our study on the stability of interacting flows of aircraft when they have to resolve conflicts in a decentralized and sequential manner. More specifically, it was felt that some of the modeling assumptions made during previous research (such offset maneuvering models) could be improved to include more realistic models such as heading changes when analyzing interacting flow stability problems. We extended our analysis to achieve this goal. The results of this study have been submitted for presentation at the 2002 American Control Conference; (2) Examining the issues associated with delay propagation across multiple enroute sectors. This study was initiated at NASA in cooperation with Dr. Karl Bilimoria. Considering a set of adjacent sectors, this ongoing study concentrates on the effect of various traffic flow management strategies on the propagation of delays and congestion across sectors. The problem description and findings so far are reported in the attached working paper "Enroute sector buffering capacity."