Economic Penalties Research Articles

Identifying Optimal Water Resources Allocation Strategies through an Interactive Multi-Stage Stochastic Fuzzy Programming Approach

In this study, an interactive multi-stage stochastic fuzzy programming (IMSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact multi-stage stochastic programming framework. IMSFP can deal with dual uncertainties expressed as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints. Moreover, IMSFP is capable of reflecting dynamics of uncertainties and the related decision processes through constructing a set of representative scenarios within a multi-stage context. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees (i.e., risk of constraint violation) has been generated for planning the water resources allocation. They can not only help quantify the relationship between the objective-function value and the risk of violating the constraints, but also enable decision makers (DMs) to identify, in an interactive way, a desired compromise between two factors in conflict: satisfaction degree of the goal and feasibility degree of constraints. Besides, a number of decision alternatives have been generated under different policies for water resources management, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised water-allocation targets are violated, and thus help DMs to identify desired water-allocation schemes under uncertainty.

Optimization of the irrigation water resources for agricultural sustainability in Tarim River Basin, China

An integrated optimization method is developed for supporting agriculture water management and planning in Tarim River Basin, Northwest China. The developed method couples two-stage stochastic programming (TSP) with inexact quadratic program (IQP). The hydrological model is provided for forecasting the available irrigation water. The simulation system is then embedded into an optimization framework, where the objective is to maximize the system benefit for water resources management. The developed method can not only deal with nonlinearities in the cost/benefit objective and uncertainties expressed as probabilities and intervals, but also support the analysis of policy scenarios that are associated with economic penalties when the promised water-allocation targets are violated. A case study is conducted for Kaidu-kongque watershed in Tarim River Basin. The results obtained can help generate desired policies for water resources management with maximized economic benefit and minimized system-failure risk.

Optimisation of real time operation of a multi-reservoir system in an electricity market contest

this paper presents the new tool OASI (Italian acronym for Optimisation of a multi-reservoir system) which is used by ENEL to optimize the real time operation of a multi reservoir system in the context of electricity market. The objective of the optimisation is to minimise the economic penalties which are charged according to the market rules if the power producer is not able to respect the energy plans scheduled by the market for each 15 minutes of the day of delivery. The optimisation is referred to the interconnected hydraulic system and, besides routine activities, is triggered any time there is the need of a new rescheduling of the production of the day, due for instance to external factors such as sudden outage of generators or actual natural flows quite different from the forecasted ones. Examples are provided about the application of the optimisation of a hydraulic system in a typical real time situation.

An interval-valued fuzzy-stochastic programming approach and its application to municipal solid waste management

In this study, an interval-valued fuzzy-stochastic programming (IVFSP) approach is developed for municipal solid waste (MSW) management under uncertainty. IVFSP can tackle multiple uncertainties presented as intervals as well as possibilistic and probabilistic distributions. The adoption of interval-valued fuzzy sets is capable of reflecting waste managers’ confidence levels over subjective judgments, and can thus enhance the system robustness. An infinite α-cuts method is employed for discretizing the interval-valued fuzzy sets in IVFSP. Such a method can communicate all fuzzy information into the optimization process without ignoring valuable uncertain information. Moreover, IVFSP can permit in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised waste-allocation targets are violated. The developed approach is applied to a MSW management problem to demonstrate its applicability. The results indicate that interval solutions associated with different risk levels of constraint violation have been generated. They can help waste managers to identify desired waste-flow-allocation schemes and capacity-expansion plans according to their preference and practical conditions, as well as facilitate in-depth analyses of tradeoffs between economic efficiency and constraint-violation risk.

The self-limiting success of Iran sanctions

Economic sanctions have often been considered an important tool for disciplining adversaries and compelling them to offer important concessions. History, however, suggests otherwise. Economic penalties rarely cause states to abandon important national assets. After decades of struggling under punitive financial measures, Iran has persisted with its objectionable policies ranging from terrorism to proliferation of weapons of mass destruction. All this suggests that ideological regimes that put a premium on their political priorities and which are seemingly insensitive to the mounting costs of their belligerence may not be suitable candidates for the type of cost-benefit analysis that sanctions diplomacy invites.

Status incongruity and backlash effects: Defending the gender hierarchy motivates prejudice against female leaders

Agentic female leaders risk social and economic penalties for behaving counter-stereotypically (i.e., backlash; Rudman, 1998), but what motivates prejudice against female leaders? The status incongruity hypothesis (SIH) proposes that agentic women are penalized for status violations because doing so defends the gender hierarchy. Consistent with this view, Study 1 found that women are proscribed from dominant, high status displays (which are reserved for leaders and men); Studies 2–3 revealed that prejudice against agentic female leaders was mediated by a dominance penalty; and in Study 3, participants' gender system-justifying beliefs moderated backlash effects. Study 4 found that backlash was exacerbated when perceivers were primed with a system threat. Study 5 showed that only female leaders who threatened the status quo suffered sabotage. In concert, support for the SIH suggests that backlash functions to preserve male dominance by reinforcing a double standard for power and control.

Simulation of catalyst loss from an industrial fluidized bed reactor on the basis of labscale attrition tests

Attrition of catalyst represents a significant economic penalty due to the necessity to make-up the losses on a continual basis. Designing fluidized bed systems to minimize attrition may sacrifice gas–solid contact efficiency that requires pressure to distribute gases in process vessels uniformly. In this paper, the attrition performance of DuPont's vanadium pyrophosphate oxide catalyst (VPP) used in their commercial Circulating Fluidized Bed (CFB) process to convert n-butane to maleic anhydride has been examined. The analysis is based on simulating the commercial conditions in the individual vessels combined with the physical characteristics of the catalyst determined in the laboratory. The comparison of the catalyst loss rate measured in the industrial plant and the simulation results indicates that the measured values are below the values predicted by the simulation. However, the relative change in the catalyst loss rate with operating time is well described. The simulation allows the quantification of the attrition sources in the process. The simulation results revealed that in the present case over 60% of the catalyst loss originates from attrition in the fluidized beds, whereas only 16% originates from attrition in the cyclones. The simulation is an appropriate tool to investigate the influence of parameter changes. Using the simulation the design parameters and operating conditions can be optimized to minimize the catalyst loss rate in the industrial plant.

Mild Hydrotreating of Bio-Oil: Effect of Reaction Severity and Fate of Oxygenated Species

Bio-oil derived by fast pyrolysis of biomass represents a potentially attractive source of hydrocarbon transportation fuels. Raw bio-oil however is completely unsuitable for application as a fuel due primarily to high organic oxygen content, which imparts a number of undesirable properties including high acidity and low stability. These problems can be overcome by catalytic hydrodeoxygenation (HDO); however, removing oxygen to very low levels by hydrotreating carries a strong economic penalty. Mild hydrotreating (where moderate levels of deoxygenation take place) coupled with coprocessing in a petroleum refinery represents an alternative to deep hydrotreating, which may help improve the economics of manufacture of hydrocarbon transportation fuels from biomass. This study reports on the effect of reaction severity on the quality of bio-oil produced via mild hydrotreating in a semibatch reactor using conventional hydroprocessing catalysts. Detailed speciation of oxygen functional groups in distillate and bo...

Inexact fuzzy two-stage programming for water resources management in an environment of fuzziness and randomness

A standard lower-side attainment values based inexact fuzzy two-stage programming (SLA-IFTSP) approach is proposed for supporting multi-water resources management under multi-uncertainties. The method improves upon the existing inexact two-stage stochastic programming by the introduction of a standard average lower-side attainment values based fuzzy linear programming. Multi-uncertainties such as intervals, probabilistic and/or possibilistic distributions and their combinations in water resources management can be directly communicated into the water allocation process. The risk of infeasibility caused by the random water availabilities can be analyzed by imposing economic penalties when the designed water allocations would not be satisfied after the occurrence of random seasonal flows. Based on the standard average lower-side attainment index, the fuzzy random relationships representing various subjective judgments in the model can be transformed into corresponding deterministic ones without additional constraints, and thus guarantee a higher computational efficiency. A hypothetical case regarding two-source water resources management is adopted for demonstrating its applicability. Reasonable solutions have been generated. They provide desired water allocations with maximized system benefit under different water availability levels. The solutions of intervals with different probabilities can be used for generating decision alternatives. Comparisons between the solutions from SLA-IFTSP and those from ITSP are also undertaken. They show that SLA-IFTSP can generate more reasonable water allocation patterns with higher net system benefits than ITSP.

Optimum nitrogen fertilization rates for second-year corn succeeding alfalfa under irrigation

The N contribution of alfalfa ( Medicago sativa L.) to the succeeding corn ( Zea mays L.) crop (FYC) is widely recognized. However, there is less information regarding the optimum N fertilization rates (ONR) for a second-year corn (SYC) following alfalfa. Thus, the objective of this study was to evaluate the response of SYC after alfalfa to N fertilization under irrigated semiarid conditions. Three field experiments of SYC following alfalfa were conducted between 2007 and 2009 in Northeast Spain. Treatments included the combination of six N rates applied to FYC (0, 50, 100, 150, 200, and 300 kg N ha −1) with four N rates applied to SYC (0, 100, 200, and 300 kg N ha −1). In one of the three fields, high SYC yields (16.8 Mg ha −1) were obtained in plots that remained unfertilized during two consecutive years after alfalfa. On the other two fields, 81–100% of the maximum corn yields were obtained with application of 200 kg N ha −1 to SYC. Results suggest that the typical N fertilizer rates applied to SYC after alfalfa in irrigated semiarid areas (300 kg N ha −1) could be reduced by at least 100 kg N ha −1, with small or no economic penalties and important reductions in N losses.

A recourse-based nonlinear programming model for stream water quality management

A recourse-based nonlinear programming (RBNP) method is developed for stream water quality management under uncertainty. It can not only reflect uncertainties expressed as interval values and probability distributions but also address nonlinearity in the objective function. A 0-1 piecewise linearization approach and an interactive algorithm are advanced for solving the RBNP model. The RBNP is applied to a case of planning stream water quality management. The RBNP modeling system can provide an effective linkage between environmental regulations and economic implications expressed as penalties or opportunity losses caused by improper policies. The solutions can be used for generating a variety of alternatives under different combinations of pre-regulated targets, which are also associated with different water-quality-violation risk levels and varied potential economic penalty or loss values.

Interactive two-stage stochastic fuzzy programming for water resources management

In this study, an interactive two-stage stochastic fuzzy programming (ITSFP) approach has been developed through incorporating an interactive fuzzy resolution (IFR) method within an inexact two-stage stochastic programming (ITSP) framework. ITSFP can not only tackle dual uncertainties presented as fuzzy boundary intervals that exist in the objective function and the left- and right-hand sides of constraints, but also permit in-depth analyses of various policy scenarios that are associated with different levels of economic penalties when the promised policy targets are violated. A management problem in terms of water resources allocation has been studied to illustrate applicability of the proposed approach. The results indicate that a set of solutions under different feasibility degrees has been generated for planning the water resources allocation. They can help the decision makers (DMs) to conduct in-depth analyses of tradeoffs between economic efficiency and constraint-violation risk, as well as enable them to identify, in an interactive way, a desired compromise between satisfaction degree of the goal and feasibility of the constraints (i.e., risk of constraint violation).

Trends in the development of environmentally friendly fouling-resistant marine coatings

'Marine biofouling', the undesired growth of marine organisms such as microorganisms, barnacles and seaweeds on submerged surfaces, is a global problem for maritime industries, with both economic and environmental penalties. The primary strategy for combating marine fouling is to use biocide-containing paints, but environmental concerns and legislation are driving science and technology towards non-biocidal solutions based solely on physico-chemical and materials properties of coatings. Advances in nanotechnology and polymer science, and the development of novel surface designs 'bioinspired' by nature, are expected to have a significant impact on the development of a new generation of environmentally friendly marine coatings.

Towards autonomic management for Cloud services based upon volunteered resources

SUMMARYMany research institutions and Universities own computational capacity that is not effectively utilized, thereby providing an opportunity for such institutions to use such capacity to offer Cloud services (to both internal and external users). However, the unreliability and unpredictability of these resources mean that their use in the context of a Service Level Agreement (SLA) is high risk, leading to a reduction in reputation as well as economic penalties in case of SLA violation. We propose a methodology that addresses the issues of unreliability and unpredictability such that Cloud software services could be hosted upon volunteered resources. To enable the harnessing of these resources we rely on autonomic fault management techniques that allow such systems to independently adapt the resources they use based upon their perception of individual resource reliability. Using our approach we were able to scale out the backend infrastructure of the Cloud service elastically (min 30thinspaces per worker), opportunistically and autonomically. We address two key questions in this article: can a campus volunteer infrastructure be used in Cloud provisioning? What measures are necessary in order to ensure reliability at the resource level? Copyright © 2011 John Wiley & Sons, Ltd.

Dummy Variable Model Analysis With Law Factors on Safety Production in Chinese Coal Mine Industry

This paper investigates the security role of “three laws and one regulation” (PRC Mine Safety Law, PRC Coal Law, PRC Safety Production Law and the Regulation of Reporting and Investigating Production Accident) on coal mine safety production in China through a dummy variable model analysis. The results show that the security role of “three laws and one regulation” made the death rate reduced by 0.895 persons per million tons coal. The terms of economic penalties and sanctions would be closely consistent with the level of economic development, and the stronger law enforcement, the better its implementation result.

Physiological and cellular aspects of phytotoxicity tolerance in plants: the role of membrane transporters and implications for crop breeding for waterlogging tolerance

Waterlogging affects large areas of agricultural land, resulting in severe economic penalties because of massive losses in crop production. Traditionally, plant breeding for waterlogging tolerance has been based on the field assessment of a range of agronomic and morphological characteristics. This review argues for a need to move towards more physiologically based approaches by targeting specific cellular mechanisms underling key components of waterlogging tolerance in plants. Also, while the main focus of researchers was predominantly on plant anoxia tolerance, less attention was given to plant tolerance to phytotoxins under waterlogged conditions. This paper reviews the production of major elemental and organic phytotoxins in waterlogged soils and describes their adverse effects on plant performance. The critical role of plasma membrane transporters in plant tolerance to secondary metabolite toxicity is highlighted, and ionic mechanisms mediating the this tolerance are discussed. A causal link between the secondary metabolite-induced disturbances to cell ionic homeostasis and programmed cell death is discussed, and a new ethylene-independent pathway for aerenchyma formation is put forward. It is concluded that plant breeding for waterlogging tolerance may significantly benefit from targeting mechanisms of tolerance to phytotoxins.

A two-stage inexact joint-probabilistic programming method for air quality management under uncertainty

A two-stage inexact joint-probabilistic programming (TIJP) method is developed for planning a regional air quality management system with multiple pollutants and multiple sources. The TIJP method incorporates the techniques of two-stage stochastic programming, joint-probabilistic constraint programming and interval mathematical programming, where uncertainties expressed as probability distributions and interval values can be addressed. Moreover, it can not only examine the risk of violating joint-probability constraints, but also account for economic penalties as corrective measures against any infeasibility. The developed TIJP method is applied to a case study of a regional air pollution control problem, where the air quality index (AQI) is introduced for evaluation of the integrated air quality management system associated with multiple pollutants. The joint-probability exists in the environmental constraints for AQI, such that individual probabilistic constraints for each pollutant can be efficiently incorporated within the TIJP model. The results indicate that useful solutions for air quality management practices have been generated; they can help decision makers to identify desired pollution abatement strategies with minimized system cost and maximized environmental efficiency.

Religion as resource: Religion and immigrant economic incorporation

Much of the immigration literature in the United States points toward a positive association between religious activity and immigrant economic adaptation. Immigrant congregations serve as informal job fairs, build social capital for entrepreneurial activity, and provide a locale for leadership skill development. Using the New Immigrant Survey, this hypothesis of religion as economic resource is tested among immigrants receiving permanent residency within the United States in 2003. Somewhat surprisingly, most findings indicate a null relationship between religion and economic outcomes (i.e. employment, occupation status, and earnings). However, in instances where a significant relationship does exist, non-Protestant immigrants suffer the greatest economic penalty, particularly among non-Protestants who are not regularly participating in a religious organization. In contrast, non-Protestants who regularly participate have a higher likelihood of employment and higher earnings than their non-participating counterparts. Therefore, this paper extends previous literature in specifying that the religion as resource hypothesis operates best for non-Protestant immigrants who are actively involved in their religious organizations.

Prejudice Toward Female Leaders: Backlash Effects and Women’s Impression Management Dilemma

Women who pursue or possess power are at risk for backlash, defined as social and economic penalties for defying stereotypic expectations (Rudman, 1998). Rule-based gender stereotypes stipulate acceptable behaviors for women and men and when these rules are violated, perceivers react negatively. We review research demonstrating the Catch-22 that female leaders face, such that they are required to display agency to overcome the lack of fit between their gender and leadership yet when they do so, they risk prejudice and hiring discrimination (i.e., backlash). Our review reveals how this dilemma encumbers women in all aspects of their career. We consider factors that moderate the likelihood of backlash effects and describe recent research that sheds light on the mechanisms responsible for negative reactions toward women striving for positions of power. Finally, we discuss the implications of backlash for preserving stereotypes in the culture-at-large and the gender status quo and suggest directions for future research.

The sustainability of clean coal technology: IGCC with/without CCS

Integrated gasification combined cycle power generation (IGCC) is one of the emerging clean coal technologies for reducing greenhouse emissions in coal-fired electricity generation. IGCC technology, both with and without CO 2 capture and storage (CCS) is compared with conventional super-critical power generation based on pulverized coal. The comparison is based on an equal consumption rate of Queensland black coal. The sustainability parameters being investigated are: thermal efficiency, environmental performance, inherent safety and economics. The IGCC processes have been modeled using commercial steady-state mass and energy balance software. Both the gross and net thermal efficiencies of the IGCC power station are reduced when the plant is configured for CCS. The net efficiency is reduced from 32.1% to 26.1%, when 81% of the CO 2 is captured. This delivers an overall reduction in CO 2 emissions per unit of electrical energy output of 73.2% compared to the reference plant. However, environmental performance in other areas suffers as a result of switching to IGCC-CCS, particularly fresh water consumption is increased by 2.5 tonne/MWh for both coastal and inland locations. Inherent safety risks associated with IGCC are also greater with the gasifier being the highest risk unit in the facility with a Dow fire and explosion index of 168 compared with an index of 107 for a conventional boiler. Toxicity hazard also increases with carbon monoxide present at concentrations several thousand times higher than the TWA limit. The minimum viable selling price of electricity for a 7% IRR is calculated to increase from USD80 MWh −1 for a conventional power station to USD101 MWh −1 for IGCC and to USD145 MWh −1 for IGCC-CCS. It is concluded that the application of IGCC-CCS is highly effective in reducing carbon dioxide emissions, the highest-profile problem associated with coal-fired electricity. There is an economic penalty which has been previously documented. However, there are also drawbacks concerning inherent safety and other environmental factors apart from CO 2 emissions, which until now have been under emphasized.