Assessing Environmental Externalities of the US Coal Base Load Electric Utility Industry Using Data Enveloping Analysis

This paper attempts to address two issues. First, is how to objectively measure carbon dioxide emissions from the generation of electricity that uses predominantly coal. Second, is how to incorporate these ‘environmental’ variables into an efficiency model. Using a technique called Data Enveloping Analysis (DEA) a non-parametric piecewise surface (or frontier) over the data is constructed, so as to be able to calculate technical efficiencies (which I call environmental efficiency) relative to this surface. These ‘environmental efficiency’ measures are analyzed. The technique utilized in this study may be extended to calculate each agent’s allocative and scale efficiencies in order to calculate a shadow price for carbon dioxide emissions and to formulate a preliminary permits scheme for carbon dioxide emissions generated by electric utilities

Unobserved State Fragility and the Political Transfer Problem

Autocrats experiencing a windfall in unearned income may find it optimal to donate to other countries some of the windfall in order to make the state a less attractive prize to potential insurgents. We put forward a model that makes that prediction, as well as the additional predictions that the recipients of the aid may themselves become more repressive with high levels of aid and experience conflict with medium levels of aid. We call these joint phenomena the political transfer problem, and argue that the largest windfall of the 20th century, the period from 1973-85 during which oil prices were at all-time highs, produced long-run political dynamics consistent with the model. In particular, major oil exporters have been politically repressive, generous with foreign aid when oil prices are high, and free of civil war; in contrast, the recipients of petro aid were relatively repressive (and peaceful) during the period of high oil prices, but subject to civil war when oil prices fell and aid was reduced. Surprisingly, the political transfer problem did not seem to materialize when oil prices again began to creep up in the 21st century; this nonexistence of the problem can be explained by the model against the backdrop of evolving geopolitics and economics

Fuel cells as an energy source for desalination applications.

Nowadays, there is a renewed interest in fuel cell technology from industry and academia, electrochemistry and catalysis scientists. This interest is due to environmental legislations for CO2 and other greenhouse gases emissions (United Nations Environment Programme and the World Trade Organization, 2009) that demand the use of high efficiency energy production systems. Such systems have great potential in the area of desalination technology (Kenet, 2003, Al-Hallaj et al., 2004, Singh, 2008, Wang et al. 2011, Jones, 2013). Fuel cells are characterised by high operation efficiency, which results in decreased fuel consumption, and low environmental impact. A fuel cell is a device that converts the chemical energy of a fuel directly into electricity through electrochemical reactions, with low waste heat (e.g. SOFC in Fig. 1). The first fuel cell was fabricated back in 1830's, and slow but steady progress has been made toward their commercialization since then

Groundwater level prediction using a multiple objective genetic algorithm-grey relational analysis based weighted ensemble of anfis models

Predicting groundwater levels is critical for ensuring sustainable use of an aquifer’s limited groundwater reserves and developing a useful groundwater abstraction management strategy. The purpose of this study was to assess the predictive accuracy and estimation capability of various models based on the Adaptive Neuro Fuzzy Inference System (ANFIS). These models included Differential Evolution-ANFIS (DE-ANFIS), Particle Swarm Optimization-ANFIS (PSO-ANFIS), and traditional Hybrid Algorithm tuned ANFIS (HA-ANFIS) for the one-and multi-week forward forecast of groundwater levels at three observation wells. Model-independent partial autocorrelation functions followed by frequentist lasso regression-based feature selection approaches were used to recognize appropriate input variables for the prediction models. The performances of the ANFIS models were evaluated using various statistical performance evaluation indexes. The results revealed that the optimized ANFIS models performed equally well in predicting one-week-ahead groundwater levels at the observation wells when a set of various performance evaluation indexes were used. For improving prediction accuracy, a weighted-average ensemble of ANFIS models was proposed, in which weights for the individual ANFIS models were calculated using a Multiple Objective Genetic Algorithm (MOGA). The MOGA accounts for a set of benefits (higher values indicate better model performance) and cost (smaller values indicate better model performance) performance indexes calculated on the test dataset. Grey relational analysis was used to select the best solution from a set of feasible solutions produced by a MOGA. A MOGA-based individual model ranking revealed the superiority of DE-ANFIS (weight = 0.827), HA-ANFIS (weight = 0.524), and HAANFIS (weight = 0.697) at observation wells GT8194046, GT8194048, and GT8194049, respectively. Shannon’s entropy-based decision theory was utilized to rank the ensemble and individual ANFIS models using a set of performance indexes. The ranking result indicated that the ensemble model outperformed all individual models at all observation wells (ranking value = 0.987, 0.985, and 0.995 at observation wells GT8194046, GT8194048, and GT8194049, respectively). The worst performers were PSO-ANFIS (ranking value = 0.845), PSO-ANFIS (ranking value = 0.819), and DE-ANFIS (ranking value = 0.900) at observation wells GT8194046, GT8194048, and GT8194049, respectively. The generalization capability of the proposed ensemble modelling approach was evaluated for forecasting 2-, 4-, 6-, and 8-weeks ahead groundwater levels using data from GT8194046. The evaluation results confirmed the useability of the ensemble modelling for forecasting groundwater levels at higher forecasting horizons. The study demonstrated that the ensemble approach may be successfully used to predict multi-week-ahead groundwater levels, utilizing previous lagged groundwater levels as inputs

Physical Aspects of Pseudo-Hermitian and PTPT-Symmetric Quantum Mechanics

For a non-Hermitian Hamiltonian H possessing a real spectrum, we introduce a canonical orthonormal basis in which a previously introduced unitary mapping of H to a Hermitian Hamiltonian h takes a simple form. We use this basis to construct the observables O of the quantum mechanics based on H. In particular, we introduce pseudo-Hermitian position and momentum operators and a pseudo-Hermitian quantization scheme that relates the latter to the ordinary classical position and momentum observables. These allow us to address the problem of determining the conserved probability density and the underlying classical system for pseudo-Hermitian and in particular PT-symmetric quantum systems. As a concrete example we construct the Hermitian Hamiltonian h, the physical observables O, the localized states, and the conserved probability density for the non-Hermitian PT-symmetric square well. We achieve this by employing an appropriate perturbation scheme. For this system, we conduct a comprehensive study of both the kinematical and dynamical effects of the non-Hermiticity of the Hamiltonian on various physical quantities. In particular, we show that these effects are quantum mechanical in nature and diminish in the classical limit. Our results provide an objective assessment of the physical aspects of PT-symmetric quantum mechanics and clarify its relationship with both the conventional quantum mechanics and the classical mechanics.Comment: 45 pages, 13 figures, 2 table

Fermionic coherent states for pseudo-Hermitian two-level systems

We introduce creation and annihilation operators of pseudo-Hermitian fermions for two-level systems described by pseudo-Hermitian Hamiltonian with real eigenvalues. This allows the generalization of the fermionic coherent states approach to such systems. Pseudo-fermionic coherent states are constructed as eigenstates of two pseudo-fermion annihilation operators. These coherent states form a bi-normal and bi-overcomplete system, and their evolution governed by the pseudo-Hermitian Hamiltonian is temporally stable. In terms of the introduced pseudo-fermion operators the two-level system' Hamiltonian takes a factorized form similar to that of a harmonic oscillator.Comment: 13 pages (Latex, article class), no figures; v2: some amendments in section 2, seven new refs adde

Implications of technology transfer in the design and construction of load-bearing masonry buildings

Load-bearing or structural masonry is a method of construction where the elements of a structure are built using masonry (bricks or blocks).Due to its technological and economic advantages, in western countries the system is widely used particularly for residential and low-rise buildings.Despite the advantages and excellent track record overseas, the system has not found its avenue in the local construction scene.Not many new buildings have been built using the system. Previous studies revealed that engineers, architects, developers, and builders lacked knowledge and experience on the design and construction using the system. A programme has been formulated for a consulting firm’s staff and their business partners to transfer the state-of-the-art knowledge on the design, detailing, costing, and construction of structures using load-bearing masonry. Additionally, value added topics on supply chain, value engineering, and strategic planning were also included.The programme involved two phases: (i) a series of seminars and workshops covering a duration of 6 months and, (ii) continuous site supervision (monitoring) for another 6 months.An auditing scheme to measure the company’s performance before and after the programme using the balance score-card technique is under formulation.The technology transfer programme has been completed covering 9 modules whereby the company managed to save further on profits by utilizing value engineering concepts in its relevant projects