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BACKGROUND: Coronary computed tomography angiography (CCTA) can identify high-risk coronary plaque types. However, the inter-observer variability for high-risk plaque features, including low attenuation plaque (LAP), positive remodelling (PR), and the Napkin-Ring sign (NRS), may reduce their utility, especially amongst less experienced readers. METHODOLOGY: In a prospective study, we compared the prevalence, location and inter-observer variability of both conventional CT-defined high-risk plaques with a novel index based on quantifying the ratio of necrotic core to fibrous plaque using individualised X-ray attenuation cut-offs (the CT-defined thin-cap fibroatheroma - CT-TCFA) in 100 patients followed-up for 7 years. RESULTS: In total, 346 plaques were identified in all patients. Seventy-two (21%) of all plaques were classified by conventional CT parameters as high-risk (either NRS or PR and LAP combined), and 43 (12%) of plaques were considered high-risk using the novel CT-TCFA definition of (Necrotic Core/fibrous plaque ratio of >0.9). The majority (80%) of the high-risk plaques (LAP&PR, NRS and CT-TCFA) were located in the proximal and mid-LAD and RCA. The kappa co-efficient of inter-observer variability (k) for NRS was 0.4 and for PR and LAP combined 0.4. While the kappa co-efficient of inter-observer variability (k) for the new CT-TCFA definition was 0.7. During follow-up, patients with either conventional high-risk plaques or CT-TCFAs were significantly more likely to have MACE (Major adverse cardiovascular events) compared to patients without coronary plaques (p value 0.03 & 0.03, respectively). CONCLUSION: The novel CT-TCFA is associated with MACE and has improved inter-observer variability compared with current CT-defined high-risk plaques.

Gasification is one of the most important methods for converting biomass to syngas currently used in energy production. However, tar content in syngas limits its direct use and thus requires additional removal techniques. The modelling of tar formation, conversion and destruction along a gasifier could give a wider understanding of the process and subsequently help in tar elimination and reduction. However, tar complexity, which contains hundreds of species, makes the modelling process hard and computationally intensive, because the chemistry of the formation and the combustion of many species have not yet been fully studied. In this work, a detailed kinetic model for the evolution and formation of tar from downdraft gasifiers, for the first-time, was built. The model incorporates four main tar species (benzene, naphthalene, toluene, and phenol) with a total of eighteen different kinetic reactions implemented in the code for every zone. Experimental work was carried out to initially validate the results of the kinetic code and found a good agreement. Further experiments were conducted at three different equivalence ratios (ERs) and at three different temperatures (800, 900, and 1100 °C). Sensitivity analysis was then carried out by the kinetic code to optimise the working parameters of a downdraft gasifier that led to a higher calorific value of syngas. The results reveal that a tar evolution model is more accurate for wood biomass materials and that using ER around 0.3, and moisture content levels lower than 10% lead to the production of higher value syngas with lower tar amounts.

Biomass is being used widely for energy production in various ways. One of the main schemes for energy production from biomass is gasification, and a powerful tool for optimising the behaviour of biomass gasifiers and also obtaining the required design for specific working conditions is the modelling. An integrated kinetic model was built by the authors ( [1], and [2]), which enabled to simulate, design and optimise the processes of downdraft biomass gasifiers for the production of high quality syngas. In the current research presented in this paper, the kinetic code has been extended by including detailed chemical mechanisms for the tar evolution and formation inside the gasifier. The model incorporated the evolution of 4 main tar species from pyrolysis to combustion and gasification with the formation and kinetic reaction rates of benzene, naphthalene, toluene, and phenol tar compounds. The effect of varying moisture content (MC) and equivalence ratio (ER) is studied to find out the optimum working conditions leading to the reduction of tar amount in the producer gas from downdraft gasifiers. The results reveals that moderate ER of 0.3, with lower MC

A kinetic model was built to estimate the optimum working parameters of a downdraft gasifier, in which a set of chemical kinetics at each zone of the gasifier was described. The model deals with a wide range of biomass types with elemental composition ranges of (38 ≤ C ≤ 52) %, (5.5 ≤ H ≤ 7) %, and (36 ≤ O ≤ 45) %. This model is able to predict gas composition, tar content, temperature and height of each zone, as well as temperature, velocity and pressure distribution at reduction zone with heating value of product gas. The model also gives full design dimensions of a downdraft gasifier. The final results, which proved to be in a good agreement with experimental works under different working conditions of biomass type, moisture content, and air-to-fuel ratio, are based on a new approach that includes calculation of the optimum height of the reduction zone. Calculation based on the optimum height ensures that all the char produced is consumed in the reduction zone, thus leading to the production of the maximum amount of gases. Results conclude that biomass with a moisture content less than 10% and equivalence ratio of 0.3–0.35 leads to the production of higher yield of syngas with low tar content. In particular, woody biomass materials are found to give the higher heating value for producer gas with a reasonable amount of tar.

The airport gate assignment problem (AGAP) is one of the most important problems operations managers face daily. Many researches have been done to solve this problem and tackle its complexity. The objective of the task is assigning each flight (aircraft) to an available gate while maximizing both conveniences to passengers and the operational efficiency of airport. This objective requires a solution that provides the ability to change and update the gate assignment data on a real time basis. In this paper, we survey the state of the art of these problems and the various methods to obtain the solution. Our survey covers both theoretical and real AGAP with the description of mathematical formulations and resolution methods such as exact algorithms, heuristic algorithms, and metaheuristic algorithms. We also provide a research trend that can inspire researchers about new problems in this area.