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Tests of goodness of fit of the generalized extreme value (GEV) and the generalized logistic (GL) distribution based on the empirical distribution function are described. Significance points for the Anderson‐Darling (Anderson and Darling, 1952, 1954) and a recently introduced modified Anderson‐ Darling (Sinclair et al., 1987) test statistic are obtained by simulation. For each of these distributions the unknown parameters are estimated from the sample data using probability weighted moments. Approximations for the probability of significance of these test statistics are provided. This enables assessment of GEV and GL flood frequency models for a hydrological region based on all the annual maximum series in the region.

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Heat exchanger networks are an integral part of chemical processes as they recover available heat and reduce utility consumption, thereby improving the overall economics of an industrial plant. This paper focuses on heat exchanger network design for multi-period operation wherein the operating conditions of a process may vary with time. A typical example is the hydrotreating process in petroleum refineries where the operators increase reactor temperature to compensate for catalyst deactivation. Superstructure based multi-period models for heat exchanger network design have been proposed previously employing deterministic optimisation algorithms, e.g. (Aaltola, 2002;Verheyen and Zhang, 2006). Stochastic optimisation algorithms have also been applied for the design of flexible heat exchanger networks recently (Ma et al., 2007(Ma et al., , 2008. The present work develops an optimisation approach using simulated annealing for design of heat exchanger networks for multi-period operation. A comparison of the new optimisation approach with previous deterministic optimisation based design approaches is presented to illustrate the utilisation of simulated annealing in design of optimal heat exchanger network configurations for multi-period operation.

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Obesity has been labeled as the global pandemic of the 21st century, resulting from a sedentary lifestyle and caloric excess. Nonalcoholic fatty liver disease (NAFLD), characterized by excessive hepatic steatosis, is strongly associated with obesity and metabolic syndrome and is estimated to be present in one-quarter of the world population, making it the most common cause of the chronic liver disease (CLD). NAFLD spectrum varies from simple steatosis to nonalcoholic steatohepatitis (NASH) and cirrhosis. The burden of NAFLD has been predicted to increase in the coming decades resulting in increased rates of decompensated cirrhosis, hepatocellular carcinoma (HCC), and liver-related deaths. In the current review, we describe the pathophysiology of NAFLD and NASH, risk factors associated with disease progression, related complications, and mortality. Later, we have discussed the changing epidemiology of HCC, with NAFLD emerging as the most common cause of CLD and HCC. We have also addressed the risk factors of HCC development in the NAFLD population (including demographic, metabolic, genetic, dietary, and lifestyle factors), presentation of NAFLD-associated HCC, its prognosis, and the issue of HCC development in non-cirrhotic NAFLD. Lastly, the problems related to HCC screening in the NAFLD population, the remaining challenges, and future directions, especially the need to identify the high-risk individuals, will be discussed. We will conclude the review by summarizing the clinical evidence for treating fibrosis and preventing HCC in those at risk with NAFLD-associated HCC.