Everything in Moderation: Investigating the U-Shaped Link Between HDL Cholesterol and Adverse Outcomes

Despite historical evidence suggesting an inverse association between HDL cholesterol (HDL-C) and adverse cardiovascular events, pharmacological efforts to increase HDL-C and improve outcomes have not been successful. Recently, a U-shaped association between HDL-C and adverse events has been demonstrated in several population cohorts, further complicating our understanding of the clinical significance of HDL. Potential explanations for this finding include genetic mutations linked to very high HDL-C, impaired HDL function at high HDL-C levels, and residual confounding. However, our understanding of this association remains premature and needs further investigation

An Overview of the Strategic Environmental Assessment System (USA)

An overview of SEAS - the Strategic Environmental Assessment System - widely used in the USA. This is an integrated series of computer models covering the economy, energy and environment. Three applications of SEAS are described in the three following chapters of the book. -K.M.Clayto

A Risk-Sharing Model for Locating Noxious Facilities

The recent proliferation of facility-siting conflicts underscores the need for new analytical techniques in which the external effects associated with noxious facilities are considered explicitly. In general, in prescriptive facility-location models it is assumed that having populations \u27closer\u27, as characterized by transport or accessibility advantages, is better for desirable facilities, but, locating \u27farther\u27 away is better for undesirable facilities. The modeling formulation developed in this paper adds two new concepts to the prescriptive modeling work on locating noxious facilities: 1) \u27complementary anticover\u27 as a measure of equity for siting facilities that provide a required capacity for producing goods or services, and 2) perceived risk attributable to the scale of these facilities. These two concepts, in conjunction with conventional cost considerations, are used to develop a multiobjective location model that may be used to find locational patterns which mitigate public opposition across a broad range of noxious facilities. -Author

Monte Carlo Simulation

The Monte Carlo method can be used to address any mathematical problem or model that is too complex, time consuming, or resource intensive to solve analytically. Instead of tackling the numerical problem directly, Monte Carlo allows the researcher to obtain an approximation of the solution through setting up an experiment of statistical sampling. As the name indicates, the method borrows from games of chance such as those played at the famous casinos of Monte Carlo in Monaco. The Monte Carlo method relies on realizations (draws) from a probability density function. Ideally, to correctly apply the Monte Carlo method and obtain valid results, the sampling method employed should be completely random. The number of realizations has to be sufficiently large to accurately represent the distribution of the input variables. There have been numerous and diverse applications of Monte Carlo methods that include, for example, science (computing multidimensional integrals and model sensitivity analysis), education (teaching and research), business (portfolio management, product life cycle analysis), environment (probabilistic risk assessment and resource allocation), health (delivery of services and epidemiology), government (project choice and standard setting), engineering (design and project management), and energy (utility management and methods for hydrogen production). Application areas seem limited only by imagination and computing power

The Maximum Capture Problem with Uncertainty

The strategic location of servers by a firm in a competitive environment is basic in the determination or division of market shares. Let us suppose that a firm wants to locate p servers so as to maximize market capture in a region where competitors are already located but where there is uncertainty - there are several possible future scenarios with respect to demand and/or the location of competitors. The firm will want a strategy of positioning that will do as \u27well as possible\u27 over the future scenarios. In this paper we will present a discrete location model formulation to address this maximum capture problem with uncertainty

The Impact of Coal Conversions on the Ports of New England

Historically, waterborne movements of coal into the New England regions were very important. This paper presents the results of a systematic study of the transportation of coal into the region to satisfy the anticipated energy demands of the electric utilities. The results of this analysis indicate that waterborne movements of coal can once again predominate. Even with the added investments necessary for the construction of new coal handling equipment at the ports of New England and the costs associated with additional coal transfers, water modes tend to be the most economical. The ports of Providence and Boston appear to have some geographical strategic importance to this coal trade.-Author

A risk-sharing model for locating noxious facilities

Abstract. The recent proliferation of facility-siting conflicts underscores the need for new analytical techniques in which the external effects associated with noxious facilities are considered explicitly. In general, in prescriptive facility-location models it is assumed that having populations "closer", as characterized by transport or accessibility advantages, is better for desirable facilities, but, locating "farther " away is better for undesirable facilities. The modeling formulation developed in this paper adds two new concepts to the prescriptive modeling work on locating noxious facilities: (1) "complementary anticover " as a measure of equity for siting facilities that provide a required capacity for producing goods or services, and (2) perceived risk attributable to the scale of these facilities. These two concepts, in conjunction with conventional cost considerations, are used to develop a multiobjective location model that may be used to find locational patterns which mitigate public opposition across a broad range of noxious facilities. "One of the first things that we concluded was that 'yes, we need to do something responsible to take care of hazardous waste '.... But to us it never made sense to have one huge facility where everything would converge." Hazardous waste facility opposition leader

A risk-sharing model for locating noxious facilities

The recent proliferation of facility-siting conflicts underscores the need for new analytical techniques in which the external effects associated with noxious facilities are considered explicitly. In general, in prescriptive facility-location models it is assumed that having populations "closer", as characterized by transport or accessibility advantages, is better for desirable facilities, but, locating "farther" away is better for undesirable facilities. The modeling formulation developed in this paper adds two new concepts to the prescriptive modeling work on locating noxious facilities: (1) "complementary anticover" as a measure of equity for siting facilities that provide a required capacity for producing goods or services, and (2) perceived risk attributable to the scale of these facilities. These two concepts, in conjunction with conventional cost considerations, are used to develop a multiobjective location model that may be used to find locational patterns which mitigate public opposition across a broad range of noxious facilities.

The maximum capture problem with uncertainty

The strategic location of servers by a firm in a competitive environment is basic in the determination or division of market shares. Let us suppose that a firm wants to locate p servers so as to maximize market capture in a region where competitors are already located but where there is uncertainty -- there are several possible future scenarios with respect to demand and/or the location of competitors. The firm will want a strategy of positioning that will do as 'well as possible' over the future scenarios. In this paper we will present a discrete location model formulation to address this maximum capture problem with uncertainty.