Effects of Anacetrapib in Patients with Atherosclerotic Vascular Disease

BACKGROUND: Patients with atherosclerotic vascular disease remain at high risk for cardiovascular events despite effective statin-based treatment of low-density lipoprotein (LDL) cholesterol levels. The inhibition of cholesteryl ester transfer protein (CETP) by anacetrapib reduces LDL cholesterol levels and increases high-density lipoprotein (HDL) cholesterol levels. However, trials of other CETP inhibitors have shown neutral or adverse effects on cardiovascular outcomes. METHODS: We conducted a randomized, double-blind, placebo-controlled trial involving 30,449 adults with atherosclerotic vascular disease who were receiving intensive atorvastatin therapy and who had a mean LDL cholesterol level of 61 mg per deciliter (1.58 mmol per liter), a mean non-HDL cholesterol level of 92 mg per deciliter (2.38 mmol per liter), and a mean HDL cholesterol level of 40 mg per deciliter (1.03 mmol per liter). The patients were assigned to receive either 100 mg of anacetrapib once daily (15,225 patients) or matching placebo (15,224 patients). The primary outcome was the first major coronary event, a composite of coronary death, myocardial infarction, or coronary revascularization. RESULTS: During the median follow-up period of 4.1 years, the primary outcome occurred in significantly fewer patients in the anacetrapib group than in the placebo group (1640 of 15,225 patients [10.8%] vs. 1803 of 15,224 patients [11.8%]; rate ratio, 0.91; 95% confidence interval, 0.85 to 0.97; P=0.004). The relative difference in risk was similar across multiple prespecified subgroups. At the trial midpoint, the mean level of HDL cholesterol was higher by 43 mg per deciliter (1.12 mmol per liter) in the anacetrapib group than in the placebo group (a relative difference of 104%), and the mean level of non-HDL cholesterol was lower by 17 mg per deciliter (0.44 mmol per liter), a relative difference of -18%. There were no significant between-group differences in the risk of death, cancer, or other serious adverse events. CONCLUSIONS: Among patients with atherosclerotic vascular disease who were receiving intensive statin therapy, the use of anacetrapib resulted in a lower incidence of major coronary events than the use of placebo. (Funded by Merck and others; Current Controlled Trials number, ISRCTN48678192 ; ClinicalTrials.gov number, NCT01252953 ; and EudraCT number, 2010-023467-18 .)

STATUS AND TRENDS OF PHYTOREMEDIATION IN SINGAPORE

Master'sMASTER OF SCIENCE (ENVIRONMENTAL MANAGEMENT) (MEM

Risk assessment of decommissioning options for offshore facilities

Decommissioning is gaining traction globally. Large project management is required to plan and execute an offshore decommissioning operation. There is also increasing interest to adopt risk assessment techniques from other industries for the offshore industry, such as in the area of dependent failure or the role of human error. Finally, piece-wise, segmental risk assessment is based on traditional risk assessment methods, without consideration of long-term effects of a decommissioned structure. This thesis proposes a risk model that consists of three parts: (i) decommissioning options analysis (ii) selected decommissioning activity risk analysis and (iii) long-term monitoring of a decommissioning solution. A case study to a well plugging and abandonment is carried out as that constitutes the largest proportion of decommissioning costs and that well leaks are underestimated. The thesis has three research objectives. The first objective is to develop an expert judgement process that can consider expert uncertainty and inherent variability in the situation that warrants an expert judgement. Decommissioning projects rely a lot on expert judgement to choose the most apt decommissioning option. The second objective is to model dependencies in terms of time dependent failure (Event 2 failure given Event 1 failure) or Common Cause Failures (CCF) in greater details (material, environment, design). This objective is meant to provide a higher level of detail amongst CCF groups/causes to give insight to relationships between events that is not covered in existing simple CCF-ratio models, where the CCF probability is a ratio of the failure probability of the basic event. The third objective is to develop long-term monitoring to consider accumulative fatigue in the annular fit and the casing strength. This allows the projection of the well barrier failure rate to a decade, which is when a well would most likely fail, if it were to fail. A risk modelling method that combines and adapts methods from different and/or similar industries have been proposed. The method comprises of the following modelling features in a Bayesian Belief Network (BBN): (i) multiple states in a node (ii) dependency analysis (iii) representation of uncertainties (iv) detailed HRA (v) continuous variables and (vi) temporal variables. Expert judgement is a crucial part of the risk modelling process in the decommissioning field. Such judgement is utilised in options analysis, comparative assessments, human reliability analysis and discrete Markov chain time slices. Expert judgement is the primary input to the BBN. This is a delicate process as it should be comprehensive enough to avoid different types of biases, yet not be overly unpractical. The method adapted from the combination of the linear interpolation method and the Bayesian aggregation method can demonstrate dominance of one factor over the other, or represent different uncertainties in relationships. The modelling is also conducted in two specialised BBN software called GeNIe and Agenarisk. The model is able to carry out a weighted sum of the probability across all possible intervals and with key values of indication of uncertainty - such as the median value, or the 5th or 95th percentile. The method also utilised linear interpolation to reduce the elicitation burden. The results demonstrate that the interpolation method still manages to capture the dependencies and that the obtained HEP values agrees with other HRA-BBN models. The model also has a dynamic component that can provide insights on long-term well failures. Since fatigue in cement is an accumulative process, dynamic BBN (discrete-time Markov model) modelling has been utilised to investigate the performance of barrier over time, in this case, the annular fit and the casing strength. The model incorporated two common cause failures: (i) changes in wellbore pressure and the (ii) change in annulus pressure acting on top of the cement, which ultimately affects the fit of the cement with respect to the well bore. The results of the sensitivity analysis and backwards diagnostic analysis agree with a statistical study of 103 wells. Decommissioned structures are meant to last in perpetuity but the proposed solutions usually do not last in perpetuity. The proposed methodology of dynamic Bayesian Belief Networks (1) captured better estimates of a well PA event by incorporating dependencies, and met regulatory requirements by authorities; and (2) utilised the same model to provide long term monitoring of a group of wells linked by common dependencies. This addressed the challenges of underestimating failure probability in plugged and abandoned wells both in the short and long term.Doctor of Philosoph

An Artificial Neural Network for fuel efficiency analysis for cargo vessel operation

There is increasing interest in understanding fuel consumption from the perspective of increasing energy efficiency on a vessel. Thus the aim of this paper is to present a new framework for data-driven estimation of fuel consumption by employing a combination of (i) traditional statistical analysis and (ii) Artificial Neural Networks. The output of the analysis is the most frequently occurring fuel-speed curves corresponding to the respective operational profile. The inputs to the model consider important explanatory variables like draft, sea current and wind. The methodology is applied to a case study of a fleet of 9000 twenty-foot equivalent units (TEU) vessels, in which telemetry data on the fuel consumption, vessel speed, current, wind direction and strength were analysed. The performance of the method is validated in terms of error estimation criterion like R 2 values and against physical phenomena obtained from the data. The results can be used to study the economic and environmental benefits of slow-steaming and or fuel levies, or by extending this part of the model into exergy analysis for a more holistic review of energy saving initiatives

Dynamic Bayesian belief network for long-term monitoring and system barrier failure analysis : decommissioned wells

There is increasing interest to consider dependent failures and human errors in the offshore industry. Permanently abandoned wells dot most of the subsea environment. The nature of a well plugging and abandonment (Well P&A) run - usually the lowest-cost contractor engaged to plug several wells tapping the same reservoir makes it an ideal case study for incorporating failures based on common causes. The heavy use of operators during a cementing job also provides the case for analysis of human error in such tasks. One proposed method to analyse the above-mentioned is the use of Bayesian Belief Networks to achieve the following objectives (1) to capture better estimates of a well PA event by incorporating dependencies, and meet regulatory requirements by authorities; and (2) to use the same model to provide long term monitoring of a group of wells linked by common dependencies. This model has not only captured the dependencies of multiple variables, but also projected it in a dynamic manner to provide a risk profile for the next decade where well integrity failure is likely to happen. Proposed adapted method capture better estimates of a well PA event by incorporating dependencies. Method allows for extension of model to long term monitoring of a group of wells linked by common dependencies

A review of offshore decommissioning regulations in five countries – strengths and weaknesses

The decommissioning of offshore structures around the world will be a persisting problem in the coming decades as many structures will exceed their shelf life, or when reservoirs are no longer productive. This paper examines an overview of the global offshore decommissioning legal regime, and a summary of regulations in countries that are deemed to be more experienced in decommissioning such as the UK, Norway and USA. Two oil-producing countries in South East Asia, Malaysia and Thailand are also reviewed to identify potential gaps in decommissioning legislation for countries in its infancy in decommissioning. The differences were identified in terms of decommissioning preparation, decommissioning technical execution, additional environmental requirements and financial security framework. In conclusion, the majority of the regulations covering the technical section are similar within all countries studied. Major differences lie in two overarching philosophies of the framework - a prescriptive regime versus a goal-setting regime. Other decommissioning aspects appear to attract increasing attention, such as in expanding clarity on in situ decommissioning, residual liabilities, optimising finance related issues of decommissioning and offshore to onshore waste movement. These gaps in the existing framework can be filled by taking an evidence-based stand in developing the framework.EDB (Economic Devt. Board, S’pore)Accepted versio