Despite massive investment opportunities and the establishment of a framework for private sector participation in highway infrastructure development programmes in India, private investment (including foreign direct investment) in this sector is not up to the expected level. A high degree of risk exposure, disagreement on many risk issues among major stakeholders, and the absence of adequate government guarantees have been identified as some of the major reasons for this lukewarm response. This paper discusses the outcome of a risk perception analysis carried out to evaluate the risk criticality, risk management capability, risk allocation/sharing preference, and factors influencing risk acceptance of major stakeholders. A survey was conducted among senior project participants such as government officials, promoters, lenders and consultants of Indian BOT road projects. Eight types of risks have been identified as very critical in the Indian road sector under BOT set up with traffic revenue risk being the most critical. Though there is fair agreement among survey respondents with respect to the risk management capabilities of stakeholders, their preferences of allocations are divergent. The significant factors influencing the risk acceptance of each stakeholder are identified through regression analysis. The study reveals that the factors and their relative influence on the risk acceptance of stakeholders are considerably different.Highway Infrastructure, Bot Projects, Risk Perception, Risk Criticality, Risk Allocation, Risk Acceptance, Regression, Traffic Revenue Risk, India,

Over the years, many private sector participation (PSP) models have been evolved for infrastructure procurement and the Build-Operate-Transfer (BOT) model is one of the most common approaches used for the same. Private infrastructure projects under BOT arrangement have a complex risk profile and to a considerable extent, the success of any BOT project is influenced by the degree to which various project risks are managed. The major steps involved in risk management of a project are risk identification, risk assessment and the processes of prioritization and response to the risks. The conventional risk assessment approaches may not be effective in privatized infrastructure projects because of the fact that, they have very long project lifecycle with many country and sector specific risk factors. The assessment of complex risks is often a difficult task when past data on similar risks are not available. In this research, a risk probability and impact assessment framework based on fuzzy-fault tree and the Delphi method is proposed. The framework includes extensive scenario modelling of critical risks in projects and systematic processing of professional judgement (subjective knowledge) of experts and is developed and demonstrated in the context of critical risks in Indian BOT road projects. Detailed scenario modelling of most critical risks such as traffic revenue risk, delay in land acquisition, demand risk and delay in financial closure are also presented. The proposed risk assessment framework is generic and can be applied with appropriate modifications to suit any complex developmental project where past data is inadequate for risk assessment.BOT projects, risk modelling, risk assessment, fuzzy sets, possibility distribution,

Purpose: To investigate a quantitative metric derived from dynamic contrast enhanced (DCE) liver MR imaging for hepatic perfusion response to radiation therapy (RT). Materials and Methods: Ten patients with intrahepatic cancers were treated by fractionated conformai RT in a dose range of 48–82 Gy, and imaged with DCE MRI before, during, 1 month and 2 month after the therapy. Voxel‐by‐voxel hepatic arterial perfusion (Fa) and portal venous perfusion (Fp) were estimated using a dual‐input single‐compartment model. To overcome some of the challenges in estimation of hepatic perfusion from DCE MRI, a portal venous perfusion ratio (PVPR) (100×Fp/(Fa+Fp)) was evaluated for liver perfusion dose‐response. Hepatic perfusion maps were co‐registered to the dose distribution via registration with the treatment planning CT. The liver voxels having PVPR between 80% and 95% before RT were considered as “normal” tissue. The relation between perfusion and dose in the “normal” liver was assessed by the venous‐perfusion‐ratio dose‐response function. Results: The PVPR in the “normal” liver regions 1 month after RT decreased compared to pre RT. The extent of the decrease was linearly correlated with the dose accumulated to the end of RT (R2=0.93). Substantial individual variations of the PVPR decreases were observed 1 month after RT. Conclusions: Our study shows dose‐dependent perfusion changes in local liver regions. There is substantial variability in the sensitivity of liver perfusion to irradiation. The PVPR may characterize the liver perfusion change in response to radiation and might be a metric for predicting radiation toxicity in the liver. The study is supported in part by R21 CA126137 and 3 P01 CA59827.

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The choice of implementing a safety system on a dedicated network or on a shared network (with a control system) rests solely on the system cost involved. To determine which option leads to a lower overall system cost, a two-tiered normalized weighted cost calculator approach that evaluates the trade-offs is presented. Applying the calculator to the decision process shows that either solution could be determined to be optimal, depending on the weights applied to specific cost factors as a result of the application environment.