High Speed Railway (HSR): India And The World

India has one of the largest rail networks in the world but has no line which can be classified as HSR allowing operational speed of 125mph. The current fastest train runs at 100 mph over a distance of only around 100 miles. However, supported by a robust political willingness, a new HSR corporation has been set up to kick-start the HSR projects from ideation to reality. Four major corridors have been identified and pre-feasibility studies have been commissioned. The first in this ambitious program is the HSR between Mumbai and Ahmedabad, two major population and commercial centers in the west of India. The success or failure of this project could show the way for future road map of HSR in India. This paper identifies and analyses the countries where HSR systems are in operation – their political, economic and social conditions relevant to HSR systems and then the features of HSR systems themselves to understand the commonalities between the nations that have opted for HSR. The objective is to identify if there is a common character or a baseline characteristic in terms of geographical, economic, political and social conditions which are essential to be a member of this exclusive club? Is there a standard financial and business model that has been adopted by these countries?Theattempt is also to compare these baseline benchmarks with those in India, to assess its strengths and weaknesses and reaffirm the chances of its success in taking up this project, one of the biggestever in its history. The results would be relevant not only for India but for all countries who aspire to be HSR countries in near future

Review Based Study On Risk Management Model For High Speed Indian Railway System

In this paper, a framework for risk management at railways has been studied and integrated into global safety management system of railways. Furthermore we studied how it was applied to a manually controlled full barrier road rail level crossing in Morocco. We studied different aspects that should be considered during the system definition phase where we suggested using functional diagrams for modeling operations at LC from the perspective of LC actors. It is a critical part for risk management and specifically for hazard identification where we provided different techniques that can be used; our experience shows that involvement of all stakeholders is a prerequisite to the success to this phase. Initiating events can be unveiled through brainstorming sessions and FTA can model complex interactions of events that have the potential to lead to accidents. Risk analysis can then be carried out provided that historical LC accident and incident data is available to estimate frequencies and consequences; ETA is the ideal tool for estimating consequences of hazards due to multiple causes. The existing risks are then classified and decisions are made regarding their tolerability, the ALARP principle can serve this purpose. A cost benefit analysis then helps prioritize risk treatment actions that should target intolerable risks. Control mechanisms should be also put in place to assess, monitor and review the risk control actions put in place. Finally, it is emphasized on the importance of having a database of historical accidents and incidents at LC for the success and efficiency for the suggested framework. Accidents at level crossings are the result of complex interactions between factors arising from the design and operations of level crossings. An important first step towards eliminating the causes of these accidents is thru understanding and assessing the risks associated with a given level crossing and acting on them. This paper presents review based study on risk management framework that serves this purpose

Apolipoprotein B, Residual Cardiovascular Risk After Acute Coronary Syndrome, and Effects of Alirocumab.

Background: Apolipoprotein B (apoB) provides an integrated measure of atherogenic risk. Whether apoB levels and apoB lowering hold incremental predictive information on residual risk after acute coronary syndrome beyond that provided by low-density lipoprotein cholesterol is uncertain. Methods: The ODYSSEY OUTCOMES trial (Evaluation of Cardiovascular Outcomes After an Acute Coronary Syndrome During Treatment With Alirocumab) compared the proprotein convertase subtilisin/kexin type 9 inhibitor alirocumab with placebo in 18 924 patients with recent acute coronary syndrome and elevated atherogenic lipoproteins despite optimized statin therapy. Primary outcome was major adverse cardiovascular events (MACE; coronary heart disease death, nonfatal myocardial infarction, fatal/nonfatal ischemic stroke, hospitalization for unstable angina). Associations between baseline apoB or apoB at 4 months and MACE were assessed in adjusted Cox proportional hazards and propensity score–matched models. Results: Median follow-up was 2.8 years. In proportional hazards analysis in the placebo group, MACE incidence increased across increasing baseline apoB strata (3.2 [95% CI, 2.9–3.6], 4.0 [95% CI, 3.6–4.5], and 5.5 [95% CI, 5.0–6.1] events per 100 patient-years in strata 35–<50, and ≤35 mg/dL, respectively). Compared with propensity score–matched patients from the placebo group, treatment hazard ratios for alirocumab also decreased monotonically across achieved apoB strata. Achieved apoB was predictive of MACE after adjustment for achieved low-density lipoprotein cholesterol or non–high-density lipoprotein cholesterol but not vice versa. Conclusions: In patients with recent acute coronary syndrome and elevated atherogenic lipoproteins, MACE increased across baseline apoB strata. Alirocumab reduced MACE across all strata of baseline apoB, with larger absolute reductions in patients with higher baseline levels. Lower achieved apoB was associated with lower risk of MACE, even after accounting for achieved low-density lipoprotein cholesterol or non–high-density lipoprotein cholesterol, indicating that apoB provides incremental information. Achievement of apoB levels as low as ≤35 mg/dL may reduce lipoprotein-attributable residual risk after acute coronary syndrome. Registration: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01663402.gov; Unique identifier: NCT01663402.URL: https://www