Proton NMR studies of the electronic structure of ZrH/sub x/

The proton spin lattice relaxation times and Knight shifts were measured in f.c.c. (delta-phase) and f.c.t. (epsilon-phase) ZrH/sub x/ for 1.5 or = to x or = to 2.0. Both parameters indicate that N(E/sub F/) is very dependent upon hydrogen content with a maximum occurring at ZrH1 83. This behavior is ascribed to modifications in N(E/sub F/) through a fcc/fct distortion in ZrH/sub x/ associated with a Jahn-Teller effect

Squamous Cell Carcinoma Metastatic to the Heart Mimicking ST-Elevation Myocardial Infarction

INTRODUCTION Heart disease remains the leading cause of mortality in the United States, accounting for about one quarter of all deaths in 20131. Acute ischemic heart disease is a major subpopulation of this group, and typically presents with characteristic electrocardiographic (EKG) changes. The most concerning of these findings are ST-elevations, as ST Elevation Myocardial Infarction (STEMI) typically indicates the need for emergent reperfusion therapy because 30-day mortality of untreated STEMI is approximately 10-15% versus 5% in treated cases2. As a result, clinicians are taught to recognize the symptoms and signs of myocardial ischemia and STEMI in order to achieve timely reperfusion either via thrombolytic therapy within 30 minutes or percutaneous coronary intervention within 90 minutes. However, ST-elevations may result from etiologies other than acute ischemia, and can be secondary to other acutely life-threatening pathologies or relatively benign, subacute causes. For example, ventricular aneurysms resulting from prior myocardial infarction and pericarditis can result in ST-elevation on EKG. Intracranial hemorrhage or stress (takotsubo) cardiomyopathy can also present with ST-elevations, theorized to be the result of increased catecholamines. Left ventricular hypertrophy, a sequela of poorly controlled hypertension, can also lead to J point elevations mimicking STEMI3,4. Here we review a case of unusual ST-elevation in a patient with oropharyngeal squamous cell carcinoma metastatic to the heart

Asset liability modelling and pension schemes: the application of robust optimization to USS

This paper uses a novel numerical optimization technique - robust optimization - that is well suited to solving the asset-liability management (ALM) problem for pension schemes. It requires the estimation of fewer stochastic parameters, reduces estimation risk and adopts a prudent approach to asset allocation. This study is the first to apply it to a real-world pension scheme, and the first ALM model of a pension scheme to maximise the Sharpe ratio. We disaggregate pension liabilities into three components - active members, deferred members and pensioners, and transform the optimal asset allocation into the scheme’s projected contribution rate. The robust optimization model is extended to include liabilities and used to derive optimal investment policies for the Universities Superannuation Scheme (USS), benchmarked against the Sharpe and Tint, Bayes-Stein, and Black-Litterman models as well as the actual USS investment decisions. Over a 144 month out-of-sample period robust optimization is superior to the four benchmarks across 20 performance criteria, and has a remarkably stable asset allocation – essentially fix-mix. These conclusions are supported by six robustness checks

A Dynamic Programming Approach to Adaptive Fractionation

We conduct a theoretical study of various solution methods for the adaptive fractionation problem. The two messages of this paper are: (i) dynamic programming (DP) is a useful framework for adaptive radiation therapy, particularly adaptive fractionation, because it allows us to assess how close to optimal different methods are, and (ii) heuristic methods proposed in this paper are near-optimal, and therefore, can be used to evaluate the best possible benefit of using an adaptive fraction size. The essence of adaptive fractionation is to increase the fraction size when the tumor and organ-at-risk (OAR) are far apart (a "favorable" anatomy) and to decrease the fraction size when they are close together. Given that a fixed prescribed dose must be delivered to the tumor over the course of the treatment, such an approach results in a lower cumulative dose to the OAR when compared to that resulting from standard fractionation. We first establish a benchmark by using the DP algorithm to solve the problem exactly. In this case, we characterize the structure of an optimal policy, which provides guidance for our choice of heuristics. We develop two intuitive, numerically near-optimal heuristic policies, which could be used for more complex, high-dimensional problems. Furthermore, one of the heuristics requires only a statistic of the motion probability distribution, making it a reasonable method for use in a realistic setting. Numerically, we find that the amount of decrease in dose to the OAR can vary significantly (5 - 85%) depending on the amount of motion in the anatomy, the number of fractions, and the range of fraction sizes allowed. In general, the decrease in dose to the OAR is more pronounced when: (i) we have a high probability of large tumor-OAR distances, (ii) we use many fractions (as in a hyper-fractionated setting), and (iii) we allow large daily fraction size deviations.Comment: 17 pages, 4 figures, 1 tabl