A study of the preparation and purification of certain amino acids.

Typewritten sheets in cover. Thesis (M.A.)--Boston University Bibliography: 3 p. at end

Estimation effects on stop-loss premiums under dependence

Even a small amount of dependence in large insurance portfolios can lead to huge errors in relevant risk measures, such as stop-loss premiums. This has been shown in a model where the majority consists of ordinary claims and a small fraction of special claims. The special claims are dependent in the sense that a whole group is exposed to damage. In this model, the parameters have to be estimated. The effect of the estimation step is studied here. The estimation error is dominated by the part of the parameters related to the special claims, because by their nature we do not have many observations of them. Although the estimation error in this way is restricted to a few parameters, it turns out that it may be quite substantial. Upper and lower confidence bounds are given for the stop-loss premium, thus protecting against the estimation effect

Effects of Network Communities and Topology Changes in Message-Passing Computation of Harmonic Influence in Social Networks

The harmonic influence is a measure of the importance of nodes in social networks, which can be approximately computed by a distributed message-passing algorithm. In this extended abstract we look at two open questions about this algorithm. How does it perform on real social networks, which have complex topologies structured in communities? How does it perform when the network topology changes while the algorithm is running? We answer these two questions by numerical experiments on a Facebook ego network and on synthetic networks, respectively. We find out that communities can introduce artefacts in the final approximation and cause the algorithm to overestimate the importance of "local leaders" within communities. We also observe that the algorithm is able to adapt smoothly to changes in the topology.Comment: 4 pages, 7 figures, submitted as conference extended abstrac

Spinal cord stimulation: fiber diameters in the dorsal columns modeled from clinical data

Computer simulations of clinical data were performed to estimate the diameter distribution of A¿ß nerve fibers in the human dorsal columns, activated by spinal cord stimulation. Qualitatively, the calculated distribution was in accordance with experimental data. Due to mismatches in impedance and limited resolution of the CT scans more patient data is needed to reliably predict the quantitative diameter distributio

Moderate deviations of minimum contrast estimators under contamination

Since statistical models are simplifications of reality, it is important in estimation theory to study the behavior of estimators also under distributions (slightly) different from the proposed model. In testing theory, when dealing with test statistics where nuisance parameters are estimated, knowledge of the behavior of the estimators of the nuisance parameters is needed under alternatives to evaluate the power. In this paper the moderate deviation behavior of minimum contrast estimators is investigated not only under the supposed model, but also under distributions close to the model. A particular example is the (multivariate) maximum likelihood estimator determined within the proposed model. The set-up is quite general, including for instance also discrete distributions. The rate of convergence under alternatives is determined both when comparing the minimum contrast estimator with a "natural" parameter in the parameter space and when comparing it with the proposed "true" value in the parameter space. It turns out that under the model the asymptotic optimality of the maximum likelihood estimator in the local sense continues to hold in the moderate deviation area

TLR3 Deficiency Leads to a Dysregulation in the Global Gene-Expression Profile in Murine Oviduct Epithelial Cells Infected with Chlamydia muridarum

OBJECTIVE Describe the implementation and effects of Mobile Acute Care for Elders (MACE) consultation at a Veterans Affairs Medical Center (VAMC). DESIGN Retrospective cohort analysis. INTERVENTION Veterans aged 65 or older who were admitted to the medicine service between October 1, 2012, and September 30, 2014, were screened for geriatric syndromes via review of medical records within 48 hours of admission. If the screen was positive, the MACE team offered the admitting team a same-day consultation involving comprehensive geriatric assessment and ongoing collaboration with the admitting team and supportive services to implement patient-centric recommendations for geriatric syndromes. RESULTS Veterans seen by MACE (n = 421) were compared with those with positive screens but without consultation (n = 372). The two groups did not significantly differ in age, comorbidity, sex, or race. All outcomes (30-day readmission, 30-day mortality, readmission costs) were in the expected direction for patients receiving MACE but did not reach statistical significance. Patients receiving MACE had lower odds of 30-day readmission (11.9% vs 14.8%; odds ratio [OR] = 0.82; 95% confidence interval [CI] = 0.54-1.25; p = .360) and 30-day mortality (5.5% vs 8.6%; OR = 0.64; CI = 0.36-1.12; p = .115), and they had lower 30-day readmission costs (MACE $15,502; CI =$12,242-$19,631; comparison =$18,335; CI = $14,641-$22,962; p = .316) than those who did not receive MACE after adjusting for age and Charlson Comorbidity Index. CONCLUSION Our MACE consultation model for older veterans with geriatric syndromes leverages the limited supply of clinicians with expertise in geriatrics. Although not statistically significant in this study of 793 subjects, MACE patients had lower odds of 30-day readmission and mortality, and lower readmission costs. J Am Geriatr Soc 67:818–824, 2019

Asynchronous opinion dynamics on the kk-nearest-neighbors graph

This paper is about a new model of opinion dynamics with opinion-dependent connectivity. We assume that agents update their opinions asynchronously and that each agent's new opinion depends on the opinions of the $k$ agents that are closest to it. We show that the resulting dynamics is substantially different from comparable models in the literature, such as bounded-confidence models. We study the equilibria of the dynamics, observing that they are robust to perturbations caused by the introduction of new agents. We also prove that if the number of agents $n$ is smaller than $2k$, the dynamics converge to consensus. This condition is only sufficient.Comment: 17 pages, 4 figures, (to be) presented at the 57th IEEE Conference on Decision and Control, 201