When Does Inflation Hurt Economic Growth? Different Nonlinearities for Different Economies

We show that the effects of inflation on growth change substantially as the inflation rate rises. Moreover the nonlinearities are quite different for industrial economies than for developing countries. We find that the threshold at which inflation first begins to seriously negatively affect growth is around 8% for industrial economies but 3% or less for developing countries. Marginal growth costs for developing countries then decline significantly above 50% inflation. Failure to account for nonlinearity biases downward the estimated effects of inflation on growth. Mixing industrial and developing economies together also produces unreliable results.inflation; growth; non-linearity

de-Broglie Wave-Front Engineering

We propose a simple method for the deterministic generation of an arbitrary continuous quantum state of the center-of-mass of an atom. The method's spatial resolution gradually increases with the interaction time with no apparent fundamental limitations. Such de-Broglie Wave-Front Engineering of the atomic density can find applications in Atom Lithography, and we discuss possible implementations of our scheme in atomic beam experiments.Comment: The figures' quality was improved, the text remains intact. 5 pages, 3 figures; submitted to PR

When Does Inflation Hurt Economic Growth? Different Nonlinearities for Different Economies

We show that the effects of inflation on growth change substantially as the inflation rate rises. Moreover the nonlinearities are quite different for industrial economies than for developing countries. We find that the threshold at which inflation first begins to seriously negatively affect growth is around 8% for industrial economies but 3% or less for developing countries. Marginal growth costs for developing countries then decline significantly above 50% inflation. Failure to account for nonlinearity biases downward the estimated effects of inflation on growth. Mixing industrial and developing economies together also produces unreliable results

Thomas Decomposition of Algebraic and Differential Systems

In this paper we consider disjoint decomposition of algebraic and non-linear partial differential systems of equations and inequations into so-called simple subsystems. We exploit Thomas decomposition ideas and develop them into a new algorithm. For algebraic systems simplicity means triangularity, squarefreeness and non-vanishing initials. For differential systems the algorithm provides not only algebraic simplicity but also involutivity. The algorithm has been implemented in Maple

Neurocognitive and Academic Outcomes at Age 10 Years of Extremely Preterm Newborns

Despite reductions in mortality and morbidity among children born extremely preterm, they remain at high risk of neurocognitive deficits, with up to 40% having significant cognitive deficits at school age. We assessed the rate of neurocognitive impairment in a contemporary US cohort of 873 children aged 10 years who were born <28 weeks’ gestation

A dynamical chiral bag model

We study a dynamical chiral bag model, in which massless fermions are confined within an impenetrable but movable bag coupled to meson fields. The self-consistent motion of the bag is obtained by solving the equations of motion exactly assuming spherical symmetry. When the bag interacts with an external meson wave we find three different kinds of resonances: {\it fermionic}, {\it geometric}, and $\sigma$-resonances. We discuss the phenomenological implications of our results.Comment: Two columns, 11 pages, 9 figures. Submitted to Physical Review

Time to shift from contemporary to high-sensitivity cardiac troponin in diagnosis of acute coronary syndromes

AbstractEarly rule-in and rule-out of non-ST-segment elevation myocardial infarction (NSTEMI) is a challenge. In patients with inconclusive findings on ECG, cardiac biomarkers play a crucial role in the diagnosis. The introduction of the new high-sensitive cardiac troponin test (hs-TnI assay) has changed the landscape of NSTEMI diagnosis.The new hs-TnI assay can detect troponin values at a lower level compared with a contemporary cardiac troponin (cTn) assay. The hs-cTnI assay has a coefficient of variation of ≤10%, well below the 99th percentile value. It reduces the time to diagnose acute myocardial infarction from 6h to 3h. A recent study has demonstrated that hs-cTnI can further reduce the time to 1h in 70% of all patients with chest pain.The European Society of Cardiology 2015 guidelines recommend including a second sample of hs-cTnI within 3h of presentation This increases the sensitivity of the hs-TnI assay from 82.3% (at admission) to 98.2% and negative predictive value from 94.7% (at admission) to 99.4%. Combining the 99th percentile at admission with serial changes in troponin increases the positive predictive value to rule in acute coronary syndrome from 75.1% at admission to 95.8% after 3h.The 2015 ESC Guidelines recommend the use of a rapid rule out protocol (0h and 1h) when hs-cTnI with a validated 0 to1h algorithm is available.Training and displaying the clinical algorithm depicting the role of hs-TnI assay in acute cardiac care units and in EDs are an efficient way to deliver the new standard of care to patients. Compared with contemporary troponin assays, the hs-cTn assay accelerates the diagnostic pathway to 0–1h, thus reducing the time for diagnosis of NSTEMI and hence, its management

A Study of Alaska's Housing Programs

Prepared for Legislative and Audit Committee Alaska State LegislatureYe

Species abundance dynamics under neutral assumptions: a Bayesian approach to the controversy

1. Hubbell's 'Unified Neutral Theory of Biodiversity and Biogeography' (UNTB) has generated much controversy about both the realism of its assumptions and how well it describes the species abundance dynamics in real communities. 2. We fit a discrete-time version of Hubbell's neutral model to long-term macro-moth (Lepidoptera) community data from the Rothamsted Insect Survey (RIS) light-traps network in the United Kingdom. 3. We relax the assumption of constant community size and use a hierarchical Bayesian approach to show that the model does not fit the data well as it would need parameter values that are impossible. 4. This is because the ecological communities fluctuate more than expected under neutrality. 5. The model, as presented here, can be extended to include environmental stochasticity, density-dependence, or changes in population sizes that are correlated between different species