\u3cem\u3eThe Cherry Beret\u3c/em\u3e by Ashton L. Kerr [Review]

Review of Colonel Ashton L. Kerr, MD, The Cherry Beret: Distant recollections of World War II as remembered by one of the first Canloan officers. Published privately

Molecular propensity as a driver for explorative reactivity studies

Quantum chemical studies of reactivity involve calculations on a large number of molecular structures and comparison of their energies. Already the set-up of these calculations limits the scope of the results that one will obtain, because several system-specific variables such as the charge and spin need to be set prior to the calculation. For a reliable exploration of reaction mechanisms, a considerable number of calculations with varying global parameters must be taken into account, or important facts about the reactivity of the system under consideration can go undetected. For example, one could miss crossings of potential energy surfaces for different spin states or might not note that a molecule is prone to oxidation. Here, we introduce the concept of molecular propensity to account for the predisposition of a molecular system to react across different electronic states in certain nuclear configurations. Within our real-time quantum chemistry framework, we developed an algorithm that allows us to be alerted to such a propensity of a system under consideration.Comment: 10 pages, 7 figure

Multiresolution wavelet analysis of heartbeat intervals discriminates healthy patients from those with cardiac pathology

We applied multiresolution wavelet analysis to the sequence of times between human heartbeats (R-R intervals) and have found a scale window, between 16 and 32 heartbeats, over which the widths of the R-R wavelet coefficients fall into disjoint sets for normal and heart-failure patients. This has enabled us to correctly classify every patient in a standard data set as either belonging to the heart-failure or normal group with 100% accuracy, thereby providing a clinically significant measure of the presence of heart-failure from the R-R intervals alone. Comparison is made with previous approaches, which have provided only statistically significant measures.Comment: 5 pages, 4 figures, to appear in Phys. Rev. Letter

Testing the Hadronuclear Origin of PeV Neutrinos Observed with IceCube

We consider implications of the IceCube excess for hadronuclear (pp) scenarios of neutrino sources such as galaxy clusters/groups and star-forming galaxies. Since the observed neutrino flux is comparable to the diffuse gamma-ray background flux obtained by Fermi, we place new, strong upper limits on the source spectral index, {\Gamma}<2.1-2.2. In addition, the new IceCube data imply that these sources contribute at least 30%-40% of the diffuse gamma-ray background in the 100 GeV range and even ~100% for softer spectra. Our results, which are insensitive to details of the pp source models, are one of the first strong examples of the multimessenger approach combining the measured neutrino and gamma-ray fluxes. The pp origin of the IceCube excess can further be tested by constraining {\Gamma} with sub-PeV neutrino observations, by unveiling the sub-TeV diffuse gamma-ray background and by observing such pp sources with TeV gamma-ray detectors. We also discuss specific pp source models with a multi-PeV neutrino break/cutoff, which are consistent with the current IceCube data.Comment: 5 pages, 3 figures, replaced to match the published versio

Smooth models of quiver moduli

For any moduli space of stable representations of quivers, certain smooth varieties, compactifying projective space fibrations over the moduli space, are constructed. The boundary of this compactification is analyzed. Explicit formulas for the Betti numbers of the smooth models are derived. In the case of moduli of simple representations, explicit cell decompositions of the smooth models are constructed.Comment: 37 pages, notations and typo corrected, references updated, new example

Selective phenotyping, entropy reduction, and the mastermind game.

BACKGROUND: With the advance of genome sequencing technologies, phenotyping, rather than genotyping, is becoming the most expensive task when mapping genetic traits. The need for efficient selective phenotyping strategies, i.e. methods to select a subset of genotyped individuals for phenotyping, therefore increases. Current methods have focused either on improving the detection of causative genetic variants or their precise genomic location separately. RESULTS: Here we recognize selective phenotyping as a Bayesian model discrimination problem and introduce SPARE (Selective Phenotyping Approach by Reduction of Entropy). Unlike previous methods, SPARE can integrate the information of previously phenotyped individuals, thereby enabling an efficient incremental strategy. The effective performance of SPARE is demonstrated on simulated data as well as on an experimental yeast dataset. CONCLUSIONS: Using entropy reduction as an objective criterion gives a natural way to tackle both issues of detection and localization simultaneously and to integrate intermediate phenotypic data. We foresee entropy-based strategies as a fruitful research direction for selective phenotyping