Gravitational Atom in Compactified Extra Dimensions

We consider quantum mechanical effects of the modified Newtonian potential in the presence of extra compactified dimensions. We develop a method to solve the resulting Schroedinger equation and determine the energy shifts caused by the Yukawa-type corrections of the potential. We comment on the possibility of detecting the modified gravitational bound state Energy spectrum by present day and future experiments.Comment: 12 pages, 2 figure

Constrained Supersymmetric Flipped SU(5) GUT Phenomenology

We explore the phenomenology of the minimal supersymmetric flipped SU(5) GUT model (CFSU(5)), whose soft supersymmetry-breaking (SSB) mass parameters are constrained to be universal at some input scale, $M_{in}$, above the GUT scale, $M_{GUT}$. We analyze the parameter space of CFSU(5) assuming that the lightest supersymmetric particle (LSP) provides the cosmological cold dark matter, paying careful attention to the matching of parameters at the GUT scale. We first display some specific examples of the evolutions of the SSB parameters that exhibit some generic features. Specifically, we note that the relationship between the masses of the lightest neutralino and the lighter stau is sensitive to $M_{in}$, as is the relationship between the neutralino mass and the masses of the heavier Higgs bosons. For these reasons, prominent features in generic $(m_{1/2}, m_0)$ planes such as coannihilation strips and rapid-annihilation funnels are also sensitive to $M_{in}$, as we illustrate for several cases with tan(beta)=10 and 55. However, these features do not necessarily disappear at large $M_{in}$, unlike the case in the minimal conventional SU(5) GUT. Our results are relatively insensitive to neutrino masses.Comment: 23 pages, 8 figures; (v2) added explanations and corrected typos, version to appear in EPJ

Mystify me: Coke, terror and the symbolic immortality boost

A panel on “Marketing as Mystification” convened at the 2011 Academy of Marketing conference in Liverpool. Ideas from the Liverpool event were supplemented by commentaries from selected other authors. Each commentary explores the aspects of “mystification” observable in marketing discourses and practices. In what follows, Laufer interprets marketing mystification as modern form of sophism, Dholakia and Firat discuss mystifying ways that inequality is marketed, Varman analyzes the perversion and mystification of “development” via neoliberal marketing of “social entrepreneurship,” Mikkonen explores mystifying marketing representations of gays and lesbians, and Freund and Jacobi present a fascinating interpretation of how Coca-Cola advertising mystically reassures us that our difficult, dangerous lifeworld is actually quite hunky-dory. </jats:p

Strengthening mechanisms in thermomechanically processed NbTi-microalloyed steel

The effect of deformation temperature on microstructure and mechanical properties was investigated for thermomechanically processed NbTi-microalloyed steel with ferrite-pearlite microstructure. With a decrease in the finish deformation temperature at 1348 K to 1098 K (1075 °C to 825 °C) temperature range, the ambient temperature yield stress did not vary significantly, work hardening rate decreased, ultimate tensile strength decreased, and elongation to failure increased. These variations in mechanical properties were correlated to the variations in microstructural parameters (such as ferrite grain size, solid solution concentrations, precipitate number density and dislocation density). Calculations based on the measured microstructural parameters suggested the grain refinement, solid solution strengthening, precipitation strengthening, and work hardening contributed up to 32 pct, up to 48 pct, up to 25 pct, and less than 3 pct to the yield stress, respectively. With a decrease in the finish deformation temperature, both the grain size strengthening and solid solution strengthening increased, the precipitation strengthening decreased, and the work hardening contribution did not vary significantly

Non-crossing dependencies: Least effort, not grammar

The use of null hypotheses (in a statistical sense) is common in hard sciences but not in theoretical linguistics. Here the null hypothesis that the low frequency of syntactic dependency crossings is expected by an arbitrary ordering of words is rejected. It is shown that this would require star dependency structures, which are both unrealistic and too restrictive. The hypothesis of the limited resources of the human brain is revisited. Stronger null hypotheses taking into account actual dependency lengths for the likelihood of crossings are presented. Those hypotheses suggests that crossings are likely to reduce when dependencies are shortened. A hypothesis based on pressure to reduce dependency lengths is more parsimonious than a principle of minimization of crossings or a grammatical ban that is totally dissociated from the general and non-linguistic principle of economy.Postprint (author's final draft

A Quantum-mechanical Approach for Constrained Macromolecular Chains

Many approaches to three-dimensional constrained macromolecular chains at thermal equilibrium, at about room temperatures, are based upon constrained Classical Hamiltonian Dynamics (cCHDa). Quantum-mechanical approaches (QMa) have also been treated by different researchers for decades. QMa address a fundamental issue (constraints versus the uncertainty principle) and are versatile: they also yield classical descriptions (which may not coincide with those from cCHDa, although they may agree for certain relevant quantities). Open issues include whether QMa have enough practical consequences which differ from and/or improve those from cCHDa. We shall treat cCHDa briefly and deal with QMa, by outlining old approaches and focusing on recent ones.Comment: Expands review published in The European Physical Journal (Special Topics) Vol. 200, pp. 225-258 (2011

Multi-dimensional modeling and simulation of semiconductor nanophotonic devices

Self-consistent modeling and multi-dimensional simulation of semiconductor nanophotonic devices is an important tool in the development of future integrated light sources and quantum devices. Simulations can guide important technological decisions by revealing performance bottlenecks in new device concepts, contribute to their understanding and help to theoretically explore their optimization potential. The efficient implementation of multi-dimensional numerical simulations for computer-aided design tasks requires sophisticated numerical methods and modeling techniques. We review recent advances in device-scale modeling of quantum dot based single-photon sources and laser diodes by self-consistently coupling the optical Maxwell equations with semiclassical carrier transport models using semi-classical and fully quantum mechanical descriptions of the optically active region, respectively. For the simulation of realistic devices with complex, multi-dimensional geometries, we have developed a novel hp-adaptive finite element approach for the optical Maxwell equations, using mixed meshes adapted to the multi-scale properties of the photonic structures. For electrically driven devices, we introduced novel discretization and parameter-embedding techniques to solve the drift-diffusion system for strongly degenerate semiconductors at cryogenic temperature. Our methodical advances are demonstrated on various applications, including vertical-cavity surface-emitting lasers, grating couplers and single-photon sources

Large-Eddy Simulations of Magnetohydrodynamic Turbulence in Heliophysics and Astrophysics

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and most challenging of these problems is turbulence. Yet, despite these advances, the extreme parameter regimes encountered in space physics and astrophysics (as in atmospheric and oceanic physics) still preclude direct numerical simulation. Numerical models must take a Large Eddy Simulation (LES) approach, explicitly computing only a fraction of the active dynamical scales. The success of such an approach hinges on how well the model can represent the subgrid-scales (SGS) that are not explicitly resolved. In addition to the parameter regime, heliophysical and astrophysical applications must also face an equally daunting challenge: magnetism. The presence of magnetic fields in a turbulent, electrically conducting fluid flow can dramatically alter the coupling between large and small scales, with potentially profound implications for LES/SGS modeling. In this review article, we summarize the state of the art in LES modeling of turbulent magnetohydrodynamic (MHD) ows. After discussing the nature of MHD turbulence and the small-scale processes that give rise to energy dissipation, plasma heating, and magnetic reconnection, we consider how these processes may best be captured within an LES/SGS framework. We then consider several special applications in heliophysics and astrophysics, assessing triumphs, challenges,and future directions

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)