1,459 research outputs found
Two-Dimensional Wigner Crystal in Anisotropic Semiconductor
We investigate the effect of mass anisotropy on the Wigner crystallization
transition in a two-dimensional (2D) electron gas. The static and dynamical
properties of a 2D Wigner crystal have been calculated for arbitrary 2D Bravais
lattices in the presence of anisotropic mass, as may be obtainable in Si
MOSFETs with (110) surface. By studying the stability of all possible lattices,
we find significant change in the crystal structure and melting density of the
electron lattice with the lowest ground state energy.Comment: 4 pages, revtex, 4 figure
The Spectrum of Electromagnetic Jets from Kerr Black Holes and Naked Singularities in the Teukolsky Perturbation Theory
We give a new theoretical basis for examination of the presence of the Kerr
black hole (KBH) or the Kerr naked singularity (KNS) in the central engine of
different astrophysical objects around which astrophysical jets are typically
formed: X-ray binary systems, gamma ray bursts (GRBs), active galactic nuclei
(AGN), etc. Our method is based on the study of the exact solutions of the
Teukolsky master equation for electromagnetic perturbations of the Kerr metric.
By imposing original boundary conditions on the solutions so that they describe
a collimated electromagnetic outflow, we obtain the spectra of possible {\em
primary jets} of radiation, introduced here for the first time. The theoretical
spectra of primary electromagnetic jets are calculated numerically. Our main
result is a detailed description of the qualitative change of the behavior of
primary electromagnetic jet frequencies under the transition from the KBH to
the KNS, considered here as a bifurcation of the Kerr metric. We show that
quite surprisingly the novel spectra describe linearly stable primary
electromagnetic jets from both the KBH and the KNS. Numerical investigation of
the dependence of these primary jet spectra on the rotation of the Kerr metric
is presented and discussed.Comment: 18 pages, 35 figures, LaTeX file. Final version. Accepted for
publication in Astrophysics and Space Science. Amendments. Typos corrected.
Novel notion -"primary jet" is introduced. New references and comments adde
Neutron Stars in a Varying Speed of Light Theory
We study neutron stars in a varying speed of light (VSL) theory of gravity in
which the local speed of light depends upon the value of a scalar field .
We find that the masses and radii of the stars are strongly dependent on the
strength of the coupling between and the matter field and that for
certain choices of coupling parameters, the maximum neutron star mass can be
arbitrarily small. We also discuss the phenomenon of cosmological evolution of
VSL stars (analogous to the gravitational evolution in scalar-tensor theories)
and we derive a relation showing how the fractional change in the energy of a
star is related to the change in the cosmological value of the scalar field.Comment: 15 pages, 2 figures. Added solutions with a more realistic equation
of state. To be published in PR
Magnetic properties of DyAs and DyP (001) films
DyP and DyAs single crystal films were grown epitaxially on GaAs substrates by molecular beam epitaxy (MBE) to study its magnetic properties using SQUID magnetometry. DyP exhibited ferromagnetic-like order below approximately 9 K, while DyAs showed an antiferromagnetic-like order below approximately 6 K. The anisotropy of the DyP was higher as compared to DyAs
Simulation of Guided Wave Propagation in Isotropic and Composite Structures using LISA
Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97117/1/AIAA2012-1387.pd
Cost-sensitive ordinal classification methods to predict SARS-CoV-2 pneumonia severity
Objective: To study the suitability of cost-sensitive ordinal artificial intelligence-machine learning (AI-ML) strategies in the prognosis of SARS-CoV-2 pneumonia severity.
Materials & methods: Observational, retrospective, longitudinal, cohort study in 4 hospitals in Spain. Information regarding demographic and clinical status was supplemented by socioeconomic data and air pollution exposures. We proposed AI-ML algorithms for ordinal classification via ordinal decomposition and for cost-sensitive learning via resampling techniques. For performance-based model selection, we defined a custom score including per-class sensitivities and asymmetric misprognosis costs. 260 distinct AI-ML models were evaluated via 10 repetitions of 5×5 nested cross-validation with hyperparameter tuning. Model selection was followed by the calibration of predicted probabilities. Final overall performance was compared against five well-established clinical severity scores and against a ‘standard’ (non-cost sensitive, non-ordinal) AI-ML baseline. In our best model, we also evaluated its explainability with respect to each of the input variables.
Results: The study enrolled =1548 patients: 712 experienced low, 238 medium, and 598 high clinical severity. =131 variables were collected, becoming =148 features after categorical encoding. Model selection resulted in our best-performing AI-ML pipeline having: a) no imputation of missing data, b) no feature selection (i.e. using the full set of features), c) ‘Ordered Partitions’ ordinal decomposition, d) cost-based reimbalance, and e) a Histogram-based Gradient Boosting classifier. This best model (calibrated) obtained a median accuracy of 68.1% [67.3%, 68.8%] (95% confidence interval), a balanced accuracy of 57.0% [55.6%, 57.9%], and an overall area under the curve (AUC) 0.802 [0.795, 0.808]. In our dataset, it outperformed all five clinical severity scores and the ‘standard’ AI-ML baseline.
Discussion & conclusion: We conducted an exhaustive exploration of AI-ML methods designed for both ordinal and cost-sensitive classification, motivated by a real-world application domain (clinical severity prognosis) in which these topics arise naturally. Our model with the best classification performance exploited successfully the ordering information of ground truth classes, coping with imbalance and asymmetric costs. However, these ordinal and cost-sensitive aspects are seldom explored in the literature
Anisotropic three-dimentional magnetic fluctuations in heavy fermion CeRhIn5
CeRhIn5 is a heavy fermion antiferromagnet that orders at 3.8 K. The
observation of pressure-induced superconductivity in CeRhIn5 at a very high Tc
of 2.1 K for heavy fermion materials has led to speculations regarding to its
magnetic fluctuation spectrum. Using magnetic neutron scattering, we report
anisotropic three-dimensional antiferromagnetic fluctuations with an energy
scale of less than 1.7 meV for temperatures as high as 3Tc. In addition, the
effect of the magnetic fluctuations on electrical resistivity is well described
by the Born approximation.Comment: 4 pages, 4 figure
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