4,669 research outputs found
Transcription of 2013 \u3cem\u3eChapman Law Review\u3c/em\u3e Symposium: The Future of Law, Business, and Legal Education: How to Prepare Students to Meet Corporate Needs
Right eigenvalue equation in quaternionic quantum mechanics
We study the right eigenvalue equation for quaternionic and complex linear
matrix operators defined in n-dimensional quaternionic vector spaces. For
quaternionic linear operators the eigenvalue spectrum consists of n complex
values. For these operators we give a necessary and sufficient condition for
the diagonalization of their quaternionic matrix representations. Our
discussion is also extended to complex linear operators, whose spectrum is
characterized by 2n complex eigenvalues. We show that a consistent analysis of
the eigenvalue problem for complex linear operators requires the choice of a
complex geometry in defining inner products. Finally, we introduce some
examples of the left eigenvalue equations and highlight the main difficulties
in their solution.Comment: 24 pages, AMS-Te
Economics of neuraminidase inhibitor stock piling for pandemic influenza, Singapore.
We compared strategies for stock piling neuraminidase inhibitors to treat and prevent influenza in Singapore. Cost-benefit and cost-effectiveness analyses, with Monte Carlo simulations, were used to determine economic outcomes. A pandemic in a population of 4.2 million would result in an estimated 525-1,775 deaths, 10,700-38,600 hospitalization days, and economic costs of 0.7 dollars to 2.2 billion Singapore dollars. The treatment-only strategy had optimal economic benefits: stock piles of antiviral agents for 40% of the population would save an estimated 418 lives and 414 million dollars, at a cost of 52.6 million dollars per shelf-life cycle of the stock pile. Prophylaxis was economically beneficial in high-risk subpopulations, which account for 78% of deaths, and in pandemics in which the death rate was >0.6%. Prophylaxis for pandemics with a 5% case-fatality rate would save 50,000 lives and 81 billion dollars. These models can help policymakers weigh the options for pandemic planning
Independent ferroelectric contributions and rare-earth-induced polarization reversal in multiferroic TbMn2O5
Three independent contributions to the magnetically induced spontaneous
polarization of multiferroic TbMn2O5 are uniquely separated by optical second
harmonic generation and an analysis in terms of Landau theory. Two of them are
related to the magnetic Mn3+/4+ order and are independent of applied fields of
up to 7 T. The third contribution is related to the long-range
antiferromagnetic Tb3+ order. It shows a drastic decrease upon the application
of a magnetic field and mediates the change of sign of the spontaneous electric
polarization in TbMn2O5. The close relationship between the rare-earth
long-range order and the non-linear optical properties points to isotropic
Tb-Tb exchange and oxygen spin polarization as mechanism for this rare-earth
induced ferroelectricity.Comment: 8 pages, 5 figure
From Andreev to Majorana bound states in hybrid superconductor-semiconductor nanowires
Electronic excitations above the ground state must overcome an energy gap in
superconductors with spatially-homogeneous s-wave pairing. In contrast,
inhomogeneous superconductors such as those with magnetic impurities or weak
links, or heterojunctions containing normal metals or quantum dots, can host
subgap electronic excitations that are generically known as Andreev bound
states (ABSs). With the advent of topological superconductivity, a new kind of
ABS with exotic qualities, known as Majorana bound state (MBS), has been
discovered. We review the main properties of ABSs and MBSs, and the
state-of-the-art techniques for their detection. We focus on hybrid
superconductor-semiconductor nanowires, possibly coupled to quantum dots, as
one of the most flexible and promising experimental platforms. We discuss how
the combined effect of spin-orbit coupling and Zeeman field in these wires
triggers the transition from ABSs into MBSs. We show theoretical progress
beyond minimal models in understanding experiments, including the possibility
of different types of robust zero modes that may emerge without a
band-topological transition. We examine the role of spatial non-locality, a
special property of MBS wavefunctions that, together with non-Abelian braiding,
is the key to realizing topological quantum computation.Comment: Review. 23 pages, 8 figures, 1 table. Shareable published version by
Springer Nature at https://rdcu.be/b7DWT (free to read but not to download
DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets
One of the grand challenges of cell biology is inferring the gene regulatory
network (GRN) which describes interactions between genes and their products
that control gene expression and cellular function. We can treat this as a
causal discovery problem but with two non-standard challenges: (1) regulatory
networks are inherently cyclic so we should not model a GRN as a directed
acyclic graph (DAG), and (2) observations have significant measurement noise,
so for typical sample sizes there will always be a large equivalence class of
graphs that are likely given the data, and we want methods that capture this
uncertainty. Existing methods either focus on challenge (1), identifying cyclic
structure from dynamics, or on challenge (2) learning complex Bayesian
posteriors over DAGs, but not both. In this paper we leverage the fact that it
is possible to estimate the "velocity" of gene expression with RNA velocity
techniques to develop an approach that addresses both challenges. Because we
have access to velocity information, we can treat the Bayesian structure
learning problem as a problem of sparse identification of a dynamical system,
capturing cyclic feedback loops through time. Since our objective is to model
uncertainty over discrete structures, we leverage Generative Flow Networks
(GFlowNets) to estimate the posterior distribution over the combinatorial space
of possible sparse dependencies. Our results indicate that our method learns
posteriors that better encapsulate the distributions of cyclic structures
compared to counterpart state-of-the-art Bayesian structure learning
approaches
ZFIRE: The Evolution of the Stellar Mass Tully-Fisher Relation to Redshift 2.0 < Z < 2.5 with MOSFIRE
Using observations made with MOSFIRE on Keck I as part of the ZFIRE survey,
we present the stellar mass Tully-Fisher relation at 2.0 < z < 2.5. The sample
was drawn from a stellar mass limited, Ks-band selected catalog from ZFOURGE
over the CANDELS area in the COSMOS field. We model the shear of the Halpha
emission line to derive rotational velocities at 2.2X the scale radius of an
exponential disk (V2.2). We correct for the blurring effect of a
two-dimensional PSF and the fact that the MOSFIRE PSF is better approximated by
a Moffat than a Gaussian, which is more typically assumed for natural seeing.
We find for the Tully-Fisher relation at 2.0 < z < 2.5 that logV2.2 =(2.18 +/-
0.051)+(0.193 +/- 0.108)(logM/Msun - 10) and infer an evolution of the
zeropoint of Delta M/Msun = -0.25 +/- 0.16 dex or Delta M/Msun = -0.39 +/- 0.21
dex compared to z = 0 when adopting a fixed slope of 0.29 or 1/4.5,
respectively. We also derive the alternative kinematic estimator S0.5, with a
best-fit relation logS0.5 =(2.06 +/- 0.032)+(0.211 +/- 0.086)(logM/Msun - 10),
and infer an evolution of Delta M/Msun= -0.45 +/- 0.13 dex compared to z < 1.2
if we adopt a fixed slope. We investigate and review various systematics,
ranging from PSF effects, projection effects, systematics related to stellar
mass derivation, selection biases and slope. We find that discrepancies between
the various literature values are reduced when taking these into account. Our
observations correspond well with the gradual evolution predicted by
semi-analytic models.Comment: 21 pages, 14 figures, 1 appendix. Accepted for publication by Apj,
February 28, 201
Cooperative Carbon Dioxide Adsorption in Alcoholamine- and Alkoxyalkylamine-Functionalized Metal-Organic Frameworks.
A series of structurally diverse alcoholamine- and alkoxyalkylamine-functionalized variants of the metal-organic framework Mg2 (dobpdc) are shown to adsorb CO2 selectively via cooperative chain-forming mechanisms. Solid-state NMR spectra and optimized structures obtained from van der Waals-corrected density functional theory calculations indicate that the adsorption profiles can be attributed to the formation of carbamic acid or ammonium carbamate chains that are stabilized by hydrogen bonding interactions within the framework pores. These findings significantly expand the scope of chemical functionalities that can be utilized to design cooperative CO2 adsorbents, providing further means of optimizing these powerful materials for energy-efficient CO2 separations
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