50,009 research outputs found
Conceptual Explanation for the Algebra in the Noncommutative Approach to the Standard Model
The purpose of this letter is to remove the arbitrariness of the ad hoc
choice of the algebra and its representation in the noncommutative approach to
the Standard Model, which was begging for a conceptual explanation. We assume
as before that space-time is the product of a four-dimensional manifold by a
finite noncommmutative space F. The spectral action is the pure gravitational
action for the product space. To remove the above arbitrariness, we classify
the irreducibe geometries F consistent with imposing reality and chiral
conditions on spinors, to avoid the fermion doubling problem, which amounts to
have total dimension 10 (in the K-theoretic sense). It gives, almost uniquely,
the Standard Model with all its details, predicting the number of fermions per
generation to be 16, their representations and the Higgs breaking mechanism,
with very little input. The geometrical model is valid at the unification
scale, and has relations connecting the gauge couplings to each other and to
the Higgs coupling. This gives a prediction of the Higgs mass of around 170 GeV
and a mass relation connecting the sum of the square of the masses of the
fermions to the W mass square, which enables us to predict the top quark mass
compatible with the measured experimental value. We thus manage to have the
advantages of both SO(10) and Kaluza-Klein unification, without paying the
price of plethora of Higgs fields or the infinite tower of states.Comment: Title change only. The title "A Dress for SM the Beggar" was changed
by the Editor of Physical Review Letter
Distributed Coupled Multi-Agent Stochastic Optimization
This work develops effective distributed strategies for the solution of
constrained multi-agent stochastic optimization problems with coupled
parameters across the agents. In this formulation, each agent is influenced by
only a subset of the entries of a global parameter vector or model, and is
subject to convex constraints that are only known locally. Problems of this
type arise in several applications, most notably in disease propagation models,
minimum-cost flow problems, distributed control formulations, and distributed
power system monitoring. This work focuses on stochastic settings, where a
stochastic risk function is associated with each agent and the objective is to
seek the minimizer of the aggregate sum of all risks subject to a set of
constraints. Agents are not aware of the statistical distribution of the data
and, therefore, can only rely on stochastic approximations in their learning
strategies. We derive an effective distributed learning strategy that is able
to track drifts in the underlying parameter model. A detailed performance and
stability analysis is carried out showing that the resulting coupled diffusion
strategy converges at a linear rate to an neighborhood of the true
penalized optimizer
Inclusive Decay Rate for in Next-to-Leading Logarithmic Order and CP Asymmetry in the Standard Model
We compute the decay rate for the CKM-suppressed electromagnetic penguin
decay (and its charge conjugate) in NLO QCD, including
leading power corrections in and in the standard model. The
average branching ratio of the decay and its charge conjugate
is estimated to be in the range , obtained by varying the CKM-Wolfenstein parameters
and in the range and and taking into account other parametric dependence. In the stated
range of the CKM parameters, we find the ratio to lie in the range between 0.017 and 0.074.
Theoretical uncertainties in this ratio are found to be small. Hence, this
ratio is well suited to provide independent constraints on the CKM parameters.
The CP-asymmetry in the decay rates is found to be in the
range . Both the decay rates and CP asymmetry are measurable in
forthcoming experiments at factories and possibly at HERA-B.Comment: 17 pages including 7 postscript figures; uses epsfig; The changes
w.r.t the previous version are: A comment about the Bremsstrahlung
corrections is added as well as a note on the feasibility of the measurement
$B -> X_d gamma
Linear Convergence of Primal-Dual Gradient Methods and their Performance in Distributed Optimization
In this work, we revisit a classical incremental implementation of the
primal-descent dual-ascent gradient method used for the solution of equality
constrained optimization problems. We provide a short proof that establishes
the linear (exponential) convergence of the algorithm for smooth
strongly-convex cost functions and study its relation to the non-incremental
implementation. We also study the effect of the augmented Lagrangian penalty
term on the performance of distributed optimization algorithms for the
minimization of aggregate cost functions over multi-agent networks
Evolution of the spectral index after inflation
In this article we investigate the time evolution of the adiabatic(curvature)
and isocurvature (entropy) spectral indices after end of inflation for all
cosmological scales and two different initial conditions. For this purpose,we
first extract an explicit equation for the time evolution of the comoving
curvature perturbation (which may be known as the generalized Mukhanov-Sasaki
equation). It shall be manifested that the evolution of adibatic spectral index
severely depends on the intial conditions and just for the super-Hubble scales
and adiabatic initial conditions is constat as be expected.Moreover,it shall be
clear that the adiabatic spectral index after recombination approach to a
constant value for the isocurvature perturbations.Finally,we re-investgate the
Sachs-Wolfe effect and show that the fudge factor 1/3 in the adiabatic ordinary
Sachs-Wolfe formula must be replaced by 0.4.Comment: 18 pages,4figure
Molecular aspects of MERS-CoV
This article is made available for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Middle East respiratory syndrome coronavirus (MERS-CoV) is a betacoronavirus which can cause acute respiratory distress in humans and is associated with a relatively high mortality rate. Since it was first identified in a patient who died in a Jeddah hospital in 2012, the World Health Organization has been notified of 1735 laboratory-confirmed cases from 27 countries, including 628 deaths. Most cases have occurred in Saudi Arabia. MERS-CoVancestors may be found in OldWorld bats of the Vespertilionidae family. After a proposed bat to camel switching event, transmission of MERS-CoV to humans is likely to have been the result of multiple zoonotic transfers from dromedary camels. Human-to-human transmission appears to require close contact with infected persons, with outbreaks mainly occurring in hospital environments. Outbreaks have been associated with inadequate infection prevention and control implementation, resulting in recommendations on basic and more advanced infection prevention and control measures by the World Health Organization, and issuing of government guidelines based on these recommendations in affected countries including Saudi Arabia. Evolutionary changes in the virus, particularly in the viral spike protein which mediates virus-host cell contact may potentially increase transmission of this virus. Efforts are on-going to identify specific evidence-based therapies or vaccines. The broad-spectrum antiviral nitazoxanide has been shown to have in vitro activity against MERS-CoV. Synthetic peptides and candidate vaccines based on regions of the spike protein have shown promise in rodent and non-human primate models. GLS-5300, a prophylactic DNA-plasmid vaccine encoding S protein, is the first MERS-CoV vaccine to be tested in humans, while monoclonal antibody, m336 has given promising results in animal models and has potential for use in outbreak situations
Band-edge Bilayer Plasmonic Nanostructure for Surface Enhanced Raman Spectroscopy
Spectroscopic analysis of large biomolecules is critical in a number of
applications, including medical diagnostics and label-free biosensing.
Recently, it has been shown that Raman spectroscopy of proteins can be used to
diagnose some diseases, including a few types of cancer. These experiments have
however been performed using traditional Raman spectroscopy and the development
of the Surface enhanced Raman spectroscopy (SERS) assays suitable for large
biomolecules could lead to a substantial decrease in the amount of specimen
necessary for these experiments. We present a new method to achieve high local
field enhancement in surface enhanced Raman spectroscopy through the
simultaneous adjustment of the lattice plasmons and localized surface plasmon
polaritons, in a periodic bilayer nanoantenna array resulting in a high
enhancement factor over the sensing area, with relatively high uniformity. The
proposed plasmonic nanostructure is comprised of two interacting nanoantenna
layers, providing a sharp band-edge lattice plasmon mode and a wide-band
localized surface plasmon for the separate enhancement of the pump and emitted
Raman signals. We demonstrate the application of the proposed nanostructure for
the spectral analysis of large biomolecules by binding a protein (streptavidin)
selectively on the hot-spots between the two stacked layers, using a low
concentration solution (100 nM) and we successfully acquire its SERS spectrum
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