37,580 research outputs found
Chiron: A Robust Recommendation System with Graph Regularizer
Recommendation systems have been widely used by commercial service providers
for giving suggestions to users. Collaborative filtering (CF) systems, one of
the most popular recommendation systems, utilize the history of behaviors of
the aggregate user-base to provide individual recommendations and are effective
when almost all users faithfully express their opinions. However, they are
vulnerable to malicious users biasing their inputs in order to change the
overall ratings of a specific group of items. CF systems largely fall into two
categories - neighborhood-based and (matrix) factorization-based - and the
presence of adversarial input can influence recommendations in both categories,
leading to instabilities in estimation and prediction. Although the robustness
of different collaborative filtering algorithms has been extensively studied,
designing an efficient system that is immune to manipulation remains a
significant challenge. In this work we propose a novel "hybrid" recommendation
system with an adaptive graph-based user/item similarity-regularization -
"Chiron". Chiron ties the performance benefits of dimensionality reduction
(through factorization) with the advantage of neighborhood clustering (through
regularization). We demonstrate, using extensive comparative experiments, that
Chiron is resistant to manipulation by large and lethal attacks
Influence of statistical fluctuations on ratios in relativistic heavy ion collisions
The influence of pure statistical fluctuations on ratio is
investigated in an event-by-event way. Poisson and the modified negative
binomial distributions are used as the multiplicity distributions since they
both have statistical background. It is shown that the distributions of the
ratio in these cases are Gaussian, and the mean and relative variance are given
analytically.Comment: 6 pages in RevTeX, 3 eps figures include
The ping-pong protocol can be attacked without eavesdropping
Attack the ping-pong protocol without eavesdropping.Comment: PACS: 03.67.H
Combinations of antioxidants and/or of epigenetic enzyme inhibitors allow for enhanced collection of mouse bone marrow hematopoietic stem cells in ambient air
Hematopoietic cell transplantation (HCT) is a treatment for malignant and non-malignant disorders. However, sometimes the numbers of donor hematopoietic stem cells (HSC) are limiting, which can compromise the success of HCT. We recently published that collection and processing of mouse bone marrow (BM) and human cord blood cells in a hypoxic atmosphere of 3% O2 or in ambient air (~21% O2) in the presence of cyclosporine A yields increased numbers of HSC. We now show that collection and processing of mouse BM cells in ambient air in the presence of specific combinations of anti-oxidants and/or inhibitors of epigenetic enzymes can also enhance the collection of HSC, information of potential relevance for enhanced efficacy of HCT
Long-lived driven solid-state quantum memory
We investigate the performance of inhomogeneously broadened spin ensembles as
quantum memories under continuous dynamical decoupling. The role of the
continuous driving field is two-fold: first, it decouples individual spins from
magnetic noise; second and more important, it suppresses and reshapes the
spectral inhomogeneity of spin ensembles. We show that a continuous driving
field, which itself may also be inhomogeneous over the ensemble, can enhance
the decay of the tails of the inhomogeneous broadening distribution
considerably. This fact enables a spin ensemble based quantum memory to exploit
the effect of cavity protection and achieve a much longer storage time. In
particular, for a spin ensemble with a Lorentzian spectral distribution, our
calculations demonstrate that continuous dynamical decoupling has the potential
to improve its storage time by orders of magnitude for the state-of-art
experimental parameters
Stability of Multiplanetary Systems in Star Clusters
Most stars form in star clusters and stellar associated. To understand the
roles of star cluster environments in shaping the dynamical evolution of
planetary systems, we carry out direct -body simulations of four planetary
systems models in three different star cluster environments with respectively
N=2k, 8k and 32k stars. In each cluster, an ensemble of initially identical
planetary systems are assigned to solar-type stars with and
evolved for 50~Myr. We found that following the depletion of protoplanetary
disks, external perturbations and planet-planet interactions are two driving
mechanisms responsible for the destabilization of planetary systems. The planet
survival rate varies from in the N=2k cluster to in the
N=32k cluster, which suggests that most planetary systems can indeed survive in
low-mass clusters, except in the central regions. We also find that planet
ejections through stellar encounters are cumulative processes, as only of encounters are strong enough to excite the eccentricity by . Short-period planets can be perturbed through orbit crossings with
long-period planets. When taking into account planet-planet interactions, the
planet ejection rate nearly doubles, and therefore multiplicity contributes to
the vulnerability of planetary systems. In each ensemble, of
planetary orbits become retrograde due to random directions of stellar
encounters. Our results predict that young low-mass star clusters are promising
sites for next-generation planet surveys, yet low planet detection rates are
expected in dense globular clusters such as 47 Tuc. Nevertheless, planets in
denser stellar environments are likely to have shorter orbital periods, which
enhances their detectability.Comment: 19 pages, 13 figures, 4 tables, accepted for publication in MNRA
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