105,158 research outputs found
Structured Prediction of Sequences and Trees using Infinite Contexts
Linguistic structures exhibit a rich array of global phenomena, however
commonly used Markov models are unable to adequately describe these phenomena
due to their strong locality assumptions. We propose a novel hierarchical model
for structured prediction over sequences and trees which exploits global
context by conditioning each generation decision on an unbounded context of
prior decisions. This builds on the success of Markov models but without
imposing a fixed bound in order to better represent global phenomena. To
facilitate learning of this large and unbounded model, we use a hierarchical
Pitman-Yor process prior which provides a recursive form of smoothing. We
propose prediction algorithms based on A* and Markov Chain Monte Carlo
sampling. Empirical results demonstrate the potential of our model compared to
baseline finite-context Markov models on part-of-speech tagging and syntactic
parsing
Interactions between unidirectional quantized vortex rings
We have used the vortex filament method to numerically investigate the
interactions between pairs of quantized vortex rings that are initially
traveling in the same direction but with their axes offset by a variable impact
parameter. The interaction of two circular rings of comparable radii produce
outcomes that can be categorized into four regimes, dependent only on the
impact parameter; the two rings can either miss each other on the inside or
outside, or they can reconnect leading to final states consisting of either one
or two deformed rings. The fraction of of energy went into ring deformations
and the transverse component of velocity of the rings are analyzed for each
regime. We find that rings of very similar radius only reconnect for a very
narrow range of the impact parameter, much smaller than would be expected from
geometrical cross-section alone. In contrast, when the radii of the rings are
very different, the range of impact parameters producing a reconnection is
close to the geometrical value. A second type of interaction considered is the
collision of circular rings with a highly deformed ring. This type of
interaction appears to be a productive mechanism for creating small vortex
rings. The simulations are discussed in the context of experiments on colliding
vortex rings and quantum turbulence in superfluid helium in the zero
temperature limit
Failure mechanisms of graphene under tension
Recent experiments established pure graphene as the strongest material known
to mankind, further invigorating the question of how graphene fails. Using
density functional theory, we reveal the mechanisms of mechanical failure of
pure graphene under a generic state of tension. One failure mechanism is a
novel soft-mode phonon instability of the -mode, whereby the graphene
sheet undergoes a phase transition and is driven towards isolated benzene rings
resulting in a reduction of strength. The other is the usual elastic
instability corresponding to a maximum in the stress-strain curve. Our results
indicate that finite wave vector soft modes can be the key factor in limiting
the strength of monolayer materials
Proteoglycan neofunctions: regulation of inflammation and autophagy in cancer biology.
Inflammation and autophagy have emerged as prominent issues in the context of proteoglycan signaling. In particular, two small, leucine-rich proteoglycans, biglycan and decorin, play pivotal roles in the regulation of these vital cellular pathways and, as such, are intrinsically involved in cancer initiation and progression. In this minireview, we will address novel functions of biglycan and decorin in inflammation and autophagy, and analyze new emerging signaling events triggered by these proteoglycans, which directly or indirectly modulate these processes. We will critically discuss the dual role of proteoglycan-driven inflammation and autophagy in tumor biology, and delineate the potential mechanisms through which soluble extracellular matrix constituents affect the microenvironment associated with inflammatory and neoplastic diseases
Strong correlation effects and optical conductivity in electron doped cuprates
We demonstrate that most features ascribed to strong correlation effects in
various spectroscopies of the cuprates are captured by a calculation of the
self-energy incorporating effects of spin and charge fluctuations. The self
energy is calculated over the full doping range of electron-doped cuprates from
half filling to the overdoped system. The spectral function reveals four
subbands, two widely split incoherent bands representing the remnant of the
split Hubbard bands, and two additional coherent, spin- and charge-dressed
in-gap bands split by a spin-density wave, which collapses in the overdoped
regime. The incoherent features persist to high doping, producing a remnant
Mott gap in the optical spectra, while transitions between the in-gap states
lead to pseudogap features in the mid-infrared.Comment: 5 pages, 4 figure
New neighborhood based rough sets
Neighborhood based rough sets are important generalizations of the classical rough sets of Pawlak, as neighborhood operators generalize equivalence classes. In this article, we introduce nine neighborhood based operators and we study the partial order relations between twenty-two different neighborhood operators obtained from one covering. Seven neighborhood operators result in new rough set approximation operators. We study how these operators are related to the other fifteen neighborhood based approximation operators in terms of partial order relations, as well as to seven non-neighborhood-based rough set approximation operators
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