10,835 research outputs found
Fixed-parameter tractability of multicut parameterized by the size of the cutset
Given an undirected graph , a collection of
pairs of vertices, and an integer , the Edge Multicut problem ask if there
is a set of at most edges such that the removal of disconnects
every from the corresponding . Vertex Multicut is the analogous
problem where is a set of at most vertices. Our main result is that
both problems can be solved in time , i.e.,
fixed-parameter tractable parameterized by the size of the cutset in the
solution. By contrast, it is unlikely that an algorithm with running time of
the form exists for the directed version of the problem, as
we show it to be W[1]-hard parameterized by the size of the cutset
Time-reversible Born-Oppenheimer molecular dynamics
We present a time-reversible Born-Oppenheimer molecular dynamics scheme,
based on self-consistent Hartree-Fock or density functional theory, where both
the nuclear and the electronic degrees of freedom are propagated in time. We
show how a time-reversible adiabatic propagation of the electronic degrees of
freedom is possible despite the non-linearity and incompleteness of the
self-consistent field procedure. Time-reversal symmetry excludes a systematic
long-term energy drift for a microcanonical ensemble and the number of
self-consistency cycles can be kept low (often only 2-4 cycles per nuclear time
step) thanks to a good initial guess given by the adiabatic propagation of the
electronic degrees of freedom. The time-reversible Born-Oppenheimer molecular
dynamics scheme therefore combines a low computational cost with a physically
correct time-reversible representation of the dynamics, which preserves a
detailed balance between propagation forwards and backwards in time.Comment: 4 pages, 4 figure
Optimality program in segment and string graphs
Planar graphs are known to allow subexponential algorithms running in time
or for most of the paradigmatic
problems, while the brute-force time is very likely to be
asymptotically best on general graphs. Intrigued by an algorithm packing curves
in by Fox and Pach [SODA'11], we investigate which
problems have subexponential algorithms on the intersection graphs of curves
(string graphs) or segments (segment intersection graphs) and which problems
have no such algorithms under the ETH (Exponential Time Hypothesis). Among our
results, we show that, quite surprisingly, 3-Coloring can also be solved in
time on string graphs while an algorithm running
in time for 4-Coloring even on axis-parallel segments (of unbounded
length) would disprove the ETH. For 4-Coloring of unit segments, we show a
weaker ETH lower bound of which exploits the celebrated
Erd\H{o}s-Szekeres theorem. The subexponential running time also carries over
to Min Feedback Vertex Set but not to Min Dominating Set and Min Independent
Dominating Set.Comment: 19 pages, 15 figure
Density-functional study of Cu atoms, monolayers, and coadsorbates on polar ZnO surfaces
The structure and electronic properties of single Cu atoms, copper monolayers
and thin copper films on the polar oxygen and zinc terminated surfaces of ZnO
are studied using periodic density-functional calculations. We find that the
binding energy of Cu atoms sensitively depends on how charge neutrality of the
polar surfaces is achieved. Bonding is very strong if the surfaces are
stabilized by an electronic mechanism which leads to partially filled surface
bands. As soon as the surface bands are filled (either by partial Cu coverage,
by coadsorbates, or by the formation of defects), the binding energy decreases
significantly. In this case, values very similar to those found for nonpolar
surfaces and for copper on finite ZnO clusters are obtained. Possible
implications of these observations concerning the growth mode of copper on
polar ZnO surfaces and their importance in catalysis are discussed.Comment: 6 pages with 2 postscript figures embedded. Uses REVTEX and epsf
macro
Scotland, Catalonia and the “right” to self-determination: a comment suggested by Kathryn Crameri’s “Do Catalans Have the Right to Decide?
No abstract available
Stability domains of actin genes and genomic evolution
In eukaryotic genes the protein coding sequence is split into several
fragments, the exons, separated by non-coding DNA stretches, the introns.
Prokaryotes do not have introns in their genome. We report the calculations of
stability domains of actin genes for various organisms in the animal, plant and
fungi kingdoms. Actin genes have been chosen because they have been highly
conserved during evolution. In these genes all introns were removed so as to
mimic ancient genes at the time of the early eukaryotic development, i.e.
before introns insertion. Common stability boundaries are found in evolutionary
distant organisms, which implies that these boundaries date from the early
origin of eukaryotes. In general boundaries correspond with introns positions
of vertebrates and other animals actins, but not much for plants and fungi. The
sharpest boundary is found in a locus where fungi, algae and animals have
introns in positions separated by one nucleotide only, which identifies a
hot-spot for insertion. These results suggest that some introns may have been
incorporated into the genomes through a thermodynamic driven mechanism, in
agreement with previous observations on human genes. They also suggest a
different mechanism for introns insertion in plants and animals.Comment: 9 Pages, 7 figures. Phys. Rev. E in pres
Exchange Monte Carlo for Molecular Simulations with Monoelectronic Hamiltonians
We introduce a general Monte Carlo scheme for achieving atomistic simulations
with monoelectronic Hamiltonians including the thermalization of both nuclear
and electronic degrees of freedom. The kinetic Monte Carlo algorithm is used to
obtain the exact occupation numbers of the electronic levels at canonical
equilibrium, and comparison is made with Fermi-Dirac statistics in infinite and
finite systems. The effects of a nonzero electronic temperature on the
thermodynamic properties of liquid silver and sodium clusters are presented
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Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
BACKGROUND: For virtually every patient with colorectal cancer (CRC), hematoxylin-eosin (HE)-stained tissue slides are available. These images contain quantitative information, which is not routinely used to objectively extract prognostic biomarkers. In the present study, we investigated whether deep convolutional neural networks (CNNs) can extract prognosticators directly from these widely available images.
METHODS AND FINDINGS: We hand-delineated single-tissue regions in 86 CRC tissue slides, yielding more than 100,000 HE image patches, and used these to train a CNN by transfer learning, reaching a nine-class accuracy of >94% in an independent data set of 7,180 images from 25 CRC patients. With this tool, we performed automated tissue decomposition of representative multitissue HE images from 862 HE slides in 500 stage I-IV CRC patients in the The Cancer Genome Atlas (TCGA) cohort, a large international multicenter collection of CRC tissue. Based on the output neuron activations in the CNN, we calculated a "deep stroma score," which was an independent prognostic factor for overall survival (OS) in a multivariable Cox proportional hazard model (hazard ratio [HR] with 95% confidence interval [CI]: 1.99 [1.27-3.12], p = 0.0028), while in the same cohort, manual quantification of stromal areas and a gene expression signature of cancer-associated fibroblasts (CAFs) were only prognostic in specific tumor stages. We validated these findings in an independent cohort of 409 stage I-IV CRC patients from the "Darmkrebs: Chancen der Verhütung durch Screening" (DACHS) study who were recruited between 2003 and 2007 in multiple institutions in Germany. Again, the score was an independent prognostic factor for OS (HR 1.63 [1.14-2.33], p = 0.008), CRC-specific OS (HR 2.29 [1.5-3.48], p = 0.0004), and relapse-free survival (RFS; HR 1.92 [1.34-2.76], p = 0.0004). A prospective validation is required before this biomarker can be implemented in clinical workflows.
CONCLUSIONS: In our retrospective study, we show that a CNN can assess the human tumor microenvironment and predict prognosis directly from histopathological images
Erratum: Search for gravitational-wave bursts in LIGO data from the fourth science run (Classical and Quatnum Gravity (2007) 24 (5343-5369))
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