9,275 research outputs found
Modeling the input history of programs for improved instruction-memory performance
When a program is loaded into memory for execution, the relative position of
its basic blocks is crucial, since loading basic blocks that are unlikely to be
executed first places them high in the instruction-memory hierarchy only to be
dislodged as the execution goes on. In this paper we study the use of Bayesian
networks as models of the input history of a program. The main point is the
creation of a probabilistic model that persists as the program is run on
different inputs and at each new input refines its own parameters in order to
reflect the program's input history more accurately. As the model is thus
tuned, it causes basic blocks to be reordered so that, upon arrival of the next
input for execution, loading the basic blocks into memory automatically takes
into account the input history of the program. We report on extensive
experiments, whose results demonstrate the efficacy of the overall approach in
progressively lowering the execution times of a program on identical inputs
placed randomly in a sequence of varied inputs. We provide results on selected
SPEC CINT2000 programs and also evaluate our approach as compared to the gcc
level-3 optimization and to Pettis-Hansen reordering
Characterizing neuromorphologic alterations with additive shape functionals
The complexity of a neuronal cell shape is known to be related to its
function. Specifically, among other indicators, a decreased complexity in the
dendritic trees of cortical pyramidal neurons has been associated with mental
retardation. In this paper we develop a procedure to address the
characterization of morphological changes induced in cultured neurons by
over-expressing a gene involved in mental retardation. Measures associated with
the multiscale connectivity, an additive image functional, are found to give a
reasonable separation criterion between two categories of cells. One category
consists of a control group and two transfected groups of neurons, and the
other, a class of cat ganglionary cells. The reported framework also identified
a trend towards lower complexity in one of the transfected groups. Such results
establish the suggested measures as an effective descriptors of cell shape
The evolution of the Sun's birth cluster and the search for the solar siblings with Gaia
We use self-consistent numerical simulations of the evolution and disruption
of the Sun's birth cluster in the Milky Way potential to investigate the
present-day phase space distribution of the Sun's siblings. The simulations
include the gravitational N-body forces within the cluster and the effects of
stellar evolution on the cluster population. In addition the gravitational
forces due to the Milky Way potential are accounted for in a self-consistent
manner. Our aim is to understand how the astrometric and radial velocity data
from the Gaia mission can be used to pre-select solar sibling candidates. We
vary the initial conditions of the Sun's birth cluster, as well as the
parameters of the Galactic potential. We show that the disruption time-scales
of the cluster are insensitive to the details of the non-axisymmetric
components of the Milky Way model and we make predictions, averaged over the
different simulated possibilities, about the number of solar siblings that
should appear in surveys such as Gaia or GALAH. We find a large variety of
present-day phase space distributions of solar siblings, which depend on the
cluster initial conditions and the Milky Way model parameters. We show that
nevertheless robust predictions can be made about the location of the solar
siblings in the space of parallaxes (), proper motions () and
radial velocities (). By calculating the ratio of the number of
simulated solar siblings to that of the number of stars in a model Galactic
disk, we find that this ratio is above 0.5 in the region given by: mas, masyr, and kms. Selecting stars from this region should increase the probability
of success in identifying solar siblings through follow up observations
[Abridged].Comment: 13 pages, 7 figures. Accepted for publication in MNRA
Diffusion Enhancement in Core-softened fluid confined in nanotubes
We study the effect of confinement in the dynamical behavior of a
core-softened fluid. The fluid is modeled as a two length scales potential.
This potential in the bulk reproduces the anomalous behavior observed in the
density and in the diffusion of liquid water. A series of Molecular
Dynamics simulations for this two length scales fluid confined in a nanotube
were performed. We obtain that the diffusion coefficient increases with the
increase of the nanotube radius for wide channels as expected for normal
fluids. However, for narrow channels, the confinement shows an enhancement in
the diffusion coefficient when the nanotube radius decreases. This behavior,
observed for water, is explained in the framework of the two length scales
potential.Comment: 17 pages, 8 figures, accept for publication at J. Chem. Phy
Heterosis in maize single crosses derived from a yellow Tuxpeño variety in Brazil.
Most maize (Zea mays L.) crosses in Tropical regions use the heterotic pattern of Tupeno dent and Caribbean flint. Corsses between related lines are not used for commercial production. Related inbred lines are used in either double or three-way hybrids with other unrelated lines to develop superior hybrids. This study was conducted to determine the combining ability among 11 related inbred lines from a Tuxpeno population. The 11 inbred lines were crossed in a diallel series and were evaluated at six locations. A combinig ability analysis was made for grain yeild. The average yield across environments for the 55 single (44.8 q/ha) was not comparable to that of the single-cross hybrid (56.5 q/ha), induced as check. General combining ability (GCA) effects and specific combining ability (SCA) effects were highly significant (P < 0.01). Variation due to GCA, however, accounted for 68% of the variation among crosses. Indicating that additive genetic effects were more important than nonadditive effects. Highly significantly positive GCA effects were observed for lines 6 (2.44 q/ha) and 7 (6.40 q/ha) and highly significantly negative GCA effects for lines 5 (1.63 q/ha), 10 (2.64 q/ha), and 11 (4,01 q/ha). Significantly positive SCA effects were observed with line 4 x line 11, line 5 x line 9, and line 5 x 11 crosses. Lines 6 and 7 may have potential use as parents for three-way or double-cross hybrids
Optimization of supply diversity for the self-assembly of simple objects in two and three dimensions
The field of algorithmic self-assembly is concerned with the design and
analysis of self-assembly systems from a computational perspective, that is,
from the perspective of mathematical problems whose study may give insight into
the natural processes through which elementary objects self-assemble into more
complex ones. One of the main problems of algorithmic self-assembly is the
minimum tile set problem (MTSP), which asks for a collection of types of
elementary objects (called tiles) to be found for the self-assembly of an
object having a pre-established shape. Such a collection is to be as concise as
possible, thus minimizing supply diversity, while satisfying a set of stringent
constraints having to do with the termination and other properties of the
self-assembly process from its tile types. We present a study of what we think
is the first practical approach to MTSP. Our study starts with the introduction
of an evolutionary heuristic to tackle MTSP and includes results from extensive
experimentation with the heuristic on the self-assembly of simple objects in
two and three dimensions. The heuristic we introduce combines classic elements
from the field of evolutionary computation with a problem-specific variant of
Pareto dominance into a multi-objective approach to MTSP.Comment: Minor typos correcte
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