2,775 research outputs found
Evaluation of Manganese (Mn) Binding Proteins in Lung Carcinoma Cells
https://openworks.mdanderson.org/sumexp23/1096/thumbnail.jp
Dynamics of a Massive Binary at Birth
Almost all massive stars have bound stellar companions, existing in binaries
or higher-order multiples. While binarity is theorized to be an essential
feature of how massive stars form, essentially all information about such
properties is derived from observations of already formed stars, whose orbital
properties may have evolved since birth. Little is known about binarity during
formation stages. Here we report high angular resolution observations of 1.3 mm
continuum and H30alpha recombination line emission, which reveal a massive
protobinary with apparent separation of 180 au at the center of the massive
star-forming region IRAS07299-1651. From the line-of-sight velocity difference
of 9.5 km/s of the two protostars, the binary is estimated to have a minimum
total mass of 18 solar masses, consistent with several other metrics, and
maximum period of 570 years, assuming a circular orbit. The H30alpha line from
the primary protostar shows kinematics consistent with rotation along a ring of
radius of 12 au. The observations indicate that disk fragmentation at several
hundred au may have formed the binary, and much smaller disks are feeding the
individual protostars.Comment: Published in Nature Astronomy. This is author's version. Full article
is available here (https://rdcu.be/brENk). 47 pages, 10 figures, including
methods and supplementary informatio
A Recommender System Approach for Very Large-scale Multiobjective Optimization
We define very large multi-objective optimization problems to be
multiobjective optimization problems in which the number of decision variables
is greater than 100,000 dimensions. This is an important class of problems as
many real-world problems require optimizing hundreds of thousands of variables.
Existing evolutionary optimization methods fall short of such requirements when
dealing with problems at this very large scale. Inspired by the success of
existing recommender systems to handle very large-scale items with limited
historical interactions, in this paper we propose a method termed Very
large-scale Multiobjective Optimization through Recommender Systems (VMORS).
The idea of the proposed method is to transform the defined such very
large-scale problems into a problem that can be tackled by a recommender
system. In the framework, the solutions are regarded as users, and the
different evolution directions are items waiting for the recommendation. We use
Thompson sampling to recommend the most suitable items (evolutionary
directions) for different users (solutions), in order to locate the optimal
solution to a multiobjective optimization problem in a very large search space
within acceptable time. We test our proposed method on different problems from
100,000 to 500,000 dimensions, and experimental results show that our method
not only shows good performance but also significant improvement over existing
methods.Comment: 12 pages, 6 figure
The SOFIA Massive (SOMA) Star Formation Survey. I. Overview and First Results
We present an overview and first results of the Stratospheric Observatory For
Infrared Astronomy Massive (SOMA) Star Formation Survey, which is using the
FORCAST instrument to image massive protostars from
--. These wavelengths trace thermal emission from
warm dust, which in Core Accretion models mainly emerges from the inner regions
of protostellar outflow cavities. Dust in dense core envelopes also imprints
characteristic extinction patterns at these wavelengths, causing intensity
peaks to shift along the outflow axis and profiles to become more symmetric at
longer wavelengths. We present observational results for the first eight
protostars in the survey, i.e., multiwavelength images, including some
ancillary ground-based MIR observations and archival {\it{Spitzer}} and
{\it{Herschel}} data. These images generally show extended MIR/FIR emission
along directions consistent with those of known outflows and with shorter
wavelength peak flux positions displaced from the protostar along the
blueshifted, near-facing sides, thus confirming qualitative predictions of Core
Accretion models. We then compile spectral energy distributions and use these
to derive protostellar properties by fitting theoretical radiative transfer
models. Zhang and Tan models, based on the Turbulent Core Model of McKee and
Tan, imply the sources have protostellar masses --50
accreting at -- inside cores of
initial masses --500 embedded in clumps with mass surface
densities --3. Fitting Robitaille
et al. models typically leads to slightly higher protostellar masses, but with
disk accretion rates smaller. We discuss reasons for these
differences and overall implications of these first survey results for massive
star formation theories.Comment: Accepted to ApJ, 32 page
The SOFIA Massive (SOMA) Star Formation Survey. II. High Luminosity Protostars
We present multi-wavelength images observed with SOFIA-FORCAST from 10
to 40 m of seven high luminosity massive protostars, as part of the SOFIA
Massive (SOMA) Star Formation Survey. Source morphologies at these wavelengths
appear to be influenced by outflow cavities and extinction from dense gas
surrounding the protostars. Using these images, we build spectral energy
distributions (SEDs) of the protostars, also including archival data from
Spitzer, Herschel and other facilities. Radiative transfer (RT) models of Zhang
& Tan (2018), based on Turbulent Core Accretion theory, are then fit to the
SEDs to estimate key properties of the protostars. Considering the best five
models fit to each source, the protostars have masses accreting at rates of inside cores of initial masses embedded in clumps with mass surface densities and span a luminosity range of . Compared with the first eight protostars in Paper I, the sources
analyzed here are more luminous, and thus likely to be more massive protostars.
They are often in a clustered environment or have a companion protostar
relatively nearby. From the range of parameter space of the models, we do not
see any evidence that needs to be high to form these massive
stars. For most sources the RT models provide reasonable fits to the SEDs,
though the cold clump material often influences the long wavelength fitting.
However, for sources in very clustered environments, the model SEDs may not be
such a good description of the data, indicating potential limitations of the
models for these regions.Comment: 30 pages, 19 figures, Accepted for publication in Ap
The Query Cube: A Framework for Assessing User Productivity with Database Information Retrieval
Three key factors that affect user productivity on database information retrieval are representation realism, expressive ease, and task complexity. Representation realism is the level of abstraction used in formulating queries. Expressive ease is the syntactic flexibility of a query language. Task complexity is the level of difficulty of queries. These factors formed a three dimensional query cube. A laboratory experiment was conducted to evaluate user productivity on database information retrieval corresponding to different vertices of the query cube. The results show that the query cube is a viable framework for assessing user productivity, both on effectiveness and efficiency perspective
- …