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 $\sim10$--$40\:\rm{\mu}\rm{m}$. 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 $m_*\sim10$--50$\:M_\odot$ accreting at $\sim10^{-4}$--$10^{-3}\:M_\odot\:{\rm{yr}}^{-1}$ inside cores of initial masses $M_c\sim30$--500$\:M_\odot$ embedded in clumps with mass surface densities $\Sigma_{\rm{cl}}\sim0.1$--3$\:{\rm{g\:cm}^{-2}}$. Fitting Robitaille et al. models typically leads to slightly higher protostellar masses, but with disk accretion rates $\sim100\times$ 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 $\sim$10 to 40 $\mu$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 $m_{*} \sim 12-64 \: M_{\odot}$ accreting at rates of $\dot{m}_{*} \sim 10^{-4}-10^{-3} \: M_{\odot} \: \rm yr^{-1}$ inside cores of initial masses $M_{c} \sim 100-500 \: M_{\odot}$ embedded in clumps with mass surface densities $\Sigma_{\rm cl} \sim 0.1-3 \: \rm g \: cm^{-2}$ and span a luminosity range of $10^{4} -10^{6} \: L_{\odot}$. 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 $\Sigma_{\rm cl}$ 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