Stellar Variability in a Forming Massive Star Cluster

We present a near-infrared (NIR) variability analysis for an 6\arcmin $\times$ 6\arcmin region, which encompasses the massive protocluster G286.21+0.17. The total sample comprises more than 5000 objects, of which 562 show signs of a circumstellar disk based on their infrared colors. The data includes HST observations taken in two epochs separated by 3 years in the F110W and F160W bands. 363 objects (7% of the sample) exhibit NIR variability at a significant level (Stetson index >1.7), and a higher variability fraction (14%) is found for the young stellar objects (YSOs) with disk excesses. We identified 4 high amplitude (>0.6 mag) variables seen in both NIR bands. Follow up and archival observations of the most variable object in this survey (G286.2032+0.1740) reveal a rising light curve over 8 years from 2011 to 2019, with a K band brightening of 3.5 mag. Overall the temporal behavior of G286.2032+0.1740 resembles that of typical FU Ori objects, however its pre-burst luminosity indicates it has a very low mass ($<0.12\:M_\odot$), making it an extreme case of an outburst event that is still ongoing.Comment: 13 pages, 8 figures, accepted by Ap

The Core Mass Function in the Massive Protocluster G286.21+0.17 revealed by ALMA

We study the core mass function (CMF) of the massive protocluster G286.21+0.17 with the Atacama Large Millimeter/submillimeter Array via 1.3~mm continuum emission at a resolution of 1.0\arcsec\ (2500~au). We have mapped a field of 5.3\arcmin$\times$5.3\arcmin\ centered on the protocluster clump. We measure the CMF in the central region, exploring various core detection algorithms, which give source numbers ranging from 60 to 125, depending on parameter selection. We estimate completeness corrections due to imperfect flux recovery and core identification via artificial core insertion experiments. For masses $M\gtrsim1\:M_\odot$, the fiducial dendrogram-identified CMF can be fit with a power law of the form ${\rm{d}}N/{\rm{d}}{\rm{log}}M\propto{M}^{-\alpha}$ with $\alpha \simeq1.24\pm0.17$, slightly shallower than, but still consistent with, the index of the Salpeter stellar initial mass function of 1.35. Clumpfind-identified CMFs are significantly shallower with $\alpha\simeq0.64\pm0.13$. While raw CMFs show a peak near $1\:M_\odot$, completeness-corrected CMFs are consistent with a single power law extending down to $\sim 0.5\:M_\odot$, with only a tentative indication of a shallowing of the slope around $\sim1\:M_\odot$. We discuss the implications of these results for star and star cluster formation theories.Comment: 11 pages, accepted by Ap

The Core Mass Function Across Galactic Environments. II. Infrared Dark Cloud Clumps

We study the core mass function (CMF) within 32 dense clumps in seven infrared dark clouds (IRDCs) with the Atacama Large Millimeter/submillimeter Array (ALMA) via 1.3~mm continuum emission at a resolution of $\sim$1". We have identified 107 cores with the dendrogram algorithm, with a median radius of about 0.02 pc. Their masses range from 0.261 to 178 $M_{\odot}$. After applying completeness corrections, we fit the combined IRDC CMF with a power law of the form $d N / d\:{\rm log} M \propto M^{-\alpha}$ and derive an index of $\alpha\simeq0.86\pm0.11$ for $M \geq 0.79\:M_\odot$ and $\alpha\simeq0.70\pm0.13$ for $M\geq 1.26\:M_\odot$, which is a significantly more top-heavy distribution than the Salpeter stellar initial mass function (IMF) index of 1.35. We also make a direct comparison of these IRDC clump CMF results to those measured in the more evolved protocluster G286 derived with similar methods, which have $\alpha\simeq1.29\pm0.19$ and $1.08\pm0.27$ in these mass ranges, respectively. These results provide a hint that, especially for the $M\geq 1.26\:M_\odot$ range where completeness corrections are modest, the CMF in high pressure, early-stage environments of IRDC clumps may be top-heavy compared to that in the more evolved, global environment of the G286 protoclusters. However, larger samples of cores probing these different environments are needed to better establish the robustness of this potential CMF variation.Comment: Accepted to ApJ, 15 pages, 7 figure

Heavy metal contamination and physical barrier are main causal agents for the genetic differentiation of Perna viridis populations in Peninsular Malaysia

A total of 19 polymorphic microsatellite loci were used to analyze the levels of genetic variations for six geographical populations of green-lipped Perna viridis collected from the coastal waters of Peninsular Malaysia. In addition, the total soft tissues of all mussel populations were determined for heavy metals (Cd, Cu, Pb and Zn). FST values revealed that all the six populations of P. viridis in Peninsular Malaysia were categorized as showing 'moderate genetic differentiation' according to the classification of Wright (1978). Cluster analysis revealed that three populations which were located in the western part of the Johor Causeway were clustered differently from the other three populations located in the eastern part. Hierarchical F-statistics and cluster analysis indicated that the Johor Causeway which blocked the free flow of the pelagic larvae swimmers of P. viridis and a distinct effect of heavy metal contamination on the Kg. Pasir Puteh population, were the two main causal agents for the genetic differentiation of the P. viridis populations investigated in this study

Effects of Government R&D Grants on IT Entrepreneurial Firm Performance: A New Perspective on Exploration vs. Exploitation

Governments keep subsidizing R&D of IT entrepreneurial firms greatly. However, the effect of these grants remains unclear. Acknowledging this gap, this study provides a nuanced perspective to understand the influence of government R&D grants on IT entrepreneurial firm performance. Based on the literature on organizational learning, we categorize government R&D grants into two types: explorative vs. exploitative. Moreover, drawing on resource complementarity theory, we articulate how the two types of government R&D grants interact with firms’ private R&D resources. In particular, we hypothesize that in the innovation stage, government explorative R&D grants complement a firm’s internal exploration in influencing innovation performance, but substitute a firm’s external exploration. We further posit that in the commercialization stage, government exploitative R&D grants complement a firm’s innovation performance and internal exploitation in impacting financial performance, but substitute a firm’s external exploitation. We advance a theory of public-private R&D interaction for IT entrepreneurial firms

Gas Kinematics of the Massive Protocluster G286.21+0.17 Revealed by ALMA

We study the gas kinematics and dynamics of the massive protocluster G286.21+0.17 with the Atacama Large Millimeter/submillimeter Array using spectral lines of $C^{18}O$(2-1), $N_2D^+$(3-2), $DCO^+$(3-2) and $DCN$(3-2). On the parsec clump scale, $C^{18}O$ emission appears highly filamentary around the systemic velocity. $N_2D^+$ and $DCO^+$ are more closely associated with the dust continuum. $DCN$ is strongly concentrated towards the protocluster center, where no or only weak detection is seen for $N_2D^+$ and $DCO^+$, possibly due to this region being at a relatively evolved evolutionary stage. Spectra of 76 continuum defined dense cores, typically a few 1000 AU in size, are analysed to measure their centroid velocities and internal velocity dispersions. There are no statistically significant velocity offsets of the cores among the different dense gas tracers. Furthermore, the majority (71\%) of the dense cores have subthermal velocity offsets with respect to their surrounding, lower density $C^{18}O$ emitting gas. Within the uncertainties, the dense cores in G286 show internal kinematics that are consistent with being in virial equilibrium. On clumps scales, the core to core velocity dispersion is also similar to that required for virial equilibrium in the protocluster potential. However, the distribution in velocity of the cores is largely composed of two spatially distinct groups, which indicates that the dense molecular gas has not yet relaxed to virial equilibrium, perhaps due to there being recent/continuous infall into the system.Comment: 26 pages, 17 figures, accepted by Ap

Deep active learning for anchor user prediction

© 2019 International Joint Conferences on Artificial Intelligence. All rights reserved. Predicting pairs of anchor users plays an important role in the cross-network analysis. Due to the expensive costs of labeling anchor users for training prediction models, we consider in this paper the problem of minimizing the number of user pairs across multiple networks for labeling as to improve the accuracy of the prediction. To this end, we present a deep active learning model for anchor user prediction (DALAUP for short). However, active learning for anchor user sampling meets the challenges of non-i.i.d. user pair data caused by network structures and the correlation among anchor or non-anchor user pairs. To solve the challenges, DALAUP uses a couple of neural networks with shared-parameter to obtain the vector representations of user pairs, and ensembles three query strategies to select the most informative user pairs for labeling and model training. Experiments on real-world social network data demonstrate that DALAUP outperforms the state-of-the-art approaches

A Novel Severe Acute Respiratory Syndrome Coronavirus Protein, U274, is transported to the Cell Surface and undergoes Endocytosis

The severe acute respiratory syndrome coronavirus (SARS-CoV) genome contains open reading frames (ORFs) that encode for several genes that are homologous to proteins found in all known coronaviruses. These are the replicase gene 1a/1b and the four structural proteins, nucleocapsid (N), spike (S), membrane (M), and envelope (E), and these proteins are expected to be essential for the replication of the virus. In addition, this genome also contains nine other potential ORFs varying in length from 39 to 274 amino acids. The largest among these is the first ORF of the second longest subgenomic RNA, and this protein (termed U274 in the present study) consists of 274 amino acids and contains three putative transmembrane domains. Using antibody specific for the C terminus of U274, we show U274 to be expressed in SARS-CoV-infected Vero E6 cells and, in addition to the full-length protein, two other processed forms were also detected. By indirect immunofluorescence, U274 was localized to the perinuclear region, as well as to the plasma membrane, in both transfected and infected cells. Using an N terminus myc-tagged U274, the topology of U274 and its expression on the cell surface were confirmed. Deletion of a cytoplasmic domain of U274, which contains Yxx and diacidic motifs, abolished its transport to the cell surface. In addition, U274 expressed on the cell surface can internalize antibodies from the culture medium into the cells. Coimmunoprecipitation experiments also showed that U274 could interact specifically with the M, E, and S structural proteins, as well as with U122, another protein that is unique to SARS-CoV.Web of Scienc