Neural Aesthetic Image Reviewer

Recently, there is a rising interest in perceiving image aesthetics. The existing works deal with image aesthetics as a classification or regression problem. To extend the cognition from rating to reasoning, a deeper understanding of aesthetics should be based on revealing why a high- or low-aesthetic score should be assigned to an image. From such a point of view, we propose a model referred to as Neural Aesthetic Image Reviewer, which can not only give an aesthetic score for an image, but also generate a textual description explaining why the image leads to a plausible rating score. Specifically, we propose two multi-task architectures based on shared aesthetically semantic layers and task-specific embedding layers at a high level for performance improvement on different tasks. To facilitate researches on this problem, we collect the AVA-Reviews dataset, which contains 52,118 images and 312,708 comments in total. Through multi-task learning, the proposed models can rate aesthetic images as well as produce comments in an end-to-end manner. It is confirmed that the proposed models outperform the baselines according to the performance evaluation on the AVA-Reviews dataset. Moreover, we demonstrate experimentally that our model can generate textual reviews related to aesthetics, which are consistent with human perception.Comment: 8 pages, 13 figure

Predicting Token Impact Towards Efficient Vision Transformer

Token filtering to reduce irrelevant tokens prior to self-attention is a straightforward way to enable efficient vision Transformer. This is the first work to view token filtering from a feature selection perspective, where we weigh the importance of a token according to how much it can change the loss once masked. If the loss changes greatly after masking a token of interest, it means that such a token has a significant impact on the final decision and is thus relevant. Otherwise, the token is less important for the final decision, so it can be filtered out. After applying the token filtering module generalized from the whole training data, the token number fed to the self-attention module can be obviously reduced in the inference phase, leading to much fewer computations in all the subsequent self-attention layers. The token filter can be realized using a very simple network, where we utilize multi-layer perceptron. Except for the uniqueness of performing token filtering only once from the very beginning prior to self-attention, the other core feature making our method different from the other token filters lies in the predictability of token impact from a feature selection point of view. The experiments show that the proposed method provides an efficient way to approach a light weighted model after optimized with a backbone by means of fine tune, which is easy to be deployed in comparison with the existing methods based on training from scratch.Comment: 10 page

Evolution of cold streams in hot gaseous halos

In the prevailing model of galaxy formation and evolution, the process of gas accretion onto central galaxies undergoes a transition from cold-dominated to hot-dominated modes. This shift occurs when the mass of the parent dark matter halos exceeds a critical threshold known as $M_{shock}$. Moreover, cold gas usually flows onto central galaxies through filamentary structures, currently referred to as cold streams. However, the evolution of cold streams in halos with masses around $M_{shock}$, particularly how they are disrupted, remains unclear. To address this issue, we conduct a set of idealised hydrodynamic simulations. Our simulations show that (1) for a gas metallicity $Z=0.001-0.1Z_{\odot}$, cold stream with an inflow rate $\sim 3\, \rm{M_{\odot}}/yr$ per each can persist and effectively transport cold and cool gas to the central region ($< 0.2$ virial radius) in halos with mass $10^{12}\, \rm{M_{\odot}}$, but is disrupted at a radius around $0.2$ virial radius due to compression heating for halos with mass $3 \times 10^{12}\, \rm{M_{\odot}}$. (2) At $z\sim 2$, the maximum halo mass that capable of hosting and sustaining cold streams $M_{stream}$ is between $1\times 10^{12} \rm{M_{\odot}}$ and $1.5\times 10^{12}\rm{M_{\odot}}$ for gas metallicity $Z=0.001Z_{\odot}$, while for a higher gas metallicity $Z=0.1Z_{\odot}$, this value increases to $\sim 1.5\times 10^{12}\rm{M_{\odot}}$. (3) The evolution and ultimate fate of cold streams are determined primarily by the rivalry between radiative cooling and compression. Stronger heating due to compression in halos more massive than $M_{stream}$ can surpass cooling and heat the gas in cold streams to the hot ($\geq 10^6\,$ K) phase.Comment: 26 pages, 18 figures, accepted for publication in MNRA

The dispersion measure of Fast Radio Bursts host galaxies: estimation from cosmological simulations

The dispersion measure(DM) of fast radio burst encodes important information such as its distance, properties of intervening medium. Based on simulations in the Illustris and IllustrisTNG projects, we analyze the DM of FRBs contributed by the interstellar medium and circumgalactic medium in the hosts, $\rm{DM_{host}}$. We explore two population models - tracing the star formation rate (SFR), and the stellar mass, i.e. young and old progenitors respectively. The distribution of $\rm{DM_{host}}$ shows significant differences at $z=0$ between two populations: the stellar mass model exhibits an excess at the low DM end with respect to the SFR model. The SFR (stellar mass) model has a median value of $\rm{DM_{host}}$=179 (63) $\rm{pc\, cm^{-3}}$ for galaxies with $M_*=10^{8-13}\,M_{\odot}$ in the TNG100-1. Galaxies in the Illustris-1 have a much smaller $\rm{DM_{host}}$. The distributions of $\rm{DM_{host}}$ deviate from log-normal function for both models. Furthermore, two populations differ moderately in the spatial offset from host galaxy's center, in the stellar mass function of hosts. $\rm{DM_{host}}$ increases with the stellar mass of hosts when $M_*<10^{10.5}\,M_{\odot}$, and fluctuate at higher mass. At $0<z<2$, $\rm{DM_{host}}$ increases with redshift. The differences in $\rm{DM_{host}}$ between two populations declines with increasing redshift. With more localized events available in the future, statistics such as $\rm{DM_{host}}$, the offset from galaxy center and the stellar mass function of hosts will be of great helpful to ascertain the origin of FRB. Meanwhile, statistics of $\rm{DM_{host}}$ of localized FRB events could help to constrain the baryon physics models in galaxy evolution.Comment: 16 pages, 12 figures, accepted for publication in MNRA

Evidence for the formation of ScbR/ScbR2 heterodimers and identification of one of the regulatory targets in Streptomyces coelicolor

The homologous transcriptional regulators ScbR and ScbR2 have previously been identified as γ-butyrolactone (GBL) and antibiotic receptors, respectively. They regulate diverse physiological processes in Streptomyces coelicolor in response to GBL and antibiotic signals. In this study, ScbR and ScbR2 proteins were shown to interact using a bacterial two-hybrid system where adenylate cyclase activity was reconstituted in Escherichia coli BH101. These ScbR/ScbR2 interactions in S. coelicolor were then demonstrated by co-immunoprecipitation. The ScbR/ScbR2 heterodimer was shown to co-exist with their ScbR and ScbR2 respective homodimers. When potential operator targets in S. coelicolor were investigated, the heterodimer was found to bind in the promoter region of sco5158, which however was not a target for ScbR or ScbR2 homodimers. These results revelaed a new mechanism 25 of regulation by ScbR and ScbR2 in S. coelicolor