137 research outputs found
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
Development of a synthetic oxytetracycline-inducible expression system for streptomycetes using de novo characterized genetic parts
Precise control of gene expression using exogenous factors is of great significance. To develop ideal inducible expression systems for streptomycetes, new genetic parts, oxytetracycline responsive repressor OtrR, operator otrO, and promoter otrBp from Streptomyces rimosus, were selected de novo and characterized in vivo and in vitro. OtrR showed strong affinity to otrO (KD = 1.7 Γ 10β10 M) and oxytetracycline induced dissociation of the OtrR/DNA complex in a concentration-dependent manner. On the basis of these genetic parts, a synthetic inducible expression system Potr* was optimized. Induction of Potr* with 0.01β4 ΞΌM of oxytetracycline triggered a wide-range expression level of gfp reporter gene in different Streptomyces species. Benchmarking Potr* against the widely used constitutive promoters ermE* and kasOp* revealed greatly enhanced levels of expression when Potr* was fully induced. Finally, Potr* was used as a tool to activate and optimize the expression of the silent jadomycin biosynthetic gene cluster in Streptomyces venezuelae. Altogether, the synthetic Potr* presents a new versatile tool for fine-tuning gene expression in streptomycetes
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 Ξ³-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
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,
. 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 shows significant differences at
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 =179 (63) for galaxies with
in the TNG100-1. Galaxies in the Illustris-1 have a
much smaller . The distributions of 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. increases with the stellar mass of hosts
when , and fluctuate at higher mass. At ,
increases with redshift. The differences in
between two populations declines with increasing redshift. With more localized
events available in the future, statistics such as , 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
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
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