290 research outputs found
Homogeneous ACM bundles on exceptional isotropic Grassmannians
In this paper, we characterize homogeneous arithmetically Cohen-Macaulay
(ACM) bundles over exceptional isotropic Grassmannians in terms of their
associated data. We show that there are only finitely many irreducible
homogeneous ACM bundles by twisting line bundles over exceptional isotropic
Grassmannians. As a consequence, we prove that some exceptional isotropic
Grassmannians are of wild representation type.Comment: 18 pages. arXiv admin note: text overlap with arXiv:2206.0917
Structural Studies of the Human Retinoic Acid Receptor Gamma Ligand-binding Domain in Complex with Anti-cancer Heteroarotinoids
Retinoids play an important role in the therapy and prevention of cancer by interacting with the retinoic acid receptors (RARs) and the retinoid receptors (RXRs), which are ligand-dependent transcription regulators. The ligand-binding domain (LBD; residues 178-423) of hRARg, which specifically binds reinoids, has been cloned with an N-terminal tag containing six histidines and over-expressed in Escherichia coli. The tag allows for the protein purification using nickel chelating chromatography followed by gel filtration chromatography. Currently, expression and purification are being optimized and preliminary crystallization trials are underway with the LBD in complex with all-trans retinoic acid to check the integrity of the construct. Small crystals have been obtained and await characterization by X-ray diffraction. The ultimate goal is to obtain X-ray crystal structures of the LBD in complex with novel anti-cancer heteroarotinoids (SHetA2 and SHetC2). Atomic resolution of the heteroarotinoids interactions with the protein will aid in optimization of the compounds.Chemistry Departmen
Seeing through the Mask: Multi-task Generative Mask Decoupling Face Recognition
The outbreak of COVID-19 pandemic make people wear masks more frequently than
ever. Current general face recognition system suffers from serious performance
degradation,when encountering occluded scenes. The potential reason is that
face features are corrupted by occlusions on key facial regions. To tackle this
problem, previous works either extract identity-related embeddings on feature
level by additional mask prediction, or restore the occluded facial part by
generative models. However, the former lacks visual results for model
interpretation, while the latter suffers from artifacts which may affect
downstream recognition. Therefore, this paper proposes a Multi-task gEnerative
mask dEcoupling face Recognition (MEER) network to jointly handle these two
tasks, which can learn occlusionirrelevant and identity-related representation
while achieving unmasked face synthesis. We first present a novel mask
decoupling module to disentangle mask and identity information, which makes the
network obtain purer identity features from visible facial components. Then, an
unmasked face is restored by a joint-training strategy, which will be further
used to refine the recognition network with an id-preserving loss. Experiments
on masked face recognition under realistic and synthetic occlusions benchmarks
demonstrate that the MEER can outperform the state-ofthe-art methods
A Survey of Face Recognition
Recent years witnessed the breakthrough of face recognition with deep
convolutional neural networks. Dozens of papers in the field of FR are
published every year. Some of them were applied in the industrial community and
played an important role in human life such as device unlock, mobile payment,
and so on. This paper provides an introduction to face recognition, including
its history, pipeline, algorithms based on conventional manually designed
features or deep learning, mainstream training, evaluation datasets, and
related applications. We have analyzed and compared state-of-the-art works as
many as possible, and also carefully designed a set of experiments to find the
effect of backbone size and data distribution. This survey is a material of the
tutorial named The Practical Face Recognition Technology in the Industrial
World in the FG2023
Sensing Aided Covert Communications: Turning Interference into Allies
In this paper, we investigate the realization of covert communication in a
general radar-communication cooperation system, which includes integrated
sensing and communications as a special example. We explore the possibility of
utilizing the sensing ability of radar to track and jam the aerial adversary
target attempting to detect the transmission. Based on the echoes from the
target, the extended Kalman filtering technique is employed to predict its
trajectory as well as the corresponding channels. Depending on the maneuvering
altitude of adversary target, two channel models are considered, with the aim
of maximizing the covert transmission rate by jointly designing the radar
waveform and communication transmit beamforming vector based on the constructed
channels. For the free-space propagation model, by decoupling the joint design,
we propose an efficient algorithm to guarantee that the target cannot detect
the transmission. For the Rician fading model, since the multi-path components
cannot be estimated, a robust joint transmission scheme is proposed based on
the property of the Kullback-Leibler divergence. The convergence behaviour,
tracking MSE, false alarm and missed detection probabilities, and covert
transmission rate are evaluated. Simulation results show that the proposed
algorithms achieve accurate tracking. For both channel models, the proposed
sensing-assisted covert transmission design is able to guarantee the
covertness, and significantly outperforms the conventional schemes.Comment: 13 pages, 12 figures, submitted to IEEE journals for potential
publicatio
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Tin-graphene tubes as anodes for lithium-ion batteries with high volumetric and gravimetric energy densities.
Limited by the size of microelectronics, as well as the space of electrical vehicles, there are tremendous demands for lithium-ion batteries with high volumetric energy densities. Current lithium-ion batteries, however, adopt graphite-based anodes with low tap density and gravimetric capacity, resulting in poor volumetric performance metric. Here, by encapsulating nanoparticles of metallic tin in mechanically robust graphene tubes, we show tin anodes with high volumetric and gravimetric capacities, high rate performance, and long cycling life. Pairing with a commercial cathode material LiNi0.6Mn0.2Co0.2O2, full cells exhibit a gravimetric and volumetric energy density of 590 W h Kg-1 and 1,252 W h L-1, respectively, the latter of which doubles that of the cell based on graphite anodes. This work provides an effective route towards lithium-ion batteries with high energy density for a broad range of applications
Fast Full-frame Video Stabilization with Iterative Optimization
Video stabilization refers to the problem of transforming a shaky video into
a visually pleasing one. The question of how to strike a good trade-off between
visual quality and computational speed has remained one of the open challenges
in video stabilization. Inspired by the analogy between wobbly frames and
jigsaw puzzles, we propose an iterative optimization-based learning approach
using synthetic datasets for video stabilization, which consists of two
interacting submodules: motion trajectory smoothing and full-frame outpainting.
First, we develop a two-level (coarse-to-fine) stabilizing algorithm based on
the probabilistic flow field. The confidence map associated with the estimated
optical flow is exploited to guide the search for shared regions through
backpropagation. Second, we take a divide-and-conquer approach and propose a
novel multiframe fusion strategy to render full-frame stabilized views. An
important new insight brought about by our iterative optimization approach is
that the target video can be interpreted as the fixed point of nonlinear
mapping for video stabilization. We formulate video stabilization as a problem
of minimizing the amount of jerkiness in motion trajectories, which guarantees
convergence with the help of fixed-point theory. Extensive experimental results
are reported to demonstrate the superiority of the proposed approach in terms
of computational speed and visual quality. The code will be available on
GitHub.Comment: Accepted by ICCV202
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