706 research outputs found
2-Chloro-N-{5-[(4R,5R,10S)-dehydroabiet-4-yl]-1,3,4-thiadiazol-2-yl}benzamide
There are two independent molecules in the asymmetric unit of the title compound, C28H32ClN3OS (systematic name: 2-chloro-N-{5-[(1R,4aS,10aR)-7-isopropyl-1,4a-dimethyl-1,2,3,4,4a,9,10,10a-octahydrophenanthren-1-yl]-1,3,4-thiadiazol-2-yl}benzamide). In each molecule, the cyclohexyl ring attached to the thiadiazole fragment adopts a classic chair conformation with two of its two methyl groups in the axial positions. In the crystal, pairs of intermolecular N—H⋯N hydrogen bonds link the molecules into centrosymmetric dimers, which are further linked via C—H⋯π interactions
Research Report on the Effect of Network Teaching Mode of Art Courses under the Concept of Ideological and Political Education
Since the National Conference on ideological and political work in Colleges and Universities, the Party Committee of Beijing United University has closely focused on the fundamental problem of “what kind of person to train, how to train and for whom to train”, and regards the course of ideological and political thinking as the fundamental measure to carry out the fundamental task of building up people by virtue. In 2020, in the event of the new epidemic situation, the school actively implemented the work plan of “stopping classes and not stopping learning” in Beijing, and opened the historic revolution of the whole school network teaching in education and teaching.In recent years, Beijing Union University in the “curriculum ideological and political” construction is constantly open up. In order to promote teaching practice and teaching research, the school teacher teaching development center set up the first teaching promoters of Beijing United University in 2019. The project team was set up by the school teaching promoters to study the effect of the online teaching mode of art courses under the concept of ideological and political education
Controllable 3D Face Generation with Conditional Style Code Diffusion
Generating photorealistic 3D faces from given conditions is a challenging
task. Existing methods often rely on time-consuming one-by-one optimization
approaches, which are not efficient for modeling the same distribution content,
e.g., faces. Additionally, an ideal controllable 3D face generation model
should consider both facial attributes and expressions. Thus we propose a novel
approach called TEx-Face(TExt & Expression-to-Face) that addresses these
challenges by dividing the task into three components, i.e., 3D GAN Inversion,
Conditional Style Code Diffusion, and 3D Face Decoding. For 3D GAN inversion,
we introduce two methods which aim to enhance the representation of style codes
and alleviate 3D inconsistencies. Furthermore, we design a style code denoiser
to incorporate multiple conditions into the style code and propose a data
augmentation strategy to address the issue of insufficient paired
visual-language data. Extensive experiments conducted on FFHQ, CelebA-HQ, and
CelebA-Dialog demonstrate the promising performance of our TEx-Face in
achieving the efficient and controllable generation of photorealistic 3D faces.
The code will be available at https://github.com/sxl142/TEx-Face.Comment: Accepted by AAAI 202
Multistate analysis of multitype recurrent event and failure time data with event feedbacks in biomarkers
From Wiley via Jisc Publications RouterHistory: received 2020-04-07, rev-recd 2021-04-19, accepted 2021-06-05, pub-electronic 2021-07-13Article version: VoRPublication status: PublishedAbstract: In this paper we propose a class of multistate models for the analysis of multitype recurrent event and failure time data when there are past event feedbacks in longitudinal biomarkers. It can well incorporate various effects, including time‐dependent and time‐independent effects, of different event paths or the number of occurrences of events of different types. Asymptotic unbiased estimating equations based on polynomial splines approximation are developed. The consistency and asymptotic normality of the proposed estimators are provided. Simulation studies show that the naive estimators which either ignore the past event feedback or the measurement errors are biased. Our method has a better coverage probability of the time‐varying/constant coefficients, compared to the naive methods. An application to the dataset from the Atherosclerosis Risk in Communities Study, which is also the motivating example to develop the method, is presented
TransHuman: A Transformer-based Human Representation for Generalizable Neural Human Rendering
In this paper, we focus on the task of generalizable neural human rendering
which trains conditional Neural Radiance Fields (NeRF) from multi-view videos
of different characters. To handle the dynamic human motion, previous methods
have primarily used a SparseConvNet (SPC)-based human representation to process
the painted SMPL. However, such SPC-based representation i) optimizes under the
volatile observation space which leads to the pose-misalignment between
training and inference stages, and ii) lacks the global relationships among
human parts that is critical for handling the incomplete painted SMPL. Tackling
these issues, we present a brand-new framework named TransHuman, which learns
the painted SMPL under the canonical space and captures the global
relationships between human parts with transformers. Specifically, TransHuman
is mainly composed of Transformer-based Human Encoding (TransHE), Deformable
Partial Radiance Fields (DPaRF), and Fine-grained Detail Integration (FDI).
TransHE first processes the painted SMPL under the canonical space via
transformers for capturing the global relationships between human parts. Then,
DPaRF binds each output token with a deformable radiance field for encoding the
query point under the observation space. Finally, the FDI is employed to
further integrate fine-grained information from reference images. Extensive
experiments on ZJU-MoCap and H36M show that our TransHuman achieves a
significantly new state-of-the-art performance with high efficiency. Project
page: https://pansanity666.github.io/TransHuman/Comment: Accepted by ICCV 202
Free-style and Fast 3D Portrait Synthesis
Efficiently generating a free-style 3D portrait with high quality and
consistency is a promising yet challenging task. The portrait styles generated
by most existing methods are usually restricted by their 3D generators, which
are learned in specific facial datasets, such as FFHQ. To get a free-style 3D
portrait, one can build a large-scale multi-style database to retrain the 3D
generator, or use a off-the-shelf tool to do the style translation. However,
the former is time-consuming due to data collection and training process, the
latter may destroy the multi-view consistency. To tackle this problem, we
propose a fast 3D portrait synthesis framework in this paper, which enable one
to use text prompts to specify styles. Specifically, for a given portrait
style, we first leverage two generative priors, a 3D-aware GAN generator (EG3D)
and a text-guided image editor (Ip2p), to quickly construct a few-shot training
set, where the inference process of Ip2p is optimized to make editing more
stable. Then we replace original triplane generator of EG3D with a
Image-to-Triplane (I2T) module for two purposes: 1) getting rid of the style
constraints of pre-trained EG3D by fine-tuning I2T on the few-shot dataset; 2)
improving training efficiency by fixing all parts of EG3D except I2T.
Furthermore, we construct a multi-style and multi-identity 3D portrait database
to demonstrate the scalability and generalization of our method. Experimental
results show that our method is capable of synthesizing high-quality 3D
portraits with specified styles in a few minutes, outperforming the
state-of-the-art.Comment: project website: https://tianxiangma.github.io/FF3
Transcriptional up-regulation of relaxin-3 by Nur77 attenuates β-adrenergic agonist-induced apoptosis in cardiomyocytes.
The relaxin family peptides have been shown to exert several beneficial effects on the heart, including anti-apoptosis, anti-fibrosis, and anti-hypertrophy activity. Understanding their regulation might provide new opportunities for therapeutic interventions, but the molecular mechanism(s) coordinating relaxin expression in the heart remain largely obscured. Previous work demonstrated a role for the orphan nuclear receptor Nur77 in regulating cardiomyocyte apoptosis. We therefore investigated Nur77 in the hopes of identifying novel relaxin regulators. Quantitative real-time PCR (qRT-PCR) and enzyme-linked immunosorbent assay (ELISA) data indicated that ectopic expression of orphan nuclear receptor Nur77 markedly increased the expression of latexin-3 (RLN3), but not relaxin-1 (RLN1), in neonatal rat ventricular cardiomyocytes (NRVMs). Furthermore, we found that the -adrenergic agonist isoproterenol (ISO) markedly stimulated RLN3 expression, and this stimulation was significantly attenuated in Nur77 knockdown cardiomyocytes and Nur77 knockout hearts. We showed that Nur77 significantly increased RLN3 promoter activity via specific binding to the RLN3 promoter, as demonstrated by electrophoretic mobility shift assay (EMSA) and chromatin immuno-precipitation (ChIP) assays. Furthermore, we found that Nur77 overexpression potently inhibited ISO-induced cardiomyocyte apoptosis, whereas this protective effect was significantly attenuated in RLN3 knockdown cardiomyocytes, suggesting that Nur77-induced RLN3 expression is an important mediator for the suppression of cardiomyocyte apoptosis. These findings show that Nur77 regulates RLN3 expression, therefore suppressing apoptosis in the heart, and suggest that activation of Nur77 may represent a useful therapeutic strategy for inhibition of cardiac fibrosis and heart failure. © 2018 You et al
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