Exploring Vision Transformers as Diffusion Learners

Score-based diffusion models have captured widespread attention and funded fast progress of recent vision generative tasks. In this paper, we focus on diffusion model backbone which has been much neglected before. We systematically explore vision Transformers as diffusion learners for various generative tasks. With our improvements the performance of vanilla ViT-based backbone (IU-ViT) is boosted to be on par with traditional U-Net-based methods. We further provide a hypothesis on the implication of disentangling the generative backbone as an encoder-decoder structure and show proof-of-concept experiments verifying the effectiveness of a stronger encoder for generative tasks with ASymmetriC ENcoder Decoder (ASCEND). Our improvements achieve competitive results on CIFAR-10, CelebA, LSUN, CUB Bird and large-resolution text-to-image tasks. To the best of our knowledge, we are the first to successfully train a single diffusion model on text-to-image task beyond 64x64 resolution. We hope this will motivate people to rethink the modeling choices and the training pipelines for diffusion-based generative models

Light adaptation strategies of Quercus mongolica at different ages in four plantations

This study investigated the allocation strategies of non-structural carbohydrates and functional traits in Quercus mongolica seedlings of different ages under different light conditions. The study took place at the Urban Forestry Demonstration Base in Harbin City, Heilongjiang Province, China. Seedlings of three age classes were collected in two light environments, the forest edge and the forest understory. By measuring specific leaf area, biomass, soluble sugar concentration and starch concentration, we revealed the growth adaptation strategies and responses to different light conditions in Q. mongolica seedlings of different age classes. Our results show that the adaptation strategies of seedlings of different age classes are very different. First, our study showed a strong coordination of soluble sugars between roots, stems, and leaves of 1−2 year old Q. mongolica seedlings, indicating an efficient partitioning of carbon between organs at this age. In 3−4 year old Q. mongolica seedlings, a significant negative correlation was observed between starch in the roots and soluble sugars in the leaves, indicating the transformation of various non-structural carbohydrates. In addition, 5−6 year old seedlings start to increase their investment in the above-ground part to achieve a height advantage. In conclusion, this study improves our understanding of the light adaptation strategies of Q. mongolica seedlings and provides valuable insights for the natural regeneration and management of Q. mongolica forest vegetation

detrex: Benchmarking Detection Transformers

The DEtection TRansformer (DETR) algorithm has received considerable attention in the research community and is gradually emerging as a mainstream approach for object detection and other perception tasks. However, the current field lacks a unified and comprehensive benchmark specifically tailored for DETR-based models. To address this issue, we develop a unified, highly modular, and lightweight codebase called detrex, which supports a majority of the mainstream DETR-based instance recognition algorithms, covering various fundamental tasks, including object detection, segmentation, and pose estimation. We conduct extensive experiments under detrex and perform a comprehensive benchmark for DETR-based models. Moreover, we enhance the performance of detection transformers through the refinement of training hyper-parameters, providing strong baselines for supported algorithms.We hope that detrex could offer research communities a standardized and unified platform to evaluate and compare different DETR-based models while fostering a deeper understanding and driving advancements in DETR-based instance recognition. Our code is available at https://github.com/IDEA-Research/detrex. The project is currently being actively developed. We encourage the community to use detrex codebase for further development and contributions.Comment: project link: https://github.com/IDEA-Research/detre

Refining GPS/GLONASS Satellite Clock Offset Estimation in the Presence of Pseudo-Range Inter-Channel Biases

Because of the frequency division multiple access (FDMA) technique, Russian global navigation satellite system (GLONASS) observations suffer from pseudo-range inter-channel biases (ICBs), which adversely affect satellite clock offset estimation. In this study, the GLONASS pseudo-range ICB is treated in four different ways: as ignorable parameters (ICB-NONE), polynomial functions of frequency (ICB-FPOL), frequency-specific parameters (ICB-RF), and satellite-specific parameters (ICB-RS). Data from 110 international global navigation satellite system (GNSS) service stations were chosen to obtain the ICBs and were used for satellite clock offset estimation. The ICBs from the different schemes varied from −20 ns to 80 ns. The ICB-RS model yielded the best results, improving the clock offset accuracy from 300 ps to about 100 ps; it could improve the GLONASS precise point positioning (PPP) accuracy and the converging time by approximately 50% and 30%, respectively. Along similar lines, we introduced the GPS-ICB parameters in the process of GPS satellite clock estimation and GPS/GLONASS PPP, as ICBs may exist for GPS because of different chip shape distortions among GPS satellites. This possibility was found to be the case. Further, the GPS-ICB magnitude ranged from −2 ns to 2 ns, and the estimated satellite clock offsets could improve the accuracy of the GPS and combined GPS/GLONASS PPP by 10%; it also accelerated the converging time by more than 15% thanks to the GPS-ICB calibration

The Optimal Intervention Time of Bone Marrow Mesenchymal Stem Cells in Ameliorating Cardiac Fibrosis Induced by Viral Myocarditis: A Randomized Controlled Trial in Mice

Bone marrow-derived mesenchymal stem cells (BMSCs) have recently been introduced to treat cardiovascular diseases, such as myocardial infarction and dilated cardiomyopathy. Nevertheless, there are few researches focused on the application of BMSCs in treating viral myocarditis, not to mention its optimal intervention timer potential mechanisms. In our study, we concentrated on finding an optimal time window to perform BMSCs treatment in a murine model of myocarditis induced by coxsackievirus B3 (CVB3). On the 1st day, 3rd day, 7th day, and 14th day after BALB/c mice were infected by CVB3, we intravenously injected equivalent BMSCs into the treatment groups. With a 28-day follow-up after inoculation, we found that the ventricular function was significantly improved in the BMSCs treatment group and cardiac fibrosis markedly ameliorated, especially when BMSCs were injected between 1 and 2 weeks after CVB3 inoculation. Furthermore, we demonstrated that after BMSCs treatment, the expressions of TGF-β, col1α1, and col3α1 were significantly decreased. Therefore, we conclude that BMSCs may have a potential to improve CVB3-induced myocarditis by ameliorating cardiac fibrosis through the inhibition of TGF-β expression