Resfusion: Prior Residual Noise embedded Denoising Diffusion Probabilistic Models

Recently, Denoising Diffusion Probabilistic Models have been widely used in image segmentation, by generating segmentation masks conditioned on the input image. However, previous works can not seamlessly integrate existing end-to-end models with denoising diffusion models. Existing research can only select acceleration steps based on experience rather than calculating them specifically. Moreover, most methods are limited to small models and small-scale datasets, unable to generalize to general datasets and a wider range of tasks. Therefore, we propose Resfusion with a novel resnoise-diffusion process, which gradually generates segmentation masks or any type of target image, seamlessly integrating state-of-the-art end-to-end models and denoising diffusion models. Resfusion bridges the discrepancy between the likelihood output and the ground truth output through a Markov process. Through the novel smooth equivalence transformation in resnoise-diffusion process, we determine the optimal acceleration step. Experimental results demonstrate that Resfusion combines the capabilities of existing end-to-end models and denoising diffusion models, further enhancing performance and achieving outstanding results. Moreover, Resfusion is not limited to segmentation tasks, it can easily generalize to any general tasks of image generation and exhibit strong competitiveness

A dual AAV system enables the Cas9-mediated correction of a metabolic liver disease in newborn mice

Many genetic liver diseases present in newborns with repeated, often lethal, metabolic crises. Gene therapy using non-integrating viruses such as AAV is not optimal in this setting because the non-integrating genome is lost as developing hepatocytes proliferate1,2. We reasoned that newborn liver may be an ideal setting for AAV-mediated gene correction using CRISPR/Cas9. Here we intravenously infuse two AAVs, one expressing Cas9 and the other expressing a guide RNA and the donor DNA, into newborn mice with a partial deficiency in the urea cycle disorder enzyme, ornithine transcarbamylase (OTC). This resulted in reversion of the mutation in 10% (6.7% – 20.1%) of hepatocytes and increased survival in mice challenged with a high-protein diet, which exacerbates disease. Gene correction in adult OTC-deficient mice was lower and accompanied by larger deletions that ablated residual expression from the endogenous OTC gene, leading to diminished protein tolerance and lethal hyperammonemia on a chow diet

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Pesticide Pollution in China

Pesticides are chemical substances that are utilized for killing pests and preventing diseases artificially. The excess pesticides are secreted in the soil or surrounding; and those hazardous compounds cause pollution. Pesticide pollution is classified into three types: soil pollution, air pollution and water pollution. Soil pollution is the most serious problem among those three pollutions. Because most of the pesticides which are used in agriculture persist in soil which take long time to be degradable will affect to human, plant and animal. The purpose of the thesis is twofold. It aims to analyze the current situation of pesticide pollution in China from three perspectives, the history of pesticides, their consumption, and the pollution they cause. Furthermore, it tries to alert the Chinese government to concentrate on pesticide pollution, by recognizing the problems of monitoring and controlling

Iterative Maximal Ratio Combining Channel Estimation for Multiuser Detection on a Time Frequency Selective Wireless CDMA Channel

In this paper, we investigate the performance of DS-CDMA systems in dispersive fading channels. We develop a low-complexity receiver that jointly performs channel estimation and multiuser decoding in an iterative manner. Pilot symbols, together with the soft decoding information on the transmitted data are harnessed to estimate the time-varying channel states, which in turn leads to improved detection and decoding results. We show through simulation and mean square error analysis that the proposed system can sustain a high-throughput WCDMA transmission

Iterative Multiuser Detection and Error Control Code Decoding in Random CDMA

The combination of forward-error control (FEC) coding with code-division multiple access (CDMA) using random spreading sequences is considered. Such systems can be viewed as serially concatenated, and iterative (turbo) decoding principles can be applied

Low-Complexity Partitioned-Spreading CDMA System with Multistage MMSE Reception

In this paper, we propose a low-complexity multistage filter for the partitioned-spreading CDMA (PS-CDMA). The proposed method embodies a MMSE filter that operates on the soft output of interference cancellation. Extrinsic information on the partitioned symbol is exchanged between the MMSE filter and the partitioned-spreading APP detector to improve the system performance. It is shown via variance evolution the signal-to-noise ratio of this novel technique achieves that of the single-user channel even for heavily loaded systems. It also outperforms IDMA by a fraction of dB to a few dBs, for a variety of system loads.The complexity of the proposed system is much lower that of its counterparts for conventional CDMA, which makes it a viable alternative for future 3G or beyond 3G systems

Iterative Multiuser Detection based on Monte Carlo Probabilistic Data Association

Multiple-Access Interference (MAI) has been considered as a major performance-limiting factor in the next-generation CDMA systems. Multiuser detection (MUD) methods have been proposed to mitigate the MAI from the co-channel users by incoporating the cross-correlation properties between users. Recently, two classes of emerging techniques, probabilistic data association (PDA) and Markov Chain Monte Carlo (MCMC) methods, have been applied to the multiuser detection. In this paper, we present a new method, named Monte Carlo PDA (MC-PDA), that incorporates the concepts of both to give a more reliable inference of the CDMA symbols by appropriately modelling and updating the MAI. The methodology is general and can be applied to other communication channels