Error Estimate of Multiscale Finite Element Method for Periodic Media Revisited

We derive the optimal energy error estimate for multiscale finite element method with oversampling technique applying to elliptic system with rapidly oscillating periodic coefficients under the assumption that the coefficients are bounded and measurable, which may admit rough microstructures. As a by-product of the energy estimate, we derive the rate of convergence in L$^{d/(d-1)}-$norm

A Novel Fusion Framework Based on Adaptive PCNN in NSCT Domain for Whole-Body PET and CT Images

The PET and CT fusion images, combining the anatomical and functional information, have important clinical meaning. This paper proposes a novel fusion framework based on adaptive pulse-coupled neural networks (PCNNs) in nonsubsampled contourlet transform (NSCT) domain for fusing whole-body PET and CT images. Firstly, the gradient average of each pixel is chosen as the linking strength of PCNN model to implement self-adaptability. Secondly, to improve the fusion performance, the novel sum-modified Laplacian (NSML) and energy of edge (EOE) are extracted as the external inputs of the PCNN models for low- and high-pass subbands, respectively. Lastly, the rule of max region energy is adopted as the fusion rule and different energy templates are employed in the low- and high-pass subbands. The experimental results on whole-body PET and CT data (239 slices contained by each modality) show that the proposed framework outperforms the other six methods in terms of the seven commonly used fusion performance metrics

RSpell: Retrieval-augmented Framework for Domain Adaptive Chinese Spelling Check

Chinese Spelling Check (CSC) refers to the detection and correction of spelling errors in Chinese texts. In practical application scenarios, it is important to make CSC models have the ability to correct errors across different domains. In this paper, we propose a retrieval-augmented spelling check framework called RSpell, which searches corresponding domain terms and incorporates them into CSC models. Specifically, we employ pinyin fuzzy matching to search for terms, which are combined with the input and fed into the CSC model. Then, we introduce an adaptive process control mechanism to dynamically adjust the impact of external knowledge on the model. Additionally, we develop an iterative strategy for the RSpell framework to enhance reasoning capabilities. We conducted experiments on CSC datasets in three domains: law, medicine, and official document writing. The results demonstrate that RSpell achieves state-of-the-art performance in both zero-shot and fine-tuning scenarios, demonstrating the effectiveness of the retrieval-augmented CSC framework. Our code is available at https://github.com/47777777/Rspell

Development and application of CRISPR-based genetic tools in Bacillus species and Bacillus phages

Recently, the clustered regularly interspaced short palindromic repeats (CRISPR) system has been developed into a precise and efficient genome editing tool. Since its discovery as an adaptive immune system in prokaryotes, it has been applied in many different research fields including biotechnology and medical sciences. The high demand for rapid, highly efficient and versatile genetic tools to thrive in bacteria-based cell factories accelerates this process. This review mainly focuses on significant advancements of the CRISPR system in Bacillus subtilis, including the achievements in gene editing, and on problems still remaining. Next, we comprehensively summarize this genetic tool's up-to-date development and utilization in other Bacillus species, including B. licheniformis, B. methanolicus, B. anthracis, B. cereus, B. smithii and B. thuringiensis. Furthermore, we describe the current application of CRISPR tools in phages to increase Bacillus hosts' resistance to virulent phages and phage genetic modification. Finally, we suggest potential strategies to further improve this advanced technique and provide insights into future directions of CRISPR technologies for rendering Bacillus species cell factories more effective and more powerful

Soil CO2 and N2O emissions and microbial abundances altered by temperature rise and nitrogen addition in active-layer soils of permafrost peatland

Changes in soil CO2 and N2O emissions due to climate change and nitrogen input will result in increased levels of atmospheric CO2 and N2O, thereby feeding back into Earth’s climate. Understanding the responses of soil carbon and nitrogen emissions mediated by microbe from permafrost peatland to temperature rising is important for modeling the regional carbon and nitrogen balance. This study conducted a laboratory incubation experiment at 15 and 20°C to observe the impact of increasing temperature on soil CO2 and N2O emissions and soil microbial abundances in permafrost peatland. An NH4NO3 solution was added to soil at a concentration of 50 mg N kg−1 to investigate the effect of nitrogen addition. The results indicated that elevated temperature, available nitrogen, and their combined effects significantly increased CO2 and N2O emissions in permafrost peatland. However, the temperature sensitivities of soil CO2 and N2O emissions were not affected by nitrogen addition. Warming significantly increased the abundances of methanogens, methanotrophs, and nirK-type denitrifiers, and the contents of soil dissolved organic carbon (DOC) and ammonia nitrogen, whereas nirS-type denitrifiers, β-1,4-glucosidase (βG), cellobiohydrolase (CBH), and acid phosphatase (AP) activities significantly decreased. Nitrogen addition significantly increased soil nirS-type denitrifiers abundances, β-1,4-N- acetylglucosaminidase (NAG) activities, and ammonia nitrogen and nitrate nitrogen contents, but significantly reduced bacterial, methanogen abundances, CBH, and AP activities. A rising temperature and nitrogen addition had synergistic effects on soil fungal and methanotroph abundances, NAG activities, and DOC and DON contents. Soil CO2 emissions showed a significantly positive correlation with soil fungal abundances, NAG activities, and ammonia nitrogen and nitrate nitrogen contents. Soil N2O emissions showed positive correlations with soil fungal, methanotroph, and nirK-type denitrifiers abundances, and DOC, ammonia nitrogen, and nitrate contents. These results demonstrate the importance of soil microbes, labile carbon, and nitrogen for regulating soil carbon and nitrogen emissions. The results of this study can assist simulating the effects of global climate change on carbon and nitrogen cycling in permafrost peatlands