Learning Image Demoireing from Unpaired Real Data

This paper focuses on addressing the issue of image demoireing. Unlike the large volume of existing studies that rely on learning from paired real data, we attempt to learn a demoireing model from unpaired real data, i.e., moire images associated with irrelevant clean images. The proposed method, referred to as Unpaired Demoireing (UnDeM), synthesizes pseudo moire images from unpaired datasets, generating pairs with clean images for training demoireing models. To achieve this, we divide real moire images into patches and group them in compliance with their moire complexity. We introduce a novel moire generation framework to synthesize moire images with diverse moire features, resembling real moire patches, and details akin to real moire-free images. Additionally, we introduce an adaptive denoise method to eliminate the low-quality pseudo moire images that adversely impact the learning of demoireing models. We conduct extensive experiments on the commonly-used FHDMi and UHDM datasets. Results manifest that our UnDeM performs better than existing methods when using existing demoireing models such as MBCNN and ESDNet-L. Code: https://github.com/zysxmu/UnDeMComment: AAAI202

MultiQuant: A Novel Multi-Branch Topology Method for Arbitrary Bit-width Network Quantization

Arbitrary bit-width network quantization has received significant attention due to its high adaptability to various bit-width requirements during runtime. However, in this paper, we investigate existing methods and observe a significant accumulation of quantization errors caused by frequent bit-width switching of weights and activations, leading to limited performance. To address this issue, we propose MultiQuant, a novel method that utilizes a multi-branch topology for arbitrary bit-width quantization. MultiQuant duplicates the network body into multiple independent branches and quantizes the weights of each branch to a fixed 2-bit while retaining the input activations in the expected bit-width. This approach maintains the computational cost as the same while avoiding the switching of weight bit-widths, thereby substantially reducing errors in weight quantization. Additionally, we introduce an amortization branch selection strategy to distribute quantization errors caused by activation bit-width switching among branches to enhance performance. Finally, we design an in-place distillation strategy that facilitates guidance between branches to further enhance MultiQuant's performance. Extensive experiments demonstrate that MultiQuant achieves significant performance gains compared to existing arbitrary bit-width quantization methods. Code is at \url{https://github.com/zysxmu/MultiQuant}

Attention switching through text dissimilarity: a cognition research on fragmented reading behavior

People tend to obtain information through fragmented reading. However, this behavior itself might lead to distraction and affect cognitive ability. To address it, it is necessary to understand how fragmented reading behavior influences readers’ attention switching. In this study, the researchers first collected online news that had 6 theme words and 60 sentences to compose the experimental material, then defined the degree of text dissimilarity, used to measure the degree of attention switching based on the differences in text content, and conducted an EEG experiment based on P200. The results showed that even after reading the fragmented text content with the same overall content, people in subsequent cognitive tasks had more working memory capacity, lower working memory load, and less negative impact on cognitive ability with the text content with lower text dissimilarity. Additionally, attention switching caused by differences in concept or working memory representation of text content might be the key factor affecting cognitive ability in fragmented reading behavior. The findings disclosed the relation between cognitive ability and fragmented reading and attention switching, opening a new perspective on the method of text dissimilarity. This study provides some references on how to reduce the negative impact of fragmented reading on cognitive ability on new media platforms

Local and systemic therapy may be safely de-escalated in elderly breast cancer patients in China: A retrospective cohort study

BackgroundFor elderly patients with breast cancer, the treatment strategy is still controversial. In China, preoperative axillary lymph node needle biopsy is not widely used, resulting in many patients receiving axillary lymph node dissection (ALND) directly. Our study aims to determine whether local and systemic therapy can be safely de-escalated in elderly breast cancer.MethodsPatients aged ≥70 years were retrospectively enrolled from our institution’s medical records between May 2013 and July 2021. Groups were assigned according to local and systemic treatment regimens, and stratified analysis was performed by molecular subtypes. Univariate and multivariate survival analyses were used to compare the effects of different regimens on relapse-free survival (RFS).ResultsA total of 653 patients were enrolled for preliminary data analysis, and 563 patients were screened for survival analysis. The mean follow-up was 19 months (range, 1–82 months). Axillary lymph node metastases were pathologically confirmed in only 2.1% of cN0 cases and up to 97.1% of cN+ cases. In the aspect of breast surgery, RFS showed no significant difference between mastectomy and BCS group (p = 0.3078). As for axillary surgery, patients in the ALND group showed significantly better RFS than those in the sentinel lymph node biopsy (SLNB) group among pN0 patients (p = 0.0128). Among these cases, the proportion of cN+ in ALND was significantly higher than that in SLNB (6.4% vs. 0.4%, p = 0.002), which meant axillary lymph nodes (ALNs) of ALND patients were larger in imaging and more likely to be misdiagnosed as metastatic. With regard to adjuvant therapy, univariate and multivariate analyses showed that RFS in different comprehensive adjuvant regimens were similar especially among hormone receptor (HR)+/human epidermal growth factor receptor 2 (HER2)− subgroup where patients who did not receive any adjuvant therapy accounted for 15.7% (p > 0.05).ConclusionsIt is feasible to reduce some unnecessary local or systemic treatments for elderly breast cancer patients, especially in HR+/HER2− subtype. Multiple patient-related factors should be considered when making treatment plans

Genetic and metabolic links between the murine microbiome and memory.

BackgroundRecent evidence has linked the gut microbiome to host behavior via the gut-brain axis [1-3]; however, the underlying mechanisms remain unexplored. Here, we determined the links between host genetics, the gut microbiome and memory using the genetically defined Collaborative Cross (CC) mouse cohort, complemented with microbiome and metabolomic analyses in conventional and germ-free (GF) mice.ResultsA genome-wide association analysis (GWAS) identified 715 of 76,080 single-nucleotide polymorphisms (SNPs) that were significantly associated with short-term memory using the passive avoidance model. The identified SNPs were enriched in genes known to be involved in learning and memory functions. By 16S rRNA gene sequencing of the gut microbial community in the same CC cohort, we identified specific microorganisms that were significantly correlated with longer latencies in our retention test, including a positive correlation with Lactobacillus. Inoculation of GF mice with individual species of Lactobacillus (L. reuteri F275, L. plantarum BDGP2 or L. brevis BDGP6) resulted in significantly improved memory compared to uninoculated or E. coli DH10B inoculated controls. Untargeted metabolomics analysis revealed significantly higher levels of several metabolites, including lactate, in the stools of Lactobacillus-colonized mice, when compared to GF control mice. Moreover, we demonstrate that dietary lactate treatment alone boosted memory in conventional mice. Mechanistically, we show that both inoculation with Lactobacillus or lactate treatment significantly increased the levels of the neurotransmitter, gamma-aminobutyric acid (GABA), in the hippocampus of the mice.ConclusionTogether, this study provides new evidence for a link between Lactobacillus and memory and our results open possible new avenues for treating memory impairment disorders using specific gut microbial inoculants and/or metabolites. Video Abstract

Amorphous 1-D nanowires of calcium phosphate/pyrophosphate : A demonstration of oriented self-growth of amorphous minerals

Amorphous inorganic solids are traditionally isotropic, thus, it is believed that they only grow in a non-preferential way without the assistance of regulators, leading to the morphologies of nanospheres or irregular aggregates of nanoparticles. However, in the presence of (ortho)phosphate (Pi) and pyrophosphate ions (PPi) which have synergistic roles in biomineralization, the highly elongated amorphous nanowires (denoted ACPPNs) form in a regulator-free aqueous solution (without templates, additives, organics, etc). Based on thorough characterization and tracking of the formation process (e.g., Cryo-TEM, spherical aberration correction high resolution TEM, solid state NMR, high energy resolution monochromated STEM-EELS), the microstructure and its preferential growth behavior are elucidated. In ACPPNs, amorphous calcium orthophosphate and amorphous calcium pyrophosphate are distributed at separated but close sites. The ACPPNs grow via either the preferential attachment of ∼2 nm nanoclusters in a 1-dimension way, or the transformation of bigger nanoparticles, indicating an inherent driving force-governed process. We propose that the anisotropy of ACPPNs microstructure, which is corroborated experimentally, causes their oriented growth. This study proves that, unlike the conventional view, amorphous minerals can form via oriented growth without external regulation, demonstrating a novel insight into the structures and growth behaviors of amorphous minerals

Efficacy and safety of low-dose IL-2 in the treatment of systemic lupus erythematosus: A randomised, double-blind, placebo-controlled trial

Objectives Open-labelled clinical trials suggested that low-dose IL-2 might be effective in treatment of systemic lupus erythematosus (SLE). A double-blind and placebocontrolled trial is required to formally evaluate the safety and efficacy of low-dose IL-2 therapy. Methods A randomised, double-blind and placebocontrolled clinical trial was designed to treat 60 patients with active SLE. These patients received either IL-2 (n=30) or placebo (n=30) with standard treatment for 12 weeks, and were followed up for additional 12 weeks. IL-2 at a dose of 1 million IU or placebo was administered subcutaneously every other day for 2 weeks and followed by a 2-week break as one treatment cycle. The primary endpoint was the SLE Responder Index-4 (SRI-4) at week 12. The secondary endpoints were other clinical responses, safety and dynamics of immune cell subsets. Results At week 12, the SRI-4 response rates were 55.17% and 30.00% for IL-2 and placebo, respectively (p=0.052). At week 24, the SRI-4 response rate of IL-2 group was 65.52%, compared with 36.67% of the placebo group (p=0.027). The primary endpoint was not met at week 12. Low-dose IL-2 treatment resulted in 53.85% (7/13) complete remission in patients with lupus nephritis, compared with 16.67% (2/12) in the placebo group (p=0.036). No serious infection was observed in the IL-2 group, but two in placebo group. Besides expansion of regulatory T cells, low-dose IL-2 may also sustain cellular immunity with enhanced natural killer cells. Conclusions Low-dose IL-2 might be effective and tolerated in treatment of SThe work was supported by the National Natural Science Foundation of China (31530020,31570880,81471601,81601417 and 81701598), Peking-Tsinghua Center for Life Sciences to ZG LI, Beijing Sci-Tech Committee Z171100000417007,Clinical Medicine Plus X-Young Scholars Project of Peking University (PKU2019LCXQ013) supported by the Fundamental Research Funds for the Central Universities, Beijing Nova Program Z171100001117025, National Key Research and Development Program of China (2017YFC0909003 to DY), BellberryViertel Senior Medical Research Fellowship to DY and Beijing SL PHARM

Roadmap on energy harvesting materials

Ambient energy harvesting has great potential to contribute to sustainable development and address growing environmental challenges. Converting waste energy from energy-intensive processes and systems (e.g. combustion engines and furnaces) is crucial to reducing their environmental impact and achieving net-zero emissions. Compact energy harvesters will also be key to powering the exponentially growing smart devices ecosystem that is part of the Internet of Things, thus enabling futuristic applications that can improve our quality of life (e.g. smart homes, smart cities, smart manufacturing, and smart healthcare). To achieve these goals, innovative materials are needed to efficiently convert ambient energy into electricity through various physical mechanisms, such as the photovoltaic effect, thermoelectricity, piezoelectricity, triboelectricity, and radiofrequency wireless power transfer. By bringing together the perspectives of experts in various types of energy harvesting materials, this Roadmap provides extensive insights into recent advances and present challenges in the field. Additionally, the Roadmap analyses the key performance metrics of these technologies in relation to their ultimate energy conversion limits. Building on these insights, the Roadmap outlines promising directions for future research to fully harness the potential of energy harvesting materials for green energy anytime, anywhere