The Ginger-shaped Asteroid 4179 Toutatis: New Observations from a Successful Flyby of Chang'e-2

On 13 December 2012, Chang'e-2 conducted a successful flyby of the near-Earth asteroid 4179 Toutatis at a closest distance of 770 $\pm$ 120 meters from the asteroid's surface. The highest-resolution image, with a resolution of better than 3 meters, reveals new discoveries on the asteroid, e.g., a giant basin at the big end, a sharply perpendicular silhouette near the neck region, and direct evidence of boulders and regolith, which suggests that Toutatis may bear a rubble-pile structure. Toutatis' maximum physical length and width are (4.75 $\times$ 1.95 km) $\pm$10$\%$, respectively, and the direction of the +$z$ axis is estimated to be (250$\pm$5$^\circ$, 63$\pm$5$^\circ$) with respect to the J2000 ecliptic coordinate system. The bifurcated configuration is indicative of a contact binary origin for Toutatis, which is composed of two lobes (head and body). Chang'e-2 observations have significantly improved our understanding of the characteristics, formation, and evolution of asteroids in general.Comment: 21 pages, 3 figures, 1 tabl

CornerFormer: Boosting Corner Representation for Fine-Grained Structured Reconstruction

Structured reconstruction is a non-trivial dense prediction problem, which extracts structural information (\eg, building corners and edges) from a raster image, then reconstructs it to a 2D planar graph accordingly. Compared with common segmentation or detection problems, it significantly relays on the capability that leveraging holistic geometric information for structural reasoning. Current transformer-based approaches tackle this challenging problem in a two-stage manner, which detect corners in the first model and classify the proposed edges (corner-pairs) in the second model. However, they separate two-stage into different models and only share the backbone encoder. Unlike the existing modeling strategies, we present an enhanced corner representation method: 1) It fuses knowledge between the corner detection and edge prediction by sharing feature in different granularity; 2) Corner candidates are proposed in four heatmap channels w.r.t its direction. Both qualitative and quantitative evaluations demonstrate that our proposed method can better reconstruct fine-grained structures, such as adjacent corners and tiny edges. Consequently, it outperforms the state-of-the-art model by +1.9\%@F-1 on Corner and +3.0\%@F-1 on Edge

Endophytic bacteria with allelopathic potential regulate gene expression and metabolite production in host Casuarina equisetifolia

IntroductionCasuarina equisetifolia is a common protective forest in coastal areas. However, artificial C. equisetifolia forests cannot self-renew, mainly due to the accumulation of allelochemicals. Endophytic bacteria may alleviate the root growth inhibition caused by allelochemicals in C. equisetifolia seedlings. B. amyloliquefaciens and B. aryabhattai were endophytic bacteria with strong allelopathy in C. equisetifolia root. The allelopathy mechanism of these two endophytes and their interaction with C. equisetifolia remains to be studied.MethodsWhole-genome sequencing of B. amyloliquefaciens and B. aryabhattai isolated from the roots of allelochemical-accumulating C. equisetifolia was performed using Illumina Hiseq and PacBio single-molecule sequencing platforms. Sterile seedlings of C. equisetifolia were treated with either individual or mixed bacterial cultures through root drenching. Transcriptional and metabolomics analyses were conducted after 3 days of infection.Results and discussionWhole-genome sequencing of Bacillus aryabhattai and Bacillus amyloliquefaciens showed that the two strains contained various horizontal gene transfer elements such as insertion sequence, prophage and transposon. In addition, these two strains also contain numerous genes related to the synthesis and catabolism of allelochemicals. After these two strains of bacteria were individually or mixed infected with C. equisetifolia, metabolomics and transcriptomic analysis of C. equisetifolia showed the 11 important secondary metabolite biosynthesis among them alkaloids biosynthesis, phenylpropanoid and terpenes biosynthesis and related genes were putatively regulated. Correlation analysis revealed that 48 differentially expressed genes had strong positive correlations with 42 differential metabolites, and 48 differentially expressed genes had strong negative correlations with 36 differential metabolites. For example, CMBL gene showed positive correlations with the allelochemical (-)-Catechin gallate, while Bp10 gene showed negative correlations with (-)-Catechin gallate.ConclusionThe intergenerational accumulation of allelochemicals may induce horizontal gene transfer in endogenic bacteria of Casuarina equisetifolia root. Endophytic Bacillus plays an allelopathic role by assisting the host in regulating gene expression and the production and/or variety of allelochemicals. This comprehensive study sheds light on the intricate genetic and metabolic interactions between Bacillus endophytes and C. equisetifolia. These findings provide insights into endophyte-mediated allelopathy and its potential uses in plant biology and forest sustainability

Invisible sensor: Simultaneous sensing and camouflaging in multiphysical fields

To manipulate various types of physical signals in one single device has long captivated the attention of scientists and engineers. This however is very challenging, if not impossible, even for emerging metamaterials. Up to date, many artificial materials have been proposed, theoretically and (or) experimentally, for manipulating various waves/signals on a one-function-one-device basis. In this work, for the very first time, we employ undecorated natural materials to experimentally demonstrate a simultaneous camouflage for thermal current and electric dc current on the same device. It demonstrates how ingenuity can overcome the limitations of natural material systems without the need for complex decoration to impart inhomogeneous and (or) anisotropic properties, which was previously considered impossible to accomplish except by using metamaterials.Comment: The paper has been published on Advanced Materials, 201

Prediction of the impact of tobacco waste hydrothermal products on compost microbial growth using hyperspectral imaging combined with machine learning

The insufficient understanding of the impact of hydrothermal products on the growth characteristics of compost microorganisms presents a significant challenge to the broader implementation of hydrothermal coupled composting for tobacco waste. Traditional biochemical detection methods are labor-intensive and time-consuming, highlighting the need for faster and more accurate alternatives. This study investigated the effects of hydrothermal treatment on tobacco straw products and their influence on compost microorganism growth, using hyperspectral imaging (HSI) technology and machine learning algorithms. Sixty-one tobacco straw samples were analyzed with a hyperspectral camera, and image processing was used to extract average spectra from regions of interest (ROI). Hierarchical cluster analysis (HCA) and principal component analysis (PCA) were applied to assess four key variables: nicotine content, total humic acid content, Penicillium chrysogenum H/C ratio, and Bacillus subtilis OD600 ratio. The effects of hydrothermal treatment on compost were classified as promoting, inhibiting, or neutral regarding microbial growth. The Competitive Adaptive Reweighted Sampling (CARS) method identified the most influential wavelengths in the 900-1700 nm spectral range. The Random Forest (RF) model outperformed SVM, KNN, and XGBoost models in predicting microbial growth responses, achieving Rc = 0.957, RMSE = 3.584. Key wavelengths were identified at 1096 nm, 1101 nm, 1163 nm, 1335 nm, and 1421 nm. The results indicate that hyperspectral imaging combined with machine learning can accurately predict changes in the chemical composition of tobacco straws and their effects on microbial activity. This method provides an innovative and effective means of improving the resource usage of tobacco straws in composting, enhancing sustainable waste management procedures

Elevated non-HDL-C to HDL-C ratio as a marker for NAFLD and liver fibrosis risk: a cross-sectional analysis

BackgroundDyslipidemia is a known independent risk factor for Nonalcoholic fatty liver disease (NAFLD). However, the relationship between NAFLD and the serum non-high-density lipoprotein cholesterol (non-HDL-C) to high-density lipoprotein cholesterol (HDL-C) ratio remains unclear. This study examined the association between the non-HDL-C to HDL-C ratio and NAFLD prevalence, including liver steatosis and fibrosis levels in the population.MethodsWe conducted a cross-sectional study using data from the National Health and Nutrition Examination Survey (NHANES) 2017–2018, including 4798 participants. Liver ultrasound and Transient Elastography (TE) were used to assess fibrosis and steatosis. Adjusted multivariable regression analyses, subgroup analyses based on BMI and sex, and a generalized additive model were employed to investigate the relationship between the non-HDL-C/HDL-C ratio and NAFLD.ResultsAmong the 4798 participants, 39.27% (n = 1,884) had NAFLD. Significant positive correlations between non-HDL-C/HDL-C and NAFLD risk were found across all models, with sex-stratified analyses indicating higher risk in men. Liver fibrosis was also associated with non-HDL-C/HDL-C ratios. The Receiver operating characteristic (ROC) analysis shows non-HDL-C/HDL-C as a better predictor for NAFLD than non-HDL-C or HDL-C alone.ConclusionElevated non-HDL-C/HDL-C levels are independently associated with increased NAFLD and liver fibrosis risk in the American population, suggesting its utility in predicting NAFLD and related liver fibrosis

DNA methyltransferase 1 modulates mitochondrial function through bridging m5C RNA methylation

DNA methyltransferase 1 (DNMT1) is an enzyme known for DNA methylation maintenance. Point mutations in its replication focus targeting sequence (RFTS) domain lead to late-onset neurodegeneration, such as autosomal dominant cerebellar ataxia-deafness and narcolepsy (ADCA-DN) disorder. Here, we demonstrated that DNMT1 has the capability to bind to mRNA transcripts and facilitate 5-methylcytosine (m5C) RNA methylation by recruiting NOP2/Sun RNA methyltransferase 2 (NSUN2). RNA m5C methylation, in turn, promotes RNA stability for those genes modulating mitochondrial function. When the DNMT1 RFTS domain is mutated in mice, it triggers aberrant DNMT1-RNA interaction and significantly elevated m5C RNA methylation and RNA stability for a portion of metabolic genes. Consequently, increased levels of metabolic RNA transcripts contribute to cumulative oxidative stress, mitochondrial dysfunction, and neurological symptoms. Collectively, our results reveal a dual role of DNMT1 in regulating both DNA and RNA methylation, which further modulates mitochondrial function, shedding light on the pathogenic mechanism of DNMT1 mutation-induced neurodegeneration