An Efficient Feature Extraction Scheme for Mobile Anti-Shake in Augmented Reality

In recent years, augmented reality on mobile devices has become popular. Mobile shakes are the most typical type of interference in mobile augmented reality. To negate such interference, anti-shake is an urgent requirement. To enhance anti-shake efficiency, we propose an efficient feature extraction scheme for mobile anti-shake in augmented reality. The scheme directly detects corners to avoid the non-extreme constraint such that the efficiency of feature extraction is improved. Meanwhile, the scheme only updates the added corners during mobile shakes, which improves the accuracy of feature extraction. In the experiments, the memory consumption of existing methods is almost double compared to that in our scheme. Further, the runtime of our scheme is only half of the runtime of the existing methods. The experimental results demonstrate that our scheme performs better than the existing classic methods on mobile anti-shake in terms of memory consumption, efficiency, and accuracy

On hydrodynamic characteristics of gap resonance between two fixed bodies in close proximity

The resonant water motion inside a narrow gap between two identical fixed boxes that are in side-by-side configuration is investigated using a two-dimensional (2D) numerical wave tank based on OpenFOAM®, an open source CFD package. Gap resonance is excited by regular waves with various wave heights, ranging from linear waves to strong nonlinear waves. This paper mainly focuses on the harmonic analyses of the free-surface elevation in the narrow gap and wave loads (including the horizontal wave forces, the vertical wave forces and the moments) on the bodies. It is found that the influences of the incident wave height on the higher-order harmonic components of different physical quantities are quite different. The effects of the incident wave height on the reflection, transmission and energy loss coefficients are also discussed. Finally, aiming at the quantitative estimation of the response time and the damping time of gap resonance, two different methods are proposed and verified for the first time on gap resonance.</p

Bergenin suppresses the growth of colorectal cancer cells by inhibiting PI3K/AKT/mTOR signaling pathway

Purpose: To investigate anticancer effects of bergenin on human colorectal cancer cell lines.Methods: Human colorectal adenocarcinoma cell line HCT116 was treated with various concentrations of bergenin for 24 and 48 h. Cell viability, apoptosis, cell cycle arrest and reactive oxygen species (ROS) level were analyzed by MTT, flow cytometry and fluorescent dye assays, respectively. DNA damage-associated protein expressions were analyzed by Western blotting.Results: Bergenin significantly suppressed the viability of HCT116 cells. Moreover, bergenin induced cells to accumulate in G1 phase and resulted in DNA breaks in HCT116 cells. It also led to marked accumulation of intracellular reactive oxygen species (ROS), a breaker of DNA strand in HCT116 cells. Interestingly, bergenin inhibited PI3K/AKT/mTOR pathway.Conclusion: Bergenin effectively suppresses the growth of colorectal  adenocarcinoma by inducing generation of intracellular ROS, DNA damage and consequent G1 phase arrest via inhibition of PI3K/AKT/mTOR pathway.Keywords: Bergenin, Colorectal cancer, DNA damage, Cell cycle arrest,  PI3K/AKT/mTO

Single-Cell Transcriptome and Network Analyses Unveil Key Transcription Factors Regulating Mesophyll Cell Development in Maize

BACKGROUND: Maize mesophyll (M) cells play important roles in various biological processes such as photosynthesis II and secondary metabolism. Functional differentiation occurs during M-cell development, but the underlying mechanisms for regulating M-cell development are largely unknown. RESULTS: We conducted single-cell RNA sequencing (scRNA-seq) to profile transcripts in maize leaves. We then identified coregulated modules by analyzing the resulting pseudo-time-series data through gene regulatory network analyses. , , , and () families were highly expressed in the early stage, whereas () and families were highly expressed in the late stage of M-cell development. Construction of regulatory networks revealed that these transcript factor (TF) families, especially and , were the major players in the early and later stages of M-cell development, respectively. Integration of scRNA expression matrix with TF ChIP-seq and Hi-C further revealed regulatory interactions between these TFs and their targets. and were primarily expressed in the leaf bases and tips, respectively, and their targets were validated with protoplast-based ChIP-qPCR, with the binding sites of HSF1 being experimentally confirmed. CONCLUSIONS: Our study provides evidence that several TF families, with the involvement of epigenetic regulation, play vital roles in the regulation of M-cell development in maize

Identification of Antioxidant Proteins With Deep Learning From Sequence Information

Antioxidant proteins have been found closely linked to disease control for its ability to eliminate excess free radicals. Because of its medicinal value, the study of identifying antioxidant proteins is on the upsurge. Many machine-learning classifiers have performed poorly owing to the nonlinear and unbalanced nature of biological data. Recently, deep learning techniques showed advantages over many state-of-the-art machine learning methods in various fields. In this study, a deep learning based classifier was proposed to identify antioxidant proteins based on mixed g-gap dipeptide composition feature vector. The classifier employed deep autoencoder to extract nonlinear representation from raw input. The t-Distributed Stochastic Neighbor Embedding (t-SNE) was used for dimensionality reduction. Support vector machine was finally performed for classification. The classifier achieved F1 score of 0.8842 and MCC of 0.7409 in 10-fold cross validation. Experimental results show that our proposed method outperformed the traditional machine learning methods and could be a promising tool for antioxidant protein identification. For the convenience of others' scientific research, we have developed a user-friendly web server called IDAod for antioxidant protein identification, which can be accessed freely at http://bigroup.uestc.edu.cn/IDAod/

Rice Xa21 primed genes and pathways that are critical for combating bacterial blight infection

Rice bacterial blight (BB) is a devastating rice disease. The Xa21 gene confers a broad and persistent resistance against BB. We introduced Xa21 into Oryza sativa L ssp indica (rice 9311), through multi-generation backcrossing, and generated a nearly isogenic, blight-resistant 9311/Xa21 rice. Using next-generation sequencing, we profiled the transcriptomes of both varieties before and within four days after infection of bacterium Xanthomonas oryzae pv. oryzae. The identified differentially expressed (DE) genes and signaling pathways revealed insights into the functions of Xa21. Surprisingly, before infection 1,889 genes on 135 of the 316 signaling pathways were DE between the 9311/Xa21 and 9311 plants. These Xa21-mediated basal pathways included mainly those related to the basic material and energy metabolisms and many related to phytohormones such as cytokinin, suggesting that Xa21 triggered redistribution of energy, phytohormones and resources among essential cellular activities before invasion. Counter-intuitively, after infection, the DE genes between the two plants were only one third of that before the infection; other than a few stress-related pathways, the affected pathways after infection constituted a small subset of the Xa21-mediated basal pathways. These results suggested that Xa21 primed critically important genes and signaling pathways, enhancing its resistance against bacterial infection

Microscopic Kinetics Pathway of Salt Crystallization in Graphene Nanocapillaries.

The fundamental understanding of crystallization, in terms of microscopic kinetic and thermodynamic details, remains a key challenge in the physical sciences. Here, by using in situ graphene liquid cell transmission electron microscopy, we reveal the atomistic mechanism of NaCl crystallization from solutions confined within graphene cells. We find that rock salt NaCl forms with a peculiar hexagonal morphology. We also see the emergence of a transitory graphitelike phase, which may act as an intermediate in a two-step pathway. With the aid of density functional theory calculations, we propose that these observations result from a delicate balance between the substrate-solute interaction and thermodynamics under confinement. Our results highlight the impact of confinement on both the kinetics and thermodynamics of crystallization, offering new insights into heterogeneous crystallization theory and a potential avenue for materials design.Royal Commission for the Exhibition of 185