Learning Position-Aware Implicit Neural Network for Real-World Face Inpainting

Face inpainting requires the model to have a precise global understanding of the facial position structure. Benefiting from the powerful capabilities of deep learning backbones, recent works in face inpainting have achieved decent performance in ideal setting (square shape with $512px$). However, existing methods often produce a visually unpleasant result, especially in the position-sensitive details (e.g., eyes and nose), when directly applied to arbitrary-shaped images in real-world scenarios. The visually unpleasant position-sensitive details indicate the shortcomings of existing methods in terms of position information processing capability. In this paper, we propose an \textbf{I}mplicit \textbf{N}eural \textbf{I}npainting \textbf{N}etwork (IN$^2$) to handle arbitrary-shape face images in real-world scenarios by explicit modeling for position information. Specifically, a downsample processing encoder is proposed to reduce information loss while obtaining the global semantic feature. A neighbor hybrid attention block is proposed with a hybrid attention mechanism to improve the facial understanding ability of the model without restricting the shape of the input. Finally, an implicit neural pyramid decoder is introduced to explicitly model position information and bridge the gap between low-resolution features and high-resolution output. Extensive experiments demonstrate the superiority of the proposed method in real-world face inpainting task.Comment: 10 pages, 5 figure

Genome-wide identification, functional analysis and expression profiling of pleiotropic drug resistance (PDR) sub-family in potato

The plant pleiotropic drug resistance (PDR) family of ATP-binding cassette (ABC) transporters has comprehensively been researched in relation to transport of antifungal agents and resistant pathogens. In our study, analyses of the whole family of PDR genes present in the potato genome were provided. This analysis resolves discrepancies of potato PDR proteins and provides an expression analysis of all annotated potato PDR genes based on RNA-seq data. The results indicate that the potato genome contains 76 encoding PDR proteins and that these genes show a specific expression patterns, both at the organ level and in response to various hormonal treatment. These data provide some clues for future molecular genetic analysis of this important subfamily of ABC transporters. In addition, potato PDR genes may also play some important roles in the transportation of antifungal agents and resistant pathogens.Keywords: ABC transporter, potato, pleiotropic drug resistance (PDR), RNA-seq.African Journal of Biotechnology Vol. 12(30), pp. 4722-472

Cross-attention learning enables real-time nonuniform rotational distortion correction in OCT

Nonuniform rotational distortion (NURD) correction is vital for endoscopic optical coherence tomography (OCT) imaging and its functional extensions, such as angiography and elastography. Current NURD correction methods require time-consuming feature tracking or cross-correlation calculations and thus sacrifice temporal resolution. Here we propose a cross-attention learning method for the NURD correction in OCT. Our method is inspired by the recent success of the self-attention mechanism in natural language processing and computer vision. By leveraging its ability to model long-range dependencies, we can directly obtain the correlation between OCT A-lines at any distance, thus accelerating the NURD correction. We develop an end-to-end stacked cross-attention network and design three types of optimization constraints. We compare our method with two traditional feature-based methods and a CNN-based method, on two publicly-available endoscopic OCT datasets and a private dataset collected on our home-built endoscopic OCT system. Our method achieved a $\sim3\times$ speedup to real time ($26\pm 3$ fps), and superior correction performance

Finite-time stochastic input-to-state stability and observer-based controller design for singular nonlinear systems

This paper investigated observer-based controller for a class of singular nonlinear systems with state and exogenous disturbance-dependent noise. A new sufficient condition for finite-time stochastic input-to-state stability (FTSISS) of stochastic nonlinear systems is developed. Based on the sufficient condition, a sufficient condition on impulse-free and FTSISS for corresponding closed-loop error systems is provided. A linear matrix inequality condition, which can calculate the gains of the observer and state-feedback controller, is developed. Finally, two simulation examples are employed to demonstrate the effectiveness of the proposed approaches

Novel Graphene Biosensor Based on the Functionalization of Multifunctional Nano-BSA for the Highly Sensitive Detection of Cancer Biomarker

Abstract A simple, convenient, and highly sensitive bio-interface for graphene field-effect transistors (GFETs) based on multifunctional nano-denatured bovine serum albumin (nano-dBSA) functionalization was developed to target cancer biomarkers. The novel graphene–protein bioelectronic interface was constructed by heating to denature native BSA on the graphene substrate surface. The formed nano-dBSA film served as the cross-linker to immobilize monoclonal antibody against carcinoembryonic antigen (anti-CEA mAb) on the graphene channel activated by EDC and Sulfo-NHS. The nano-dBSA film worked as a self-protecting layer of graphene to prevent surface contamination by lithographic processing. The improved GFET biosensor exhibited good specificity and high sensitivity toward the target at an ultralow concentration of 337.58 fg mL−1. The electrical detection of the binding of CEA followed the Hill model for ligand–receptor interaction, indicating the negative binding cooperativity between CEA and anti-CEA mAb with a dissociation constant of 6.82 × 10−10 M. The multifunctional nano-dBSA functionalization can confer a new function to graphene-like 2D nanomaterials and provide a promising bio-functionalization method for clinical application in biosensing, nanomedicine, and drug delivery

Fibre optic chemical sensor based on graphene oxide-coated long period grating

In this work, a graphene oxide-coated long period fibre grating (GO-LPG) is proposed for chemical sensing application. Graphene oxide (GO) has been deposited on the surface of long period grating to form a sensing layer which significantly enhances the interaction between LPG propagating light and the surrounding-medium. The sensing mechanism of GO-LPG relies on the change of grating resonance intensity against surrounding-medium refractive index (SRI). The proposed GO-LPG has been used to measure the concentrations of sugar aqueous solutions. The refractive index sensitivities with 99.5 dB/RIU in low refractive index region (1.33-1.35) and 320.6 dB/RIU in high index region (1.42-1.44) have been achieved, showing an enhancement by a factor of 3.2 and 6.8 for low and high index regions, respectively. The proposed GO-LPG can be further extended to the development of optical biochemical sensor with advantages of high sensitivity, real-time and label-free sensing

Displacement behavior of methane in organic nanochannels in aqueous environment

Shale is rich in organic nanopores where shale gas mainly resides. Shale gas development is often accompanied by water, so studying interactions of gas and water in organic nanopores has become an important topic. Here, we performed molecular dynamics simulations to study the interaction of gas and water in organic nanochannels. It was found that water molecules in the nanochannel could be displaced by methane molecules. And the entered methane molecules would exhibit different layered structures. The above phenomenon is attributed to the fact that methane molecules have lower potential of mean force than water molecules in nanochannels. The revealed mechanism of displacing water molecules with methane molecules in organic nanochannels provides an insight into the interaction of water molecules and methane molecules in organic nanochannels and has tremendous potentials in the development of shale gas.Cited as: Huai, J., Xie, Z., Li, Z., Lou, G., Zhang, J., Kou, J., Zhao, H. Displacement behavior of methane in organic nanochannels in aqueous environment. Capillarity, 2020, 3(4): 56-61, doi: 10.46690/capi.2020.04.0

Graphene oxide functionalized long period grating for ultrasensitive label-free immunosensing

We explore graphene oxide (GO) nanosheets functionalized dual-peak long period grating (dLPG) based biosensor for ultrasensitive label-free antibody-antigen immunosensing. The GO linking layer provides a remarkable analytical platform for bioaffinity binding interface due to its favorable combination of exceptionally high surface-to-volume ratio and excellent optical and biochemical properties. A new GO deposition technique based on chemical-bonding in conjunction with physical-adsorption was proposed to offer the advantages of a strong bonding between GO and fiber device surface and a homogeneous GO overlay with desirable stability, repeatability and durability. The surface morphology of GO overlay was characterized by Atomic force microscopy, Scanning electron microscope, and Raman spectroscopy. By depositing the GO with a thickness of 49.2 nm, the sensitivity in refractive index (RI) of dLPG was increased to 2538 nm/RIU, 200% that of non-coated dLPG, in low RI region (1.333–1.347) where bioassays and biological events were usually carried out. The IgG was covalently immobilized on GO-dLPG via EDC/NHS heterobifunctional cross-linking chemistry leaving the binding sites free for target analyte recognition. The performance of immunosensing was evaluated by monitoring the kinetic bioaffinity binding between IgG and specific anti-IgG in real-time. The GO-dLPG based biosensor demonstrates an ultrahigh sensitivity with limit of detection of 7 ng/mL, which is 10-fold better than non-coated dLPG biosensor and 100-fold greater than LPG-based immunosensor. Moreover, the reusability of GO-dLPG biosensor has been facilitated by a simple regeneration procedure based on stripping off bound anti-IgG treatment. The proposed ultrasensitive biosensor can be further adapted as biophotonic platform opening up the potential for food safety, environmental monitoring, clinical diagnostics and medical applications