Reflection Coefficients on Surfaces of Different Periodic Structure

Diffraction properties of lossy periodic gratings with the metal base were investigated by solving Maxwell's equations numerically using the differential method. Two periodic surfaces were employed in the simulation: triangle structure and tilting triangle structure. Based on the numerical solution and in conjunction with the algorithm of Adams-Moulton, we computed reflection coefficients of plane waves with different wavelengths and different incident angles. The dielectric properties were also explored using various dielectric constants. The results show that the reflection coefficients of both TE and TM waves are quite sensitive to the incident angles of the plane waves when the metal sheet exists, which is in good agreement with the experimental data

Direct Adversarial Training: A New Approach for Stabilizing The Training Process of GANs

Generative Adversarial Networks (GANs) are the most popular models for image generation by optimizing discriminator and generator jointly and gradually. However, instability in training process is still one of the open problems for all GAN-based algorithms. In order to stabilize training, some regularization and normalization techniques have been proposed to make discriminator meet the Lipschitz continuity constraint. In this paper, a new approach inspired by works on adversarial attack is proposed to stabilize the training process of GANs. It is found that sometimes the images generated by the generator play a role just like adversarial examples for discriminator during the training process, which might be a part of the reason of the unstable training. With this discovery, we propose to introduce a adversarial training method into the training process of GANs to improve its stabilization. We prove that this DAT can limit the Lipschitz constant of the discriminator adaptively. The advanced performance of the proposed method is verified on multiple baseline and SOTA networks, such as DCGAN, WGAN, Spectral Normalization GAN, Self-supervised GAN and Information Maximum GAN

Electrochemically Active Thin Carbon Films with Enhanced Adhesion to Silicon Substrates

Thin carbon films deposited on technologically relevant substrates, such as silicon wafers, can be easily implemented in miniaturized electrochemical devices and used for sensing applications. However, a major issue in most carbon films is the weak film/substrate adhesion that shortens the working device lifetime. This paper describes the facile preparation of robust thin carbon films on silicon substrates by one-pot sol-gel synthesis. The improved adherence of these carbon films is based on the incorporation of silica through the controlled synthesis of a resorcinol/formaldehyde gel modified with aminopropyltriethoxysilane. The films demonstrate excellent adhesion to the silicon substrate, good homogeneity, excellent electrical conductivity and superior electrochemical performance. Moreover, this approach opens the door to the fabrication of carbon thin-film electrodes by photolithographic techniques.G. Antorrena from the Laboratorio de Microscopias Avanzadas of the Instituto de Nanociencia de Aragón is acknowledged for performing XPS analysis. This research was partially funded by, the European Union’s 7th Framework Programme (FP7/2007-2013) under grant agreement number 614155, the Spanish Ministry of Economy and Competitiveness in cofounding with the European Social Funds through the MAT2012-35324 project, the “Severo Ochoa” Programme for Centres of Excellence in R&D (SEV- 2015-0496) and the Generalitat de Catalunya (2014SGR213, 2014SGR1645). The Chinese Scholarship Council fellowship (201206240033) to P.N. and the COST Action MP1202 are also acknowledged.Peer Reviewe

A Microbiome-Based Index for Assessing Skin Health and Treatment Effects for Atopic Dermatitis in Children.

A quantitative and objective indicator for skin health via the microbiome is of great interest for personalized skin care, but differences among skin sites and across human populations can make this goal challenging. A three-city (two Chinese and one American) comparison of skin microbiota from atopic dermatitis (AD) and healthy pediatric cohorts revealed that, although city has the greatest effect size (the skin microbiome can predict the originated city with near 100% accuracy), a microbial index of skin health (MiSH) based on 25 bacterial genera can diagnose AD with 83 to ∼95% accuracy within each city and 86.4% accuracy across cities (area under the concentration-time curve [AUC], 0.90). Moreover, nonlesional skin sites across the bodies of AD-active children (which include shank, arm, popliteal fossa, elbow, antecubital fossa, knee, neck, and axilla) harbor a distinct but lesional state-like microbiome that features relative enrichment of Staphylococcus aureus over healthy individuals, confirming the extension of microbiome dysbiosis across body surface in AD patients. Intriguingly, pretreatment MiSH classifies children with identical AD clinical symptoms into two host types with distinct microbial diversity and treatment effects of corticosteroid therapy. These findings suggest that MiSH has the potential to diagnose AD, assess risk-prone state of skin, and predict treatment response in children across human populations.IMPORTANCE MiSH, which is based on the skin microbiome, can quantitatively assess pediatric skin health across cohorts from distinct countries over large geographic distances. Moreover, the index can identify a risk-prone skin state and compare treatment effect in children, suggesting applications in diagnosis and patient stratification

TRIE++: Towards End-to-End Information Extraction from Visually Rich Documents

Recently, automatically extracting information from visually rich documents (e.g., tickets and resumes) has become a hot and vital research topic due to its widespread commercial value. Most existing methods divide this task into two subparts: the text reading part for obtaining the plain text from the original document images and the information extraction part for extracting key contents. These methods mainly focus on improving the second, while neglecting that the two parts are highly correlated. This paper proposes a unified end-to-end information extraction framework from visually rich documents, where text reading and information extraction can reinforce each other via a well-designed multi-modal context block. Specifically, the text reading part provides multi-modal features like visual, textual and layout features. The multi-modal context block is developed to fuse the generated multi-modal features and even the prior knowledge from the pre-trained language model for better semantic representation. The information extraction part is responsible for generating key contents with the fused context features. The framework can be trained in an end-to-end trainable manner, achieving global optimization. What is more, we define and group visually rich documents into four categories across two dimensions, the layout and text type. For each document category, we provide or recommend the corresponding benchmarks, experimental settings and strong baselines for remedying the problem that this research area lacks the uniform evaluation standard. Extensive experiments on four kinds of benchmarks (from fixed layout to variable layout, from full-structured text to semi-unstructured text) are reported, demonstrating the proposed method's effectiveness. Data, source code and models are available

Autonomous Coordinator Selection in Beamformed 60GHz Wireless Networks

In 60 GHz wireless networks, autonomous coordinator selection is required to find a device to coordinate the transmissions among devices. In order to minimize the power consumption for the coordinator, we utilize the direction information extracted from beamformed transmissions in finding the coordinator automatically. The problem is formulated as a K-center problem, which is a NP-hard problem in general. Analysis is carried out to find optimal solutions in certain tractable topologies. Numerical algorithms and simulation results are further presented for random two dimensional topologies

H2O+: An Improved Framework for Hybrid Offline-and-Online RL with Dynamics Gaps

Solving real-world complex tasks using reinforcement learning (RL) without high-fidelity simulation environments or large amounts of offline data can be quite challenging. Online RL agents trained in imperfect simulation environments can suffer from severe sim-to-real issues. Offline RL approaches although bypass the need for simulators, often pose demanding requirements on the size and quality of the offline datasets. The recently emerged hybrid offline-and-online RL provides an attractive framework that enables joint use of limited offline data and imperfect simulator for transferable policy learning. In this paper, we develop a new algorithm, called H2O+, which offers great flexibility to bridge various choices of offline and online learning methods, while also accounting for dynamics gaps between the real and simulation environment. Through extensive simulation and real-world robotics experiments, we demonstrate superior performance and flexibility over advanced cross-domain online and offline RL algorithms

Macrophage inhibits the osteogenesis of fibroblasts in ultrahigh molecular weight polyethylene (UHMWPE) wear particle-induced osteolysis

Background In the ultrahigh molecular weight polyethylene (UHMWPE) prosthetic environment, fibroblasts affected by wear particles have the capacity of osteogenesis to reduce osteolysis. We aimed to assess the effects of macrophages on the osteogenic capability of fibroblasts treated with UHMWPE wear particles. Methods The effect of different concentrations of UHMWPE (0, 0.01, 0.1, and 1 mg/ml, respectively) on macrophage proliferation were validated by MTT assay to determine the optimum one. The fibroblasts viability was further determined in the co-culture system of UHMWPE particles and macrophage supernatants. The experiment was designed as seven groups: (A) fibroblasts only; (B) fibroblasts + 1 mg/ml UHMWPE particles; and (C1–C5) fibroblasts + 1/16, 1/8, 1/4, 1/2, and 1/1 supernatants of macrophage cultures stimulated by 1 mg/ml UHMWPE particles vs. fibroblast complete media, respectively. Alizarin red staining was used to detect calcium accumulation. The expression levels of osteogenic proteins were detected by Western blot and ELISA, including alkaline phosphatase (ALP) and osteocalcin (OCN). Results The concentration of 0.1 mg/ml was considered as the optimum concentration for macrophage proliferation due to the survival rate and was highest among the four concentrations. Fibroblast viability was better in the group of fibroblasts + 1/16 ratio of macrophage supernatants stimulated by 1 mg/ml of UHMWPE particles than the other groups (1:8, 1:4, 1:2, 1:1). ALP and OCN expressions were significantly decreased in the group of fibroblasts + 1/4, 1/2, and 1/1 supernatants stimulated by 1 mg/ml of UHMWPE particles compared with other groups (1/8, 1/16) and the group of fibroblasts + 1 mg/ml UHMWPE (p < 0.5). Conclusions Macrophages are potentially involved in the periprosthetic osteolysis by reducing the osteogenic capability of fibroblasts treated with wear particles generated from UHMWPE materials in total hip arthroplasty.China Sholarship Council (Grant 201506370173)China. National Natural Science Foundation (Grant 31200739)China. National Natural Science Foundation (Grant 31470948

Preparation and characterization of chitosan film incorporated with thinned young apple polyphenols as an active packaging material

The objective of this study was to characterize the physical, mechanical and bioactive properties of chitosan film incorporated with thinned young apple polyphenols (YAP). The results indicated that the addition of YAP resulted in a significant increase in the thickness, density, swelling degree, solubility and opacity of chitosan film, but the water content, water vapor permeability and mechanical properties of the film were decreased. Besides, the antioxidant and antimicrobial properties of chitosan film were significantly enhanced by YAP. Both the NMR and FTIR spectra indicated the interactions between YAP and chitosan were likely to be non-covalent. Furthermore, the thermal stability of the film was decreased by YAP addition, suggested by DSC. Interestingly, the changing tendency of crystalline degree indicated by X-ray kept pace with that of thermal stability for YAP-chitosan films. Overall, YAP-chitosan film was shown a potential as a bioactive packaging material to extend food shelf-life