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A multiscale analysis method was developed to simulate the reaction-diffusion process of SiC/SiC composite structures in a coupled thermo-chemo-mechanical environment. For the diffusion process, the airflow channel was characterized by an equivalent diffusion coefficient model, which was established in this study. The corresponding calculation was developed using a numerical analysis method to obtain the gas concentration distribution in the structure. For the reaction process, an oxidation kinetics model was adopted to calculate morphological evolution of the airflow channel. The equivalent diffusion coefficient was then updated, and the reaction–diffusion coupling calculation was performed through an iterative scheme. To validate the model, an oxidation tensile test was conducted at 1200 °C. Finally, an adjustment sheet model was calculated as an example to analyze its reaction-diffusion process, proving that this method can be applied to SiC/SiC components under complex aerodynamic and temperature loads.

Skin lesion image segmentation task has many difficulties due to the hair occlusion or low contrast. Traditional methods based image quality are powerless when processing these kinds of skin images. In this paper, a segmentation architecture based adversarial networks is proposed. The architecture is consist of a segmentation network based U-net and a discrimination network linked by certain convolutional layers. Both two networks are trained alternately and at last segmentation network gets a high segmentation accuracy. We test our architecture on dataset PH2 and dataset obtained from “Skin Lesion Analysis Toward Melanoma Detection” challenge which was hosted by ISBI 2016 conference and we achieved segmentation average accuracy of 0.97, dice coefficient of 0.94 which outperform other existed segmentation network, including winner of ISBI 2016 challenge for skin melanoma segmentation.

In this paper, we study the problem of recommending the appropriate datasets for authors, which is implemented to infer the proximity between authors and datasets by leveraging the information from a three-layered network, composed by authors, papers and datasets. To link author-dataset semantically by taking advantage of the rich content information of papers in the intermediate layer, we design an attentive and aggregate multi-layer network learning model. The aggregation is for integrating the intra-layer information of paper content and citations, while the attention is used for coordinating authors at the top-layer and datasets at the bottom-layer in the semantic space learned from papers in the intermediate layer. The experimental study demonstrates the superiority of our method compared with the solutions that extend existing models to our problem.

This study has developed a novel sensing platform for the investigation of cell oxygen metabolism. With chitosan@TiO2 nanocomposites as supporting matrix which was decorated on the surface of indium tin oxide glass, it can effectively absorb A549 cells and sensitize the electrochemiluminescence (ECL) of luminol. On this platform, the ECL output is dependent on the level of reactive oxygen species (ROSs), which was evidenced by the intervening of resveratrol, a typical ROSs’ scavenger. The results indicated that the ECL signal was quenched by the resveratrol within its concentration range from 0.10 nM to 2.97 µM. Thus, it is believable that the ECL of luminol sensitively responded upon oxygenic matters on this living cell platform would be powerful for cell oxygen metabolism monitoring.

In this report, an ultrasensitive electrochemical aptasensor for the detection of prostate specific antigen (PSA) in human serum is presented. DNA tetrahedron molecular layer is designed on the interface of a gold working electrode, which provides the recognition element for PSA capture. Next, exonuclease-aided target recycling amplification is performed, which determines the amount of attached silver nanoparticles (AgNPs) via silver-amino chemistry. By recording electrochemical responses from AgNPs, initial concentration of PSA can be easily evaluated. The limit of detection is pushed down to 0.11 pg mL−1, which is attributed to the cyclic digestion effect of exonuclease and highly effective electrochemical reporters of AgNPs. The efficiency and robustness of this approach are further studied using human serum samples. The achieved results are satisfactory for future clinical applications.

Ag dendrites were readily achieved via the redox reaction between polyaniline and AgNO3 in aqueous dispersion. The diffusion-limited aggregation was adopted for the generation of dendrite structure and the oxidized polyaniline was not removed for purifying the Ag dendrites. The existence of the Ag and polyaniline was confirmed by X-ray powder diffraction patterns and Fourier transform infrared spectra. The oxygen reduction reaction activity of the product was examined with rotating disk electrode voltammetry in 0.1 M KOH aqueous solution. The presence of the polyaniline greatly enhanced the oxygen reduction reaction catalytic activity of Ag dendrites and an onset and half-wave potential of 0.846 and 0.651 V vs. reversible hydrogen electrode, respectively, were obtained. We demonstrate the possible positive effect of the template that might be ignored in many cases and this can lead us to construct series of similar catalytic systems.

In this work, a novel amperometric biosensor based on carbon nanoplatelets derived from ground cherry (Physalis peruviana) husks (GCHs-CNPTs) is reported for the sensitive and selective detection of ascorbic acid (AA). The structure of the nanoplatelets, the oxygen-containing groups and edge-plane-like defective sites (EPDSs) on the GCHs-CNPTs were characterized by scanning electron microscopy, X-ray diffraction, Raman spectroscopy, X-ray photoelectron spectroscopy and Fourier transform infrared spectroscopy. The presence of GCHs-CNPTs with a high density of EPDSs effectively enhances the electron transfer between AA and the glassy carbon electrode (GCE), and thus induces a substantial decrease in the overvoltage for AA oxidation compared with both a bare GCE and a GCE modified with carbon nanotubes (CNTs/GCE). In particular, an amperometric biosensor based on GCHs-CNPTs exhibited a wider linear range (0.01–3.57mM), higher sensitivity (208.63μAmM−1cm−2), a lower detection limit (1.09μM, S/N=3) and better resistance to fouling for AA determination compared to a CNTs/GCE. The great potential of the GCHs-CNPTs/GCE for practical and reliable AA analysis was demonstrated by the successful determination of AA in samples taken from a medical injection dose and a soft drink. Keywords: Carbon nanoplatelets, Ascorbic acid, Edge-plane-like defective sites, Electroanalysis

CeO2 nanoparticles were incorporated into the cavity of zeolitic imidazolate framework-8 (ZIF-8) materials followed by high temperature pyrolysis to generate CeO2@N doped carbon materials. The introduction of the CeO2 nanoparticles greatly enhanced the oxygen reduction reaction (ORR) catalytic activity of the ZIF-8 derived carbon materials owing to existence of amounts of Ce3+ in CeO2 and oxygen vacancies with high chemisorbed oxygen content and the well-maintained skeleton of the original ZIF-8 with uniform mesoporous structure. The resulted sample treated at 900 oC (CeO2@N-C-900) presented an excellent ORR catalytic activity under both acidic and alkaline electrolyte. The ORR test revealed the onset and half-wave potentials of the CeO2@N-C-900 were 1.003 V and 0.908 V vs. RHE, respectively, in 0.1 M KOH aqueous solution, which were comparable to those of Pt/C catalysts. Furthermore, it displayed much better stability and methanol crossover tolerance than Pt/C, indicating its good possibility to be a good candidate for the application in energy conversion.

Eccentric encapsulation of silver by polypyrrole was realized via the direct redox reaction between AgNO 3 and pyrrole in the presence of sodium dodecyl sulfate. A facile method based on the relative amount of the Ag embedded in the normalized PPy sphere was developed and utilized to compare the interface tension between Ag, PPy and the solution. Via the aid of the embedding ratio, the formation of the eccentric silver@polypyrrole (Ag@PPy) was investigated by a temporal process and tuning the surfactant concentration and reaction temperature. Furthermore, such a unique nanostructure allowed the manipulation on the Ag end to achieve mushroom-like Au/Ag-PPy via the galvanic replacement reaction between Ag and HAuCl 4 , which was also dependent on the embedding ratio. After generating the above later nanostructure, much more active sites were available and much better catalytic activity was achieved taking the reduction of 4-nitrophenol by NaBH 4 as an example reaction.

The redox reaction between KMnO4 and Ni was carried out on a chain-like Ni surface under hydrothermal conditions and γ-MnO2 nanosheets were produced through this facile route. The original Ni nanochains, as cores, dominated the final morphology of the composites with MnO2 nanosheets loaded on their surface. The uniform assemblies of MnO2 , with large amounts of exposed sites, allowed them to be good candidates for application in various fields. The reduction of 4-nitrophenol by NaBH4 was selected as model reaction to test the catalytic activity of the samples and the samples could also be made into electrodes for supercapacitor measurement. Both the results revealed the advantages of the γ-MnO2 assembled on the Ni chain surfaces. Furthermore, the magnetic cores facilitated the recycling of the sample and increased the stability upon charge-discharge cycles.

Based on the previous generation of yolk-shell nanostructured polyaniline@SiO2 particles, a confined carbonization process followed by etching the SiO2 layer is carried out to achieve carbon particles. The existence of the SiO2 shell helps to preserve the original well-dispersed morphology of the polyaniline that retains amounts of active sites for oxygen reduction reaction. Furthermore, the CeO2 oxidant and the SiO2 shell lead to the increased amount of oxygen existing in the product and the oxygen reduction reaction results show the well-maintained nanostructure with mesopores and the effective O doping benefit for achieving enhanced catalytic activity.

The authors have prepared organized assemblies of a hemoglobin-chitosan(CS)@Fe3O4 composite on glassy carbon electrodes (GCEs) via three strategies with the aim of preparing tunable Hb-coated GCEs with good stability and long-term oxygen storage capability. The formation and morphology of the Hb-CS@Fe3O4 composite was characterized by scanning electrochemical microscopy, XRD and UV–vis spectroscopy. It is shown that Hb is fully integrated into the CS@Fe3O4 and can be manipulated by a magnetic field whilst maintaining its biological activity. In the absence of oxygen, a surface-controlled electrode process occurs with an interfacial electron transfer rate (k s) of 2.14 s−1. The modified GCE also has a favorable oxygen storage lifetime (almost 6 h). One Hb-CS@Fe3O4 film on the electrode displays particularly good electrocatalytic reduction activity towards oxygen. The linear range for detection of O2 is 1.2 × 10−7 ~ 2.0 × 10−4 mol L−1 with a detection limit of 4.0 × 10−8 mol L−1. In our opinion, this method has great potential in terms of enhanced oxygen storage capability of Hb, which can be applied in special situations such as space operations, down hole mining, mountaineering and diving.

In this paper, an interactive dynamic simulation method is proposed to solve computational models of soft tissue undergoing large deformation, collision detection, and volume conservation in medical surgical simulation visualization. During the process of implementation of the interactive dynamic simulation method, the point-based method is used to simulate the elastic solids undergoing large deformations and the position-based method is used to simulate the objects collision, friction and volume conservation. Numerical results demonstrate that the proposed method improves the efficiency and stability of the response of heterogeneous soft tissue undergoing contact or even the multi-organs interactions, and it can be extended to interactive biopsy and cutting simulation.

A simple, highly sensitive, and cost-effective electrochemical method for the detection of Zn 2 + is constructed employing unmodified gold nanoparticles (AuNPs) and a specific binding peptide. AuNPs are firstly modified on a glassy carbon electrode, which show excellent electrical conductivity and provide a large superficial area for subsequent attachment of peptide with cysteine residues. Acidic amino acids residues of the peptide contribute to large electron transfer resistance, which is recorded by electrochemical impedance spectroscopy. Nevertheless, in the presence of Zn 2 + , the recognition sequence of the peptide (CCPGC) binds to Zn 2 + with a high affinity and is therefore not able to be modified on the electrode. By analyzing the decrease in electron transfer resistance, Zn 2 + level could be determined. The sensitivity of the proposed method is comparable to atomic absorption spectrometry and higher than most fluorescent, colorimetric and electrochemical sensors for Zn 2 + assay. Moreover, negligible interference is observed when detecting other ions. Therefore, the developed method has great potential environmental monitoring and clinical applications.

This work aimed to optimize the washcoat slurry for hydrotalcite-based lean NOx trap (LNT) catalyst. The effects of the slurry properties including pH, solid content, binder and additive on the hydrotalcite-based slurry viscosity were investigated. The particle size distribution of the optimal hydrotalcite-based slurry was measured. A cordierite material was used to coat the optimal slurry, and the washcoat was characterized by X-ray diffraction, scanning electron microscopy and N2 adsorption. The optimal slurry containing Pt and Ba was coated on the cordierite for the preparation of hydrotalcite-based LNT catalyst, and the performances of this catalyst were evaluated by NOx storage test, temperature programmed desorption and NOx reduction. For comparison, the performance of the commercial LNT catalyst with Pt/BaO/Al2O3 was analyzed. After coating, the hydrotalcite-based washcoat was closely contacted with the support, being the main phase MgO and presenting a specific surface area of 86.3 m2/g. The hydrotalcite-based LNT catalyst had better NOx storage and desorption ability, selectivity to N2 and LNT efficiency than the Pt/BaO/Al2O3 catalyst.

Collaborative filtering (CF) aims to produce recommendations based on other users' ratings to an item. Most existing CF methods rely on the overall ratings an item has received. However, these ratings alone sometimes cannot provide sufficient information to understand users' behaviors. For example, a user giving a high rating may indicate that he loves the item as a whole; however, it is still likely that he dislikes some particular aspects at the same time. In addition, users tend to place different emphases on different aspects when reaching an overall rating. This emphasis on aspects may even vary from users to items, and has a significant impact on a user's final decision. To make a better understanding of a user' behavior and generate a more accurate recommendation, we propose a framework that incorporates both user opinions and preferences on different aspects. This framework is composed of three components, namely, an opinion mining component, an aspect weighting computing component, and a rating inference component. The first component exploits opinion mining techniques to extract and summarize opinions on multiple aspects from reviews, and generates ratings on various aspects. The second component applies a tensor factorization strategy to automatically infer weights of different aspects in reaching an overall rating. The last one infers the overall rating of an item based on both aspect ratings and weights. Experiments on two real datasets prove that our model performs better compared with the baseline methods.

Aptamers are a kind of special nucleic acids that have the ability to bind various targets (e.g. small molecules, macromolecules, and cells) with high affinity and specificity. As a type of efficient recognition component in analytical designs and applications, aptamers have gained intense achievements in the designs of biosensors. Especially, the past few years have witnessed the fast development of electrochemical aptasensors. In this mini-review, we summarize recent progresses in electrochemical biosensors based on aptamers. Different targets and the corresponding detection principles are introduced. The methods to enhance detectable signals are mentioned including the employment of nanomaterials. Also, some possible limitations and future perspectives are discussed.

Hierarchical hollow nanostructured MnO 2 has been fabricated using polyaniline spheres as reactive templates. The reaction between KMnO 4 and polyaniline leads to the reduction of KMnO 4 into Mn 2+ ions that are further oxidized by excessive KMnO 4 into MnO 2 layers. Meanwhile, the polyaniline cores are over-oxidized and diffuse into the solution to form the cavity. The ratio of the KMnO 4 and polyaniline plays an important role in achieving the hollow structure via establishing a reasonable diffusion/reaction rate equilibrium. Owing to the unique nanostructure, the MnO 2 electrode exhibits a specific capacitance of 308 F g −1 at a current density of 0.2 A g −1 and maintains 91% capacitance value after 3000 cycles at a current density of 2 A g −1 . An asymmetric supercapacitor assembled by the hollow MnO 2 and activated carbon presents energy densities of 20.93∼7.23 W h kg −1 under the power densities of 180∼9000 W kg −1 and 24% capacitance fading is detected after 2000 cycles at a current density of 4 A g −1 .

A hemoglobin (Hb)-modified electrode based on chitosan/Fe3O4 nanocomposite coated glassy carbon has been constructed for trichloroacetic acid (TCA) detection. The structure of chitosan/Fe3O4 nanocomposite was investigated using energy-dispersive X-ray analysis (EDS) and X-ray diffraction (XRD) patterns. The electron transfer rate constant (k s) of Hb was estimated for as high as 3.12 s−1. The immobilized Hb exhibited excellent electro-catalytic activity toward the reduction of TCA. The response current regressed to the concentration of TCA within the range of 5.70 μM to 205 μM with a detection limit of 1.9 μM (S/N = 3).

Network embedding, also known as graph representation, is a classical topic in data mining. It has been widely used in real-world network applications such as node classification and community detection. However, it remains open to find a method that is scalable and preserves both structure and content information. Based on generative adversarial networks, we propose an unsupervised network embedding framework NEGAN, which is featured by combining graph topology and node content. In NEGAN, network nodes are mapped to the target space in a highly flexible non-linear way, guided by the content of the nodes. This mapping is learned from the generator of the generative adversarial networks, and node adjacency in the input network is preserved. Experiments on real datasets show that NEGAN outperforms all the existing methods on many scenarios including node classification, visualization and community detection tasks.

A fast segmentation algorithm of single medical image and sequence images based on active contour model are proposed in this paper. We give out the initial contour forecast segmentation model of 3D medical image first, and then, numerical solution of the image segmentation model algorithm is presented, send data blocks to different processors to do numerical calculations, finally combine the segmentation results. At the same time, parallel designing methods of node allocation, task allocation and load balancing methods are researched. The experiment results show that the parallel method can significantly improve the segmentation speed of 3D medical image.