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Pigments are often used in water borne barrier coatings but tend to make the coatings prone to failure. The pigment properties effects on this issue is lacking in literature. In this work, coatings that used pigments with different moduli but with similar size and aspect ratio were characterized in terms of water vapor resistance before and after folding. Coatings with talc had better water vapor resistance than coatings with similar sized kaolin. Talc also limited the degradation of barrier properties when folded. Coatings with metalized poly(ethylene terephthalate) (PET) flakes had better failure resistance than coatings with similarly sized rigid mica. Both results are likely caused by the ability of the low modulus pigment to deform and allow for strain to occur in the pigment as well as the latex phase. Styrene-butadiene (SB) and natural rubber (NR) latex coatings had a better failure resistance than styrene-acrylate (SA) latex, which is likely due to their low glass transition temperatures and high strain-to-failure values. However, coatings with high amounts of SB or NR latex may lead to blocking issues in production. Adding kaolin into SA and SB latex mixtures resulted in improved water vapor barrier property and failure resistance. [ABSTRACT FROM AUTHOR]

Purpose: Medical image segmentation is critical for many medical image analysis applications. 3D convolutional neural networks (CNNs) have been widely adopted in the segmentation of volumetric medical images. The recent development of channelwise and spatialwise attentions achieves the state‐of‐the‐art feature representation performance. However, these attention strategies have not explicitly modeled interdependencies among slices in 3D medical volumes. In this work, we propose a novel attention module called progressive attention module (PAM) to explicitly model the slicewise importance for 3D medical image analysis. Methods: The proposed method is composed of three parts: Slice Attention (SA) block, Key‐Slice‐Selection (KSS) block, and Channel Attention (CA) block. First, the SA is a novel attention block to explore the correlation among slices for 3D medical image segmentation. SA is designed to explicitly reweight the importance of each slice in the 3D medical image scan. Second, the KSS block, cooperating with the SA block, is designed to adaptively emphasize the critical slice features while suppressing the irrelevant slice features, which helps the model focus on the slices with rich structural and contextual information. Finally, the CA block receives the output of KSS as input for further feature recalibration. Our proposed PAM organically combines SA, KSS, and CA, progressively highlights the key slices containing rich information for the relevant tasks while suppressing those irrelevant slices. Results: To demonstrate the effectiveness of PAM, we embed it into 3D CNNs architectures and evaluate the segmentation performance on three public challenging data sets: BraTS 2018 data set, MALC data set, and HVSMR data set. We achieve 80.34%, 88.98%, and 84.43% of the Dice similarity coefficient on these three data sets, respectively. Experimental results show that the proposed PAM not only boosts the segmentation accuracy of the standard 3D CNNs methods consistently, but also outperforms the other attention mechanisms with slight extra costs. Conclusions: We propose a new PAM to identify the most informative slices and recalibrate channelwise feature responses for volumetric medical image segmentation. The proposed method is evaluated on three public data sets, and the results show improvements over other methods. This proposed technique can effectively assist physicians in many medical image analysis. It is also anticipated to be generalizable and transferable to assist physicians in a wider range of medical imaging applications to produce greater value and impact to health. [ABSTRACT FROM AUTHOR]

This paper proposes an interactive image-segmentation method which is based on superpixel. To achieve fast segmentation, the method is used to establish a Graphcut model using superpixels as nodes, and a new energy function is proposed. Experimental results demonstrate that the authors’ method has excellent performance in terms of segmentation accuracy and computation efficiency compared with other segmentation algorithm based on pixels.

Ubiquitous in nature, Aspergillus rarely invades the brain to induce infection in general. However, in clinical practice, some patients with hematological malignancies or immunosuppression may suffer from Aspergillus infection of the central nervous system, which arises most commonly as a result of hematogenous dissemination from a pulmonary focus or direct extension from the paranasal sinus infection. Treatment is clinically challenging and the mortality rate is relatively high. Recently, a case diagnosed with acute lymphocytic leukemia was admitted to the Department of Neurosurgery, The First People's Hospital of Huzhou (First Affiliated Hospital of Huzhou University, Huzhou, China). During chemotherapy, space-occupying lesions were observed in the right occipital lobe of the patient, and lesion progression was captured. After treatment with surgery, an analysis of specimens collected from the patient was performed and was suggestive of Aspergillus infection. Following the symptomatic therapy with voriconazole, the patient's disease prognosis was favorable. The focus of infection due to pulmonary aspergillosis or Aspergillus sinusitis was not detected in the patient and the focus was not a common site of hematogenous infection. In addition, the patient exhibited no obvious clinical symptoms. In view of the above observations, the possibility of hospital-acquired infection was considered, to which clinicians should be alert. [ABSTRACT FROM AUTHOR]

A hybrid cyanate ester resin containing polysilazane was prepared via the prepolymerization of bisphenol-A dicyanate ester monomer (BADCy) in the presence of polysilazane (PSZ) under low temperature conditions in a short period of time. Fourier transform-infrared (FT-IR) spectroscopy and nuclear magnetic resonance (NMR) spectroscopy reveal that the polymerization reaction of BADCy can be carried out in the presence of PSZ to obtain a hybrid resin below 100°C and polymethylsilazane (PHS) exhibits an improved prepolymerization effect when compared to polydimethylsilazane (PMS). FT-IR spectroscopy and gel permeation chromatography (GPC) showed that the prepolymerization degree of the PHS/BADCy resin increased upon increasing PHS mass fraction from 0 to 12 wt%, polymerization temperature from 60 to 100°C and polymerization time from 0 to 4 h. The PHS/BADCy hybrid resins samples were prepared and their process properties were investigated by rheometry and Differential scanning calorimetry (DSC). The results indicated that their viscosity was <10 Pa.s in the temperature range of 60–130°C, and the initial curing temperature and curing exothermic enthalpy were 121.9°C and 358.9 J/g, respectively. Furthermore, the cured PHS/BADCy resin possesses excellent thermal and mechanical properties, the 5% weight loss temperature (Td5) and glass transition temperature (Tg) were 424–441°C and 273–282°C, respectively. The cured PHS/BADCy resin with 4 wt% PHS showed the highest flexural strength of 146 MPa and flexural modulus of 4.1 GPa. [ABSTRACT FROM AUTHOR]

Cooperative localization has emerged as an appealing technology since it can improve the localization performance without any infrastructure change compared with non-cooperative localization. However, some well-localized agents may not be willing to sacrifice additional power to improve the others’ localization accuracy. This paper proposes an incentive mechanism from an economic perspective for cooperative localization, whereby a pricing scheme is designed to lead each agent to the optimal state. A game-theoretic algorithm is proposed where each player (agent) can obtain the optimal budget strategy to minimize its individual utility. To make profits in the game, the relationship between the agent's network condition and its budget strategy is derived. Furthermore, a fairness-aware price allocation rule (PAR) is developed to distribute the budget among the reference agents proportional to each node's contribution. Analytical and numerical results show that agents with better network conditions are more likely to join the cooperation under the proposed incentive mechanism, leading to an improved localization performance. [ABSTRACT FROM AUTHOR]

Silicon‐containing arylacetylene resins (PSAs) can be used in high temperature environment due to their excellent thermal stability. However, their high temperature oxidation is still bottle‐neck for further application. Herein, Materials Genome Initiative (MGI) was utilized to identify a target monomer, 3,6‐diethynylcarbazole (DEC), to design new PSAs with enhanced antioxidant properties and heat resistance. After incorporation of DEC, the thermal curing behavior observed using differential scanning calorimetry (DSC), fourier transform infrared (FTIR) and thermogravimetric analysis (TGA) revealed that obtained silicon‐containing carbazolylacetylene resins (PSA‐VBC) can exhibit hydroamination reaction to decrease the initial curing temperature. And the temperature at 5% weight loss (Td5) occurred in cured copolymers ranged from 665°C to 691°C, which showed excellent heat resistance. Moreover, the oxidation behavior of cured resins was investigated by thermogravimetric/derivative thermogravimetry (TG/DTG), X‐ray photoelectron spectroscopy (XPS) and scanning electron microscope (SEM). Upon the incorporation of DEC, the thermal oxidation decomposition temperature of PSA‐VBC were 100°C higher than those observed for PSAs, which also proved by XPS analysis results that the oxygen content of PSA‐VBC solidified oxide was lower than that of PSAs. In addition, the surface morphology of cured PSA‐VBC resins still maintained integrity after oxidation at 400°C for 2 hr, which showed excellent oxidation resistance. [ABSTRACT FROM AUTHOR]