Highlights BAI score of respondents here is higher than those in previous studies with Chinese. Quarantined people presented the highest BAI score and incidence of anxiety. People in high epidemic area showed higher BAI score and incidence of anxiety. All factors impacted respondents’ anxiety level significantly, except gender.

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In this paper, we propose a partition-masked Convolution Neural Network (CNN) to achieve compressed-video enhancement for the state-of-the-art coding standard, High Efficiency Video Coding (HECV). More precisely, our method utilizes the partition information produced by the encoder to guide the quality enhancement process. In contrast to existing CNN-based approaches, which only take the decoded frame as the input to the CNN, the proposed approach considers the coding unit (CU) size information and combines it with the distorted decoded frame such that the degradation introduced by HEVC is reduced more efficiently. Experimental results show that our approach leads to over 9.76% BD-rate saving on benchmark sequences, which achieves the state-of-the-art performance.

BackgroundDeep vein thrombosis (DVT) is a common but elusive illness that can result in long-term disability or death. Accurate detection of thrombosis and assessment of its size and distribution are critical for treatment decision-making. In the present study, we sought to develop and evaluate a cardiovascular magnetic resonance (CMR) black-blood thrombus imaging (BTI) technique, based on delay alternating with nutation for tailored excitation black-blood preparation and variable flip angle turbo-spin-echo readout, for the diagnosis of non-acute DVT.MethodsThis prospective study was approved by institutional review board and informed consent obtained from all subjects. BTI was first conducted in 11 healthy subjects for parameter optimization and then conducted in 18 non-acute DVT patients to evaluate its diagnostic performance. Two clinically used CMR techniques, contrast-enhanced CMR venography (CE-MRV) and three dimensional magnetization prepared rapid acquisition gradient echo (MPRAGE), were also conducted in all patients for comparison. All images obtained from patients were analyzed on a per-segment basis. Using the consensus diagnosis of CE-MRV as the reference, the sensitivity (SE), specificity (SP), positive and negative predictive values (PPV and NPV), and accuracy (ACC) of BTI and MPRAGE as well as their diagnostic agreement with CE-MRV were calculated. Besides, diagnostic confidence and interreader diagnostic agreement were evaluated for all three techniques.ResultsBTI with optimized parameters effectively nulled the venous blood flow signal and allowed directly visualizing the thrombus within the black-blood lumen. Higher SE (90.4% vs 67.6%), SP (99.0% vs. 97.4%), PPV (95.4% vs. 85.6%), NPV (97.8% vs 92.9%) and ACC (97.4% vs. 91.8%) were obtained by BTI in comparison with MPRAGE. Good diagnostic confidence and excellent diagnostic and interreader agreements were achieved by BTI, which were superior to MPRAGE on detecting the chronic thrombus.ConclusionBTI allows direct visualization of non-acute DVT within the dark venous lumen and has the potential to be a reliable diagnostic tool without the use of contrast medium.

Nanocomposites have been shown to significantly reduce the peak heat release rate, as measured by cone calorimetry, for many polymers but they typically have no effect on the oxygen index or the UL-94 classification. In this review, we will cover what is known about the processes by which nanocomposite formation may bring this about. Montmorillonite will be the focus in this paper but attention will also be devoted to other materials, including carbon nanotubes and layered double hydroxides. A second section will be devoted to combinations of nanocomposite formation with conventional (and unconventional) fire retardants. The paper will conclude with a section attempting to forecast the future.

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Polypropylene (PP)/organically‐modified layered double hydroxides (LDH) and PP/organo‐LDH/zinc borate (BZn) (nano)composites were prepared by the melt blending method. The structures and morphologies of (nano)composites were characterized by X‐ray diffraction and TEM. The flammability properties and thermal stability were studied using TGA, cone calorimeter, limiting oxygen index (LOI), and the UL94 protocol. The basal spacing of organo‐LDH increases to 3.89 nm from 0.76 nm in pristine LDH. When 10% of the organo‐LDH was melt blended with PP, the basal spacing of the LDH increases to 4.01 nm. The onset temperature and thermal decomposition temperature of the PP/organo‐LDH and PP/organo‐LDH/zinc borate (nano)composites have no significant change compared to pristine PP, but the amount of non‐volatile residue remaining at 600°C is significantly higher than that in pure PP. The cone calorimetric results show a 38% reduction in the peak heat release rate for PP/10%BZn and 48, 50 and 63% reductions for PP/organo‐LDH/10%BZn (nano)composites at 3, 5 and 10% organo‐LDH loading. The limiting oxygen indices of all samples increase by a slight amount and all samples can obtain a UL‐94 HB rating. The char content of PP/LDH/BZn and PP/BZn/organo‐LDH (nano)composites is much greater than that of PP/LDH, PP/BZn and PP/organo‐LDH. Copyright © 2011 John Wiley & Sons, Ltd.

What are the novel findings of this work?In this study, we developed and validated an artificial intelligence system, the Prenatal ultrasound diagnosis Artificial Intelligence Conduct System (PAICS), to detect nine specific intracranial-malformation patterns in standard sonographic reference planes of the fetal central nervous system (CNS). The PAICS achieved excellent performance on both internal and external validation, with accuracy comparable to that of expert sonologists, while requiring significantly less time. What are the clinical implications of this work?The PAICS is a real-time artificial intelligence-aided image recognition system capable of detecting fetal intracranial malformations. This fast, accurate algorithm has the potential to be an effective and efficient tool in screening for congenital CNS malformations. It should be particularly useful in community hospitals, which often lack imaging expertise.