Efficient Electromagnetic Wave Absorption and Thermal Infrared Stealth in PVTMS@MWCNT Nano-Aerogel via Abundant Nano-Sized Cavities and Attenuation Interfaces.

Pre-polymerized vinyl trimethoxy silane (PVTMS)@MWCNT nano-aerogel system was constructed via radical polymerization, sol-gel transition and supercritical CO2 drying. The fabricated organic-inorganic hybrid PVTMS@MWCNT aerogel structure shows nano-pore size (30-40 nm), high specific surface area (559 m2 g-1), high void fraction (91.7%) and enhanced mechanical property: (1) the nano-pore size is beneficial for efficiently blocking thermal conduction and thermal convection via Knudsen effect (beneficial for infrared (IR) stealth); (2) the heterogeneous interface was beneficial for IR reflection (beneficial for IR stealth) and MWCNT polarization loss (beneficial for electromagnetic wave (EMW) attenuation); (3) the high void fraction was beneficial for enhancing thermal insulation (beneficial for IR stealth) and EMW impedance match (beneficial for EMW attenuation). Guided by the above theoretical design strategy, PVTMS@MWCNT nano-aerogel shows superior EMW absorption property (cover all Ku-band) and thermal IR stealth property (ΔT reached 60.7 °C). Followed by a facial combination of the above nano-aerogel with graphene film of high electrical conductivity, an extremely high electromagnetic interference shielding material (66.5 dB, 2.06 mm thickness) with superior absorption performance of an average absorption-to-reflection (A/R) coefficient ratio of 25.4 and a low reflection bandwidth of 4.1 GHz (A/R ratio more than 10) was experimentally obtained in this work.

Salt-Induced Coil-Globule Transition of Sulfonate-Modified HPAM is Affected by the Branched Chain Length.

Polymer flooding is a cheap and efficient method for tertiary oil recovery. However, the failure of partially hydrolyzed polyacrylamide (HPAM) molecules reduces the oil displacement efficiency under high salinity conditions. In this study, we modified HPAM molecules by sulfonic acid groups with different branched chain lengths, and we characterized the structures of these molecules in different salinity solutions through all-atoms molecular dynamics simulation. Compared with the acrylic group, the sulfonate group has excellent salt resistance because of its weak ability to attract cations. When using different lengths of branched linked branch sulfonates, increasing the length of the branched chain can improve the movement ability of sulfonates, so as to play a better salt resistance effect. However, excessive growth of branched chains can cause their association with each other and can lead to polymer folding. Therefore, we believe that the branched chain length of sulfonate should be moderately increased. These results are expected to provide theoretical support for the design and use of salt-resistant polymers..

Pulsed-lighting LED luminaire for agriculture with a geometrical optical solution.

Light-emitting diodes (LEDs) are the 4th plant supplemental lighting source. Pulsed lighting is benefit to increase energy utilization efficiency in greenhouse production. A pulsed-lighting LED luminaire with geometrical optical solution is proposed to overcome the shortcoming with pulse width modulation (PWM) solution. In addition, this luminaire also achieves uniform lighting by designing optical surfaces. In the illumination area, the lighting frequency is 117.6 Hz and the illuminance uniformity is 0.789, which is better than 0.75 (+/- 12.5%). In an actual planting experiment of Brassica chinensis, the average fresh weight of the plants under the pulsed-lighting LED luminaire was 33.1% higher than that under the conventional LED luminaire. The results showed that the energy utilization efficiency of the pulsed-lighting LED luminaire is 22.9% higher than that of the conventional LED luminaire.

Effects of Background Fitting of e-Commerce Live Streaming on Consumers' Purchase Intentions: A Cognitive-Affective Perspective.

Purpose: The purpose of this paper is to explore the effects of the background fitting of e-commerce live streaming on consumers' purchase intentions and the relevant internal psychological mechanism from the cognitive-affective perspective. Methods: In this study, a theoretical framework model of SOR comprising six variables is established. SPSS and SmartPLS are used to test the model and analyze data collected from a comprehensive questionnaire survey of 424 Chinese online consumers. Results: Results demonstrate that the impact of background fitting in e-commerce live streaming on consumers' purchase intentions can be divided into three stages. In the first stage, background fitting (comprised of both product-background fit and anchor-background fit) positively affect consumer cognitive process (perceived trust and perceived value). Perceived trust is mainly affected by anchor-background fit, while perceived value is mainly affected by product-background fit. In the second stage, consumers' cognitive process subsequently affects their affective process (perceived pleasure). Perceived value also has a greater positive effect on consumers' perceived pleasure than perceived trust, although perceived trust is a prerequisite for improving perceived value. In the third stage, the affective process further promotes consumers' purchase intentions. Conclusion: Combining both SOR theory and cognitive-affective perspective, this study reveals that the internal influence mechanism of background fitting in e-commerce live streaming on consumers' purchase intentions is divided into three stages. Theoretically, this study not only expands the application of SOR theory in the research field of e-commerce live streaming from the perspective of external background stimulation, but also importantly contributes to the application of cognitive-emotional perspective in e-commerce live streaming. Practically, the study suggests optimizing background fitting as an effective way to improve consumer purchase intention in e-commerce live streaming, and it is better to optimize background fitting from the perspective of improving perceived trust, perceived value, and perceived pleasure.

Genetic diversity of the cultivated Salvia miltiorrhiza populations revealed by four intergenic spacers.

For better understanding the genetic diversity and phylogeny of the cultivated Salvia miltiorrhiza populations, four intergenic spacer sequences, ETS, psbA-trnH, trnL-trnF, and ycf1-rps15 of the 40 populations collected from China were Polymerase Chain Reaction (PCR) amplified, analyzed both individually and in combination. Haplotype diversity analysis showed that the cultivated S. miltiorrhiza populations had a very rich genetic diversity and an excellent capacity to resist environmental pressure. The best-fit nucleotide substitution models for ETS, psbA-trnH, trnL-trnF, ycf1-rps15, and their combined sequences were HKY+I, T92, T92, T92+G, and T92+G, respectively; the nucleotide conversion frequency in the combined sequences was lower than the transversion, and the relatively high nucleotide substitution frequencies suggests its high genetic variability. Neutral tests showed that the spacer sequences of the populations conform with the neutral evolution model, and there has been no current expansion events occurred. Phylogeny analyses based on both the individual and the combined sequences showed that the 40 populations were clustered in two clades with a very similar topological structure. The discrimination rate of the combined sequence marker is significantly increased to 52.5% (21 populations) over the highest 35% (13 populations) by the single marker of ETS, though still inadequate but a big step forward. Further exploration of more DNA markers is needed. This study for the first time revealed the rich genetic diversity and phylogeny of the currently cultivated S. miltiorrhiza populations in China and provides novel alternative molecular markers for the genetic identification and resources evaluation of the cultivated S. miltiorrhiza populations.

I2F: A Unified Image-to-Feature Approach for Domain Adaptive Semantic Segmentation.

Unsupervised domain adaptation (UDA) for semantic segmentation is a promising task freeing people from heavy annotation work. However, domain discrepancies in low-level image statistics and high-level contexts compromise the segmentation performance over the target domain. A key idea to tackle this problem is to perform both image-level and feature-level adaptation jointly. Unfortunately, there is a lack of such unified approaches for UDA tasks in the existing literature. This paper proposes a novel UDA pipeline for semantic segmentation that unifies image-level and feature-level adaptation. Concretely, for image-level domain shifts, we propose a global photometric alignment module and a global texture alignment module that align images in the source and target domains in terms of image-level properties. For feature-level domain shifts, we perform global manifold alignment by projecting pixel features from both domains onto the feature manifold of the source domain; and we further regularize category centers in the source domain through a category-oriented triplet loss, and perform target domain consistency regularization over augmented target domain images. Experimental results demonstrate that our pipeline significantly outperforms previous methods. In the commonly tested GTA5 →Cityscapes task, our proposed method using Deeplab V3+ as the backbone surpasses previous SOTA by 8%, achieving 58.2% in mIoU.

Defocus Image Deblurring Network With Defocus Map Estimation as Auxiliary Task.

Different from the object motion blur, the defocus blur is caused by the limitation of the cameras' depth of field. The defocus amount can be characterized by the parameter of point spread function and thus forms a defocus map. In this paper, we propose a new network architecture called Defocus Image Deblurring Auxiliary Learning Net (DID-ANet), which is specifically designed for single image defocus deblurring by using defocus map estimation as auxiliary task to improve the deblurring result. To facilitate the training of the network, we build a novel and large-scale dataset for single image defocus deblurring, which contains the defocus images, the defocus maps and the all-sharp images. To the best of our knowledge, the new dataset is the first large-scale defocus deblurring dataset for training deep networks. Moreover, the experimental results demonstrate that the proposed DID-ANet outperforms the state-of-the-art methods for both tasks of defocus image deblurring and defocus map estimation, both quantitatively and qualitatively. The dataset, code, and model is available on GitHub: https://github.com/xytmhy/DID-ANet-Defocus-Deblurring.

Synergistic Manipulation of Zero-Dimension and One-Dimension Hybrid Nanofillers in Multi-Layer Two-Dimension Thin Films to Construct Light Weight Electromagnetic Interference Material.

Nanocomposite foam with a large expansion ratio and thin cell walls is promising for electromagnetic interference (EMI) shielding materials, due to the low electromagnetic (EM) reflection and high EM absorption. To overcome the dimensional limitation from two-dimension (2D) thin walls on the construction of conductive network, a strategy combining hybrid conductive nanofillers in semi-crystalline matrix together with supercritical CO2 (scCO2) foaming was applied: (1) one-dimension (1D) CNTs with moderate aspect ratio was used to minimize the dimensional confinement from 2D thin walls while constructing the main EM absorbing network; (2) zero-dimension (0D) carbon black (CB) with no dimensional confinement was used to connect the separated CNTs in thin walls and to expand the EM absorbing network; (3) scCO2 foaming was applied to obtain a cellular structure with multi-layer thin walls and a large amount of air cells to reduce the reflected EM; (4) semi-crystalline polymer was selected so that the rheological behavior could be adjusted by optimizing crystallization and filler content to regulate the cellular structure. Consequently, an advanced material featured as lightweight, high EM absorption and low EM reflection was obtained at 0.48 vol.% hybrid nanofillers and a density of 0.067 g/cm3, whose specific EMI shielding performance was 183 dB cm3/g.

Fiber-optic distributed acoustic sensor utilizing LiNbO3 straight through waveguide phase modulator.

A novel fiber-optic distributed acoustic sensor (DAS) utilizing a LiNbO3 straight through waveguide phase modulator as phase generation carrier (PGC) modulation module for the detection of acoustic signal is presented. The sensitive principle and the phase demodulation method of the system based on phase-sensitive optical time domain reflectometer (Φ-OTDR) are described. This scheme solves the problems of low modulation frequency and unstable performance of piezoelectric transducer (PZT) in the traditional homodyne detection system and depends only on the pulse repetition frequency. The efficacy of the new approach is demonstrated experimentally, showing that the weak acoustic signal can be demodulated accurately. The noise level of the system is < 4.2×10-3 rad/√Hz, the signal to noise ratio (SNR) is > 16 dB, and the spatial resolution is 10 m, as well as a detection frequency can theoretically achieve 25 kHz at 2 km sensing fiber. It provides a new research idea for DAS and is expected to replace PZT to achieve a high-frequency response, which has good potential in the applications of low cost, long distance and high frequency detection.

New HIV diagnoses in patients with COVID-19: two case reports and a brief literature review.

BACKGROUND: COVID-19 is novel infectious disease with an evolving understanding of its epidemiology and clinical manifestations. Severe cases developed life-threatening complications, such as respiratory failure, shock, and multiple organs dysfunction. Immunocompromised patients often present atypical presentations of viral infected diseases. CASE PRESENTATION: We report newly diagnosed HIV infections in two patients with COVID-19 in China. In our two cases, both patients with elevated IL-6 received Tocilizumab treatment, but did not present obvious therapeutic effect. CONCLUSIONS: These cases highlight possible co-detection of known immunocompromised diseases such as HIV. The two cases we reported stressed the risk of misdiagnosis, especially during the pandemic of an infectious disease and the importance of extended testing even if in immune-compromised condition the immune state may be ignored.

An α-Matte Boundary Defocus Model-Based Cascaded Network for Multi-focus Image Fusion.

Capturing an all-in-focus image with a single camera is difficult since the depth of field of the camera is usually limited. An alternative method to obtain the all-in-focus image is to fuse several images that are focused at different depths. However, existing multi-focus image fusion methods cannot obtain clear results for areas near the focused/defocused boundary (FDB). In this paper, a novel α-matte boundary defocus model is proposed to generate realistic training data with the defocus spread effect precisely modeled, especially for areas near the FDB. Based on this α-matte defocus model and the generated data, a cascaded boundary-aware convolutional network termed MMF-Net is proposed and trained, aiming to achieve clearer fusion results around the FDB. Specifically, the MMF-Net consists of two cascaded subnets for initial fusion and boundary fusion. These two subnets are designed to first obtain a guidance map of FDB and then refine the fusion near the FDB. Experiments demonstrate that with the help of the new α-matte boundary defocus model, the proposed MMF-Net outperforms the state-of-the-art methods both qualitatively and quantitatively.

Solution structure of TbUfm1 from Trypanosoma brucei and its binding to TbUba5.

Ubiquitin-like proteins are conserved in eukaryotes and involved in numerous cellular processes. Ufm1 is proved to play important roles in endoplasmic reticulum homeostasis, vesicle transportation and embryonic development. Enzyme cascade of Ufm1 is similar to that of ubiquitin. Mature Ufm1 is activated and conjugated to substrates by assistance of Ufm1 activating enzyme Uba5 (E1), Ufm1 conjugating enzyme Ufc1 (E2), and Ufm1 ligating enzyme Ufl1 (E3). Here, we determined the solution structure of TbUfm1 from Trypanosoma brucei (T. brucei) by NMR spectroscopy and explored the interactions between TbUfm1 and TbUba5/TbUfc1/TbUfl1. TbUfm1 adopts a typical ß-grasp fold, which partially wraps a central α-helix and the other two helixes. NMR chemical shift perturbation indicated that TbUfm1 interacts with TbUba5 via a hydrophobic pocket formed by α1α2ß1ß2. Although the structure and Uba5-interaction mode of TbUfm1 are conserved in Ufm1 proteins, there are also some differences, which might reflect the potential diversity of Ufm1 in evolution and biological functions.

Trypanosoma brucei centrin5 is enriched in the flagellum and interacts with other centrins in a calcium-dependent manner.

Centrin is an evolutionarily conserved EF-hand-containing protein, which is present in eukaryotic organisms as diverse as algae, yeast, and humans. Centrins are associated with the microtubule-organizing center and with centrosome-related structures, such as basal bodies in flagellar and ciliated cells, and the spindle pole body in yeast. Five centrin genes have been identified in Trypanosoma brucei (T. brucei), a protozoan parasite that causes sleeping sickness in humans and nagana in cattle in sub-Saharan Africa. In the present study, we identified that centrin5 of T. brucei (TbCentrin5) is localized throughout the cytosol and nucleus and enriched in the flagellum. We further identified that TbCentrin5 binds Ca2+ ions with a high affinity and constructed a model of TbCentrin5 bound by Ca2+ ions. Meanwhile, we observed that TbCentrin5 interacts with TbCentrin1, TbCentrin3, and TbCentrin4 and that the interactions are Ca2+ -dependent, suggesting that TbCentrin5 is able to form different complexes with other TbCentrins to participate in relevant cellular processes. Our study provides a foundation for better understanding of the biological roles of TbCentrin5.

Automatic Color Sketch Generation Using Deep Style Transfer.

Recent advances in deep learning based algorithms have made it feasible to transfer image styles from an example image to other images. However, it is still hard to transfer the style of color sketches due to their unique texture statistics. In this paper, an automatic color sketch generation system is developed from existing real-time style transfer methods. We choose a suitable image from a set of carefully selected color sketch examples as the style target for every content image during training. We also propose a novel style transfer convolutional neural network with spatial refinement to realize high-resolution style transfer. Finally, gouache color is introduced to the generated images via a linear color transform followed by a guided filtering operation. Experimental results illustrate that our system can produce vivid color sketch images and greatly reduce artifacts compared to previous state-of-the-art methods.