•The novel coronavirus (COVID-19) pneumonia has caused 355 confirmed cases on the Diamond Princess cruise ship as of February 16, 2020.•We estimated that the Maximum-Likelihood (ML) value of ...reproductive number (R0) was 2.28 for COVID-19 outbreak at the early stage on the ship.•If R0 value was reduced by 25% and 50%, the estimated total number of cumulative cases would be reduced from 1296 (1145–1452) to 874 (780–978) and 573 (512–644) as of February 26, 2020, respectively.
Up to February 16, 2020, 355 cases have been confirmed as having COVID-19 infection on the Diamond Princess cruise ship. It is of crucial importance to estimate the reproductive number (R0) of the novel virus in the early stage of outbreak and make a prediction of daily new cases on the ship.
We fitted the reported serial interval (mean and standard deviation) with a gamma distribution and applied “earlyR” package in R to estimate the R0 in the early stage of COVID-19 outbreak. We applied “projections” package in R to simulate the plausible cumulative epidemic trajectories and future daily incidence by fitting the data of existing daily incidence, a serial interval distribution, and the estimated R0 into a model based on the assumption that daily incidence obeys approximately Poisson distribution determined by daily infectiousness.
The Maximum-Likelihood (ML) value of R0 was 2.28 for COVID-19 outbreak at the early stage on the ship. The median with 95% confidence interval (CI) of R0 values was 2.28 (2.06–2.52) estimated by the bootstrap resampling method. The probable number of new cases for the next ten days would gradually increase, and the estimated cumulative cases would reach 1514 (1384–1656) at the tenth day in the future. However, if R0 value was reduced by 25% and 50%, the estimated total number of cumulative cases would be reduced to 1081 (981–1177) and 758 (697–817), respectively.
The median with 95% CI of R0 of COVID-19 was about 2.28 (2.06–2.52) during the early stage experienced on the Diamond Princess cruise ship. The future daily incidence and probable outbreak size is largely dependent on the change of R0. Unless strict infection management and control are taken, our findings indicate the potential of COVID-19 to cause greater outbreak on the ship.
We report the development of a highly sensitive ratiometric fluorescent lateral flow immunoassay (RFLFIA) strip for rapid and accurate detection of acute myocardial infarction biomarker, namely ...heart‐type fatty acid binding protein (H‐FABP). The RFLFIA strip works in terms of ratiometric change of fluorescence signal, arising from blending of fluorescence emitted by two composite nanostructures conjugated to capture and probe antibodies and inner filter effect of gold nanoparticles. In conjunction with using custom smartphone‐based analytical device and tonality analysis, quantitative detection of H‐FABP was achieved with a low limit of detection at 0.21 ng mL−1. The RFLFIA strip can generate a visually distinguishable green‐to‐red color change around the threshold concentration of H‐FABP (6.2 ng mL−1), thus allowing the semi‐quantitative diagnosis by the naked eye.
Ratiometric fluorescent lateral flow immunoassay is achieved by inner filter effect‐mediated double‐signal‐reverse change, which not only enables highly sensitive quantitative analysis by combing with the smartphone platform, but also allows the visual readout of H‐FABP concentration by the naked eye. The developed strip can be used for rapid and accurate point‐of‐care testing of acute myocardial infarction.
Topological insulator (TI), a promising quantum and semiconductor material, has gapless surface state and narrow bulk band gap. Firstly, the properties, classifications and compounds of TI are ...introduced. Secondly, the preparation and doping of TI are assessed. Some results are listed. (1) Although various preparation methods are used to improve the crystal quality of the TI, it cannot reach the industrialization. Fermi level regulation still faces challenges; (2) The carrier type and lattice of TI are affected by non-magnetic impurities. The most promising property is the superconductivity at low temperature; (3) Magnetic impurities can destroy the time-reversal symmetry of the TI surface, which opens the band gap on the TI surface resulting in some novel physical effects such as quantum anomalous Hall effect (QAHE). Thirdly, this paper summarizes various applications of TI including photodetector, magnetic device, field-effect transistor (FET), laser, and so on. Furthermore, many of their parameters are compared based on TI and some common materials. It is found that TI-based devices exhibit excellent performance, but some parameters such as signal to noise ratio (S/N) are still lower than other materials. Finally, its advantages, challenges and future prospects are discussed. Overall, this paper provides an opportunity to improve crystal quality, doping regulation and application of TI.
Gas sensors are devices that convert a gas volume fraction into electrical signals, and they are widely used in many fields such as environmental monitoring. Graphene is a new type of two-dimensional ...crystal material that has many excellent properties including large specific surface area, high conductivity, and high Young’s modulus. These features make it ideally suitable for application for gas sensors. In this paper, the main characteristics of gas sensor are firstly introduced, followed by the preparation methods and properties of graphene. In addition, the development process and the state of graphene gas sensors are introduced emphatically in terms of structure and performance of the sensor. The emergence of new candidates including graphene, polymer and metal/metal oxide composite enhances the performance of gas detection significantly. Finally, the clear direction of graphene gas sensors for the future is provided according to the latest research results and trends. It provides direction and ideas for future research.
Graphene, having a perfect two-dimensional crystal structure, has many excellent features such as a high specific surface area, and extraordinary electrical, thermal and mechanical properties. ...However, during the production process, lattice defects will inevitably be produced. Therefore, the performance of graphene with various defects is much lower than its theoretical value. We summarize the major advances of research into graphene defects in engineering in this paper. Firstly, the main types and causes of defects in graphene are introduced. Secondly, the influence of different defects in graphene on the chemical, electronic, magnetic and mechanical properties is discussed. Also, the control methods of graphene defects are reviewed. Finally, we propose the future challenges and prospects for the study of the defects of graphene and other nano-carbon materials.
Hyperspectral image with high dimensionality always increases the computational consumption, which challenges image processing. Deep learning models have achieved extraordinary success in various ...image processing domains, which are effective to improve classification performance. There remain considerable challenges in fully extracting abundant spectral information, such as the combination of spatial and spectral information. In this article, a novel unsupervised hyperspectral feature extraction architecture based on spatial revising variational autoencoder (AE) (<inline-formula> <tex-math notation="LaTeX">U_{\text {Hfe}}\text {SRVAE} </tex-math></inline-formula>) is proposed. The core concept of this method is extracting spatial features via designed networks from multiple aspects for the revision of the obtained spectral features. Multilayer encoder extracts spectral features, and then, latent space vectors are generated from the obtained means and standard deviations. Spatial features based on local sensing and sequential sensing are extracted using multilayer convolutional neural networks and long short-term memory networks, respectively, which can revise the obtained mean vectors. Besides, the proposed loss function guarantees the consistency of the probability distributions of various latent spatial features, which obtained from the same neighbor region. Several experiments are conducted on three publicly available hyperspectral data sets, and the experimental results show that <inline-formula> <tex-math notation="LaTeX">U_{\text {Hfe}}\text {SRVAE} </tex-math></inline-formula> achieves better classification results compared with comparison methods. The combination of spatial feature extraction models and deep AE models is designed based on the unique characteristics of hyperspectral images, which contributes to the performance of this method.
Inflammation recently has been considered to be participated in the pathogenesis of major depressive disorder (MDD). However, the detailed mechanism of inflammation in depression has not been ...completely understood yet. In the present study, depression mice model was established by chronic social defeat stress (CSDS) method and confirmed by behavior examinations including forced swimming test and sucrose preference test. The decrease of spine density and postsynaptic density protein 95 (PSD95) in hippocampus further verified the depression model. Then, the microglia polarization state and endoplasmic reticulum (ER) stress were investigated. At transcriptional level, M1 marker (inducible nitric oxide synthase (iNOS), CD16, CD86, CXCL10) in CSDS mice was higher than that in control group while there was no difference in M2 marker (Arginase and CD206) between two groups. And it was observed in the hippocampus of CSDS induced depression mice that increased activated microglia was merged with iNOS instead of arginase by immunofluorescence staining. Furthermore, the M1 marker Interleukin (IL)-1β and tumor necrosis factor (TNF)-α were increased in depression mice while the M1 marker IL-6 and M2 marker IL-10 remained unchanged. The expression of ER stress signaling factors, including protein kinase RNA-like ER kinase (PERK), Phosphorylated α-subunit of eukaryotic translation initiation factor 2(p-eIF2α), C/EBP homologous protein (CHOP), and X-box binding protein 1(XBP1) were significantly higher in CSDS-induced depression mice than in control mice. In all, our results suggest that M1 polarization and ER stress play a vital role in MDD pathogenesis.
Inspired by the framework of the rolling guidance filter (RGF), a novel improved RGF for synthetic aperture radar (SAR) images is proposed in this letter, named SAR‐IRGF. Based on the model of ...additive noise, the RGF has the complete control of detailed smoothing under a scale measure for optical images. However, the speckle is well known as a multiplicative noise, which invalidates the RGF for SAR images. In this letter, an appropriate edge guidance is utilized to optimize the RGF for SAR image denoising. Compared with the original version, better convergence is achieved. Experimental results on natural Ku‐band airborne SAR images show that the proposed SAR‐IRGF reduces more speckle while sharpening the edges effectively. Simultaneously, the SAR‐IRGF demonstrates a significant nearly 5.5‐fold improvement than RGF in the equivalent number of looks (ENL).
A multi-exposure imaging approach proposed in earlier studies is used to increase star sensors’ attitude update rate by N times. Unfortunately, serious noises are also introduced in the star image ...due to multiple exposures. Therefore, a star centroid extraction method based on Kalman Filter is proposed in this paper. Firstly, star point prediction windows are generated based on centroids’ kinematic model. Secondly, the classic centroid method is used to calculate the coarse centroids of the star points within the prediction windows. Lastly, the coarse centroids are, respectively, processed by each Kalman Filter to filter image noises, and thus fine centroids are obtained. Simulations are conducted to verify the Kalman-Filter-based estimation model. Under noises with zero mean and ±0.4, ±1.0, and ±2.5 pixel maximum deviations, the coordinate errors after filtering are reduced to about 37.5%, 26.3%, and 20.7% of the original ones, respectively. In addition, experiments are conducted to verify the star point prediction windows. Among 100 star images, the average proportion of the number of effective star point objects obtained by the star point prediction windows in the total object number of each star image is calculated as only 0.95%. Both the simulated and experimental results demonstrate the feasibility and effectiveness of the proposed method.
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