An Efficient Method for Traffic Image Denoising

AbstractIn this paper, a novel method for traffic image denoising based on the low-rank decomposition is proposed. Firstly, the low-rank decomposition is carried out. Under the sparse and low-rank constraints of low-rank decomposition, the foreground images with complanate background and moving vehicles and the background images with similar road scene are obtained. Then the foreground image is segmented into blocks of a certain size. The variance of each block is calculated, among that the minimum is considered the estimate of the noise power. KSVD algorithm is performed for the foreground image denoising. Furthermore, the noisy pixel discrimination algorithm is performed to distinguish the noisy pixels from the noiseless pixels and the eight- neighborhood weight interpolation algorithm is performed to reconstruct the noisy pixels, where the weighted coefficients are inversely proportional to the Euclidean distances between the pixels. And PCA recovery combined with noisy pixel discrimination and eight-neighborhood weight interpolation is adopted for the background image denoising. Finally, our proposed method is conducted based on the traffic videos obtained under the same view and angle. Moreover, our proposed method is compared with several state-of-the-art denoising methods including BM3D, KSVD and PCA recovery. The experiment results illustrate that our proposed method can more effectively remove the noise, preserve the useful information and achieve a better performance in terms of both PSNR index and visual qualities

Recent progress in rechargeable alkali metal–air batteries

AbstractRechargeable alkali metal–air batteries are considered as the most promising candidate for the power source of electric vehicles (EVs) due to their high energy density. However, the practical application of metal–air batteries is still challenging. In the past decade, many strategies have been purposed and explored, which promoted the development of metal–air batteries. The reaction mechanisms have been gradually clarified and catalysts have been rationally designed for air cathodes. In this review, we summarize the recent development of alkali metal–air batteries from four parts: metal anodes, electrolytes, air cathodes and reactant gases, wherein we highlight the important achievement in this filed. Finally problems and prospective are discussed towards the future development of alkali metal–air batteries

How to coadd images: II. Anti-aliasing and PSF deconvolution

We have developed a novel method for co-adding multiple under-sampled images that combines the iteratively reweighted least squares and divide-and-conquer algorithms. Our approach not only allows for the anti-aliasing of the images but also enables PSF deconvolution, resulting in enhanced restoration of extended sources, the highest PSNR, and reduced ringing artefacts. To test our method, we conducted numerical simulations that replicated observation runs of the CSST/VST telescope and compared our results to those obtained using previous algorithms. The simulation showed that our method outperforms previous approaches in several ways, such as restoring the profile of extended sources and minimizing ringing artefacts. Additionally, because our method relies on the inherent advantages of least squares fitting, it is more versatile and does not depend on the local uniformity hypothesis for the PSF. However, the new method consumes much more computation than the other approaches.Comment: 16 pages, 5 figures, 2 tables, accepted for publishing on RA

A rolling bearing fault diagnosis method based on VMD – multiscale fractal dimension/energy and optimized support vector machine

To achieve the goal of automated rolling bearing fault diagnosis, a variational mode decomposition (VMD) based diagnosis scheme was proposed. VMD was firstly used to decompose the vibration signals into a series of band-limited intrinsic mode functions (BLIMFs). Subsequently, the multiscale fractal dimension (MSFD) and multiscale energy (MSEN) of each BLIMF were calculated and combined together as features of the original vibration signals. In an attempt to accelerate the classification speed, one-way analysis of variance (ANOVA) test was adopted to extract significant features from the redundant features. Finally, those significant features were fed into the optimized support vector machine (SVM), which was optimized by the genetic algorithm (GA), for classification. Experimental results on the international public Case Western Reserve University bearing data indicate the effectiveness of the proposed method with a classification accuracy of 99.75 % for seven classes. Moreover, our approach also shows good anti-noise performance in different signal-to-noise ratios (SNRs)

Global prevalence of norovirus gastroenteritis after emergence of the GII.4 Sydney 2012 variant: a systematic review and meta-analysis

IntroductionNorovirus is widely recognized as a leading cause of both sporadic cases and outbreaks of acute gastroenteritis (AGE) across all age groups. The GII.4 Sydney 2012 variant has consistently prevailed since 2012, distinguishing itself from other variants that typically circulate for a period of 2–4 years.ObjectiveThis review aims to systematically summarize the prevalence of norovirus gastroenteritis following emergence of the GII.4 Sydney 2012 variant.MethodsData were collected from PubMed, Embase, Web of Science, and Cochrane databases spanning the period between January 2012 and August 2022. A meta-analysis was conducted to investigate the global prevalence and distribution patterns of norovirus gastroenteritis from 2012 to 2022.ResultsThe global pooled prevalence of norovirus gastroenteritis was determined to be 19.04% (16.66–21.42%) based on a comprehensive analysis of 70 studies, which included a total of 85,798 sporadic cases with acute gastroenteritis and identified 15,089 positive cases for norovirus. The prevalence rate is higher in winter than other seasons, and there are great differences among countries and age groups. The pooled attack rate of norovirus infection is estimated to be 36.89% (95% CI, 36.24–37.55%), based on a sample of 6,992 individuals who tested positive for norovirus out of a total population of 17,958 individuals exposed during outbreak events.ConclusionThe global prevalence of norovirus gastroenteritis is always high, necessitating an increased emphasis on prevention and control strategies with vaccine development for this infectious disease, particularly among the children under 5 years old and the geriatric population (individuals over 60 years old)

Effects of Inflorescence Stem Structure and Cell Wall Components on the Mechanical Strength of Inflorescence Stem in Herbaceous Peony

Herbaceous peony (Paeonia lactiflora Pall.) is a traditional famous flower, but its poor inflorescence stem quality seriously constrains the development of the cut flower. Mechanical strength is an important characteristic of stems, which not only affects plant lodging, but also plays an important role in stem bend or break. In this paper, the mechanical strength, morphological indices and microstructure of P. lactiflora development inflorescence stems were measured and observed. The results showed that the mechanical strength of inflorescence stems gradually increased, and that the diameter of inflorescence stem was a direct indicator in estimating mechanical strength. Simultaneously, with the development of inflorescence stem, the number of vascular bundles increased, the vascular bundle was arranged more densely, the sclerenchyma cell wall thickened, and the proportion of vascular bundle and pith also increased. On this basis, cellulose and lignin contents were determined, PlCesA3, PlCesA6 and PlCCoAOMT were isolated and their expression patterns were examined including PlPAL. The results showed that cellulose was not strictly correlated with the mechanical strength of inflorescence stem, and lignin had a significant impact on it. In addition, PlCesA3 and PlCesA6 were not key members in cellulose synthesis of P. lactiflora and their functions were also different, but PlPAL and PlCCoAOMT regulated the lignin synthesis of P. lactiflora. These data indicated that PlPAL and PlCCoAOMT could be applied to improve the mechanical strength of P. lactiflora inflorescence stem in genetic engineering