Exact Global Control of Small Divisors in Rational Normal Form

Rational normal form is a powerful tool to deal with Hamiltonian partial differential equations without external parameters. In this paper, we build rational normal form with exact global control of small divisors. As an application to nonlinear Schr\"{o}dinger equations in Gevrey spaces, we prove sub-exponentially long time stability results for generic small initial data

Documented Evidence of Agricultural Injury in China

Objective: To describe the documented evidence concerning agricultural injury in China and to identify topics for future research.Method: Literature search and review were conducted to collect publications that were relevant to agricultural injury in China. The process included defining agricultural injury for the purpose of this study, selecting articles according to inclusion criteria and extracting data from each paper. Descriptive methods were used to analyze the contents, research approaches, distribution of authors, and cooperation percentage of agricultural injury studies.Results: After applying the inclusion criteria, 89 articles were included in this study. The author collaboration percentage (number of articles with more than one author divided by number of total articles) and the institutional collaboration percentage (number of articles with more than one organization divided by number of total articles) among the 89 articles were 85.4% and 42.7%, respectively. Most of the authors are affiliated with a Center for Disease Control and Prevention (CDC) or an academic institution located in 10 of the 31 provinces in mainland China. Among the 89 articles, only 6 were on injuries related to agricultural work, the rest (83) dealt with injuries among rural residents with or without clarifying occupations or ongoing activities. Conclusions: Research on agricultural injuries in China is currently in its early stage. More research is needed to obtain evidence that can be used in policy making for agricultural injury control. Our study is the first to describe the documented evidence on agricultural injuries in China and identify topics for future research

Enhanced visible-light absorption of nitrogen-doped titania induced by shock wave

This paper presents a new method to prepare nitrogen-doped titania by detonation-driven flyer impact. The samples were shocked at different flyer impact velocities and recovered successfully. XRD, UV-Vis and XPS spectra were employed to characterize the phase composition, N doping concentration and energy gap of recovered samples. The results show that anatase transforms to rutile and srilankite appears at a higher flyer velocity (1.9-2.52 km/s), and the concentration of doped nitrogen in the recovered samples increases with increasing flyer velocity, while the maximum concentration of nitrogen is 13.45 at.%. The edge adsorption wavelength of nitrogen-doped titania induced by shock wave is shifted from 435 nm to 730 nm and the corresponding energy gap is reduced from 2.85 eV to 1.73 eV. High concentration nitrogen-doped titania is achieved by lattice displacement-atomic exchange mechanism during the formation of srilankite highpressure phase induced by shock wave

Non-aligned supervision for Real Image Dehazing

Removing haze from real-world images is challenging due to unpredictable weather conditions, resulting in misaligned hazy and clear image pairs. In this paper, we propose a non-aligned supervision framework that consists of three networks - dehazing, airlight, and transmission. In particular, we explore a non-alignment setting by utilizing a clear reference image that is not aligned with the hazy input image to supervise the dehazing network through a multi-scale reference loss that compares the features of the two images. Our setting makes it easier to collect hazy/clear image pairs in real-world environments, even under conditions of misalignment and shift views. To demonstrate this, we have created a new hazy dataset called "Phone-Hazy", which was captured using mobile phones in both rural and urban areas. Additionally, we present a mean and variance self-attention network to model the infinite airlight using dark channel prior as position guidance, and employ a channel attention network to estimate the three-channel transmission. Experimental results show that our framework outperforms current state-of-the-art methods in the real-world image dehazing. Phone-Hazy and code will be available at https://github.com/hello2377/NSDNet