Above-threshold ionization photoelectron spectrum from quantum trajectory

Many nonlinear quantum phenomena of intense laser-atom physics can be intuitively explained with the concept of trajectory. In this paper, Bohmian mechanics (BM) is introduced to study a multiphoton process of atoms interacting with the intense laser field: above-threshold ionization (ATI). Quantum trajectory of an atomic electron in intense laser field is obtained from the Bohm-Newton equation first and then the energy of the photoelectron is gained from its trajectory. With energies of an ensemble of photoelectrons, we obtain the ATI spectrum which is consistent with the previous theoretical and experimental results. Comparing BM with the classical trajectory Monte-Carlo method, we conclude that quantum potential may play a key role to reproduce the spectrum of ATI. Our work may present a new approach to understanding quantum phenomena in intense laser-atom physics with the image of trajectory.Comment: 10 pages, 3 figure

HTS transformer and its related loss measurement and quench protection techniques

Recently research and development concerning applications of high temperature superconducting (HTS) transformers have been progressed actively in the world. Besides the HTS rated current capability, it is also essential to develop the relevant and precise performance test and protection systems for HTS transformers. This paper mainly presents elementary test and protection methods of HTS transformers including AC loss measurement, and quench detection and protection. A new integrated measurement system for HTS transformers is also proposed by using the Labview virtual instrument software

Phenolic Characterisation and Antioxidant Capacity of Young Wines Made From Different Grape Varieties Grown in Helanshan Donglu Wine Zone (China)

The Helanshan Donglu wine zone (China) is one of the most successful wine region of China, and the phenolic characterisation and antioxidant capacity of the primarily young, monovarietal wines from there were evaluated. The result showed that Helanshan Donglu wines contained abundant phenolic compounds, especially flavan-3-ols, and possessed high antioxidant capacity. In different grape varieties, the phenolic profiles varied greatly in both red and white wines. For red wines, Cabernet Sauvignon represented the highest total phenols (2 631 mg/L GAE), total flavonoids (1 840.83 mg/L CTE) and antioxidant capacity. Gamay and Cabernet Gernischt possessed the highest total flavan-3-ols (1 108.08 mg/L CTE) and total anthocyanins (258.78 mg/L CGE). Amongst the white wines, Chardonnay and Chenin blanc showed the highest phenolic contents and antioxidant capacity. (+)-Catechin and (-)-epicatechin were dominant phenolic constituents in both the red and white wines. Gallic acid and salicylic acid were the second most abundant in red wines, while gentisic acid was the second most abundant in white wines

An independent test of the photometric selection of white dwarf candidates using LAMOST DR3

In Gentile Fusillo et al. (2015) we developed a selection method for white dwarf candidates which makes use of photometry, colours and proper motions to calculate a probability of being a white dwarf (Pwd). The application of our method to the Sloan Digital Sky Survey (SDSS) data release 10 resulted in nearly 66,000 photometrically selected objects with a derived Pwd, approximately 21000 of which are high confidence white dwarf candidates. Here we present an independent test of our selection method based on a sample of spectroscopically confirmed white dwarfs from the LAMOST (Large Sky Area Multi-Fiber Spectroscopic Telescope) survey. We do this by cross matching all our $\sim$66,000 SDSS photometric white dwarf candidates with the over 4 million spectra available in the third data release of LAMOST. This results in 1673 white dwarf candidates with no previous SDSS spectroscopy, but with available LAMOST spectra. Among these objects we identify 309 genuine white dwarfs. We find that our Pwd can efficiently discriminate between confirmed LAMOST white dwarfs and contaminants. Our white dwarf candidate selection method can be applied to any multi-band photometric survey and in this work we conclusively confirm its reliability in selecting white dwarfs without recourse to spectroscopy. We also discuss the spectroscopic completeness of white dwarfs in LAMOST, as well as deriving effective temperatures, surface gravities and masses for the hydrogen-rich atmosphere white dwarfs in the newly identified LAMOST sample.Comment: 10 pages, 7 figures. Accepted for publication in MNRAS. The full catalogue presented in table 4 is available at http://www2.warwick.ac.uk/fac/sci/physics/research/astro/catalogues/SDSS_WD_candidates_with_LAMOST_spectra.cs

The stability of transgene expression and effect of DNA methylation on post transcriptional gene silencing (PTGS) in birch

In this paper, we selected transgenic birch (Betula platyphylla Suk) plants, which included nonsilencing plants, transcriptional silence plants including TP96, TP74, TP73 and the post-transcriptional silence ones (TP67 and TP72). The transcription of the bgt gene in different tissues and organs were significantly different. The transcriptional level of bgt gene in the different tissues and organs was in the following order: leaf > female flower and male flower > branch bark > phloem > root. The transgenic lines were monitored for foreign gene expression for a long-term period of 8 years during their continuous growth under field conditions. GUS protein expression was not reactivated in the transgene silencing lines TP72 and TP67 when cultured in field conditions for long-term period. Meanwhile, no cases of gene silencing were observed again during the study period in the field conditions. Our results suggest that transgene expression in transgenic birch plants appears to be stable under field conditions. The frequencies of methylated cytosines in the code regions of gus gene was studied. Relation of transgene expression and DNA methylation was analysed. The data of restriction enzyme digestion (HpaII and MspI) indicated that DNA methylation resulted in post transcriptional gene silencing (PTGS) in transgenic birch.Key words: Transgenic birch, DNA methylation, gene silencing

Seasonal variation, flux estimation, and source analysis of dissolved emerging organic contaminants in the Yangtze Estuary, China.

The occurrence and seasonal variation of 24 dissolved emerging organic contaminants in the Yangtze Estuary were studied, including 12 non-antibiotic pharmaceuticals, seven sulfonamides, two macrolides and three chloramphenicols. Sulfadiazine, erythromycin, thiamphenicol and paracetamol were the primary contaminants in sulfonamides, macrolides, chloramphenicols and non-antibiotic pharmaceutical groups, respectively. Compared to the concentrations at Datong, chloramphenicols at Xuliujing were significantly higher in autumn and winter, while macrolides were lower in spring. Based on the flux estimation, approximately 37.1 tons of sulfonamides, 17.4 tons of macrolides, 79.2 tons of chloramphenicols and 14.1 tons of non-antibiotic pharmaceuticals were discharged into the Yangtze Estuary from June 2013 to May 2014. However, the total flux from the Huangpu River only represented 5% of the total. The pharmaceutical sources were speculated on by analyzing the seasonal variations in pharmaceutical concentrations and fluxes at various sites. Both environmental and social factors might affect the fluxes

Ret3D: Rethinking Object Relations for Efficient 3D Object Detection in Driving Scenes

Current efficient LiDAR-based detection frameworks are lacking in exploitingobject relations, which naturally present in both spatial and temporal manners.To this end, we introduce a simple, efficient, and effective two-stagedetector, termed as Ret3D. At the core of Ret3D is the utilization of novelintra-frame and inter-frame relation modules to capture the spatial andtemporal relations accordingly. More Specifically, intra-frame relation module(IntraRM) encapsulates the intra-frame objects into a sparse graph and thusallows us to refine the object features through efficient message passing. Onthe other hand, inter-frame relation module (InterRM) densely connects eachobject in its corresponding tracked sequences dynamically, and leverages suchtemporal information to further enhance its representations efficiently througha lightweight transformer network. We instantiate our novel designs of IntraRMand InterRM with general center-based or anchor-based detectors and evaluatethem on Waymo Open Dataset (WOD). With negligible extra overhead, Ret3Dachieves the state-of-the-art performance, being 5.5% and 3.2% higher than therecent competitor in terms of the LEVEL 1 and LEVEL 2 mAPH metrics on vehicledetection, respectively.<br

Both Style and Fog Matter: {C}umulative Domain Adaptation for Semantic Foggy Scene Understanding

Although considerable progress has been made in semantic scene understanding under clear weather, it is still a tough problem under adverse weather conditions, such as dense fog, due to the uncertainty caused by imperfect observations. Besides, difficulties in collecting and labeling foggy images hinder the progress of this field. Considering the success in semantic scene understanding under clear weather, we think it is reasonable to transfer knowledge learned from clear images to the foggy domain. As such, the problem becomes to bridge the domain gap between clear images and foggy images. Unlike previous methods that mainly focus on closing the domain gap caused by fog -- defogging the foggy images or fogging the clear images, we propose to alleviate the domain gap by considering fog influence and style variation simultaneously. The motivation is based on our finding that the style-related gap and the fog-related gap can be divided and closed respectively, by adding an intermediate domain. Thus, we propose a new pipeline to cumulatively adapt style, fog and the dual-factor (style and fog). Specifically, we devise a unified framework to disentangle the style factor and the fog factor separately, and then the dual-factor from images in different domains. Furthermore, we collaborate the disentanglement of three factors with a novel cumulative loss to thoroughly disentangle these three factors. Our method achieves the state-of-the-art performance on three benchmarks and shows generalization ability in rainy and snowy scenes