The ortho-to-para ratio of interstellar NH2_2: Quasi-classical trajectory calculations and new simulations

Based on recent $Herschel$ results, the ortho-to-para ratio (OPR) of NH$_2$ has been measured towards the following high-mass star-forming regions: W31C (G10.6-0.4), W49N (G43.2-0.1), W51 (G49.5-0.4), and G34.3+0.1. The OPR at thermal equilibrium ranges from the statistical limit of three at high temperatures to infinity as the temperature tends toward zero, unlike the case of H$_{2}$. Depending on the position observed along the lines-of-sight, the OPR was found to lie either slightly below the high temperature limit of three (in the range $2.2-2.9$) or above this limit ($\sim3.5$, $\gtrsim 4.2$, and $\gtrsim 5.0$). In low temperature interstellar gas, where the H$_{2}$ is para-enriched, our nearly pure gas-phase astrochemical models with nuclear-spin chemistry can account for anomalously low observed NH$_2$-OPR values. We have tentatively explained OPR values larger than three by assuming that spin thermalization of NH$_2$ can proceed at least partially by H-atom exchange collisions with atomic hydrogen, thus increasing the OPR with decreasing temperature. In this paper, we present quasi-classical trajectory calculations of the H-exchange reaction NH$_2$ + H, which show the reaction to proceed without a barrier, confirming that the H-exchange will be efficient in the temperature range of interest. With the inclusion of this process, our models suggest both that OPR values below three arise in regions with temperatures $\gtrsim20-25$~K, depending on time, and values above three but lower than the thermal limit arise at still lower temperatures.Comment: 12 pages, 12 figures. Accepted for publication in A&

How is Gaze Influenced by Image Transformations? Dataset and Model

Data size is the bottleneck for developing deep saliency models, because collecting eye-movement data is very time consuming and expensive. Most of current studies on human attention and saliency modeling have used high quality stereotype stimuli. In real world, however, captured images undergo various types of transformations. Can we use these transformations to augment existing saliency datasets? Here, we first create a novel saliency dataset including fixations of 10 observers over 1900 images degraded by 19 types of transformations. Second, by analyzing eye movements, we find that observers look at different locations over transformed versus original images. Third, we utilize the new data over transformed images, called data augmentation transformation (DAT), to train deep saliency models. We find that label preserving DATs with negligible impact on human gaze boost saliency prediction, whereas some other DATs that severely impact human gaze degrade the performance. These label preserving valid augmentation transformations provide a solution to enlarge existing saliency datasets. Finally, we introduce a novel saliency model based on generative adversarial network (dubbed GazeGAN). A modified UNet is proposed as the generator of the GazeGAN, which combines classic skip connections with a novel center-surround connection (CSC), in order to leverage multi level features. We also propose a histogram loss based on Alternative Chi Square Distance (ACS HistLoss) to refine the saliency map in terms of luminance distribution. Extensive experiments and comparisons over 3 datasets indicate that GazeGAN achieves the best performance in terms of popular saliency evaluation metrics, and is more robust to various perturbations. Our code and data are available at: https://github.com/CZHQuality/Sal-CFS-GAN

Global patterns, trends, and drivers of water use efficiency from 2000 to 2013

Water use efficiency (WUE; gross primary production [GPP]/evapotranspiration [ET]) estimates the tradeoff between carbon gain and water loss during photosynthesis and is an important link of the carbon and water cycles. Understanding the spatiotemporal patterns and drivers of WUE is helpful for projecting the responses of ecosystems to climate change. Here we examine the spatiotemporal patterns, trends, and drivers of WUE at the global scale from 2000 to 2013 using the gridded GPP and ET data derived from the Moderate Resolution Imaging Spectroradiometer (MODIS). Our results show that the global WUE has an average value of 1.70 g C/kg H2O with large spatial variability during the 14-year period. WUE exhibits large variability with latitude. WUE also varies much with elevation: it first remains relatively constant as the elevation varies from 0 to 1000 m and then decreases dramatically. WUE generally increases as precipitation and specific humidity increase; whereas it decreases after reaching maxima as temperature and solar radiation increases. In most land areas, the temporal trend of WUE is positively correlated with precipitation and specific humidity over the 14-year period; while it has a negative relationship with temperature and solar radiation related to global warming and dimming. On average, WUE shows an increasing trend of 0.0025 g C·kg−1 H2O·yr−1 globally. Our global-scale assessment of WUE has implications for improving our understanding of the linkages between the water and carbon cycles and for better projecting the responses of ecosystems to climate change

Magneto-Optical Stern-Gerlach Effect in Atomic Ensemble

We study the birefringence of the quantized polarized light in a magneto-optically manipulated atomic ensemble as a generalized Stern-Gerlach Effect of light. To explain this engineered birefringence microscopically, we derive an effective Shr\"odinger equation for the spatial motion of two orthogonally polarized components, which behave as a spin with an effective magnetic moment leading to a Stern-Gerlach split in an nonuniform magnetic field. We show that electromagnetic induced transparency (EIT) mechanism can enhance the magneto-optical Stern-Gerlach effect of light in the presence of a control field with a transverse spatial profile and a inhomogeneous magnetic field.Comment: 7 pages, 5 figure