Atmospheric chemistry-climate feedbacks

We extend the theory of climate feedbacks to include atmospheric chemistry. A change in temperature caused by a radiative forcing will include, in general, a contribution from the chemical change that is fed back into the climate system; likewise, the change in atmospheric burdens caused by a chemical forcing will include a contribution from the associated climate change that is fed back into the chemical system. The theory includes two feedback gains, G_(che) and G_(cli). G_(che) is defined as the ratio of the change in equilibrium global mean temperature owing to long-lived greenhouse gas radiative forcing, under full climate-chemistry coupling, to that in the absence of coupling. G_(cli) is defined as the ratio of the change in equilibrium mean aerosol or gas-phase burdens owing to chemical forcing under full coupling, to that in the absence of coupling. We employ a climate-atmospheric chemistry model based on the Goddard Institute for Space Studies (GISS) GCM II', including tropospheric gas-phase chemistry, sulfate, nitrate, ammonium, black carbon, and organic carbon. While the model describes many essential couplings between climate and atmospheric chemistry, not all couplings are accounted for, such as indirect aerosol forcing and the role of natural dust and sea salt aerosols. Guided by the feedback theory, we perform perturbation experiments to quantify G_(che) and G_(cli). We find that G_(che) for surface air temperature is essentially equal to 1.00 on a planetary scale. Regionally, G_(che) is estimated to be 0.80–1.30. The gains are small compared to those of the physical feedbacks in the climate system (e.g., water vapor, and cloud feedbacks). These values for G_(che) are robust for the specific model used, but may change when using more comprehensive climate-atmospheric chemistry models. Our perturbation experiments do not allow one to obtain robust values for G_(cli). Globally averaged, the values range from 0.99 to 1.28, depending on the chemical species, while, in areas of high pollution, G_(cli) can be up to 1.15 for ozone, and as large as 1.40 for total aerosol. These preliminary values indicate a significant role of climate feedbacks in the atmospheric chemistry system

Learning to Detect Important People in Unlabelled Images for Semi-supervised Important People Detection

Important people detection is to automatically detect the individuals who play the most important roles in a social event image, which requires the designed model to understand a high-level pattern. However, existing methods rely heavily on supervised learning using large quantities of annotated image samples, which are more costly to collect for important people detection than for individual entity recognition (eg, object recognition). To overcome this problem, we propose learning important people detection on partially annotated images. Our approach iteratively learns to assign pseudo-labels to individuals in un-annotated images and learns to update the important people detection model based on data with both labels and pseudo-labels. To alleviate the pseudo-labelling imbalance problem, we introduce a ranking strategy for pseudo-label estimation, and also introduce two weighting strategies: one for weighting the confidence that individuals are important people to strengthen the learning on important people and the other for neglecting noisy unlabelled images (ie, images without any important people). We have collected two large-scale datasets for evaluation. The extensive experimental results clearly confirm the efficacy of our method attained by leveraging unlabelled images for improving the performance of important people detection

Bˉ0→Kˉ(∗) 0X\bar B^0 \to \bar K^{(*) \,0} X, B−→K(∗) −XB^- \to K^{(*) \, -} X, Bˉs0→η(η′,ϕ)X\bar B_s^0 \to \eta (\eta', \phi) X from the X(3872)X(3872) molecular perspective

We study the decays $\bar B^0 \to \bar K^0 \, X$, $B^- \to K^- \, X$, $\bar B^0_s \to \eta (\eta')\, X$, $\bar B^0 \to \bar K^{*0} \, X$, $B^- \to K^{*-} \, X$ , $\bar B_s^0 \to \phi \, X$, with $X \equiv X(3872)$, from the perspective of the $X(3872)$ being a molecular state made from the interaction of the $D^{*+} D^-, D^{*0} \bar D^0$ and $c.c.$ components. We consider both the external and internal emission decay mechanisms and find an explanation for the $\bar K^0 \, X$ and $K^- \, X$ production rates, based on the mass difference of the charged and neutral $D^* \bar D$ components. We also find that the internal and external emission mechanisms add constructively in the $\bar B^0 \to \bar K^0 \, X$, $B^- \to K^- \, X$ reactions, while they add destructively in the case of $\bar B^0 \to \bar K^{*0} \, X$, $B^- \to K^{*-} \, X$ reactions. This feature explains the decay widths of the present measurements and allows us to make predictions for the unmeasured modes of $\bar B^0_s \to \eta (\eta')\, X(3872)$ and $B^- \to K^{*-} \, X(3872)$. The future measurement of these decay modes will help us get a better perspective on the nature of the $X(3872)$ and the mechanisms present in production reactions of that state.Comment: 15 pages, 5 figures, 2 table

3′,6′-Bis(ethyl­amino)-2′,7′-dimethyl-2-{[2-[(E)-3,4-methyl­enedioxy­benzyl­idene­amino]eth­yl}spiro­[isoindoline-1,9′-xanthen]-3-one

The title compound, C36H36N4O4, was prepared as a spiro­lactam ring formation of the rhodamine dye for comparison with a ring-opened form. The xanthene ring system is approximately planar [r.m.s. deviations from planarity = 0.023 (9) Å for the xanthene ring]. The dihedral angles formed by the spiro­lactam and 1,3-benzodioxole rings with the xanthene ring system are 86.8 (1) and 74.3 (1)°, respectively