CP asymmetry from resonance effect of B meson decay process with π\pi and K final states

We introduce the new resonance of $V\rightarrow K^{+}K^{-}$ $(V=\phi, \rho, \omega)$, which produces some new strong phase associated with vector meson resonance and thus can cause relatively large CP asymmetry at the range of interferences. There are the resonances of $\phi \rightarrow K^{+}K^{-}$, $\rho \rightarrow K^{+}K^{-}$ and $\omega \rightarrow K^{+}K^{-}$ due to the mixing of vector mesons $\phi$, $\rho$, $\omega$. We calculate the CP asymmetry from the decay modes of $B \rightarrow KK\pi(K)$. Meanwhile, the localised CP asymmetries are presented and some detailed analysis can be found. The CP asymmetry from the decay mode of ${B}^{-}\rightarrow \phi\pi^{-}\rightarrow K^{+}K^{-}\pi^{-}$ is also presented in our framework which is well consisted with LHC experiment. The introduced CP asymmetry can provide a favorable theoretical support for the experimental exploration in the future

Evaluation and projection of precipitation extremes under 1.5 degrees C and 2.0 degrees C GWLs over China using bias-corrected CMIP6 models

China is facing an increasing challenge from severe precipitation-related extremes with accelerating global warming. In this study, using a bias-corrected CMIP6 ensemble, future responses of precipitation extreme indices at 1.5°C and 2.0°C global warming levels (GWLs) under the SSP245, SSP370 and SSP585 scenarios are investigated. Despite different change magnitudes, extreme precipitation events will be more frequent and more intense over China as a whole under higher emissions and GWLs. The increase in annual total precipitation could attribute to a sharp increase in the intensity and days of very heavy precipitation in future global warming scenarios. Limiting global warming to 1.5°C and low emission pathways (i.e., SSP245) instead of 2°C and high emission pathways (i.e., SSP585) would have substantial benefits for China in terms of reducing occurrences of extreme precipitation events

Two Heads are Better than One: Towards Better Adversarial Robustness by Combining Transduction and Rejection

Both transduction and rejection have emerged as important techniques for defending against adversarial perturbations. A recent work by Tram\`er showed that, in the rejection-only case (no transduction), a strong rejection-solution can be turned into a strong (but computationally inefficient) non-rejection solution. This detector-to-classifier reduction has been mostly applied to give evidence that certain claims of strong selective-model solutions are susceptible, leaving the benefits of rejection unclear. On the other hand, a recent work by Goldwasser et al. showed that rejection combined with transduction can give provable guarantees (for certain problems) that cannot be achieved otherwise. Nevertheless, under recent strong adversarial attacks (GMSA, which has been shown to be much more effective than AutoAttack against transduction), Goldwasser et al.'s work was shown to have low performance in a practical deep-learning setting. In this paper, we take a step towards realizing the promise of transduction+rejection in more realistic scenarios. Theoretically, we show that a novel application of Tram\`er's classifier-to-detector technique in the transductive setting can give significantly improved sample-complexity for robust generalization. While our theoretical construction is computationally inefficient, it guides us to identify an efficient transductive algorithm to learn a selective model. Extensive experiments using state of the art attacks (AutoAttack, GMSA) show that our solutions provide significantly better robust accuracy

How Extreme Events in China Would Be Affected by Global Warming-Insights From a Bias-Corrected CMIP6 Ensemble

In recent years, concurrent climate extreme conditions (i.e., hot-dry, cold-dry, hot-wet, and cold-wet) have led to various unprecedented natural disasters (e.g., floods, landslide, wildfire, droughts, etc.), causing significant damages to human societies and ecosystems. This is especially true for China where many unprecedented natural disasters have been reported due to the recent warming in local climate. In this paper, we focus on the issue of ultra-extreme events (1‰ threshold) and address how future global warming would affect the climate extreme conditions in China. Specifically, to reduce the uncertainties from models, we use a downscaled and bias-corrected CMIP6 ensemble under two continuously-warming scenarios to evaluate the impact of global warming on ultra-extreme events over China. The results show that, under both SSP245 and SSP585 scenarios, extreme hot conditions would become dominant in most regions of China and some regions are likely to experience over 50 extreme hot days at future warming levels. The frequency of extreme cold events is projected to be small. More frequent extreme hot-wet events with concurrence in the same month and year would be expected for China under the continuously-warming scenarios. This is particularly obvious for the west where more than 6 hot-wet months are likely to take place under future warming scenarios. This may imply that more extreme heat waves and flooding events would coincide in the same month or year for China in the future. For univariate ultra-extreme events, both extreme hot events and extreme wet events would drop by above 25% from 2.0°C to 1.5°C global warming level, particularly under the SSP245 scenario. When the global mean temperature is limited to 1.5°C rather than 2°C, the avoided impacts of hot-wet and cold-wet extremes concurring in the same month will be larger than those of dry-related compound extremes. Overall, the results suggest that slowing down global warming can reduce the frequency of concurrent climate extreme conditions in China, highlighting the importance of immediate action toward carbon emission reduction

Silicon acquisition and accumulation in plant and its significance for agriculture

Although silicon (Si) is ubiquitous in soil and plant, evidence is still lacking that Si is essential for higher plants. However, it has been well documented that Si is beneficial for healthy growth of many plant species. Si can promote plant mechanical strength, light interception, as well as resistance to various forms of abiotic and biotic stress, thus improving both yield and quality. Indeed, application of Si fertilizer is a rather common agricultural practice in many countries and regions. As the beneficial effects provided by Si are closely correlated with Si accumulation level in plant, elucidating the possible mechanisms of Si uptake and transport in plants is extremely important to utilize the Si-induced beneficial effects in plants. Recently, rapid progress has been made in unveiling molecular mechanisms of Si uptake and transport in plants. Based on the cooperation of Si influx channels and efflux transporters, a model to decipher Si uptake, transport and distribution system in higher plants has been developed, which involves uptake and radial transport in root, xylem and inter-vascular transport and xylem unloading and deposition in leaf. In this paper, we overviewed the updated knowledge concerning Si uptake, transport and accumulation and its significance for the major crops of agricultural importance and highlighted the further research needs as well