Aesthetically Relevant Image Captioning

Image aesthetic quality assessment (AQA) aims to assign numerical aesthetic ratings to images whilst image aesthetic captioning (IAC) aims to generate textual descriptions of the aesthetic aspects of images. In this paper, we study image AQA and IAC together and present a new IAC method termed Aesthetically Relevant Image Captioning (ARIC). Based on the observation that most textual comments of an image are about objects and their interactions rather than aspects of aesthetics, we first introduce the concept of Aesthetic Relevance Score (ARS) of a sentence and have developed a model to automatically label a sentence with its ARS. We then use the ARS to design the ARIC model which includes an ARS weighted IAC loss function and an ARS based diverse aesthetic caption selector (DACS). We present extensive experimental results to show the soundness of the ARS concept and the effectiveness of the ARIC model by demonstrating that texts with higher ARS's can predict the aesthetic ratings more accurately and that the new ARIC model can generate more accurate, aesthetically more relevant and more diverse image captions. Furthermore, a large new research database containing 510K images with over 5 million comments and 350K aesthetic scores, and code for implementing ARIC are available at https://github.com/PengZai/ARIC.Comment: Aceepted by AAAI2023. Code and results available at https://github.com/PengZai/ARI

Postnatal maintenance of the 5-Ht1a-Pet1 autoregulatory loop by serotonin in the raphe nuclei of the brainstem

BACKGROUND: Despite the importance of 5-HT1A as a major target for the action of several anxiolytics/antidepressant drugs, little is known about its regulation in central serotonin (5-hydroxytryptamine, 5-HT) neurons. RESULTS: We report that expression of 5-HT1A and the transcription factor Pet1 was impaired in the rostral raphe nuclei of mice lacking tryptophan hydroxylase 2 (Tph2) after birth. The downregulation of Pet1 was recapitulated in 5-Ht1a( -/- ) mice. Using an explant culture system, we show that reduction of Pet1 and 5-HT1A was rescued in Tph2( -/- ) brainstem by exogenous 5-HT. In contrast, 5-HT failed to rescue reduced expression of Pet1 in 5-Ht1a( -/- ) brainstem explant culture. CONCLUSIONS: These results suggest a causal relationship between 5-HT1A and Pet1, and reveal a potential mechanism by which 5-HT1A-Pet1 autoregulatory loop is maintained by 5-HT in a spatiotemporal-specific manner during postnatal development. Our results are relevant to understanding the pathophysiology of certain psychiatric and developmental disorders

Edge Charge Asymmetry in Top Pair Production at the LHC

In this brief report, we propose a new definition of charge asymmetry in top pair production at the LHC, namely the edge charge asymmetry (ECA). ECA utilizes the information of drifting direction only for single top (or anti-top) with hadronically decay. Therefore ECA can be free from the uncertainty arising from the missing neutrino in the $t\bar{t}$ event reconstruction. Moreover rapidity $Y$ of top (or anti-top) is required to be greater than a critical value $Y_{\rm C}$ in order to suppress the symmetric $t\bar{t}$ events mainly due to the gluon-gluon fusion process. In this paper ECA is calculated up to next-to-leading order QCD in the standard model and the choice of the optimal $Y_{\rm C}$ is investigated.Comment: 10 pages, 6 figure

Discriminating Different Z′Z^\primes via Asymmetries at the LHC

In practice the asymmetry, which is defined based on the angular distribution of the final states in scattering or decay processes, can be utilized to scrutinize underlying dynamics in and/or beyond the standard model (BSM). As one of the possible BSM physics which might be discovered early at the LHC, extra neutral gauge bosons $Z^\prime$s are theoretical well motivated. Once $Z^\prime$s are discovered at the LHC, it is crucial to discriminate different $Z^\prime$s in various BSM. In principle such task can be accomplished by measuring the angular distribution of the final states which are produced via $Z^\prime$-mediated processes. In the real data analysis, asymmetry is always adopted. In literature several asymmetries have been proposed at the LHC. Based on these works, we stepped further on to study how to optimize the asymmetries in the left-right model and the sequential standard model, as the examples of BSM. In this paper, we examined four kinds of asymmetries, namely rapidity-dependent forward-backward asymmetry, one-side forward-backward asymmetry, central charge asymmetry and edge charge asymmetry (see text for details), with $\ell^+\ell^-$ ($\ell=e,\mu$), $b\bar b$ and $t\bar t$ as the final states. In the calculations with $b\bar b$ and $t\bar t$ final states, the QCD-induced higher order contributions to the asymmetric cross section were also included. For each kind of final states, we estimated the four kinds of asymmetries and especially the optimal cut usually associated with the definition of the asymmetry. Our numerical results indicated that the capacity to discriminate $Z^\prime$ models can be improved by imposing the optimal cuts.Comment: 17 pages, 20 ps file

Dynamics of Bid-ask Spread Return and Volatility of the Chinese Stock Market

Bid-ask spread is taken as an important measure of the financial market liquidity. In this article, we study the dynamics of the spread return and the spread volatility of four liquid stocks in the Chinese stock market, including the memory effect and the multifractal nature. By investigating the autocorrelation function and the Detrended Fluctuation Analysis (DFA), we find that the spread return is lack of long-range memory, while the spread volatility is long-range time correlated. Moreover, by applying the Multifractal Detrended Fluctuation Analysis (MF-DFA), the spread return is observed to possess a strong multifractality, which is similar to the dynamics of a variety of financial quantities. Differently from the spread return, the spread volatility exhibits a weak multifractal nature

Memory effect and multifractality of cross-correlations in financial markets

An average instantaneous cross-correlation function is introduced to quantify the interaction of the financial market of a specific time. Based on the daily data of the American and Chinese stock markets, memory effect of the average instantaneous cross-correlations is investigated over different price return time intervals. Long-range time-correlations are revealed, and are found to persist up to a month-order magnitude of the price return time interval. Multifractal nature is investigated by a multifractal detrended fluctuation analysis.Comment: 11 pages, 4 figures