Bulk Strong Matter: the Trinity

Our world is wonderful because of the normal but negligibly small baryonic part (i.e., atoms) although unknown dark matter and dark energy dominate the Universe. A stable atomic nucleus could be simply termed as ``strong matter'' since its nature is dominated by the fundamental strong interaction. Is there any other form of strong matter? Although nuclei are composed of 2-flavoured (i.e., up and down flavours of valence quarks) nucleons, it is conjectured that bulk strong matter could be 3-flavoured (with additional strange quarks) if the baryon number exceeds the critical value, $A_{\rm c}$, in which case quarks could be either free (so-called strange quark matter) or localized (in strangeons, coined by combining ``strange nucleon''). Bulk strong matter could be manifested in the form of compact stars, cosmic rays, and even dark matter. This trinity will be explained in this brief review, that may impact dramatically on today's physics, particularly in the era of multi-messenger astronomy after the discovery of gravitational wave.Comment: 12 pages, 2 figures. Accepted by Advances in Physics:

Singular positone and semipositone boundary value problems of nonlinear fractional differential equations

We present some new existence results for singular positone and semipositone nonlinear fractional boundary value problem where μ > 0, a, and f are continuous, α ∈ 3, 4 is a real number, and D α 0 is Riemann-Liouville fractional derivative. Throughout our nonlinearity may be singular in its dependent variable. Two examples are also given to illustrate the main results

Fabrication of β-cyclodextrin modified mesostructured silica coated multi-walled carbon nanotubes composites and application for paraben removal

In this work, the novel β-cyclodextrin modified mesostructured silica coated multi-walled carbon nanotubes (MWCNTs) composites were synthesized and applied for the removal of parabens in aqueous solution. The prepared MWCNTs/SiO2/β-CD composites were characterized by Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy and thermogravimetric analysis. The effects of the amount of adsorbent, pH and elution solvents on the removal efficiency of parabens from water solutions were investigated. Under the optimized conditions, over 95% removal efficiency was achieved by using 40 mg of MWCNTs/SiO2/β-CD adsorbents to absorb the parabens from 60 mL of 0.5 μg/mL parabens solutions. The solution pH in the range from 5 to 9 has no influence on the removal efficiency and the parabens sorption capacity of the prepared adsorbents were around 0.75 μg/mg. Furthermore, the stability and reusability studies demonstrated that the prepared MWCNTs/SiO2/β-CD composites are cost-effective adsorbents for the removal of parabens from water with high regeneration efficiency. The composites fabricated in this study could become an attractive candidate for water purification

Modeling Occasion Evolution in Frequency Domain for Promotion-Aware Click-Through Rate Prediction

Promotions are becoming more important and prevalent in e-commerce to attract customers and boost sales, leading to frequent changes of occasions, which drives users to behave differently. In such situations, most existing Click-Through Rate (CTR) models can't generalize well to online serving due to distribution uncertainty of the upcoming occasion. In this paper, we propose a novel CTR model named MOEF for recommendations under frequent changes of occasions. Firstly, we design a time series that consists of occasion signals generated from the online business scenario. Since occasion signals are more discriminative in the frequency domain, we apply Fourier Transformation to sliding time windows upon the time series, obtaining a sequence of frequency spectrum which is then processed by Occasion Evolution Layer (OEL). In this way, a high-order occasion representation can be learned to handle the online distribution uncertainty. Moreover, we adopt multiple experts to learn feature representations from multiple aspects, which are guided by the occasion representation via an attention mechanism. Accordingly, a mixture of feature representations is obtained adaptively for different occasions to predict the final CTR. Experimental results on real-world datasets validate the superiority of MOEF and online A/B tests also show MOEF outperforms representative CTR models significantly