Surjective endomorphisms of projective surfaces -- the existence of infinitely many dense orbits

Let $f \colon X \to X$ be a surjective endomorphism of a normal projective surface. When $\operatorname{deg} f \geq 2$, applying an (iteration of) $f$-equivariant minimal model program (EMMP), we determine the geometric structure of $X$. Using this, we extend the second author's result to singular surfaces to the extent that either $X$ has an $f$-invariant non-constant rational function, or $f$ has infinitely many Zariski-dense forward orbits; this result is also extended to Adelic topology (which is finer than Zariski topology)

The Photometric Investigation of V921 Her using the Lunar-based Ultraviolet Telescope of Chang'e-3 mission

The light curve of V921 Her in ultraviolet band observed by the Lunar-based Ultraviolet Telescope (LUT) is analyzed by the Wilson-Devinney code. Our solutions conclude that V921 Her is an early type marginal contact binary system with an additional close-in component. The binary system is under poor thermal contact with a temperature difference of nearly $700K$ between the two components. The close-in component contributes about $19\,\%$ of the total luminosity in the triple system. Combining the radial velocity study together with our photometric solutions, the mass of the primary star and secondary one are calculated to be $M_1 = 1.784(\pm0.055)M_\odot$, $M_2 = 0.403(\pm0.012)M_\odot$. The evolutionary scenario of V921 Her is discussed. All times of light minimum of V921 Her available in the bibliography are taken into account and the $O - C$ curve is analyzed for the first time. The most probable fitting results are discussed in the paper, which also confirm the existence of a third component ($P_3=10.2$ year) around the binary system. The period of V921 Her is also undergoing a continuously rapid increase at a rate of $dP/dt=+2.79\times{10^{-7}}day\cdot year^{-1}$, which may due to mass transfer from the less massive component to the more massive one

Regulation of Fgf15 expression in the intestine by glucocorticoid receptor

Fibroblast growth factor 15 (FGF15) was previously identified to be highly expressed in the ileum and functions as an endocrine factor to regulate bile acid synthesis in the liver. FGF15 targets its receptor fibroblast growth factor receptor 4 in the liver and serves important roles in energy metabolism, including bile acid homeostasis, glucose metabolism and protein synthesis. The expression of FGF15 is known to be regulated by the transcription factor farnesoid X receptor (FXR). In the present study, reverse transcription-quantitative polymerase chain reaction was used for measuring Fgf15 expression from the animal and tissue culture experiments, and it was identified that dexamethasone, a drug widely used in anti-inflammation therapy, and a classical inducer of glucocorticoid receptor (GR)- and pregnane X receptor (PXR)-target genes, may downregulate Fgf15 expression in the ileum. GR was identified to be highly expressed in the ileum by western blot analysis. Furthermore, it was demonstrated that the downregulation of Fgf15 by dexamethasone is due to the repression of ileal FXR activity via GR; however, not PXR, in the ileum. The present results provide insight for a better understanding of the adverse effects associated with dexamethasone therapy.National Institute of General Medical Sciences [GM082978]; Chinese National Nature Sciences Foundation [31501232]; Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry; Fujian Provincial Nature Science Foundation [2015J05052]; Fujian Agriculture and Forestry University Science Fund for Distinguished Young Scholars [xjq201629]; (Fuzhou, China)6 month embargo; published online: 30 January 2019This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Enabling CMF Estimation in Data-Constrained Scenarios: A Semantic-Encoding Knowledge Mining Model

Precise estimation of Crash Modification Factors (CMFs) is central to evaluating the effectiveness of various road safety treatments and prioritizing infrastructure investment accordingly. While customized study for each countermeasure scenario is desired, the conventional CMF estimation approaches rely heavily on the availability of crash data at given sites. This not only makes the estimation costly, but the results are also less transferable, since the intrinsic similarities between different safety countermeasure scenarios are not fully explored. Aiming to fill this gap, this study introduces a novel knowledge-mining framework for CMF prediction. This framework delves into the connections of existing countermeasures and reduces the reliance of CMF estimation on crash data availability and manual data collection. Specifically, it draws inspiration from human comprehension processes and introduces advanced Natural Language Processing (NLP) techniques to extract intricate variations and patterns from existing CMF knowledge. It effectively encodes unstructured countermeasure scenarios into machine-readable representations and models the complex relationships between scenarios and CMF values. This new data-driven framework provides a cost-effective and adaptable solution that complements the case-specific approaches for CMF estimation, which is particularly beneficial when availability of crash data or time imposes constraints. Experimental validation using real-world CMF Clearinghouse data demonstrates the effectiveness of this new approach, which shows significant accuracy improvements compared to baseline methods. This approach provides insights into new possibilities of harnessing accumulated transportation knowledge in various applications.Comment: 39 pages, 9 figure