Is f1(1420)f_1(1420) the partner of f1(1285)f_1(1285) in the 3P1^3P_1 qqˉq\bar{q} nonet?

Based on a $2\times 2$ mass matrix, the mixing angle of the axial vector states $f_1(1420)$ and $f_1(1285)$ is determined to be $51.5^{\circ}$, and the theoretical results about the decay and production of the two states are presented. The theoretical results are in good agreement with the present experimental results, which suggests that $f_1(1420)$ can be assigned as the partner of $f_1(1285)$ in the $^3P_1$ $q\bar{q}$ nonet. We also suggest that the existence of $f_1(1510)$ needs further experimental confirmation.Comment: Latex, 6 pages, to be published in Chin. Phys. let

Tetrabenazine is neuroprotective in Huntington's disease mice

<p>Abstract</p> <p>Background</p> <p>Huntington's disease (HD) is a neurodegenerative disorder caused by a polyglutamine (polyQ) expansion in Huntingtin protein (Htt). PolyQ expansion in Httexp causes selective degeneration of striatal medium spiny neurons (MSN) in HD patients. A number of previous studies suggested that dopamine signaling plays an important role in HD pathogenesis. A specific inhibitor of vesicular monoamine transporter (VMAT2) tetrabenazine (TBZ) has been recently approved by Food and Drug Administration for treatment of HD patients in the USA. TBZ acts by reducing dopaminergic input to the striatum.</p> <p>Results</p> <p>In previous studies we demonstrated that long-term feeding with TBZ (combined with L-Dopa) alleviated the motor deficits and reduced the striatal neuronal loss in the yeast artificial chromosome transgenic mouse model of HD (YAC128 mice). To further investigate a potential beneficial effects of TBZ for HD treatment, we here repeated TBZ evaluation in YAC128 mice starting TBZ treatment at 2 months of age ("early" TBZ group) and at 6 months of age ("late" TBZ group). In agreement with our previous studies, we found that both "early" and "late" TBZ treatments alleviated motor deficits and reduced striatal cell loss in YAC128 mice. In addition, we have been able to recapitulate and quantify depression-like symptoms in TBZ-treated mice, reminiscent of common side effects observed in HD patients taking TBZ.</p> <p>Conclusions</p> <p>Our results further support therapeutic value of TBZ for treatment of HD but also highlight the need to develop more specific dopamine antagonists which are less prone to side-effects.</p

Evidence of Ising pairing in superconducting NbSe2_2 atomic layers

Two-dimensional transition metal dichalcogenides with strong spin-orbit interactions and valley-dependent Berry curvature effects have attracted tremendous recent interests. Although novel single-particle and excitonic phenomena related to spin-valley coupling have been extensively studied, effects of spin-momentum locking on collective quantum phenomena remain unexplored. Here we report an observation of superconducting monolayer NbSe$_2$ with an in-plane upper critical field over six times of the Pauli paramagnetic limit by magneto-transport measurements. The effect can be understood in terms of the competing Zeeman effect and large intrinsic spin-orbit interactions in non-centrosymmetric NbSe$_2$ monolayers, where the electronic spin is locked to the out-of-plane direction. Our results provide a strong evidence of unconventional Ising pairing protected by spin-momentum locking and open up a new avenue for studies of non-centrosymmetric superconductivity with unique spin and valley degrees of freedom in the exact two-dimensional limit

SGAT4PASS: Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation

As an important and challenging problem in computer vision, PAnoramic Semantic Segmentation (PASS) gives complete scene perception based on an ultra-wide angle of view. Usually, prevalent PASS methods with 2D panoramic image input focus on solving image distortions but lack consideration of the 3D properties of original $360^{\circ}$ data. Therefore, their performance will drop a lot when inputting panoramic images with the 3D disturbance. To be more robust to 3D disturbance, we propose our Spherical Geometry-Aware Transformer for PAnoramic Semantic Segmentation (SGAT4PASS), considering 3D spherical geometry knowledge. Specifically, a spherical geometry-aware framework is proposed for PASS. It includes three modules, i.e., spherical geometry-aware image projection, spherical deformable patch embedding, and a panorama-aware loss, which takes input images with 3D disturbance into account, adds a spherical geometry-aware constraint on the existing deformable patch embedding, and indicates the pixel density of original $360^{\circ}$ data, respectively. Experimental results on Stanford2D3D Panoramic datasets show that SGAT4PASS significantly improves performance and robustness, with approximately a 2% increase in mIoU, and when small 3D disturbances occur in the data, the stability of our performance is improved by an order of magnitude. Our code and supplementary material are available at https://github.com/TencentARC/SGAT4PASS.Comment: Accepted by IJCAI 202