Interpretation of 750 GeV Diphoton Excess at LHC in Singlet Extension of Color-octet Neutrino Mass Model

We propose that the possible 750 GeV diphoton excess can be explained in the color-octet neutrino mass model extended with a scalar singlet $\Phi$. The model generally contains $N_s$ species of color-octet, electroweak doublet scalars $S$ and $N_f$ species of color-octet, electroweak triplet $\chi$ or singlet $\rho$ fermions. While both scalars and fermions contribute to the production of $\Phi$ through gluon fusion, only the charged members induce the diphoton decay of $\Phi$. The diphoton rate can be significantly enhanced due to interference between the scalar and fermion loops. We show that the diphoton cross section can be from 3 to 10 fb for O(TeV) color-octet particles while evading all current LHC limits.Comment: 12 pages, 4 figures; v2: 13 pages, 4 figures, version to appear in EPJC, clarified a few things, updated numerical analysis using the most recent bound on color-octet fermions but without changing conclusions, corrected a mistake when quoting the branching ratio to Z gamma, added some references missed in v

Self-Dictionary Sparse Regression for Hyperspectral Unmixing: Greedy Pursuit and Pure Pixel Search are Related

This paper considers a recently emerged hyperspectral unmixing formulation based on sparse regression of a self-dictionary multiple measurement vector (SD-MMV) model, wherein the measured hyperspectral pixels are used as the dictionary. Operating under the pure pixel assumption, this SD-MMV formalism is special in that it allows simultaneous identification of the endmember spectral signatures and the number of endmembers. Previous SD-MMV studies mainly focus on convex relaxations. In this study, we explore the alternative of greedy pursuit, which generally provides efficient and simple algorithms. In particular, we design a greedy SD-MMV algorithm using simultaneous orthogonal matching pursuit. Intriguingly, the proposed greedy algorithm is shown to be closely related to some existing pure pixel search algorithms, especially, the successive projection algorithm (SPA). Thus, a link between SD-MMV and pure pixel search is revealed. We then perform exact recovery analyses, and prove that the proposed greedy algorithm is robust to noise---including its identification of the (unknown) number of endmembers---under a sufficiently low noise level. The identification performance of the proposed greedy algorithm is demonstrated through both synthetic and real-data experiments

Ready for Robot Assistance? Exploring Gender Influences on Service Robot Adoption in Luxury vs. Economy Hotels

The hospitality and service industries have rapidly integrated advanced robotics and artificial intelligence (AI) to elevate guest service, assist human staff, and provide unique experiences. During the COVID-19 pandemic, this trend accelerated as hotels particularly adopted technology-oriented services to meet stringent health and safety standards. Despite the evolution of consumption behaviors and preferences, a gap remains in understanding guests’ service preferences, specifically concerning the acceptance of service robots in the post pandemic hotel sector. In response, this study examines the role of gender in adopting service robots following the COVID-19 pandemic. The findings indicate that different hotel segments influence guests’ attitudes toward service robot adoption. Furthermore, the pandemic has shifted the perceptions of female hotel guests regarding service robots, making them more receptive to such services in luxury hotels, particularly when there are pronounced health and safety concerns