Neutrino mu-tau reflection symmetry and its breaking in the minimal seesaw

In this paper, we attempt to implement the neutrino $\mu$-$\tau$ reflection symmetry (which predicts $\theta^{}_{23} = \pi/4$ and $\delta = \pm \pi/2$ as well as trivial Majorana phases) in the minimal seesaw (which enables us to fix the neutrino masses). For some direct (the preliminary experimental hints towards $\theta^{}_{23} \neq \pi/4$ and $\delta \neq - \pi/2$) and indirect (inclusion of the renormalization group equation effect and implementation of the leptogenesis mechanism) reasons, we particularly study the breakings of this symmetry and their phenomenological consequences.Comment: 20 pages, 7 figures, accepted for publication in JHE

Electrical Control of Magnetization in Charge-ordered Multiferroic LuFe2O4

LuFe2O4 exhibits multiferroicity due to charge order on a frustrated triangular lattice. We find that the magnetization of LuFe2O4 in the multiferroic state can be electrically controlled by applying voltage pulses. Depending on with or without magnetic fields, the magnetization can be electrically switched up or down. We have excluded thermal heating effect and attributed this electrical control of magnetization to an intrinsic magnetoelectric coupling in response to the electrical breakdown of charge ordering. Our findings open up a new route toward electrical control of magnetization.Comment: 14 pages, 5 figure

Unifying ultrafast demagnetization and intrinsic Gilbert damping in Co/Ni bilayers with electronic relaxation near the Fermi surface

The ability to controllably manipulate the laser-induced ultrafast magnetic dynamics is a prerequisite for future high speed spintronic devices. The optimization of devices requires the controllability of the ultrafast demagnetization time, , and intrinsic Gilbert damping, . In previous attempts to establish the relationship between and , the rare-earth doping of a permalloy film with two different demagnetization mechanism is not a suitable candidate. Here, we choose Co/Ni bilayers to investigate the relations between and by means of time-resolved magneto-optical Kerr effect (TRMOKE) via adjusting the thickness of the Ni layers, and obtain an approximately proportional relation between these two parameters. The remarkable agreement between TRMOKE experiment and the prediction of breathing Fermi-surface model confirms that a large Elliott-Yafet spin-mixing parameter is relevant to the strong spin-orbital coupling at the Co/Ni interface. More importantly, a proportional relation between and in such metallic films or heterostructures with electronic relaxation near Fermi surface suggests the local spin-flip scattering domains the mechanism of ultrafast demagnetization, otherwise the spin-current mechanism domains. It is an effective method to distinguish the dominant contributions to ultrafast magnetic quenching in metallic heterostructures by investigating both the ultrafast demagnetization time and Gilbert damping simultaneously. Our work can open a novel avenue to manipulate the magnitude and efficiency of Terahertz emission in metallic heterostructures such as the perpendicular magnetic anisotropic Ta/Pt/Co/Ni/Pt/Ta multilayers, and then it has an immediate implication of the design of high frequency spintronic devices

Diagnotic Value of the Combined Determination of Telomerase Activity in Induced Sputum, Pleural Effusion and Fiberobronchoscopic Biopsy Samples in Lung Cancer

Background and objective It has been proven that telomerase activation correlates with the carcinogenesis, aggressiveness and turnover of lung cancer. Telomerase is one of the improtant molecular biomarkers for diagnosis and targeting therapy in lung cancer. The aim of this study is to investigate the diagnostic value of the combined determination of telomerase activity in induced sputum, pleural effusion and fiberobronchoscopic biopsy in lung cancer patients. Methods The technique of TRAP (telomeric repeat amplification protocal)-PCR-ELISA was employed to detect telomease levels of induced sputum, pleural effusion and fiberobronchoscopic biopsy in 80 lung cancer patients with pleural effusion and 50 benign pulmonary disease patients with pleural effusion. Results Telomemse levels of induced sputum, pleural effusion and fiberobronchoscopic biopsy were all significantly higher in patients with lung cancer than those with benign pulmonary disease (P < 0.001). There was no significant difference in the level of telomerase activity between different pathologic types (P>0.05). The sensitivity of induced sputum, pleural effusion and fiberobronchoscopic biopsy were 62.5% (50/80), 46.3% (37/80) and 60.0% (48/80), respectively. The specificity were 72.0% (36/50), 66.0% (33/50) and 70.0% (35/50), respectively. The overall accuracy were 66.2% (86/130), 53.8% (70/130) and 63.8% (83/130), respectively. The sensitivity, specificity and overall accuracy of combined induced sputum, pleural effusion and fiberobronchoscopic biopsy were 85.0% (68/80), 78.0% (39/50) and 82.3% (107/130), respectively. The sensitivity of telomease level in combined detection for diagnosis of lung cancer was much higher than that in single sample detection (P < 0.01). Conclusion The sensitivity of telomease activity in combined three samples was the highest. It can further improve the accuracy for the diagnosis of lung cancer with pleural effusion

Res2Net: A New Multi-scale Backbone Architecture

Representing features at multiple scales is of great importance for numerous vision tasks. Recent advances in backbone convolutional neural networks (CNNs) continually demonstrate stronger multi-scale representation ability, leading to consistent performance gains on a wide range of applications. However, most existing methods represent the multi-scale features in a layer-wise manner. In this paper, we propose a novel building block for CNNs, namely Res2Net, by constructing hierarchical residual-like connections within one single residual block. The Res2Net represents multi-scale features at a granular level and increases the range of receptive fields for each network layer. The proposed Res2Net block can be plugged into the state-of-the-art backbone CNN models, e.g., ResNet, ResNeXt, and DLA. We evaluate the Res2Net block on all these models and demonstrate consistent performance gains over baseline models on widely-used datasets, e.g., CIFAR-100 and ImageNet. Further ablation studies and experimental results on representative computer vision tasks, i.e., object detection, class activation mapping, and salient object detection, further verify the superiority of the Res2Net over the state-of-the-art baseline methods. The source code and trained models are available on https://mmcheng.net/res2net/.Comment: 11 pages, 7 figure