Magnetic miniband and magnetotransport property of a graphene superlattice

The eigen energy and the conductivity of a graphene sheet subject to a one-dimensional cosinusoidal potential and in the presence of a magnetic field are calculated. Such a graphene superlattice presents three distinct magnetic miniband structures as the magnetic field increases. They are, respectively, the triply degenerate Landau level spectrum, the nondegenerate minibands with finite dispersion and the same Landau level spectrum with the pristine graphene. The ratio of the magnetic length to the period of the potential function is the characteristic quantity to determine the electronic structure of the superlattice. Corresponding to these distinct electronic structures, the diagonal conductivity presents very strong anisotropy in the weak and moderate magnetic field cases. But the predominant magnetotransport orientation changes from the transverse to the longitudinal direction of the superlattice. More interestingly, in the weak magnetic field case, the superlattice exhibits half-integer quantum Hall effect, but with large jump between the Hall plateaux. Thus it is different from the one of the pristine graphene.Comment: 7 pages, 5 figure

Efficient Private ERM for Smooth Objectives

In this paper, we consider efficient differentially private empirical risk minimization from the viewpoint of optimization algorithms. For strongly convex and smooth objectives, we prove that gradient descent with output perturbation not only achieves nearly optimal utility, but also significantly improves the running time of previous state-of-the-art private optimization algorithms, for both $\epsilon$-DP and $(\epsilon, \delta)$-DP. For non-convex but smooth objectives, we propose an RRPSGD (Random Round Private Stochastic Gradient Descent) algorithm, which provably converges to a stationary point with privacy guarantee. Besides the expected utility bounds, we also provide guarantees in high probability form. Experiments demonstrate that our algorithm consistently outperforms existing method in both utility and running time

DEVELOPING PHOTOCHEMICAL PRECURSORS FOR INDEPENDENT GENERATION OF NEUTRAL PURINE RADICALS AND INVESTIGATING THE REACTIVITY OF 2′-DEOXYADENOSIN-N6-YL RADICAL IN DNA

DNA damage is deleterious to cells and can lead to cell death or cancer. The cytotoxicity of DNA damage is exploited by cancer treatments such as radiotherapy. Ionizing radiation damages DNA indirectly by reacting with hydroxyl radicals to generate reactive intermediates, e.g., nucleobase and deoxyribose radicals; or by directly generating nucleobase radicals. Neutral purine radicals (dA•, dG(N1-H)•, and dG(N2-H)•) generated by formal hydrogen atom abstraction of purines are believed to play a prominent role in oxidative DNA damage and DNA hole migration. However, very little is known about their reactivity. Studying these intermediates via radiolysis is complicated due to the concomitant formation of other reactive species. To overcome the dearth of methods for photochemically generating neutral purine radicals, we developed two general strategies. The first type of precursors utilized photoinduced homolytic cleavage of weak covalent bonds (3, 4 and 5). The second type of precursors (6 and 7) underwent a Norrish Type I photocleavage and β-fragmentation cascade to form neutral purine radicals and acetone. These precursors allowed mechanistic studies on the reactivity of neutral purine radicals as monomers in solutions or within DNA. Herein, we report that dA• initiates tandem lesion formation in 5'-d(GTA) sequences but does not induce DNA hole migration. We propose that the tandem lesion formation is initiated by dA• abstracting the hydrogen atom from the C5-methyl group of the 5'-adjacent thymidine. dA• is converted to dA in this process, and thus the involvement of dA• in the tandem lesion formation is traceless by typical product analysis. Furthermore, we demonstrate, for the first time, that dA• is protonated at neutral pH when flanked by dA. The formation of dA•+ by this protonation results in DNA damage arising from hole transfer. Finally, we disprove the published mechanism for the formation of strand damage observed during DNA hole migration in poly(dA-T) sequences and provide support for an alternative mechanism, in which the strand damage is tracelessly induced by dA•

Surface-SOS:Self-Supervised Object Segmentation via Neural Surface Representation

Self-supervised Object Segmentation (SOS) aims to segment objects without any annotations. Under conditions of multi-camera inputs, the structural, textural and geometrical consistency among each view can be leveraged to achieve fine-grained object segmentation. To make better use of the above information, we propose Surface representation based Self-supervised Object Segmentation (Surface-SOS), a new framework to segment objects for each view by 3D surface representation from multi-view images of a scene. To model high-quality geometry surfaces for complex scenes, we design a novel scene representation scheme, which decomposes the scene into two complementary neural representation modules respectively with a Signed Distance Function (SDF). Moreover, Surface-SOS is able to refine single-view segmentation with multi-view unlabeled images, by introducing coarse segmentation masks as additional input. To the best of our knowledge, Surface-SOS is the first self-supervised approach that leverages neural surface representation to break the dependence on large amounts of annotated data and strong constraints. These constraints typically involve observing target objects against a static background or relying on temporal supervision in videos. Extensive experiments on standard benchmarks including LLFF, CO3D, BlendedMVS, TUM and several real-world scenes show that Surface-SOS always yields finer object masks than its NeRF-based counterparts and surpasses supervised single-view baselines remarkably.</p