Atomic resolution imaging at 2.5 GHz using near-field microwave microscopy

Atomic resolution imaging is demonstrated using a hybrid scanning tunneling/near-field microwave microscope (microwave-STM). The microwave channels of the microscope correspond to the resonant frequency and quality factor of a coaxial microwave resonator, which is built in to the STM scan head and coupled to the probe tip. We find that when the tip-sample distance is within the tunneling regime, we obtain atomic resolution images using the microwave channels of the microwave-STM. We attribute the atomic contrast in the microwave channels to GHz frequency current through the tip-sample tunnel junction. Images of the surfaces of HOPG and Au(111) are presented.Comment: 9 pages, 5 figures, submitted to Applied Physics Letter

Social Turing Tests: Crowdsourcing Sybil Detection

As popular tools for spreading spam and malware, Sybils (or fake accounts) pose a serious threat to online communities such as Online Social Networks (OSNs). Today, sophisticated attackers are creating realistic Sybils that effectively befriend legitimate users, rendering most automated Sybil detection techniques ineffective. In this paper, we explore the feasibility of a crowdsourced Sybil detection system for OSNs. We conduct a large user study on the ability of humans to detect today's Sybil accounts, using a large corpus of ground-truth Sybil accounts from the Facebook and Renren networks. We analyze detection accuracy by both "experts" and "turkers" under a variety of conditions, and find that while turkers vary significantly in their effectiveness, experts consistently produce near-optimal results. We use these results to drive the design of a multi-tier crowdsourcing Sybil detection system. Using our user study data, we show that this system is scalable, and can be highly effective either as a standalone system or as a complementary technique to current tools

Static and dynamic experimental analysis of an immersion joint

As the weakest part of an immersed tunnel, the immersion joint is the key element in research in this field. Relatively large deformations and internal forces may be induced in the immersion joint subjected to various loading types. Based on a real project, the shear mechanical behaviour is investigated by large scale model test. To explore the performance of the immersion joint, compression-shear loads are applied on a tunnel segment in a specific test set-up. For the applied loading schemes, different levels of axial force, corresponding to the water depth of the joint, are considered as well as varying amplitudes of the shear force. Based on these results, both the static and dynamic shear stiffness of an immersion joint were analysed. The results of the test indicate that the static shear stiffness of the joint increases linearly with the axial force and the same trend is found for the dynamic one. Moreover, the dynamic stiffness is larger than the static one

mmeta: An R Package for Multivariate Meta-Analysis

This paper describes the core features of the R package mmeta, which implements the exact posterior inference of odds ratio, relative risk, and risk difference given either a single 2 x 2 table or multiple 2 x 2 tables when the risks within the same study are independent or correlated

An efficient threshold dynamics method for topology optimization for fluids

We propose an efficient threshold dynamics method for topology optimization for fluids modeled with the Stokes equation. The proposed algorithm is based on minimization of an objective energy function that consists of the dissipation power in the fluid and the perimeter approximated by nonlocal energy, subject to a fluid volume constraint and the incompressibility condition. We show that the minimization problem can be solved with an iterative scheme in which the Stokes equation is approximated by a Brinkman equation. The indicator functions of the fluid-solid regions are then updated according to simple convolutions followed by a thresholding step. We demonstrate mathematically that the iterative algorithm has the total energy decaying property. The proposed algorithm is simple and easy to implement. A simple adaptive time strategy is also used to accelerate the convergence of the iteration. Extensive numerical experiments in both two and three dimensions show that the proposed iteration algorithm converges in much fewer iterations and is more efficient than many existing methods. In addition, the numerical results show that the algorithm is very robust and insensitive to the initial guess and the parameters in the model.Comment: 23 pages, 24 figure