An equivalent-effect phenomenon in eddy current non-destructive testing of thin structures

The inductance/impedance due to thin metallic structures in non-destructive testing (NDT) is difficult to evaluate. In particular, in Finite Element Method (FEM) eddy current simulation, an extremely fine mesh is required to accurately simulate skin effects especially at high frequencies, and this could cause an extremely large total mesh for the whole problem, i.e. including, for example, other surrounding structures and excitation sources like coils. Consequently, intensive computation requirements are needed. In this paper, an equivalent-effect phenomenon is found, which has revealed that alternative structures can produce the same effect on the sensor response, i.e. mutual impedance/inductance of coupled coils if a relationship (reciprocal relationship) between the electrical conductivity and the thickness of the structure is observed. By using this relationship, the mutual inductance/impedance can be calculated from the equivalent structures with much fewer mesh elements, which can significantly save the computation time. In eddy current NDT, coils inductance/impedance is normally used as a critical parameter for various industrial applications, such as flaw detection, coating and microstructure sensing. Theoretical derivation, measurements and simulations have been presented to verify the feasibility of the proposed phenomenon

A New Targeted Password Guessing Model

TarGuess-I is a leading targeted password guessing model using users\u27 personally identifiable information(PII) proposed at ACM CCS 2016 by Wang et al. Owing to its superior guessing performance, TarGuess-I has attracted widespread attention in password security. Yet, TarGuess-I fails to capture popular passwords and special strings in passwords correctly. Thus we propose TarGuess-I$^+$: an improved password guessing model, which is capable of identifying popular passwords by generating top-300 most popular passwords from similar websites and grasping special strings by extracting continuous characters from user-generated PII. We conduct a series of experiments on 6 real-world leaked datasets and the results show that our improved model outperforms TarGuess-I by 9.07\% on average with 1000 guesses, which proves the effectiveness of our improvements

Machine-Learning Recognition of Dzyaloshinskii-Moriya Interaction from Magnetometry

The Dzyaloshinskii-Moriya interaction (DMI), which is the antisymmetric part of the exchange interaction between neighboring local spins, winds the spin manifold and can stabilize non-trivial topological spin textures. Since topology is a robust information carrier, characterization techniques that can extract the DMI magnitude are important for the discovery and optimization of spintronic materials. Existing experimental techniques for quantitative determination of DMI, such as high-resolution magnetic imaging of spin textures and measurement of magnon or transport properties, are time consuming and require specialized instrumentation. Here we show that a convolutional neural network can extract the DMI magnitude from minor hysteresis loops, or magnetic "fingerprints" of a material. These hysteresis loops are readily available by conventional magnetometry measurements. This provides a convenient tool to investigate topological spin textures for next-generation information processing

Detection and differentiation of Borrelia burgdorferi sensu lato in ticks collected from sheep and cattle in China

<p>Abstract</p> <p>Background</p> <p>Lyme disease caused by <it>Borrelia burgdorferi </it>sensu lato complex is an important endemic zoonosis whose distribution is closely related to the main ixodid tick vectors. In China, isolated cases of Lyme disease infection of humans have been reported in 29 provinces. Ticks, especially ixodid ticks are abundant and a wide arrange of <it>Borrelia </it>natural reservoirs are present. In this study, we developed a reverse line blot (RLB) to identify <it>Borrelia </it>spp. in ticks collected from sheep and cattle in 7 Provinces covering the main extensive livestock regions in China.</p> <p>Results</p> <p>Four species-specific RLB oligonucleotide probes were deduced from the spacer region between the 5S-23S rRNA gene, along with an oligonucleotide probe which was common to all. The species specific probes were shown to discriminate between four genomic groups of <it>B. burgdorferi </it>sensu lato i.e. <it>B. burgdorferi </it>sensu stricto, <it>B. garinii, B. afzelii</it>, and <it>B. valaisiana</it>, and to bind only to their respective target sequences, with no cross reaction to non target DNA. Furthermore, the RLB could detect between 0.1 pg and 1 pg of <it>Borrelia </it>DNA.</p> <p>A total of 723 tick samples (<it>Haemaphysalis, Boophilus, Rhipicephalus </it>and <it>Dermacentor</it>) from sheep and cattle were examined with RLB, and a subset of 667 corresponding samples were examined with PCR as a comparison. The overall infection rate detected with RLB was higher than that of the PCR test.</p> <p>The infection rate of <it>B. burgdoreri </it>sensu stricto was 40% in south areas; while the <it>B. garinii infection rate </it>was 40% in north areas. The highest detection rates of <it>B. afzelii </it>and <it>B. valaisiana </it>were 28% and 22%, respectively. Mixed infections were also found in 7% of the ticks analyzed, mainly in the North. The proportion of <it>B. garinii </it>genotype in ticks was overall highest at 34% in the whole investigation area.</p> <p>Conclusion</p> <p>In this study, the RLB assay was used to detect <it>B. burgdorferi </it>sensu lato in ticks collected from sheep and cattle in China. The results showed that <it>B. burdorferi senso stricto </it>and <it>B. afzelii </it>were mainly distributed in the South; while <it>B. garinii </it>and <it>B. valaisiana </it>were dominant in the North. <it>Borrelia </it>spirochaetes were detected in <it>Rhipicephalus </it>spp for the first time. It is suggested that the <it>Rhipicephalus </it>spps might play a role in transmitting <it>Borrelia </it>spirochaetes.</p

Research capacity of global health institutions in China: a gap analysis focusing on their collaboration with other low-income and middle-income countries.

INTRODUCTION: This paper presented qualitative and quantitative data collected on the research capacity of global health institutions in China and aimed to provide a landscaping review of the development of global health as a new discipline in the largest emerging economy of the world. METHODS: Mixed methods were used and they included a bibliometric analysis, a standardised survey and indepth interviews with top officials of 11 selected global health research and educational institutions in mainland China. RESULTS: The bibliometric analysis revealed that each institution had its own focus areas, some with a balanced focus among chronic illness, infectious disease and health systems, while others only focused on one of these areas. Interviews of key staff from each institution showed common themes: recognition that the current research capacity in global health is relatively weak, optimism towards the future, as well as an emphasis on mutual beneficial networking with other countries. Specific obstacles raised and the solutions applied by each institution were listed and discussed. CONCLUSION: Global health institutions in China are going through a transition from learning and following established protocols to taking a more leading role in setting up China's own footprint in this area. Gaps still remain, both in comparison with international institutions, as well as between the leading Chinese institutions and those that have just started. More investment needs to be made, from both public and private domains, to improve the overall capacity as well as the mutual learning and communication within the academic community in China