308 research outputs found

    The normal-auxeticity mechanical phase transition in graphene

    Get PDF
    When a solid object is stretched, in general, it shrinks transversely. However, the abnormal ones are auxetic, which exhibit lateral expansion, or negative Poisson ratio. While graphene is a paradigm 2D material, surprisingly, graphene converts from normal to auxetic at certain strains. Here, we show via molecular dynamics simulations that the normal-auxeticity mechanical phase transition only occurs in uniaxial tension along the armchair direction or the nearest neighbor direction. Such a characteristic persists at temperatures up to 2400 K. Besides monolayer, bilayer and multi-layer graphene also possess such a normal-auxeticity transition. This unique property could extend the applications of graphene to new horizons

    A 3D Wide Passband Frequency Selective Surface with Sharp Roll-off Sidebands and Angular Stability

    Get PDF

    Divergent changes in particulate and mineral-associated organic carbon upon permafrost thaw

    Get PDF
    Acknowledgements This work was supported by the National Natural Science Foundation of China (31988102, 31825006, 91837312, and 32101332), the Second Tibetan Plateau Scientific Expedition and Research (STEP) program (2019QZKK0106 and 2019QZKK0302), and the Fundamental Research Foundation of Chinese Academy of Forestry (CAFYBB2020MA008).Peer reviewedPublisher PD

    A Novel Cross-layer Communication Protocol for Vehicular Sensor Networks

    Get PDF
    Communication protocols in Vehicular Sensor Networks (VSNs) in urban areas play an important role in intelligent transport systems applications. Many cross layer communication protocols studies are originated from topology-based algorithms, which is not suitable for the frequently-changing computational scenario. In addition, the influence factors that have been considered for VSNs routing are not enough. With these aspects in mind, this paper proposes a multi-factor cross layer position-based routing (MCLPR) protocol for VSNs to improve reliability and efficiency in message delivery. Considering the complex intersection environment, the algorithm for vehicles selection at intersections (called AVSI) is further proposed, in which comprehensive factors are taken into account including the position and direction of vehicle, the vehicle density, the signal-to-noise-plus-interference ratio (SNIR), as well as the frame error rate (FER) in MAC layer. Meanwhile, the dynamic HELLO STREAM broadcasting system with the various vehicle speeds is proposed to increase the decisions accuracy. Experimental results in Network Simulator 3 (NS-3) show the advantage of MCLPR protocol over traditional state-of the-art algorithms in terms of packet delivery ratio (PDR), overhead and the mean end-to-end delay

    Application of Ambient Ionization Mass Spectrometry in Forensic Toxicological Analysis

    Get PDF
    Ambient ionization mass spectrometry(AIMS)is a mass spectrometry technology which could be used to analyze target analytes in samples under atmospheric pressure without or with simple sample pretreatment. With the advantages of simplicity, rapidness, non-destructiveness and wide application range, it is widely used in forensic toxicological analysis. This article gives a brief over- view on the ambient ionization(AI)technique, and the samples are divided into two types: in vivo test materials and in vitro test materials. The application of AIMS in the poison analysis of different types of test materials is summarized, and its application direction in forensic toxicological analysis is prospected

    Therapeutic effects of neuregulin-1 in diabetic cardiomyopathy rats

    Get PDF
    BACKGROUND: Diabetic cardiomyopathy (DCM) is a disorder of the heart muscle in people with diabetes, which is characterized by both systolic and diastolic dysfunction. The effective treatment strategy for DCM has not been developed. METHODS: Rats were divided into 3 groups with different treatment. The control group was only injected with citrate buffer (n = 8). The diabetes group and diabetes treated group were injected with streptozotocin to induce diabetes. After success of diabetes induction, the rats with diabetes were treated with (diabetes treated group, n = 8) or without (diabetes group, n = 8) recombinant human Neuregulin-1 (rhNRG-1). All studies were carried out 16 weeks after induction of diabetes. Cardiac catheterization was performed to evaluate the cardiac function. Apoptotic cells were determined by TUNEL staining. Left ventricular (LV) sections were stained with Masson to investigate myocardial collagen contents. Related gene expressions were analyzed by quantitative real-time PCR (qRT-PCR). RESULTS: Diabetes impaired cardiac function manifested by reduced LV systolic pressure (LVSP), maximum rate of LV pressure rise and fall (+dp/dt max and -dp/dt max) and increased LV end-diastolic pressure (LVEDP). The rhNRG-1 treatment could significantly alleviate these symptoms and improve heart function. More TUNEL staining positive cells were observed in the diabetic group than that in the control group, and the rhNRG-1 treatment decreased apoptotic cells number. Furthermore, qRT-PCR assay demonstrated that rhNRG-1 treatment could decrease the expression of bax and caspase-3 and increase that of bcl-2. Collagen volume fraction was higher in the diabetic group than in the control group. Fibrotic and fibrotic related mRNA (type I and type III collagen) levels in the myocardium were significantly reduced by administration of rhNRG-1. CONCLUSION: rhNRG-1 could significantly improve the heart function and reverse the cardiac remodeling of DCM rats with chronic heart failure. These results support the clinical possibility of applying rhNRG-1 as an optional therapeutic strategy for DCM treatment in the future

    Motion Planning for Autonomous Driving: The State of the Art and Future Perspectives

    Full text link
    Thanks to the augmented convenience, safety advantages, and potential commercial value, Intelligent vehicles (IVs) have attracted wide attention throughout the world. Although a few autonomous driving unicorns assert that IVs will be commercially deployable by 2025, their implementation is still restricted to small-scale validation due to various issues, among which precise computation of control commands or trajectories by planning methods remains a prerequisite for IVs. This paper aims to review state-of-the-art planning methods, including pipeline planning and end-to-end planning methods. In terms of pipeline methods, a survey of selecting algorithms is provided along with a discussion of the expansion and optimization mechanisms, whereas in end-to-end methods, the training approaches and verification scenarios of driving tasks are points of concern. Experimental platforms are reviewed to facilitate readers in selecting suitable training and validation methods. Finally, the current challenges and future directions are discussed. The side-by-side comparison presented in this survey not only helps to gain insights into the strengths and limitations of the reviewed methods but also assists with system-level design choices.Comment: 20 pages, 14 figures and 5 table
    corecore