The discovery of two-dimensional (2D) material graphene has opened a door towards a class of layered novel nanomaterials with unique photonic and optoelectronic properties. Recently many new 2D ...materials have been reported, including topological insulators (TIs), transition metal dichalcogenides (TMDs) and black phosphorus (BP). These materials have been demonstrated high optical nonlinearity and Pauli blocking used as saturable absorbers (SAs) in pulsed lasers. In this paper, we summarize the current specifications from these 2D materials based mode-locked and Q-switched lasers. The laser performance in operating wavelength, optical bandwidth, repetition rate and pulse energy is reviewed. Finally future perspective is suggested.
•Mode-locked and Q-switched lasers based on three 2D materials are reviewed.•Best specifications of bandwidth, repetition rate and pulse energy are summarized.•Material basic properties, fabrication and characterization are also introduced.
We demonstrate a proof-of-concept saturable absorption based pulsewidth measurement (SAPM) by exploring the intensity dependent nonlinear transmission (i.e., saturable absorption) of low-dimensional ...material (LDM) carbon nanotubes. A minimum pulse energy of 75 fJ is experimentally detected with an average-power-peak-power product (P
⋅ P
) of 5.44×10
W
near 1550 nm. A minimum detectable pulse energy of 10 fJ with a P
⋅ P
of 1.3×10
W
is estimated with further optimization. The nanometer-level thickness and femtosecond-level decay time of LDMs allow ultrafast light interaction on a very small footprint, which potentially supports chip-scale characterization of ultrafast pulses with minimum distortion.
This paper presents Balloon, a scalable blockchain consensus protocol which could dynamically adapt its performance to the overall computation power change. Balloon is based on a parallel chain ...architecture combined with a greedy heaviest sub-chain selection strategy. It adopts an inovative block sampling approach to assess the change of block generation rate in the network. By introducing view change mechanism, Balllon is able to dynamically adjust the number of parallel sub-chains. Balloon redefines the concept of block subtree weight with view change in consideration, so that a total order of blocks could be obtained safely. To deal with rapidly increasing block generation rate in the blockchain network, participants of previous Nakamoto-style protocols are required to continuously increase their mining difficulty so as to maintain an expected security gurantee. Balloon, however, could accomadate a fixed difficulty setup and assign superfluous block processing capability to new sub-chains, which makes it more open and also economical.
Supply chain finance can reduce the financing cost of enterprises, which is of great significance for promoting inclusive finance. However, there are many problems in the current supply chain ...finance, e.g., information asymmetry, inefficient financing, and high performance risk. In this paper, we propose a novel supply chain financial service platform based on blockchain technology. We first analyze the limitations of mainstream supply chain finance mode. Then, we introduce the proposed financial service platform in detail, including its components, operation process, and advantages. Toward the end, we discussed the future development trends of the platform. This paper is aimed at providing helpful guidance and reference for future research efforts.
Blockchain is considered to be one of the most promising transformational technologies in the era of digital economy, but it is still in the initial stage in tourism industry. Toward this end, in ...this paper, we put forward a systematic framework of tourism comprehensive service platform based on the blockchain technology. We first analyze the problems of the current tourism industry and the value of blockchain to it. Then, we introduce the proposed platform in detail, including its component modules and advantages. Lastly, we discuss the limitations and development trends of the platform. This paper is aimed at providing helpful guidance and reference for future research efforts.
We propose and demonstrate a novel pulsewidth measurement technology based on carbon nanotube saturable absorber which achieves a minimum pulse energy of 75 fJ and an average-power-peak-power product ...of 5.44×10 -7 W 2 near 1560 nm.
Quasi-autocorrelation system based on carbon-nanotube saturable absorber is demonstrated at l550nm with 75fJ pulses measured. The nanometer-level thickness and femtosecond-level decay time of ...nanomaterials allow compact and ultrafast light interaction for future chip-scale pulse characterization.
We discuss the potential of high-precision optical quantization based on soliton self-frequency shift. For a soliton pulse with optimal τ = 150 fs wide, 8-bit quantization is achievable with current ...optical technologies.
Elderly patients are susceptible to postoperative infections with increased mortality. Analyzing with a deep learning model, the perioperative factors that could predict and/or contribute to ...postoperative infections may improve the outcome in elderly. This was an observational cohort study with 2014 elderly patients who had elective surgery from 28 hospitals in China from April to June 2014. We aimed to develop and validate deep learning-based predictive models for postoperative infections in the elderly. 1510 patients were randomly assigned to be training dataset for establishing deep learning-based models, and 504 patients were used to validate the effectiveness of these models. The conventional model predicted postoperative infections was 0.728 (95% CI 0.688–0.768) with the sensitivity of 66.2% (95% CI 58.2–73.6) and specificity of 66.8% (95% CI 64.6–68.9). The deep learning model including risk factors relevant to baseline clinical characteristics predicted postoperative infections was 0.641 (95% CI 0.545–0.737), and sensitivity and specificity were 34.2% (95% CI 19.6–51.4) and 88.8% (95% CI 85.6–91.6), respectively. Including risk factors relevant to baseline variables and surgery, the deep learning model predicted postoperative infections was 0.763 (95% CI 0.681–0.844) with the sensitivity of 63.2% (95% CI 46–78.2) and specificity of 80.5% (95% CI 76.6–84). Our feasibility study indicated that a deep learning model including risk factors for the prediction of postoperative infections can be achieved in elderly. Further study is needed to assess whether this model can be used to guide clinical practice to improve surgical outcomes in elderly.
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