Highlights EMV-ID tracker is used to measure the infectious disease pandemic. GARCH-MIDAS is adopted to model the impacts of EMV-ID on stock market volatility. Lagged realized volatility and economic policy uncertainty are used as controlling variables. Infectious disease pandemic imposes significant positive impact on stock market volatility. Infectious disease pandemic has the smallest impact on permanent volatility of china's stock market.

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The success of artificial vascular graft in the host to obtain functional tissue regeneration and remodeling is a great challenge in the field of small diameter tissue engineering blood vessels. In our previous work, poly(ε-caprolactone) (PCL)/fibrin vascular grafts were fabricated by electrospinning. It was proved that the PCL/fibrin vascular graft was a suitable small diameter tissue engineering vascular scaffold with good biomechanical properties and cell compatibility. Here we mainly examined the performance of PCL/fibrin vascular graft in vivo. The graft showed randomly arranged nanofiber structure, excellent mechanical strength, higher compliance and degradation properties. At 9 months after implantation in the rat abdominal aorta, the graft induced the regeneration of neoarteries, and promoted ECM deposition and rapid endothelialization. More importantly, the PCL/fibrin vascular graft showed more microvessels density and fewer calcification areas at 3 months, which was beneficial to improve cell infiltration and proliferation. Moreover, the ratio of M2/M1macrophage in PCL/fibrin graft had a higher expression level and the secretion amount of pro-inflammatory cytokines started to increase, and then decreased to similar to the native artery. Thus, the electrospun PCL/fibrin tubular vascular graft had great potential to become a new type of artificial blood vessel scaffold that can be implanted in vivo for long term.

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Bradford Scholars -how to deposit your paper Overview Copyright check• Check if your publisher allows submission to a repository.• Use the Sherpa RoMEO database if you are not sure about your publisher's position or email openaccess@bradford.ac.uk.

Being more and more popular in the past 10 years, Bitcoin has drawn extensive attention from the press, scholars, and practitioners. The aim of this paper is to investigate which predictor is more predictive for Bitcoin volatility from the aspects of in-sample and out-of-sample in a high-speed changing world. We utilise the GARCH-MIDAS model to examine the predictive power of five crucial predictors, including VIX, GVZ, Google Trends, GEPU, and GPR. Our findings provide strong evidence that GVZ exhibits strongest predictability for Bitcoin volatility over other competing predictors. Other empirical results based on different out-of-sample forecasting periods, alternative loss functions and combination methods further ensure our major conclusions are robust.

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