pneumonia" OR " coronavirus"), AND " Myocarditis" OR " Cycle threshold (Ct)" OR " Altitude". We found that one article analyzed the risk factors affecting the prognosis of adult patients with COVID-19 in terms of survivorship, without considering Ct values as extrinsic factors.Moreover, there are no reported studies on viral myocarditis caused by COVID-19 and the relationship between the altitude and COVID-19. Added value of this studyWe retrospectively analyzed the clinical data, Ct values, laboratory indicators and imaging findings of 84 adult patients with confirmed COVID-19. Three key-independent risk factors of COVID-19 were identified in our study, including age [OR 2.350; 95% CI (1.206 to 4.580); p=0.012], Ct value [OR 0.158; 95% CI (0.025 to 0.987); p=0.048] and PII [OR 1.912; 95% CI (1.187 to 3.079); p=0.008]. Amongst 84 patients, 13 patients (15.48%) were noted with abnormal electrocardiograms (ECGs) and serum myocardial enzyme levels; whereas 4 (4.8%) were clinically diagnosed as SARS-CoV-2 myocarditis. Moreover, altitude should be considered for COVID-19 severity classification, given that oxygen partial pressure and blood oxygen saturation of regional patients vary with altitudes.

This article investigates a resource allocation problem of second‐order nonlinear multiagent systems. The resource allocation problem arises from many fields such as economic dispatch, network utility maximization, and demand response. Due to the dynamics of agents, we cannot solve this problem by using existing resource allocation algorithms. In order to achieve the optimal allocation, we propose a distributed protocol for agents based on gradient descent. Besides, we analyze the global convergence of the algorithm by constructing a suitable Lyapunov function. Finally, we provide examples to illustrate our result.

SummaryIn this paper, we study the resource allocation problem of second‐order multiagent systems with exogenous disturbances, and the communication networks are weight‐balanced digraphs. Different from the well‐studied resource allocation problems, our problem involves the disturbed second‐order dynamics of agents. In order to achieve the optimal allocation, we propose a distributed algorithm based on gradient descent and internal model approach. Furthermore, we analyze the convergence of the algorithm by constructing a suitable Lyapunov function. Moreover, we prove that the agents in the network can achieve the exact optimal allocation even in the presence of external disturbances. Finally, we provide two examples to illustrate our result.

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Planar waveguides in x-cut YVO4 crystals were produced by ion-implanted Si+ ions with energies from 2.6 to 3.0 MeV at doses of 1×1013−1.5×1014 ions/cm2. The number of propagation modes varied from 1 to 3 as the doses of the implanted ions increased. The effective refractive indices of all the observed waveguide modes were higher than the refractive index of the substrate, which meant an index-enhanced guiding layer with thickness of ∼2 μm formed to confine the light propagation. The minimum propagation loss of the measured YVO4 waveguide was 0.27 dB/cm after annealing under suitable conditions.

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