Background Nirmatrelvir–ritonavir has been authorized for emergency use by many countries for the treatment of coronavirus disease 2019 (Covid-19). However, the supply falls short of the global demand, which creates a need for more options. VV116 is an oral antiviral agent with potent activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods We conducted a phase 3, noninferiority, observer-blinded, randomized trial during the outbreak caused by the B.1.1.529 (omicron) variant of SARS-CoV-2. Symptomatic adults with mild-to-moderate Covid-19 with a high risk of progression were assigned to receive a 5-day course of either VV116 or nirmatrelvir–ritonavir. The primary end point was the time to sustained clinical recovery through day 28. Sustained clinical recovery was defined as the alleviation of all Covid-19–related target symptoms to a total score of 0 or 1 for the sum of each symptom (on a scale from 0 to 3, with higher scores indicating greater severity; total scores on the 11-item scale range from 0 to 33) for 2 consecutive days. A lower boundary of the two-sided 95% confidence interval for the hazard ratio of more than 0.8 was considered to indicate noninferiority (with a hazard ratio of >1 indicating a shorter time to sustained clinical recovery with VV116 than with nirmatrelvir–ritonavir). Results A total of 822 participants underwent randomization, and 771 received VV116 (384 participants) or nirmatrelvir–ritonavir (387 participants). The noninferiority of VV116 to nirmatrelvir–ritonavir with respect to the time to sustained clinical recovery was established in the primary analysis (hazard ratio, 1.17; 95% confidence interval [CI], 1.01 to 1.35) and was maintained in the final analysis (median, 4 days with VV116 and 5 days with nirmatrelvir–ritonavir; hazard ratio, 1.17; 95% CI, 1.02 to 1.36). In the final analysis, the time to sustained symptom resolution (score of 0 for each of the 11 Covid-19–related target symptoms for 2 consecutive days) and to a first negative SARS-CoV-2 test did not differ substantially between the two groups. No participants in either group had died or had had progression to severe Covid-19 by day 28. The incidence of adverse events was lower in the VV116 group than in the nirmatrelvir–ritonavir group (67.4% vs. 77.3%). Conclusions Among adults with mild-to-moderate Covid-19 who were at risk for progression, VV116 was noninferior to nirmatrelvir–ritonavir with respect to the time to sustained clinical recovery, with fewer safety concerns. (Funded by Vigonvita Life Sciences and others; ClinicalTrials.gov number, NCT05341609 ; Chinese Clinical Trial Registry number, ChiCTR2200057856.)

Color constancy is an important perceptual ability of humans to recover the color of objects invariant of light information. It is also necessary for a robust machine vision system. Until now, a number of color constancy algorithms have been proposed in the literature. In particular, the edge-based color constancy uses the edge of an image to estimate light color. It is shown to be a rich framework that can represent many existing illumination estimation solutions with various parameter settings. However, color constancy is an ill-posed problem; every algorithm is always given out under some assumptions and can only produce the best performance when these assumptions are satisfied. In this article, we have investigated a combination strategy relying on the Extreme Learning Machine (ELM) technique that integrates the output of edge-based color constancy with multiple parameters. Experiments on real image data sets show that the proposed method works better than most single-color constancy methods and even some current state-of-the-art color constancy combination strategies.

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Abstract:To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability.

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Composite indices of femoral neck strength may be valuable in the assessment of the biomechanics of bone fragility; however, they do not appear to add diagnostic value to the simple measurement of BMD.

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