nCoV) infections in children. MATERIALS AND METHODS: The clinical characteristics and radiological findings (chest radiography and chest computed tomography [CT]) of nine children infected with the 2019-nCoV were reviewed in this retrospective case series. RESULTS: Among the children, six had fever (including two children with cough), one had only cough, one had a stuffy nose when initially diagnosed, and one was an asymptomatic carrier. Chest radiographs seemed mostly normal in six cases whereas increased and/or disordered bilateral bronchovascular shadows and dense hilar shadows were seen in three cases. Chest CT exhibited no obvious abnormal signs in four cases. Typical CT findings included patchy, peripheral ground-grass opacities, subpleural lamellar dense shadows, and parenchymal bands. Pleural effusions, mediastinal lymphadenopathy, cavitation, and pleural thickening were absent. CONCLUSION: The clinical manifestations and radiological findings of the 2019-nCoVinfected children were mild and lacked a typical pattern.

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Quantifying movement variability is a crucial aspect for clinical and laboratory investigations in several contexts. However, very few studies have assessed, in detail, the intra-subject variability across movements and the inter-subject variability. Muscle synergies are a valuable method that can be used to assess such variability. In this study, we assess, in detail, intra-subject and inter-subject variability in a scenario based on a comprehensive dataset, including multiple repetitions of multi-directional reaching movements. The results show that muscle synergies are a valuable tool for quantifying variability at the muscle level and reveal that intra-subject variability is lower than inter-subject variability in synergy modules and related temporal coefficients, and both intra-subject and inter-subject similarity are higher than random synergy matching, confirming shared underlying control structures. The study deepens the available knowledge on muscle synergy-based motor function assessment and rehabilitation applications, discussing their applicability to real scenarios.

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Fleet characteristics of the highest-fuel-consuming vehicle types by GVWR class and body type in each vehicle subcategory, based on 2002 VIUS data .