Results:A total of 100 (76%) patients had a history of close contact with people living in Wuhan, Hubei. The clinical manifestations of COVID-19 included cough, fever. Most of the lesions identified in chest CT images were multiple lesions of bilateral lungs, lesions were more localized in the peripheral lung, 109 (83%) patients had more than two lobes involved, 20 (15%) patients presented with patchy ground glass opacities, patchy ground glass opacities and consolidation of lesions co-existing in 61 (47%) cases. Complications such as pleural thickening, hydrothorax, pericardial effusion, and enlarged mediastinal lymph nodes were detected but only in rare cases. For the follow-up chest CT examinations (91 cases), We found 66 (73%) cases changed very quickly, with an average of 3.5 days, 25 cases (27%) presented absorbed lesions, progression was observed in 41 cases (46%), 25 (27%) cases showed no significant changes. Conclusion:Chest CT plays an important role in diagnosing COVID-19. The imaging pattern of multifocal peripheral ground glass or mixed consolidation is highly suspicious of COVID-19, that can quickly change over a short period of time.

High-temperature during flowering in rice causes spikelet sterility and is a major threat to rice productivity in tropical and subtropical regions, where hybrid rice development is increasingly contributing to sustain food security. However, the sensitivity of hybrids to increasing temperature and physiological responses in terms of dynamic fertilization processes is unknown. To address these questions, several promising hybrids and inbreds were exposed to control temperature and high day-time temperature (HDT) in Experiment 1, and hybrids having contrasting heat tolerance were selected for Experiment 2 for further physiological investigation under HDT and high-night-time-temperature treatments. The day-time temperature played a dominant role in determining spikelet fertility compared with the night-time temperature. HDT significantly induced spikelet sterility in tested hybrids, and hybrids had higher heat susceptibility than the high-yielding inbred varieties. Poor pollen germination was strongly associated with sterility under high-temperature. Our novel observations capturing the series of dynamic fertilization processes demonstrated that pollen tubes not reaching the viable embryo sac was the major cause for spikelet sterility under heat exposure. Our findings highlight the urgent need to improve heat tolerance in hybrids and incorporating early-morning flowering as a promising trait for mitigating HDT stress impact at flowering.

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Accurate regional and global information on land cover and its changes over time is crucial for environmental monitoring, land management, and planning. In this study, we selected Fengning County, in China's Hebei Province, as a case study area. Using satellite data, we generated fused normalized-difference vegetation index (NDVI) data with high spatial and temporal resolution by utilizing the STARFM algorithm to produce a fused GF-1 and MODIS NDVI dataset. We extracted seven phenological parameters (including the start, end, and length of the growing season, base value, mid-season date, maximum NDVI, seasonal NDVI amplitude) from a fused NDVI time-series after reconstruction using the TIMESAT software. We developed four classification scenarios based on different combinations of GF-1 spectral features, the fused NDVI time-series, and the phenological parameters. We then classified the land cover using a support vector machine and analyzed the classification accuracies. We found that the proposed method achieved satisfactory classification results, and that the combination of the fused NDVI data with the extracted phenological parameters significantly improved classification accuracy. The classification accuracy based on the composited GF-1 multi-spectral bands combined with the phenological parameters was the highest among the four scenarios, with an overall classification accuracy of 88.8% and a Kappa coefficient of 0.8714, which represent increases of 9.3 percentage points and 0.1073, respectively, compared with GF-1 spectral data alone. The producer's and user's accuracy for different land cover types improved, with a few exceptions, and cropland and broadleaf forest had the largest increase.

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