Abbreviations (no more than 10): CT = Computed Tomography CXR = Chest radiograph RT-PCR = Reverse Transcription Polymerase Chain Reaction SARS = Severe acute respiratory syndrome Key Results: 1. Chest radiograph and CT findings of 21 patients with confirmed 2019 novel coronavirus infection in Shenzhen and Hong Kong are described and compared 2. A literature review and tabulation of the radiographic features in original publications are presented 3. One asymptomatic patient had evidence of consolidation on chest CT Abstract: Background: COVID-19 (formerly known as the 2019 novel coronavirus [2019-nCoV]) has rapidly spread in mainland China and into multiple countries worldwide. The radiographic profile of this infection continues to evolve as more cases present beyond the epicenter of Wuhan, China. Purpose: We present 21 COVID-19 cases from two Chinese centers with CT and chest radiograph (CXR) findings, as well as follow-up imaging in 5 cases. Materials and Methods: Retrospective study in Shenzhen and Hong Kong. Patients with COVID-19 infection were included. A systematic review of the published literature on COVID-19 infection's radiological features. Results: The predominant imaging pattern is of ground-glass opacification with occasional consolidation in the peripheries. Pleural effusions and lymphadenopathy were absent in all cases. Patients demonstrate evolution of the ground-glass opacities into consolidation, and subsequent resolution of the airspaces changes. Ground-glass and consolidative opacities visible on CT are sometimes undetectable on chest radiographs, suggesting that CT is a more sensitive imaging modality for investigation. The systematic review identified 4 other studies confirming the findings of bilateral and peripheral ground glass with or without consolidation as the predominant finding on CT chest examinations. Conclusion: The COVID-19 infection pulmonary manifestation is predominantly characterized by ground-glass opacification with occasional consolidation on CT. Radiographic findings in patients presenting in Shenzhen and Hong Kong are in keeping with 4 previous publications from other sites.

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to water penetrating and permissibility of vapor transmitting. [ 1 ] According to the previous researches, the fascinating properties of breathable and waterproof performance would be mainly come from the porous structure consisted of hydrophobic raw materials. [ 2 ] Therefore, it has developed various methods to fabricate membranes with outstanding breathable and waterproof performance, such as biaxial stretching, [ 3 ] template-based methods, [ 4 ] and phase separation. [ 5 ] Nevertheless, these methods are still subjected to the diffi culty in regulating the porous structure to achieve best equilibrium of breathable and waterproof performance, as well as the complicated fabricating procedure.Recently, electrospinning method that could obtain fi brous membranes with tunable porous structure has been considered as an available strategy for preparing membranes with breathable and waterproof performance. [ 6 ] Consequently, many kinds of electrospun breathable and waterproof membranes have been prepared using various polymers, including poly urethane (PU), [ 7 ] polyvinylidene fl uoride, [ 8 ] polyacrylonitrile, [ 9 ] and polypropylene. [ 10 ] Among these studies, PU has gained the most attention owing to the prominent elasticity and abrasive resistance, which is important for the practical application. [ 11 ] However, on account of the bad hydrophobicity and relative large fi ber diameter, the electrospun PU membranes in the previous studies exhibited either poor breathability (water vapor transmission (WVT) rate ≤5 kg m −2 d −1 ) or inferior waterproofness (hydrostatic pressure ≤10 kPa). [ 7,12 ] Our group has reported a fabrication strategy of waterproof and breathable fi brous membranes by introducing of hydrophobic PU and carbon nanotubes. Benefi ting from the low surface energy property of PU and hierarchical roughness built from carbon nanotubes, the membranes exhibit high WVT rate (9.2 kg m −2 d −1 ) and hydrostatic pressure (108 kPa). [ 13 ] But, carbon nanotubes are hard to be dispersed in polymer solution and easy to aggregate during electrospinning, which would bring about enormous degradation of performance. Therefore, it is remain a serious challenge to develop an effective and facile strategy to fabricate membranes with outstanding breathable and waterproof performance.It is well known that the electrospun membranes are constructed from randomly accumulating of fi bers, which result Breathable and waterproof membranes have great importance in various applications due to their permissibility of vapor transmitting and resistance to water penetrating. Despite the available strategies, it remains a serious challenge to fabricate membranes with best equilibrium of breathable and waterproof performance. Herein, hydrophobic fi brous membranes have been designed and prepared via electrospinning using polyurethane and fl uorinated polyurethane as the raw polymers. By regulating the relative humidity and electrospinning time, fi brous membranes with tunable porous structure have obtained. Signifi cantly...

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Accurate state-of-charge (SOC) estimation is critical for driving range prediction of electric vehicles and optimal charge control of batteries. In this paper, a stacked long short-term memory network is proposed to model the complex dynamics of lithium iron phosphate batteries and infer battery SOC from current, voltage, and temperature measurements. The proposed network is trained and tested using data collected from the dynamic stress test, US06 test, and federal urban driving schedule. The performance on SOC estimation is evaluated regarding tracking accuracy, computation time, robustness against unknown initial states, and compared with results from the model-based filtering approach (unscented Kalman filter). Moreover, different training and testing data sets are constructed to test its robustness against varying loading profiles. The experimental results show that the proposed network well captures the nonlinear correlation between SOC and measurable signals and provides better tracking performance than the unscented Kalman filter. In case of inaccurate initial SOCs, the proposed network presents quick convergence to the true SOC, with root mean square errors within 2% and mean average errors within 1%. Moreover, the estimation time at each time step is sub-millisecond, making it appropriate for real-time applications. INDEX TERMS State-of-charge estimation, lithium iron phosphate batteries, long short-term memory, recurrent neural network, unscented Kalman filter.