Jianghan University

About: Jianghan University is a education organization based out in Wuhan, China. It is known for research contribution in the topics: Catalysis & Materials science. The organization has 3387 authors who have published 3216 publications receiving 35397 citations. The organization is also known as: Jiānghàn Dàxúe.

Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.

Abstract: Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to detect COVID-19 using chest CT and evaluate its performance. Materials and Methods In this retrospective and multicenter study, a deep learning model, the COVID-19 detection neural network (COVNet), was developed to extract visual features from volumetric chest CT scans for the detection of COVID-19. CT scans of community-acquired pneumonia (CAP) and other non-pneumonia abnormalities were included to test the robustness of the model. The datasets were collected from six hospitals between August 2016 and February 2020. Diagnostic performance was assessed with the area under the receiver operating characteristic curve, sensitivity, and specificity. Results The collected dataset consisted of 4352 chest CT scans from 3322 patients. The average patient age (±standard deviation) was 49 years ± 15, and there were slightly more men than women (1838 vs 1484, respectively; P = .29). The per-scan sensitivity and specificity for detecting COVID-19 in the independent test set was 90% (95% confidence interval [CI]: 83%, 94%; 114 of 127 scans) and 96% (95% CI: 93%, 98%; 294 of 307 scans), respectively, with an area under the receiver operating characteristic curve of 0.96 (P < .001). The per-scan sensitivity and specificity for detecting CAP in the independent test set was 87% (152 of 175 scans) and 92% (239 of 259 scans), respectively, with an area under the receiver operating characteristic curve of 0.95 (95% CI: 0.93, 0.97). Conclusion A deep learning model can accurately detect coronavirus 2019 and differentiate it from community-acquired pneumonia and other lung conditions. © RSNA, 2020 Online supplemental material is available for this article.

Poly(ethylene oxide)-based electrolytes for lithium-ion batteries

Abstract: Poly(ethylene oxide) (PEO) based materials are widely considered as promising candidates of polymer hosts in solid-state electrolytes for high energy density secondary lithium batteries. They have several specific advantages such as high safety, easy fabrication, low cost, high energy density, good electrochemical stability, and excellent compatibility with lithium salts. However, the typical linear PEO does not meet the production requirement because of its insufficient ionic conductivity due to the high crystallinity of the ethylene oxide (EO) chains, which can restrain the ionic transition due to the stiff structure especially at low temperature. Scientists have explored different approaches to reduce the crystallinity and hence to improve the ionic conductivity of PEO-based electrolytes, including blending, modifying and making PEO derivatives. This review is focused on surveying the recent developments and issues concerning PEO-based electrolytes for lithium-ion batteries.

Clinical characteristics of novel coronavirus cases in tertiary hospitals in Hubei Province.

Abstract: BACKGROUND: The 2019 novel coronavirus (2019-nCoV) causing an outbreak of pneumonia in Wuhan, Hubei province of China was isolated in January 2020. This study aims to investigate its epidemiologic history, and analyze the clinical characteristics, treatment regimens, and prognosis of patients infected with 2019-nCoV during this outbreak. METHODS: Clinical data from 137 2019-nCoV-infected patients admitted to the respiratory departments of nine tertiary hospitals in Hubei province from December 30, 2019 to January 24, 2020 were retrospectively collected, including general status, clinical manifestations, laboratory test results, imaging characteristics, and treatment regimens. RESULTS: None of the 137 patients (61 males, 76 females, aged 20-83 years, median age 57 years) had a definite history of exposure to Huanan Seafood Wholesale Market. Major initial symptoms included fever (112/137, 81.8%), coughing (66/137, 48.2%), and muscle pain or fatigue (44/137, 32.1%), with other, less typical initial symptoms observed at low frequency, including heart palpitations, diarrhea, and headache. Nearly 80% of the patients had normal or decreased white blood cell counts, and 72.3% (99/137) had lymphocytopenia. Lung involvement was present in all cases, with most chest computed tomography scans showing lesions in multiple lung lobes, some of which were dense; ground-glass opacity co-existed with consolidation shadows or cord-like shadows. Given the lack of effective drugs, treatment focused on symptomatic and respiratory support. Immunoglobulin G was delivered to some critically ill patients according to their conditions. Systemic corticosteroid treatment did not show significant benefits. Notably, early respiratory support facilitated disease recovery and improved prognosis. The risk of death was primarily associated with age, underlying chronic diseases, and median interval from the appearance of initial symptoms to dyspnea. CONCLUSIONS: The majority of patients with 2019-nCoV pneumonia present with fever as the first symptom, and most of them still showed typical manifestations of viral pneumonia on chest imaging. Middle-aged and elderly patients with underlying comorbidities are susceptible to respiratory failure and may have a poorer prognosis.

Efficient and stable perovskite solar cells prepared in ambient air irrespective of the humidity.

Abstract: Poor stability of organic-inorganic halide perovskite materials in humid condition has hindered the success of perovskite solar cells in real applications since controlled atmosphere is required for device fabrication and operation, and there is a lack of effective solutions to this problem until now. Here we report the use of lead (II) thiocyanate (Pb(SCN)2) precursor in preparing perovskite solar cells in ambient air. High-quality CH3NH3PbI3-x(SCN)x perovskite films can be readily prepared even when the relative humidity exceeds 70%. Under optimized processing conditions, we obtain devices with an average power conversion efficiency of 13.49% and the maximum efficiency over 15%. In comparison with typical CH3NH3PbI3-based devices, these solar cells without encapsulation show greatly improved stability in humid air, which is attributed to the incorporation of thiocyanate ions in the crystal lattice. The findings pave a way for realizing efficient and stable perovskite solar cells in ambient atmosphere.

Enhanced Catalysis of Electrochemical Overall Water Splitting in Alkaline Media by Fe Doping in Ni3S2 Nanosheet Arrays

Abstract: The development of bifunctional electrocatalysts with high performance for both hydrogen evolution reaction (HER) and oxygen evolution reaction (OER) with earth-abundant elements is still a challenge in electrochemical water splitting technology. Herein, we fabricated a free-standing electrocatalyst in the form of vertically oriented Fe-doped Ni3S2 nanosheet array grown on three-dimensional (3D) Ni foam (Fe-Ni3S2/NF), which presented a high activity and durability for both HER and OER in alkaline media. On the basis of systematic experiments and calculation, the Fe-doping was evidenced to increase the electrochemical surface area, improve the water adsorption ability, and optimize the hydrogen adsorption energy of Ni3S2, which resulted in the enhancement of HER activity on Fe-Ni3S2/NF. Moreover, metal sites of Fe-Ni3S2/NF were proved to play a significant role in the HER process. During the catalysis of OER, the formation of Ni–Fe (oxy)hydroxide was observed on the near-surface section of Fe-Ni3S2/NF, and...