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1.
Physics of Fluids ; 35(5), 2023.
Article in English | Web of Science | ID: covidwho-20241533

ABSTRACT

Understanding particle settlement in channeled fluids has wide applications, such as fine particulate matter, coronavirus particle transport, and the migration of solid particles in water. Various factors have been investigated but few studies have acknowledged the channel's effect on settlement dynamics. This study developed a coupled interpolated bounce-back lattice Boltzmann-discrete element model and examined how a channel's width affects particle settlement. A factor k denoting the ratio of the channel's width and the particle diameter was defined. The terminal settling velocity for a single particle is inversely proportional to k, and the time that the particle takes to reach the terminal velocity is positively related to k. When k is greater than 15, the channel width's effects are negligible. For dual particles of the same size, the drafting-kissing-tumbling (DKT) process occurs infinitely in a periodic pattern, with the two particles swapping positions and settling around the channel's centerline. The smaller the k, the sooner the DKT process occurs. The particles collide with the channel wall when k <= 10. For dual particles of different sizes, the DKT process occurs once so that the bigger particle leads the settlement. Both particles settle along the channel's centerline in a steady state. The bigger the k, the bigger the difference in their terminal settling velocities until k = 15. The small particle collides with the channel wall if released under the big particle when k = 6. The findings of this study are expected to inform channeling or pipeline design in relevant engineering practices.

2.
Cell Reports Physical Science ; 4(1), 2023.
Article in English | Scopus | ID: covidwho-2268911

ABSTRACT

Monitoring respiration is vital for personal diagnosis of chronic diseases. However, the existing respiratory sensors have severe limitations, such as single function, finite detection parameters, and lack of smart signal analysis. Here, we present an integrated wearable and low-cost smart respiratory monitoring sensor (RMS) system with artificial intelligence (AI)-assisted diagnosis of respiratory abnormality by detecting multi-parameters of human respiration. Coupling with intelligent analysis and data mining algorithms embedded in a phone app, the lighter system of 7.3 g can acquire real-time self-calibrated parameters, including breathing frequency, apnea hypopnea index (AHI), vital capacity (VC), peak expiratory flow (PEF), and other respiratory indexes with an accuracy >95.21%. The data can be wirelessly transferred to the user's data cloud terminal. The RMS system enables comprehensive multi-physiological parameters analysis for auxiliary diagnosing and classifying diseases, including sleep apnea, rhinitis, and chronic lung diseases, as well as rehabilitation of COVID-19, and exhibits advantages of portable healthcare. © 2022 The Authors

3.
Zhonghua Er Ke Za Zhi ; 60(11): 1153-1157, 2022 Nov 02.
Article in Chinese | MEDLINE | ID: covidwho-2099941

ABSTRACT

Objective: To investigate the diagnostic value of rapid antigen test based on colloidal gold immunochromatographic assay for the detection of SARS-CoV-2 infection in symptomatic patients. Methods: From May 20 to June 5 2022, 76 hospitalized children and their 55 accompanying family members with confirmed SARS-CoV-2 infection in the COVID-19 isolation unit of the Children's Hospital of Fudan University (designated referral hospital for SARS-CoV-2 infection in Shanghai) enrolled. Their nasopharyngeal swab specimens were consecutively collected. The samples were tested for SARS-CoV-2 nucleic acid by real-time quantitative. SARS-CoV-2 antigen was tested by immunochromatography. The correlation between the antigen detection results and the change of the cycle threshold (Ct) values were evaluated, as well as the sensitivity and specificity of SARS-CoV-2 antigen detection at different periods after the onset of the disease. Kappa consistency test was conducted to investigate the consistency between the 2 diagnostic methods. Results: Of the enrolled SARS-CoV-2 symptomatic infections, 76 were children, including 41 males and 35 females, with an age of 5 (2, 9) years; 55 were accompanying families, including 8 males and 47 females, with an age of 38 (32, 41) years. All 478 samples were simultaneously tested for SARS-CoV-2 antigen and nucleic acid. In any period from disease onset to negative conversion of viral nucleic acid, the overall sensitivity of the rapid antigen test was 48.2% (119/247), the specificity was 98.3% (227/231), and antigen test and nucleic acid test showed moderate consistency (κ=0.46, P<0.05). The sensitivity of antigen test was 100% (82/82) when the Ct value was ≤25. And the sensitivity of antigen test was 8/10, 4/15 and 8.3% (3/36) when the Ct value was 26, 30 and 35, respectively. All antigen tests were negative when Ct value was >35. During the period of 1-2 days, 3-5 days, 6-7 days, 8-10 days and >10 days after onset, the sensitivity and specificity of SARS-CoV-2 antigen test were 5/8 and 5/5, 90.2% (37/41) and 5/5, 88.9% (24/27) and 2/5, 45.0% (36/80) and 94.1% (32/34), 18.7% (17/91) and 98.9% (183/185) respectively. The Ct values of nasopharyngeal swabs were<26 during 2 to 7 days after onset, 28.7±5.0 on day 8, 34.5±2.9 on day 13 and > 35 after 14 days, respectively. Conclusion: SARS-CoV-2 antigen test in the patients with SARS-CoV-2 infection shows acceptable sensitivity and specificity within 7 days after onset of disease, and the sensitivity was positively correlated with viral load and negatively correlated with onset time.


Subject(s)
COVID-19 , Nucleic Acids , Male , Child , Female , Humans , SARS-CoV-2 , China , COVID-19 Testing
5.
Zhonghua Er Ke Za Zhi ; 60(11): 1212-1214, 2022 Nov 02.
Article in Chinese | MEDLINE | ID: covidwho-2099936

Subject(s)
COVID-19 , Child , Humans , Family
6.
Ecology and Society ; 27(3):10, 2022.
Article in English | Web of Science | ID: covidwho-1979578

ABSTRACT

Both anthropogenic and climatic factors are important determinants of landscape fire. Because the two groups of factors are intertwined and often act simultaneously, dissecting their effects on landscape fire is challenging. We used the COVID-19 lockdown event in Hubei, in which all immediate influences of anthropogenic factors were effectively removed, to quantify the effects of anthropogenic factors on landscape fire occurrence. We hypothesized that outdoor incense burning is the main causal factor of landscape fire. To test the hypothesis, we used random forest algorithm to model fire occurrence, including fire frequency, total area burned, and area of forest burned, for the lockdown period. We then estimated the differences between historical, simulated, and observed values of landscape fire and used the differences to represent the effects of anthropogenic activities on landscape fire. Our results showed that during the lockdown, landscape fire frequency was reduced by 77%, total area burned by 80%, and area of forest burned by 63%. By month, fire frequency decreased the most in April (85%), followed by February (80%), coinciding with the Qingming and Spring Festivals of 2020. The cessation of outdoor incense burning during the festival season was likely to be the most important factor that decreased fire occurrence, confirming our hypothesis about the causal relationship between outdoor incense-burning and landscape fire. Thus, educational programs encouraging people to stop outdoor incense burning during the festival season could reduce the occurrence of landscape fire.

7.
AIP Adv. ; 11(10):9, 2021.
Article in English | Web of Science | ID: covidwho-1475555

ABSTRACT

Deep ultraviolet light-emitting diodes (DUV LEDs) are promising light sources for disinfection, especially during the pandemic of novel coronavirus (COVID-19). Despite much effort in the development of DUV LEDs, the device temperature and ideality factor are key parameters of devices, which are often neglected. Here, we developed a simple and convenient method to study the behavior of a 280 nm AlGaN-based DUV LED, obtaining the electrical, optical, and thermal properties within one measurement. From the experimental results, we find that the light output power and wall-plug efficiency of the AlGaN-based DUV LED are strongly affected by device temperature, ideality factor (beta), and series resistance (R-s). beta decreases from 9.3 to 8.1 at 40 mA when the temperature increases from 302 to 317 K. We compared these results with simulations and found that the high potential barriers inside the device and the carrier concentration in n-type or p-type layers, especially the hole concentration in p-type layers, are the two key factors for the high value of the ideality factor from the LED structure. As the device temperature increases, carriers with higher energy would overcome some potential barriers and Mg acceptor activation would be more efficient, which are beneficial for carrier transportation. However, these also lead to the carrier overflow and weaken the radiative recombination rate. The trade-off role of device temperature in carriers between transportation and overflow is needed to be considered in the future development of DUV LEDs with higher efficiency and higher brightness.

8.
Ieee Transactions on Industrial Informatics ; 17(9):6528-6538, 2021.
Article in English | Web of Science | ID: covidwho-1307656

ABSTRACT

Automatic segmentation of lung lesions from COVID-19 computed tomography (CT) images can help to establish a quantitative model for diagnosis and treatment. For this reason, this article provides a new segmentation method to meet the needs of CT images processing under COVID-19 epidemic. The main steps are as follows: First, the proposed region of interest extraction implements patch mechanism strategy to satisfy the applicability of 3-D network and remove irrelevant background. Second, 3-D network is established to extract spatial features, where 3-D attention model promotes network to enhance target area. Then, to improve the convergence of network, a combination loss function is introduced to lead gradient optimization and training direction. Finally, data augmentation and conditional random field are applied to realize data resampling and binary segmentation. This method was assessed with some comparative experiment. By comparison, the proposed method reached the highest performance. Therefore, it has potential clinical applications.

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