ABSTRACT
This paper selects mainland China as the research area, studies the development status of children's musicals in the region, and puts forward five problems in the development of children's musicals in mainland China: First, the development level of children's musical shows regional, and the development field is unbalanced. Second,The creators of children's musicals who know drama don't know music, and those who know music don't know drama. Third, the creators do not have enough knowledge about children's development, so the works created do not meet children's unique requirements. Fourth, the market operation mechanism is not mature. Due to the COVID-19 pandemic, children's musicals have been stagnant for the past few years. By grasping the existing problems in the development of children's musicals in mainland China, this paper provides some suggestions for the creators and researchers engaged in this field. © 2022, Association Res Militaris. All rights reserved.
ABSTRACT
The Coronavirus disease (COVID-19) pandemic has caused social and economic crisis to the globe. Contact tracing is a proven effective way of containing the spread of COVID-19. In this paper, we propose CAPER, a Cellular-Assisted deeP lEaRning based COVID-19 contact tracing system based on cellular network channel state information (CSI) measurements. CAPER leverages a deep neural network based feature extractor to map cellular CSI to a neural network feature space, within which the Euclidean distance between points strongly correlates with the proximity of devices. By doing so, we maintain user privacy by ensuring that CAPER never propagates one client's CSI data to its server or to other clients. We implement a CAPER prototype using a software defined radio platform, and evaluate its performance in a variety of real-world situations including indoor and outdoor scenarios, crowded and sparse environments, and with differing data traffic patterns and cellular configurations in common use. Microbenchmarks show that our neural network model runs in 12.1 microseconds on the OnePlus 8 smartphone. End-to-end results demonstrate that CAPER achieves an overall accuracy of 93.39%, outperforming the accuracy of BLE based approach by 14.96%, in determining whether two devices are within six feet or not, and only misses 1.21% of close contacts. CAPER is also robust to environment dynamics, maintaining an accuracy of 92.35% after running for ten days. © 2022 Owner/Author.
ABSTRACT
Our understanding of COVID-19 pandemic epidemiology has many gaps, with many challenges arising on a global scale. This paper looks at the problem at a smaller geo-graphical scale, the extent of the campus of a large organization. Equipped with an asymptomatic testing program and rough location data from the campus wireless network, we make the case that epidemiological models may be informed from this new source of data, which offers fidelity at the temporal resolution of seconds and spatial resolution of a Wi-Fi cell size, in particular for the tasks of pinpointing clusters of cases and contexts of infection transmission. We sketch the design of a system that fuses the two foregoing information streams and explain how the result can be incorporated into standard epidemiological models of communicable disease, both for better parameter estimation in elementary models, as well as for providing spatial inputs into more sophisticated models. We conclude with logistical and privacy considerations we have encountered in an associated ongoing study, to inform similar efforts at other organizations.
ABSTRACT
Objective: To analyze the clinical value of serum 2019 novel coronavirus (2019-nCoV) immunoglobulin M (IgM) and immunoglobulin G (IgG) antibodies in the diagnosis of COVID-19. Methods: A total of 116 patients diagnosed with NCP in the First Affiliated Hospital of Hunan University of Chinese Medicine and the First Affiliated Hospital of Xiamen University were enrolled from January to February 2020 as the disease group. A total of 134 cases, including 84 non-NCP inpatients and 50 healthy individuals served as the control group. Serum samples from all subjects were collected. A fully-automated chemiluminescence immunoassay analyzer was used to detect the concentration of 2019-nCoV IgM and IgG antibodies in serum. The sensitivity and specificity of the 2019-nCoV IgM and IgG antibody single test and combined detection were compared using the χ2 test. χ2 test and Wilcoxon's rank sum test were used to compare the positive rates and concentrations of IgM and IgG antibodies in NCP patients before and after their 2019-nCoV nucleic acid tests turning negative, respectively. The change trend of 2019-nCoV antibody concentration in the process of NCP patients was analyzed by Wilcoxon's rank sum test. Results: The sensitivity of 2019-nCoV IgG (90.5%, 105/116) was higher than that of 2019-nCoV IgM (75.9%, 88/116), the difference was statistically significant (χ2=8.91, P<0.05);The specificity of 2019-nCoV IgG (99.3%,133/134) was higher than that of 2019-nCoV IgM (94.0%, 126/134), the difference was statistically significant (χ2=5.63,P<0.05). The sensitivity (89.7%,87/97) of 2019-nCoV IgM combined with IgG was higher than that of 2019-nCoV IgM, the difference was statistically significant (χ2=6.89,P<0.05). The specificity (100%, 125/125) of 2019-nCoV IgM combined with IgG was higher than that of 2019-nCoV IgM, the difference was statistically significant (χ2=7.70, P<0.05). After 2019-nCoV nucleic acid test converted to negative, the positive rate (9/17) and concentration [13.0 (4.9, 24.7) AU/ml] of serum 2019-nCoV IgM antibody were significantly lower than those when the nucleic acid test was positive, positive rate (15/17) and concentration [29.5 (14.0, 61.3) AU/ml], respectively (χ2=5.10, Z=-3.195, both P<0.05). In the course of NCP, patients' serum samples were collected from the first day of diagnosis to every three days, three times in total. The first 2019-nCoV IgM and IgG antibody concentrations [19.4 (12.4, 63.7) AU/ml, 105.8 (74.8, 126.1) AU/ml, respectively] were significantly higher than the second concentrations [15.8 (7.1, 40.3)AU/ml, 80.5 (66.7, 105.9) AU/ml], Z were-2.897,-3.179, both P<0.05. Conclusions: 2019-nCoV IgG antibody has a good application value in the diagnosis of NCP. The concentration of 2019-nCoV IgM antibody has a certain correlation with the detection of 2019-nCoV nucleic acid. The combination of 2019-nCoV IgM and IgG antibodies with 2019-nCoV nucleic acid test may be the best laboratory index for the diagnosis of NCP at present.