A Statistical Analysis of the Covid-19 Outbreak Data

The exponential model is a commonly used epidemic model for the analysis of initial outbreak data due to an infectious disease. But there have been questions about its validity in practice. This article examines this issue through statistical analysis on 22 countries' initial COVID-19 outbreak data provided by the World Health Organization. For each of 22 countries, a general regression analysis is conducted for the cumulative confirmed cases. Our regression function is a 3-5 piecewise fitted functions which are obtained via regression analysis

Does digital economy development reduce carbon emission intensity?

Carbon emissions from human activities are the main cause of climate warming. Under the background of economic and social digital transformation, accurately assessing the carbon emission reduction effect of the development of the digital economy is of great significance for countries to deal with climate warming in the post-COVID-19 era. This paper constructs a dynamic evaluation model of orthogonal projection to measure the level of digital economy development at the provincial level in China from 2007 to 2019. On this basis, the panel fixed effects model and mediation model are used to empirically test the impact of digital economy development on carbon emission intensity and its mechanism. The results indicate that: (1) The development of China's digital economy is unbalanced among regions, showing a geospatial pattern of decreasing from east to west. (2) China's carbon emission intensity has a trend of decreasing year by year, and there are geospatial differences of "high in the west and low in the east” and "high in the north and low in the south.” (3) The digital economy development can effectively reduce regional carbon emission intensity through industrial structure optimization effect and resource allocation effect, and the industrial structure optimization effect can suppress carbon emission intensity more obviously. (4) The development of digital economy in different regions has different degrees of reducing carbon emission intensity. The development of digital economy in the eastern region has a stronger inhibitory effect on carbon emission intensity than that in the middle and western regions, and the development of digital economy in economically developed regions can suppress carbon emission intensity more. This paper provides enlightenment for policy makers to deal with climate warming. Copyright © 2023 Lyu, Zhang and Wang.

[Prediction and analysis of B cell and T cell epitopes in the spike protein of SARS-CoV-2 by bioinformatics]

Objective To analyze structural features for spike (S) protein of the SARS-CoV-2 and to predict potential B cell and T cell epitopes using bioinformatics. Methods The amino acid sequence of S protein from the NCBI GenBank database was retrieved. Its physicochemical properties were analyzed using ProtParam online program. The secondary structure of S protein was analyzed using Lasergene software and SOPMA online service. The tertiary structure model of S protein was established by Phyre2 and Rasmol software. Finally, B cell epitopes were predicted using ABCpred, BepiPred and BcePred;T cell epitopes were predicted using IDBE software. Results S protein is a 1273 amino acid sequence with the isoelectric point at 6.24 and atomic composition as C(6336)H(9770)N(1656)O(1894)S(54), which was classified as a stable and hydrophilic protein. GramierRobson method analysis revealed that the secondary structure of S protein comprised 23.5% α-helixes, 53.7% β-sheets, 14.9% β-turns and 8.33% random coils. Chou-Fasman method analysis revealed that the secondary structure of S protein comprised 20.9% α-helixes, 35.5% β-sheets, 35.2% β-turns. Online service SOPMA analysis revealed that the secondary structure of S protein comprised 28.59% α-helixes, 23.25% β-sheets, 3.38% β-turns and 44.78% random coils. The numbers of B cell epitopes according to ABCpred, BepiPred and BcePred databases were 5,11 and 6. Five epitopes for CD8(+) T cell and CD4(+) T cell were chosen as potential epitopes. Conclusion Bioinformatics can predict B cell and T cell epitopes in the S protein of the SARS-CoV-2, which lays a foundation for developing vaccines.

Dockerized Knowledge-Oriented Multi-modal Social Event Detection System

Faced with an increasing amount of unstructured multimodal data appearing on various social platforms (e.g., Twitter/Instagram), we seek to effectively understand the complex social events portrayed on these platforms. However, conventional information extraction systems cannot understand these data because they cannot handle real-world analysis or require extensive tuning and many manually annotated examples to successfully comprehend these events. To solve this problem, this paper develops a knowledge-oriented artificial intelligence system that can identify and analyze these data and complex events and bring them to the user's attention. Our research aims to understand complex events described in multimedia inputs by developing a semi-automated system that identifies, links, and temporally sequences their subsidiary elements, the participants involved, as well as the complex event type. This project proposes a systematic analysis of world events, such as the Boston Marathon bombing, Capital Riots, Covid-19, etc. We have successfully evaluated our system on various datasets and have shown significant improvement compared to other previous methods. © 2022 IEEE.

[The influence of meteorological factors on SARS-CoV-2 transmission: evidence from laboratory and epidemiological studies].

SARS-CoV-2 has infected more than 600 million people worldwide and caused more than 6 million deaths. The emerging novel variants have made the epidemic rebound in many places. Meteorological factors can affect the epidemic spread by changing virus activity, transmission dynamic parameters and host susceptibility. This paper systematically analyzed the currently available laboratory and epidemiological studies on the association between the meteorological factors and COVID-19 incidence, in order to provide scientific evidence for future epidemic control and prevention, as well as developing early warning system.

[Analysis of liver function injury associated with 2019-nCoV Omicron mutant strains].

Objective: To investigate the clinical features and influencing factors of liver function injury in patients with 2019-nCoV/SARS-CoV-2 Omicron mutant strains. Methods: 1 183 confirmed imported cases of SARS-CoV-2 who were admitted at Shanghai Public Health Clinical Center (affiliated to Fudan University) from July 1, 2021 to January 15, 2022 were collected. Clinical data, viral genotyping and laboratory test results were collected to retrospectively analyze the basic condition and clinical characteristics of liver function injury. Statistical analysis was performed using t-test or Wilcoxon rank-sum test, χ2 test or Fisher's exact test, Pearson correlation test and logistic regression analysis. Results: 125 (10.6%) cases had raised baseline ALT level and 60 (5.1%) cases had abnormal baseline AST level. Among them, 33 cases (2.8%) had received hepatoprotective drugs. Liver function injury was generally mild in SARS-CoV-2 infection and minimal in Omicron mutant strains. Leukocyte count was increased in patients with raised alanine aminotransferase (ALT) [(6.96±1.78)×109/L vs. (6.41±1.96)×109/L, P=0.005 2], CT scan showed the proportion of liver hypodensity was significantly increased (2.4% vs. 0.3%, P=0.018 0). High-sensitivity C-reactive protein [(7.83±22.36) mg/L vs. (2.68±6.21) mg/L, P=0.007 8] and D-dimer [(0.34±0.39) µg/ml vs. (0.31±0.75) µg/ml, P=0.047 5] levels were higher in patients with raised AST than normal group. 26 cases had normal liver function at hospital admission; however, abnormal liver function was occurred during the course of the disease. Another 8 patients had abnormal liver function at hospital admission, and reduced liver function further during the course of treatment. Recovery time and length of hospital stay was significantly affected in patients with worsened liver function. Baseline body mass index value [odds ratio (OR)]=1.80, P=0.047), non-Omicron strains (OR=12.63, P=0.046), D-dimer (OR=2.36, P=0.047) and interleukin-6 levels (OR=1.03, P=0.009), and those who used glucocorticoids and/or ulinastatin after hospital admission (OR=6.89, P=0.034) had a higher risk of worsening liver function. Conclusions: Liver dysfunction could be observed among COVID-19 patients. Patients infected with omicron variant generally showed mild liver injury. Dynamic monitoring of liver function is necessary, especially among those with baseline elevated IL-6, D-Dimer level and use of antiinflammation medication during treatment.

Privacy Data Protection Scheme for Patients with Major Outbreaks

In 2020, the global outbreak of COVID-19 made the global healthcare system face huge test, and the security of COVID-19 patients privacy data is an extremely important part of the healthcare information system. During the outbreak, there were numerous cases of privacy data leakage of Chinese patients with COVID-19, which caused great distress to patients. This paper proposes a patient privacy data protection scheme combined with blockchain for major epidemics using delegated Byzantine fault tolerant (dBFT) mechanism. The scheme is based on a federated chain, distributing different players such as government agencies, medical institutions and the public in a dual-chain model of main and side chains, and using side chain technology to interact with information between the main and side chains for secure sharing of patient data. It proposes the on-chain hierarchical data encryption scheme (HDES), which protects the patient privacy data on the chain at a fine-grained level using hierarchical encryption technology. Finally, the requested data throughput of the main-side dual-chain model and the encryption and decryption efficiency of the HDES scheme are experimentally analyzed and compared with the existing blockchain electronic medical case scheme. The comparison results show that this scheme has certain efficiency, strong security and high relevance. © 2022, Journal of Computer Engineering and Applications Beijing Co., Ltd.;Science Press. All rights reserved.

Cultural Influences on Chinese Citizens' Adoption of Digital Contact Tracing: A Human Infrastructure Perspective

Digital contact tracing is an ICT approach for controlling public health crises. It identifies users' risk of infection based on their healthcare and travel information. In the COVID-19 pandemic, many countries implemented digital contact tracing to contain the coronavirus outbreak. However, the adoption rates vary significantly across different countries. In this study, we investigate Chinese people's adoption of digital contact tracing. We aim at finding the influence of Chinese culture on people's attitudes and behaviors toward the technology. We interviewed 26 Chinese participants and used thematic analysis to interpret the data. Our findings showed that Chinese culture shaped citizens' interactions with the digital contact tracing at multiple levels;driven by the culture, Chinese citizens accepted digital contact tracing and contributed to making digital contact tracing a socio-technical infrastructure of people's daily lives. We also discuss such cultural influences with the growing literature of human infrastructure and crisis informatics. © 2022 ACM.

Structure and function of SARS-CoV-2 spike protein and its receptor

Corona virus disease 2019 is an acute infectious disease caused by SARS-CoV-2 infection and has entered the state of global pandemic. Spike protein ( S protein) , a key protein that mediates SARS-CoV-2 to infect host cells, has the characteristics of specific receptor binding and membrane fusion, playing an important role in host tropism and virulence. The spontaneous closed and open conformation of S protein trimer is crucial for receptor binding and initiation of conformational changes in membrane fusion, and its unique furin recognition site may be a crucial factor leading to high infectivity. Therefore, to study the structure and function of SARS-CoV-2 S protein and its receptor has important implications for invasion mechanisms of SARS- CoV-2 and the development of relevant targeted drugs.

Analysis of the characteristics of ocular trauma diseases during the novel coronavirus epidemic

AIM: To analyze the epidemiological characteristics of patients hospitalized for ocular trauma during the novel coronavirus (COVID-19) epidemic. METHODS: A retrospective case analysis. Totally 876 cases (905 eyes) of ocular trauma were analyzed in this study, including 545 cases (565 eyes) from January to June 2019 were enrolled ascontrol group, and 331 cases (340 eyes) from January to June 2020 were enrolled in the research group. Information regarding age, sex, location of injury, cause of injury, place of residence, and type of injury were collected and analyzed. RESULTS: The number of hospitalisation for ocular trauma in the research group decreased by 39.3% compared with the control group. The age distribution of patients showed a double peak, at 0-10 years (20.55%, 21.45%) and 41-50 years (17.98%, 19.03%) in the control group and research group, respectively. There was no statistically significant difference in the age distribution between the two groups (P=0.907). Men were predominantly injured in both the control and the research groups, accounting for 80.37% and 83.69%, respectively (P=0.219). The proportion of home injuries in the research group (28.40%) was higher than the control group (11.38%) (P<0.001). The proportion of mechanical eye injuries in the research group (98.19%) was higher than the control group (95.60%) (P=0.041), and the proportion of open globe injuries (85.54%) was also higher than the control group (76.58%) (P=0.001). The proportion of patients with no light perception in the research group (18.86%) was higher than that of the control group (9.53%) (P<0.001). CONCLUSION: During the COVID-19 epidemic period, the total number of ocular trauma cases was significantly reduced. Mechanical eye injuries are still the main type for hospitalisation of patients with eye injuries. The awareness of eye injury prevention should be strengthened during the period of epidemic. Copyright 2022 by the IJO Press.

Research on the development of photovoltaic industry based on A company

As the main source of electricity from renewable energy, PV will play a key role in various fields and scenarios to achieve carbon neutrality. With technological advances in the photovoltaic industry and declining costs per kilowatt-hour, the cost of photovoltaic per kilowatt-hour has fallen by more than 90% globally in the past decade, with the biggest decline compared to wind, natural gas, coal and nuclear power. The year 2020 has been an extraordinary year. Under the pressure test and numerous challenges of the global epidemic, the global photovoltaic industry has maintained a good momentum of development thanks to the rapid and effective control of the COVID-19 in China and the obvious growth of the domestic market. Based on the domestic monocrystalline silicon photovoltaic leading A company as an example, through to the company business model and the results of data analysis in recent years, suggested that the company in the four aspects to carry on the improvement and optimization, including: further globalization, adhere to customer value orientation, implement the product strategy and tries to build up A creative organization, leading to the photovoltaic industry as A whole in China benign development help. © 2021 The Author(s)

Improving Generalizability in Limited-Angle CT Reconstruction with Sinogram Extrapolation

Computed tomography (CT) reconstruction from X-ray projections acquired within a limited angle range is challenging, especially when the angle range is extremely small. Both analytical and iterative models need more projections for effective modeling. Deep learning methods have gained prevalence due to their excellent reconstruction performances, but such success is mainly limited within the same dataset and does not generalize across datasets with different distributions. Hereby we propose ExtraPolationNetwork for limited-angle CT reconstruction via the introduction of a sinogram extrapolation module, which is theoretically justified. The module complements extra sinogram information and boots model generalizability. Extensive experimental results show that our reconstruction model achieves state-of-the-art performance on NIH-AAPM dataset, similar to existing approaches. More importantly, we show that using such a sinogram extrapolation module significantly improves the generalization capability of the model on unseen datasets (e.g., COVID-19 and LIDC datasets) when compared to existing approaches. © 2021, Springer Nature Switzerland AG.

Time Series Analysis of the COVID-19 Impact on the US Airline Companies Based on ARMA model

The US stock market has been through several ups and downs since the first COVID-19 infection was confirmed in January 20, 2020. Traditional industries like tourism, manufacturing, and hospitality were among the most vulnerable ones. We are most interested in generalizing the stock trends of the United States airline companies, since their curves have shown great similarities. In this project, we did an in-depth analysis on the stock time series' dynamics and made predictions based on the ARMA model. The fitted ARMA model is used for computer output of portfolio stock prices. I finally came to the conclusion that the model with exponential deterministic trend and automobile portfolio as an indicator produces the best result, as it has the lowest RMSE = 1.538. © 2021 ACM.

Optimization of 3D printing parameters for high-performance biodegradable materials

Developing 3D printing high-performance biodegradable materials is important to protect the environment and deal with emergencies such as COVID-19. Fused deposition modeling (FDM), one of the 3D printing methods, has many advantages, such as low cost and wide range of materials. However, the weak interlayer adhesion is an important factor restricting the development of FDM. In addition to the influence of material properties, the optimization of 3D printing parameters is also an important means to give full play to the inherent properties of materials. The optimal 3D printing parameters are conducive to the diffusion and entanglement of molecular chains between adjacent layers. PLA/PBAT/PLA-g-GMA (70/30/10 wt%, PLA-g-GMA was a compatibilizer synthesized in our lab) was used as the research object. This work aims to analyze the mechanical properties response of biodegradable polymers products manufactured through FDM. Herein, the effect of 3D printing parameters including layer thickness, nozzle temperature, printing speed and platform temperature have been systematically investigated by orthogonal experimental design. The result showed that the excellent performance of 3D printing specimen was obtained when the layer thickness was 0.15 mm, the printing speed was 50 mm·s−1, the nozzle temperature was 200°C and the platform temperature was 50°C. The SEM images showed that the optimal 3D printing products had the best interlayer adhesion and the lowest porosity. Undergoing optimization of 3D printing processing, the yield strength and elongation at break of specimen increased by 115% and 229%, respectively. In this paper, the interlayer adhesion and mechanical properties of 3D printing products can be significantly improved by simply optimizing the 3D printing parameters without complex material modification. This work provided a new method for improving the interlayer adhesion of FDM and the mechanical properties of FDM products. © 2021 Wiley Periodicals LLC.