The Economic Impact of COVID-19 Crisis Based on Complex Network Evolution Model

The Covid-19 crisis impacts the economy with non-equilibrium and non-linear shocks. This paper builds a trading network model based on the theory of trading economics. Using the network model, the evolutionary procedure of the economic depression triggered by the shocks are researched. The study shows that under the impact of shocks, small and medium-sized trading agents with weak profitability will first experience cash flow crisis. Then the crisis contagion is formed in upstream and downstream through the trading network. The credit reduction caused by the business deterioration will make the interest rate in the economy increase and promote each other with the bankruptcy of trading entities. Eventually, it leads to the feedback loop in liquidity crisis and debt crisis, which accelerates the bankruptcy of enterprises and possibly causing a debt crisis in the banking sector. It is found that after the shock, the economic recovery may take three patterns: stable recovery, slow recession and secondary crisis. Finally, the paper proposes relevant policy recommendations to reduce the impact of the crisis. © 2023 Editorial Borad of Complex Systems and Complexity Science. All rights reserved.

A Simple, Pipette-free, and Power-free Device for Virus Nucleic Acid Detection

A portable, inexpensive, and easy-to-manufacture microfluidic device is developed for the detection of SARS-CoV-2 dsDNA fragments. In this device, four reaction chambers separated by carbon fiber rods are pre-loaded with isothermal amplification and CRISPR-Cas12a reagents. The reaction is carried out by simply pulling the rods, without the need for manual pipetting. To facilitate power-free pathogen detection, the entire detection is designed to be heated with a disposable hand warmer. After the CRISPR reaction, the fluorescence signal generated by positive samples is identified by naked eye, using an inexpensive flashlight. This simple and sensitive device will serve as a new model for the next-generation viral diagnostics in either hospital or resource-limited settings. © 2023 SPIE.

Design of an Intelligent Educational Evaluation System Using Deep Learning

Nowadays, online education has been a more general demand in context of COVID-19 epidemic. The intelligent educational evaluation systems assisted by intelligent techniques are in urgent demand. To deal with this issue, this paper introduces the strong information processing ability of deep learning, and proposes the design of an intelligent educational evaluation system using deep learning. Inside the algorithm part, the low-complexity offset minimal sum (OMS) is selected as the front-end processor of deep neural network, so as to reduce following computational complexity in deep neural network. And the deep neural network is adopted as the major calculation backbone. In this paper, our OMS deep neural network parameters are 23 and 57 compared with other parameters, which can save about 59.64% of the network parameters, and the training time is 11270 s and 25000 s respectively, which saves the training time 54.92%. It can be also reflected from experiments that the proposal further improves the performance of unbalanced data classification in this problem scenario. © 2013 IEEE.

Distilling Business Value from COVID - 19 Public Media Dataset with Machine Learning and Natural Language Processing

While manual analysis of news coverage is difficult and time consuming, methods in natural language processing can be used to uncover otherwise hidden semantics. This work analyses more than 370,000 news articles to explore connections and trends in business decisions and their financial impact during the COVID-19 pandemic. Topic modelling, sentiment analysis and named entity recognition methods are used to identify connections between the articles and the financial performance of selected companies or industries. This report sets out the results of the individual natural language processing methods and the resulting analysis with financial data. Interesting contrasting topics in the media can be filtered out that are associated with the companies with the highest or lowest positive sentiment. This information could be useful to companies to gain an understanding of topics that are currently treated favourably or unfavourably by the media and hence assist with communication strategies and competitive intelligence. © 2022 IEEE.

Experts' consensus on severe acute respiratory syndrome coronavirus-2 vaccination of children.

At present, severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still rampant worldwide.As of September 10, 2021, there were about 222 million confirmed cases of corona virus disease 2019(COVID-19)and more than 4.6 million deaths worldwide.With the development of COVID-19 vaccines and the gradual vaccination worldwide, the increasing number of cases in children and unvaccinated young people has drawn attention.According to World Health Organization surveillance data, the proportion of COVID-19 infection cases in children gradually increased, and the proportion of cases in the age groups of under 5 years and 5-14 years increased from 1.0% and 2.5% in January 2020 to 2.0% and 8.7% in July 2021, respectively.At present, billions of adults have been vaccinated with various COVID-19 vaccines worldwide, and their protective effects including reducing infection and transmission, reducing severe disease and hospitalization, and reducing death, as well as high safety have been confirmed.Canada, the United States, Europe and other countries have approved the emergency COVID-19 vaccination in children and adolescents aged 12 to 17 years, and China has also approved the phased vaccination of COVID-19 vaccination in children and adolescents aged 3 to 17 years. For smooth advancement and implementation of COVID-19 vaccination in children, academic institutions, including National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, and The Society of Pediatrics, Chinese Medical Association organized relevant experts to reach this consensus on COVID-19 vaccination in children.Copyright © 2021 by the Chinese Medical Association.

Twenty key issues on severe acute respiratory syndrome coronavirus-2 vaccination in children.

Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still worldwide.As a vulnerable group, severe and dead pediatric cases are also reported.Under this severe epidemic situation, children should be well protected.With the widespread vaccination of SARS-CoV-2 vaccine in adults, the infection rate have decreased.Therefore, SARS-CoV-2 vaccine inoculation for children groups step by step is of great significance to the protection of children and the prevention and control of corona virus disease 2019(COVID-19) as a whole.But the safety of children vaccinated with SARS-CoV-2 vaccine is a main concern of parents.Therefore, in order to ensure the safety of vaccination and the implementation of vaccination work, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health and the Society of Pediatrics, Chinese Medical Association organized experts to interpret the main issue of parents about SARS-CoV-2 vaccine for children, in order to answer the doubts of parents.Copyright © 2021 by the Chinese Medical Association.

Diagnosis, treatment and prevention of 2019 novel coronavirus infection in children: experts' consensus statement (Third Edition).

2019 novel coronavirus(2019-nCoV) outbreak is one of the public health emergency of international concern.Since the 2019-nCoV outbreak, China has been adopting strict prevention and control measures, and has achieved remarkable results in the initial stage of prevention and control.However, some imported cases and sporadic regional cases have been found, and even short-term regional epidemics have occurred, indicating that the preventing and control against the epidemic remains grim.With the change of the incidence proportion and the number of cases in children under 18 years old, some new special symptoms and complications have appeared in children patients.In addition, with the occurrence of virus mutation, it has not only attracted attention from all parties, but also proposed a new topic for the prevention and treatment of 2019-nCoV infection in children of China.Based on the second edition, the present consensus further summarizes the clinical characteristics and experience of children's cases, and puts forward recommendations on the diagnostic criteria, laboratory examination, treatment, prevention and control of children's cases for providing reference for further guidance of treatment of 2019-nCoV infection in children.Copyright © 2021 Chinese Medical Association

The Effect of COVID-19 Shelter-in-Place Orders on Pediatric Craniofacial Trauma.

Objectives: To investigate the impacts of the shelter-in-place orders on the injury patterns among children with craniofacial trauma. Materials and Methods: Pediatric (<18 years old) craniofacial trauma cases presenting to a regional level I trauma center 1 year before and after the initiation of Washington's shelter-in-place order were retrospectively reviewed. Demographic and injury-related variables were recorded, and bivariate and logistic regression analyses were computed. Results: One hundred nineteen children were evaluated over 2-year period (46 pre- and 73 post-shelter-in-place and were comparable in age, gender, and ethnicity (p ≥ 0.17)). The distribution of injury mechanisms between pre- and post-shelter-in-place were significantly different (p = 0.02), with the largest proportional increase in falls (10.5%) and had higher rates of associated brain injury (p ≤ 0.02). After adjusting for effect modifiers and confounders, children presenting during the post-shelter-in-place period were more likely to have associated brain injuries (odds ratio 3.4, 95% confidence interval: 1.11-10.6, p = 0.03). Conclusions: Among pediatric craniofacial injury cases, the shelter-in-place order was associated with a higher likelihood of brain injury and significant changes in injury mechanisms, with a higher proportion of falls.

Optimal low-carbon governance model of livestreaming supply chain based on multiple scenarios

Supply chain emissions reduction is an important way to promote the development of a low-carbon economy and address climate challenges. Although the scale of livestream shopping has demonstrated unprecedented growth globally, especially since the COVID-19 outbreak, livestreaming supply chains have also contributed significantly to carbon emissions. Currently, optimisation models for the low-carbon governance of livestreaming supply chains are relatively lacking. To address the issue of carbon emission reduction in livestreaming supply chains, this study paper proposes three low-carbon governance decision-making models based on environmental and operating costs to compare which governance model is optimal. The most suitable decision result for the policymaker and supply chain is both cost-effective and environmentally successful under the model considering carbon tax and carbon trade. The results show that 1) governance based only on carbon tax and collaborative operation will decrease the total cost of the livestreaming supply chain but increase the environmental cost. 2) Governance based only on carbon trading and collaborative operation will increase the total cost of the livestreaming supply chain, while the environmental cost will not change. 3) Under governance that combines carbon tax and carbon trading, collaborative operations can effectively reduce both the total cost and the environmental cost of livestreaming supply chains. Theoretically, our study enriches the research on the low-carbon governance of livestreaming supply chains. Moreover, the research results provide useful insights into the formulation of a low-carbon policy for livestreaming supply chains.

[Time to initial diagnosis of imported malaria and its influencing factors in Jiangsu Province].

OBJECTIVE: To investigate the health-seeking behaviors of imported malaria cases after returning to China, and to investigate the factors affecting the time to initial diagnosis, so as to provide the scientific evidence for early identification of imported malaria cases and prevention of severe cases development and secondary transmission. METHODS: The individual demographic features, and the disease onset and the time to initial diagnosis of imported malaria cases in Jiangsu Province in 2019 were captured from the National Notifiable Disease Report System and the Information Management System for Parasitic Disease Control in China. The characteristics of health-seeking behaviors and epidemiological features of imported malaria cases were descriptively analyzed, and the factors affecting the time to initial diagnosis of imported malaria cases after returning to China were identified using multivariate logistic regression analysis. RESULTS: A total of 244 imported malaria cases were reported in Jiangsu Province in 2019, and the time to initial diagnosis of the cases were 1-12 days, with mean time of (1.53 ± 1.65) days, with median time of one day. The highest number of malaria cases seeking healthcare services were found on the day of developing primary symptoms (76 cases, 31.1%), followed by on the second day (68 cases, 27.9%), on the third day (46 cases, 18.9%), and 54 cases (22.1%) received initial diagnosis 3 days following presence of primary symptoms, including 3 cases with initial diagnosis at more than one week. High proportions of imported malaria cases with a delay in the time to initial diagnosis were seen in migrant workers who returned to China in January (14 cases, 5.7%) and December (13 cases, 5.3%) and those aged between 41 and 50 years (32 cases, 13.1%). Multivariate logistic regression analysis showed relative short time to initial diagnosis among imported malaria cases returning to China on March [odds ratio (OR) = 0.16, P = 0.03, 95% confidence interval (CI): (0.03, 0.85)] and those with a history of overseas malaria parasite infections [OR = 0.36, P = 0.001, 95% CI: (0.19, 0.67)]. CONCLUSIONS: Timely health-seeking behaviors should be improved among imported malaria cases in Jiangsu Province, patients with a history of overseas malaria infections require faster health-seeking activities.

The method of GF-7 satellite laser altimeter on-orbit geometric calibration without field site

On-orbit geometric calibration without field site is a key problem for future multi-beam laser altimetry satellites. In view of the linear system full waveform laser altimeter loaded on the GF-7 satellite, a non-field step by step calibration method based on terrain and waveform matching is proposed. Based on the analysis of the characteristics of the GF-7 satellite laser altimeter, a rigorous geometric positioning model is constructed. The field-free on orbit geometric calibration test is carried out by using the open topographic reference data and the basic geographic information of DOM and LiDAR DSM in a certain area, which has greatly improved the accuracy of the laser altimetry data. With this method, during the first half of 2020, the calibration parameter configuration and data processing of GF-7 satellite laser altimeter was not affected, even the field calibration can't be implemented due to the negative impact of the COVID-19. The accuracy is compared with the field calibration results after the COVID-19, and the results show that the plane error of the non-field calibration is 11.597±3.693 m and the minimum value is 7.115 m. The elevation accuracy of flat area is better than 0.3 m, although it is slightly lower than the results of field calibration, it can basically meet the requirements of 1: 10 000 elevation control points. © 2022, Surveying and Mapping Press. All right reserved.

Acquisition of a Laser Powder Bed Fusion System to Transform the Additive Manufacturing Value Chain

Metal additive manufacturing (AM) has significant relevance to the missions of all branches of the Department of Defense (DoD) as it has the capability to bring parts to the warfighter more quickly and cost effectively However, DoD's goals of utilizing and deploying AM will not be achieved without substantial research and development to address the technology's current limitations, which exist at every facet of the AM value chain. The DURIP award, along with supplementary funding provided by Virginia Tech, enabled the acquisition of a reactive metal laser powder bed fusion (LPBF) AM system. The advanced AM system acquired through this program features open-access to all process parameters and features integrated in-situ monitoring technologies that enable research focused in increasing materials selection, creating new design for AM tools and methods, enhancing part quality through process-property-structure models, in-situ monitoring and post-processing techniques, and securing the platforms from cyber-physical vulnerabilities. The system is installed as a showcase piece in a newly created multidisciplinary educational and research space dedicated to preparing undergraduate and graduate students for future careers in Industry 4.0 technologies. As such, the new system will enable multi-disciplinary research and education across the entire value chain of AM.

Innovative Contactless Palmprint Recognition System Based on Dual-Camera Alignment

Recently, contactless bimodal palmprint recognition technology has attracted increased attention due to the COVID-19 pandemic. Many dual-camera-based sensors have been proposed to capture palm vein and palmprint images synchronously. However, translations between captured palmprint and palm vein images differ depending on the distance between the hand and the sensors. To address this issue, we designed a low-cost method to align the bimodal palm regions for current dual-camera systems. In this study, we first implemented a contactless palm image acquisition device with a dual-camera module and a single-point time of flight (TOF) ranging sensor. Using this device, we collected a dataset named DCPD under different distances and light source intensities from 271 different palms. Then, a bimodal palm image alignment method is proposed based on the imaging and ranging models. After the system model is calibrated, the translation between the visible light and infrared light palm regions can be estimated quickly based on the palm distance. Finally, we designed a convolutional neural network (CNN) to effectively extract the fine- and coarse-grained palm features. Compared to widely used existing methods, the proposed networks achieved the lowest equal error rate (EER) on the Tongji, IITD, and DCPD datasets, and the average time cost of the system to perform one-time identification is approximately 0.15 s. The experimental results indicate that the proposed methods achieved high efficiency and comparable accuracy. In addition, the system's EER and rank-1 on the DCPD dataset were 0.304%and 98.66%, respectively. IEEE

Deep Active Context Estimation for Automated COVID-19 Diagnosis

Many studies on automated COVID-19 diagnosis have advanced rapidly with the increasing availability of large-scale CT annotated datasets. Inevitably, there are still a large number of unlabeled CT slices in the existing data sources since it requires considerable consuming labor efforts. Notably, cinical experience indicates that the neighboring CT slices may present similar symptoms and signs. Inspired by such wisdom, we propose DACE, a novel CNN-based deep active context estimation framework, which leverages the unlabeled neighbors to progressively learn more robust feature representations and generate a well-performed classifier for COVID-19 diagnosis. Specifically, the backbone of the proposed DACE framework is constructed by a well-designed Long-Short Hierarchical Attention Network (LSHAN), which effectively incorporates two complementary attention mechanisms, i.e., short-range channel interactions (SCI) module and long-range spatial dependencies (LSD) module, to learn the most discriminative features from CT slices. To make full use of such available data, we design an efficient context estimation criterion to carefully assign the additional labels to these neighbors. Benefiting from two complementary types of informative annotations from K-nearest neighbors, i.e., the majority of high-confidence samples with pseudo labels and the minority of low-confidence samples with hand-annotated labels, the proposed LSHAN can be fine-tuned and optimized in an incremental learning manner. Extensive experiments on the Clean-CC-CCII dataset demonstrate the superior performance of our method compared with the state-of-the-art baselines.

Twenty key issues on severe acute respiratory syndrome coronavirus-2 vaccination in children

Severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still worldwide.As a vulnerable group, severe and dead pediatric cases are also reported.Under this severe epidemic situation, children should be well protected.With the widespread vaccination of SARS-CoV-2 vaccine in adults, the infection rate have decreased.Therefore, SARS-CoV-2 vaccine inoculation for children groups step by step is of great significance to the protection of children and the prevention and control of corona virus disease 2019(COVID-19) as a whole.But the safety of children vaccinated with SARS-CoV-2 vaccine is a main concern of parents.Therefore, in order to ensure the safety of vaccination and the implementation of vaccination work, National Clinical Research Center for Respiratory Diseases, National Center for Children's Health and the Society of Pediatrics, Chinese Medical Association organized experts to interpret the main issue of parents about SARS-CoV-2 vaccine for children, in order to answer the doubts of parents. Copyright © 2021 by the Chinese Medical Association.

Experts' consensus on severe acute respiratory syndrome coronavirus-2 vaccination of children

At present, severe acute respiratory syndrome coronavirus-2(SARS-CoV-2)infection is still rampant worldwide.As of September 10, 2021, there were about 222 million confirmed cases of corona virus disease 2019(COVID-19)and more than 4.6 million deaths worldwide.With the development of COVID-19 vaccines and the gradual vaccination worldwide, the increasing number of cases in children and unvaccinated young people has drawn attention.According to World Health Organization surveillance data, the proportion of COVID-19 infection cases in children gradually increased, and the proportion of cases in the age groups of under 5 years and 5-14 years increased from 1.0% and 2.5% in January 2020 to 2.0% and 8.7% in July 2021, respectively.At present, billions of adults have been vaccinated with various COVID-19 vaccines worldwide, and their protective effects including reducing infection and transmission, reducing severe disease and hospitalization, and reducing death, as well as high safety have been confirmed.Canada, the United States, Europe and other countries have approved the emergency COVID-19 vaccination in children and adolescents aged 12 to 17 years, and China has also approved the phased vaccination of COVID-19 vaccination in children and adolescents aged 3 to 17 years. For smooth advancement and implementation of COVID-19 vaccination in children, academic institutions, including National Clinical Research Center for Respiratory Diseases, National Center for Children's Health, and The Society of Pediatrics, Chinese Medical Association organized relevant experts to reach this consensus on COVID-19 vaccination in children. Copyright © 2021 by the Chinese Medical Association.