Maritime Disruption Impact Evaluation Using Simulation and Big Data Analytics

Disruptions in maritime networks may cause significant financial burden and damage to business. Recently, some international ports have been experiencing unprecedented congestions due to the COVID19 pandemic and other disruptions. It is paramount for the maritime industry to further enhance the capability to assess and predict impacts of disruptions. With more data available from industrial digitization and more advanced technologies developed for big data analytics and simulation, it is possible to build up such capability. In this study, we developed a discrete event simulation model backed with big data analytics for realistic and valid inputs to assess impacts of the Suez Canal blockage to the Port of Singapore. The simulation results reveal an interesting finding that, the blockage occurred in the Suez Canal can hardly cause significant congestion in the Port of Singapore. The work can be extended to evaluate impacts of other types of disruptions, even occurring concurrently. © 2022 IEEE.

Evaluating the Covid-19 Screening Regime for Cross-Border Workers

Global travel and trade have been hit hard by the COVID-19 pandemic. Border closures have impacted both leisure and business travel. The socioeconomic costs of border closure are particularly severe for individuals living and working across state lines, for which previously unhindered passage has been curtailed, and daily commute across borders is now virtually impossible. Here, we examine how the periodic screening of daily cross-border commuters across territories with relatively low COVID-19 incidence will impact the transmission of SARS-CoV-2 across borders using agent-based simulation. We find that periodic testing at practical frequencies of once every 7, 14 or 21 days would reduce the number of infected individuals crossing the border. The unique transmission characteristics of SARS-CoV-2 suggest that periodic testing of populations with low incidence is of limited use in reducing cross-border transmission and is not as cost-effective as other mitigation measures for preventing transmission. © 2022 IEEE.

STOBE: A Long-COVID Syndromic Study using Real-World data in Brazil : Heitor Cavalini

Background The COVID-19 pandemic has changed the way infectious diseases are perceived. Global healthcare systems have faced challenges since the start of the COVID-19 epidemic, particularly in developing countries. Some individuals with an acute COVID-19 diagnosis have developed symptoms persisting beyond 90 days. Long-Covid is the new term for this syndrome (LC). LC, on the other hand, is poorly known and appears to cause a wide range of symptoms, particularly among Brazilian patients. As a result, utilizing retrospective data from patients in Petrolina, Brazil’s largest city in the northeast, we conducted an exploratory epidemiology study. Methods A retrospective, cohort study design was used with a real-world dataset. The primary aim was to evaluate the prevalence of LC within Petrolina. The sample size was 1,164 LC patients. A comparative and subgroup analysis was conducted to evaluate demographics, comorbidities, clinical symptoms, and mortality. A k means model was used to assess disease severity using a clustering analysis based on the presence of comorbidities. Results The prevalence of physical symptoms identified was 69·5%. The strongest physical symptom was fever with resultant of 64·09% followed by pain, 43·64%. The prevalence of autonomic and neurological symptomatology was 8·59% and 8·16% respectively. A higher prevalence of autonomic symptoms were reported among older men of Black and Caucasian in comparison to Pardo. Disease severity within the sample could be associated with the presence of comorbidities which were identified based on medication history. Pregnant women have high rate of comorbidities. 529 patients have at least one comorbidity and 28·73% of them are pregnant. Conclusions It is useful to evaluate symptoms although a definitive diagnosis of LC is essential. This study provides insightful information around LC within a Brazilian population to develop better infection control protocols, as well as future management of similar pandemics. Key messages • This study could potentially improve the prognosis and mortality among LC patients with comorbidities. • Our findings could be combined with other regional datasets to predict pattern inferences of LC spread, prognosis and morbidity, including for multimorbidity and pregnant patients.

Direct and Indirect Implications of the COVID-19 Pandemic on Amazon's Financial Situation

We provide theoretical and empirical insights into the impact of COVID-19 on Amazon's financial position. A longitudinal case study of Amazon's financial situation during the 2016-2020 period, and time-series analysis, ratio analysis, and DuPont analysis, are employed as a quantitative methodology to explore Amazon's financial situation changes before and after the COVID-19 pandemic. As for the robustness of the in-depth analysis, we compare Amazon's financial performance and position with Walmart. The result shows that the COVID-19 pandemic did not have a huge negative impact on the companies' financial performance because of its promotion of their development. However, this study provides an in-depth analysis of the influence of COVID-19 on Amazon's financial situation, which financial aspects are most affected by COVID-19, which are not, and the company's response to COVID-19. Therefore, this study sheds light on the accounting literature to demonstrate the impact of COVID-19 on Internet companies' financial performance and provides some reference values for subsequent academic research.

AN ELECTROCHEMICAL BIOSENSING PLATFORM FOR RAPID DETECTION OF SARS-COV-2 ANTIBODIES

A portable and low-cost electrochemical immunosensor platform is developed for rapid (13 min) and accurate quantification of SARS-CoV-2 serum antibodies (10.1 ng/mL − 60 µg/mL for IgG and 1.64 ng/mL − 50 µg/mL for IgM). No obvious cross-reactivity with other interference proteins was observed. Stable performance of the immunosensor within 24-week storage at room temperature was achieved. The practical use of the immunosensor was demonstrated using real patient samples. © 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.

Impact of Epidemic on Consumer Economy via Transaction Data

The sudden COVID-19 pandemic has led to unprecedented impact on China's economic and social development, especially on consumer economy. Payment is the most closely related economic activity regarding consumers, the data of which can accurately capture the characteristic of the consumer economy. Given the point of view, this paper makes an in-depth exploration in the research direction of payment data. Based on the transaction data from China UnionPay, this paper quantifies the impact of the epidemic on consumer economy and makes a comparative analysis of different provinces and industries. The paper quantitatively reveals that the epidemic progress significantly affects the consumer confidence and the development of consumer economy. According to our analysis, it is unwise to restart work resumption when the epidemic is still not under effective control. From the perspective of payment, this paper profoundly tells about the story of how China fights against the epidemic and puts forward relevant suggestions for the follow-up epidemic prevention and control as well as the comprehensive economic recovery policies. © 2022, Editorial Office of Journal of Applied Sciences. All right reserved.

Classification Models for Medical Data with Interpretative Rules

The raging of COVID-19 has been going on for a long time. Thus, it is essential to find a more accurate classification model for recognizing positive cases. In this paper, we use a variety of classification models to recognize the positive cases of SARS. We conduct evaluation with two types of SARS datasets, numerical and categorical types. For the sake of more clear interpretability, we also generate explanatory rules for the models. Our prediction models and rule generation models both get effective results on these two kinds of datasets. All explanatory rules achieve an accuracy of more than 70%, which indicates that the classification model can have strong inherent explanatory ability. We also make a brief analysis of the characteristics of different rule generation models. We hope to provide new possibilities for the interpretability of the classification models. © 2021, Springer Nature Switzerland AG.

Global food security assessment during 1961–2019

Quantified components of the global food system are used to assess long-term global food security under a series of socio-economic, epidemic normalization and climate change scenarios. Here, we evaluate the global food security including the global farming system as well as the global food trade, reserve and loss systems from 1961 to 2019, and analyze their temporal and spatial characteristics by using the global food vulnerability (GFV) model. The spatio–temporal patterns of the vulnerability of the global food system were consistent with the GFSI. As food production and consumption vary greatly in different countries which have continued for a long time, food exports from many developed agricultural countries have compensated for food shortages in most countries (about 120 net grain-importing countries). As a result, many countries have relied heavily on food imports to maintain their domestic food supplies, ultimately causing the global food trade stability to have an increasing impact on the food security of most countries. The impact of global food trade on global food security increased from 9% to 17% during 1961–2019, which has increased the vulnerability of the global food system. The food damage in the United States, Russia, China, and India has varied significantly, and global cereal stocks have fluctuated even more since 2000. From 1961 to 2019, the food system security of some Nordic countries significantly improved, while the food system security of most African countries significantly deteriorated. Most countries with high food insecurity are located in Africa and South Asia. In order to cope with extreme events, these countries need to strengthen and improve their own food production and storage systems, which will help the World Food and Agriculture Organization to formulate relevant food policies and maintain sustainable development. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

Ensemble Distillation for BERT-Based Ranking Models

Over the past two years, large pretrained language models such as BERT have been applied to text ranking problems and showed superior performance on multiple public benchmark data sets. Prior work demonstrated that an ensemble of multiple BERT-based ranking models can not only boost the performance, but also reduce the performance variance. However, an ensemble of models is more costly because it needs computing resource and/or inference time proportional to the number of models. In this paper, we study how to retain the performance of an ensemble of models at the inference cost of a single model by distilling the ensemble into a single BERT-based student ranking model. Specifically, we study different designs of teacher labels, various distillation strategies, as well as multiple distillation losses tailored for ranking problems. We conduct experiments on the MS MARCO passage ranking and the TREC-COVID data set. Our results show that even with these simple distillation techniques, the distilled model can effectively retain the performance gain of the ensemble of multiple models. More interestingly, the performances of distilled models are also more stable than models fine-tuned on original labeled data. The results reveal a promising direction to capitalize on the gains achieved by an ensemble of BERT-based ranking models. © 2021 Owner/Author.

Extracting prerequisite relations among concepts from the introduction of online courses

Affected by the COVID-19 pandemic, teaching tasks have gradually shifted from offline to online, which expanded online education resources unprecedentedly. “Concept” is a professional vocabulary in the curriculum. Exploring the prerequisite relations among concepts is of great significance to educational planning. This research extracts concepts from online course introduction and proposes a mixed method for extracting concept prerequisite relations. Experiments on public data set show that this method outperforms existing ones. Tests were also carried out on the datasets of eleven schools, which proves that this model has good scalability. © 2021 Knowledge Systems Institute Graduate School. All rights reserved.

An Experiment of Mobile Application Design Course Based on Crises Experiences in COVID-19 Pandemic

Confronting the COVID-19 pandemic, China has adopted strict control policies, which have greatly changed normal lifestyle and learning methods in a short space of time. Under such circumstances, the course of mobile application (app) design adopts an online teaching method, encourages students to conduct independent learning, guides students to experience and record the crises in life, and helps students to find solutions to these crises. In the course, students not only completed the required practical tasks of designing two apps for the crisis caused by the epidemic but also acquired an improved ability of autonomous learning, as well as crisis identifying and solving. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Design and Implementation of Distributed Video Live-Streaming System Based on SRS

Since the COVID-19 pandemic, video live-streaming technologies that ensure learning continuity have evolved rapidly. With the epidemic under control in China, a growing number of colleges classroom teaching will be online live simultaneously. Traditional offline teaching will gradually transform to the combination of online and offline mode. With the demand for the normality high-definition online live-streaming, the traditional live broadcast system faces the problems of limited scalability, poor fault tolerant ability and poor user experience. In this paper, a distributed online live-streaming system cross multiple campuses which based on SRS is designed and realized. Through dynamic distributed push, upstream and downstream traffic separation, and multi-level load balancing mechanism, the system can satisfy the need of the automatic and unattended normal video live-streaming teaching of large-scale classrooms. In this loosely coupled system, all components are distributed on each campus and communicate via message queues and HTPP API. The system has been applied to Xi'an Jiaotong University daily online and offline teaching for 700 classrooms spread over three campuses.

Examination on the Ecological Civilization Governance System and Capacity With the Case of COVID-19 Pandemic: Review and Improvement

The COVID-19 disease broke out globally, bringing great challenges to public health security and increasing the difficulties in constructing ecological civilization governance system. Under the leadership of the Central Committee of the Communist Party of China with Comrade Xi Jinping at its core, the Chinese Government and people have fought against the disease with courage and put people's health and safety first. Through hard work, China has made achievements in controlling the COVID-19 pandemic and accelerated the restoring of work and life back to normalcy. While continuing to control the pandemic domestically, China promotes the building of a human community with shared destiny, and plays an active role in promoting global cooperation in public health, contributing extraordinarily to global public health and world economy. Guided by Xi Jinping's Thought of Ecological Civilization, China has endeavored for modernization characterized by harmonious coexistence between man and nature. In response to the current crisis in public health and the challenges facing human-nature harmony thus incurred, the Editorial Department of Chinese Journal of Urban and Environmental Studies has co-hosted a seminar with CASS Thinktank for Eco-civilization Studies, aiming at brainstorming on and enhancing faith in continuing the building of an ecological civilization after completing the construction of a moderately well-off society in all respects. This paper intends to call for other countries to exchange and cooperate in building ecological civilization and building the world into a beautiful home for all.

Analysis of Urban Greenway Planning Strategies by the Orientation of Healthy City

In the first half-year of 2020, the COVID-19 (Coronavirus disease 2019) outbreak spread rapidly around the world. Under the impact of the crisis of Public Health Emergency, the development of healthy cities and people's lives must be experienced a tough test, and it will trigger the thinking and practice of urban construction as well. Taking the construction of Nanning greenway system as an example, and trying to discuss the route and the significance of healthy cities construction by greenway supporting, we came up with suggestions for greenway construction by the orientation of the concept healthy city. © The Authors, published by EDP Sciences, 2020.

Deep thought of COVID-19 based on Diamond Princess's quarantine and home quarantine.

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