The World Trade Organization and the Digital Economy Partnership Agreement: Analog Trade Rules in a Digital Era

The multilateralism of post-Bretton Woods international entities, such as the WTO, World Bank, and International Monetary Fund, has been in a state of constant crisis since the failure of the Doha Round of WTO negotiations in 2001. The lack of consensus on tariffs for agricultural and industrial products led to fragile agreements and noncompliance by developed countries. Negotiations on the services sector made little progress, which boosted agreements parallel to the WTO, such as the Transatlantic Trade and Investment Partnership (TTIP), Trade in Services Agreement (TISA), and TPP. The most recent development in the regulatory approach to digital trade by WTO member states is the Digital Economy Partnership Agreement signed in the middle of 2020, the year of the outbreak of the COVID-19 pandemic. There has been a lack of significant progress in multilateral negotiations on the inclusion of the specific fields of electronic commerce and digital trade in preferential trade agreements. However, the enormous scale achieved by Big Tech firms points to an acceleration of rule-making pertaining to this sector, as states develop their own legislation that effects international markets. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Concluding Remarks

Today, the world has entered into an unknown new era of deglobalization, one that profoundly reshapes the landscape of global economy, international politics, and international organization. In the wake of the unprecedented Covid-19 pandemic, the year 2020 has definitely been a turning point in world history. Rival ideologies, power blocs, leaders, and institutions are being stress-tested in the court of world opinion. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Regional International Organizations Under the COVID-19 Influence

Regional organizations are also being strongly impacted as COVID-19 spreads around the world. This chapter discusses three typical regional organizations, the EU, the NATO, and the ASEAN. These significant regional organizations not only play an important role in the integration of geopolitical concepts in their geographic regions, such as internal cooperation in aspects of politics, economy, and social culture, but also influence changes and the implementation of the world order as a non-negligible element in international relations, such as some organizations (NATO) that are political and military alliances with common essential and enduring purposes, or common values of ideology and goals (liberty, democracy, equal rights and so on) that actively promote foreign military and political processes as a whole to foreshadow or solve crises and safeguard the freedom and security of their members. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Global International Organizations Under the COVID-19 Influence

In this chapter, we analyze the performance of global international organizations in the COVID-19 era. Three of the most influential global international organizations in politics, health, and economy, namely, the U.N., the WHO, and the WTO, respectively, are selected for case studies. Amid the COVID-19 pandemic, it is urgent for the whole world to have a strong method of organization to take a leadership role in fighting the virus. Therefore, multilateral regimes are supposed to function and be strengthened under the background of a global crisis. However, such regimes are dysfunctional and even undermined by reemerging unilateralism worldwide. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Unprecedented Times: The COVID-19 Pandemic that Swept the World

The year 2020 was dominated by coronavirus disease 2019 (COVID-19), and many countries worldwide are experiencing second or third waves of COVID-19 cases as the weather becomes colder during the winter of 2021. In such a circumstance, this book chronicles the pandemic evolvement in 2020 at the beginning. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Chinese Named Entity Recognition of Epidemiological Investigation of Information on COVID-19 Based on BERT

The named entity recognition based on the epidemiological investigation of information on COVID-19 can help analyze the source and route of transmission of the epidemic to control the spread of the epidemic better. Therefore, this paper proposes a Chinese named entity recognition model BERT-BiLSTM-IDCNN-ELU-CRF (BBIEC) based on the epidemiological investigation of information on COVID-19 of the BERT pre-training model. The model first processes the unlabeled epidemiological investigation of information on COVID-19 into the character-level corpus and annotates it with artificial entities according to the BIOES character-level labeling system and then uses the BERT pre-training model to obtain the word vector with position information;then, through the bidirectional long-short term memory neural network (BiLSTM) and the improved iterated dilated convolutional neural network (IDCNN) extract global context and local features from the generated word vectors and concatenate them serially;output all possible label sequences to the conditional random field (CRF);finally pass the condition random The airport decodes and generates the entity tag sequence. The experimental results show that the model is better than other traditional models in recognizing the entity of the epidemiological investigation of information on COVID-19.

Light Deep Learning Model Architecture for Chest X-ray based Covid-19 Detection

Covid-19 is a serious public health problem worldwide. To date, it has spanned worldwide with 12.8 million infected and 566, 909 confirm death. Covid-19 screening is indeed an important task and has to be done quickly as possible to many people so that early treatment can be done. The current world RT-PCR standard screening for Covid-19 detection no longer can cope to the demand of large world population. There is a need of other quick diagnosis procedure such as to use chest x-ray images and light computing algorithm to accelerate the covid-19 screening. This paper proposes Covid-19 detection based on chest X-ray image with a light computer processing. The proposed work introduces the combination of Gray Level Co-occurrence Matrix (GLCM) and Convolutional Neural Network (CNN) methods to detect Covid-19 symptom. The light version is coming from GLCM simplicity and convolutional neural network (CNN) single layer. It is fast and suitable method for places where computing resources are minimal. With light processing component, the proposed work gives the highest classification performance with 97.06% accuracy compared to other similar works. © 2021 IEEE.

[Clinical analysis and countermeasures of 739 cases treated in the emergency department of stomatology in general hospital during COVID-19 epidemic]

PURPOSE: In this paper, based on the age, sex, disease type, and consultation time of dental emergency during COVID-19 epidemic, a comprehensive analysis of dental emergency management and prevention and control of COVID-19 was conducted. METHODS: A total of 739 emergency dental cases were collected from January 29 2020 to February 28 2020. They were divided into 3 groups,including adolescents (<=18 years), young adults (18 ~ 60 years), and elderly ( >=60 years old). The data was analyzed using SPSS 21.0 software package. RESULTS: The ratio of male to female was 1.24:1. There were 655 emergency cases during the day and 84 cases during the night. The types of diseases included pericoronitis (15.83%), apical periodontitis (14.21%), pulpitis (13.40%), periodontitis (12.31%), oral mucosal disease (12.18%), Oral and maxillofacial trauma (10.55%), oral and maxillofacial space infection (8.39%), dental disease in children (5.41%), oral and maxillofacial tumors (2.84%), temporomandibular joint dislocations and disorders (1.76%), and others (3.11%). CONCLUSIONS: Under the epidemic situation of the new coronavirus, as one of the high-risk departments, it is of great significance to enhance the clinical emergency skills and ability of emergency treatment, improve patients' oral health awareness, address the diagnosis and treatment of essential diseases, for the improvement the quality of dental medical care and the prevention and control of COVID-19 epidemic.

Analyzing the early ct findings and clinical features of 12 patients with 2019 novel coronavirus disease (COVID-19) in china

Background: Regarding the outbreak of highly contagious the 2019 Novel Coronavirus (2019-nCoV) in various countries and regions, data have been needed on the early chest CT images and clinical characteristics of the affected patients. Objectives: To explore the early clinical and computed tomography (CT) characteristics of the 2019 Novel Coronavirus Disease (COVID-19) patients to improve the diagnostic level of this contagious respiratory disease. Methods: An analysis retrospectively was implemented on the radiological features and clinical characteristics of 12 patients with COVID-19 who had undergone chest CT scanning in the designated hospital from Jan 23, 2020, to Feb 18, 2020. The clinical data on general information, epidemiological, cardinal symptoms, blood test, and CT imaging characteristics were obtained. Results: According to the relevant diagnostic criteria, the patients were divided into two groups: mild (2 cases), and ordinary type (10 cases). The main symptoms of 2019-nCoV pneumonia were fever (9/12) and cough (8/12) with or without respiratory and other systemic symptoms. The blood test of the patients showed that most of the white blood cell count was normal (10/12), decreased lymphocyte count (6/12), and increased hypersensitive C reactive protein (hs-CRP) (5/12). In the early stage of COVID-19, the chest CT images showed patchy mixed ground-glass opacity (GGO) (8/12), mainly distributed in the periphery and posterior part of both lungs. The internal density of image lesion area was uneven, and lesions primarily manifested as "crazy-paving pattern" (8/12), with grid-like, interlobular septal thickening, thickened bronchovascular bundle and air bronchus sign and multiple fibrosis. A few cases showed pulmonary atelectasis (1/12), bilateral pleural effusion (1/12), no mediastinal or bilateral hilar lymph node enlargement. Conclusions: The clinical characteristics of 2019-nCoV pneumonia are similar to those of common viral pneumonia. The chest CT images may be helpful for the early detection of novel coronavirus pneumonia.