Early Cyberspace Emergency Response by Predicting Social-Emotional Security

With the intensified social conflicts and cyberspace crises, the public is facing the emotional impact and lack of security feelings responding to emergencies. The most recent research only focuses on the influence of discrete emotions, but the induced stressful feeling of emotional security has not been a concern by the government. In this work, we first propose a concept of social-emotional security, evolving from the classical theories of risk society and psychological resilience. Second, we integrate a social-emotional security index measurement method with the proposed three metrics: emotional bias, situational risk, and potential hazard. We also suggest a grading scheme for the emotional regulation strategy with a 0.3 safety valve. Finally, the accuracy is over 78% for detecting the potential risk of emerging events, and the method is feasible in another 30 social safety events with a trend coincidence beyond 63.3%.

Quantification of Cytokine Storms During Virus Infections.

Highly pathogenic virus infections usually trigger cytokine storms, which may have adverse effects on vital organs and result in high mortalities. The two cytokines interleukin (IL)-4 and interferon (IFN)-γ play key roles in the generation and regulation of cytokine storms. However, it is still unclear whether the cytokine with the largest induction amplitude is the same under different virus infections. It is unknown which is the most critical and whether there are any mathematical formulas that can fit the changing rules of cytokines. Three coronaviruses (SARS-CoV, MERS-CoV, and SARS-CoV-2), three influenza viruses (2009H1N1, H5N1 and H7N9), Ebola virus, human immunodeficiency virus, dengue virus, Zika virus, West Nile virus, hepatitis B virus, hepatitis C virus, and enterovirus 71 were included in this analysis. We retrieved the cytokine fold change (FC), viral load, and clearance rate data from these highly pathogenic virus infections in humans and analyzed the correlations among them. Our analysis showed that interferon-inducible protein (IP)-10, IL-6, IL-8 and IL-17 are the most common cytokines with the largest induction amplitudes. Equations were obtained: the maximum induced cytokine (max) FC = IFN-γ FC × (IFN-γ FC/IL-4 FC) (if IFN-γ FC/IL-4 FC > 1); max FC = IL-4 FC (if IFN-γ FC/IL-4 FC < 1). For IFN-γ-inducible infections, 1.30 × log2 (IFN-γ FC) = log10 (viral load) - 2.48 - 2.83 × (clearance rate). The clinical relevance of cytokines and their antagonists is also discussed.

The Role of Alveolar Edema in COVID-19.

The coronavirus disease 2019 (COVID-19) has spread over the world for more than one year. COVID-19 often develops life-threatening hypoxemia. Endothelial injury caused by the viral infection leads to intravascular coagulation and ventilation-perfusion mismatch. However, besides above pathogenic mechanisms, the role of alveolar edema in the disease progression has not been discussed comprehensively. Since the exudation of pulmonary edema fluid was extremely serious in COVID-19 patients, we bring out a hypothesis that severity of alveolar edema may determine the size of poorly-ventilated area and the blood oxygen content. Treatments to pulmonary edema (conservative fluid management, exogenous surfactant replacements and ethanol-oxygen vapor therapy hypothetically) may be greatly helpful for reducing the occurrences of severe cases. Given that late mechanical ventilation may cause mucus (edema fluid) to be blown deep into the small airways, oxygen therapy should be given at the early stages. The optimal time and blood oxygen saturation (SpO2) threshold for oxygen therapy are also discussed.

Perceiving Social-Emotional Volatility and Triggered Causes of COVID-19.

Health support has been sought by the public from online social media after the outbreak of novel coronavirus disease 2019 (COVID-19). In addition to the physical symptoms caused by the virus, there are adverse impacts on psychological responses. Therefore, precisely capturing the public emotions becomes crucial to providing adequate support. By constructing a domain-specific COVID-19 public health emergency discrete emotion lexicon, we utilized one million COVID-19 theme texts from the Chinese online social platform Weibo to analyze social-emotional volatility. Based on computed emotional valence, we proposed a public emotional perception model that achieves: (1) targeting of public emotion abrupt time points using an LSTM-based attention encoder-decoder (LAED) mechanism for emotional time-series, and (2) backtracking of specific triggered causes of abnormal volatility in a cognitive emotional arousal path. Experimental results prove that our model provides a solid research basis for enhancing social-emotional security outcomes.

Corrigendum: Do Humidity and Temperature Impact the Spread of the Novel Coronavirus?

[This corrects the article DOI: 10.3389/fpubh.2020.00240.].