Gaussian Process-aided Transfer Learning for Probabilistic Load Forecasting against Anomalous Events

A probabilistic load forecasting method that can deal with sudden load pattern changes caused by abnormal events such as COVID-19 is proposed in this paper. The deep residual network (ResNet) is first applied to extract the load pattern for the normal period from historical data. When an abnormal event occurs, a Gaussian Process (GP) with a composite kernel is utilized to adapt to the changes on load pattern by estimating the forecasting residual of the ResNet. The designed kernel enables the proposed method to adapt rapidly to changes in the load pattern and effectively quantify the uncertainties caused by the abnormal event using a few training samples. Comparative tests with state-of-the-art point and probabilistic forecasting methods demonstrate the effectiveness of the proposed method. IEEE

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

A review on the identification of COVID-19, SARS and MERS.

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases.Copyright © 2020 Chinese Medical Association

A YOLOv5-based Target Detection Algorithm Design

At the beginning of 2020 Gengzi, a new coronavirus pneumonia (COVID - 19) that swept the world from the sky ravaged the land of God. In order to effectively organize the massive spread of the epidemic, this paper proposes a system that combines YOLOv5 to provide detection of faces wearing masks. The system is in a situation where one or more persons wearing masks in different scenarios can be detected. The design first uses a collection of mask face data under a variety of different wearing conditions and obtains a trained detection model using the above method to achieve the detection of whether a face is wearing a mask. The detection system can effectively detect the face mask wearing situation detected in the local picture elements, local video elements and the camera real- time shooting screen. The recognition effect of the system is verified to be 0.945, which is a significant improvement compared with other algorithms. © 2022 IEEE.

Global DSGE models

We introduce our GDSGE framework and a novel global solution method, called simultaneous transition and policy function iterations (STPFIs), for solving dynamic stochastic general equilibrium models. The framework encompasses many well-known incomplete markets models with highly nonlinear dynamics such as models of financial crises and models with rare disasters including the current COVID-19 pandemic. Using consistency equations, our method is most effective at solving models featuring endogenous state variables with implicit laws of motion such as wealth or consumption shares. Finally, we incorporate this method in an automated and publicly available toolbox that solves many important models in the aforementioned topics, and in many cases, more efficiently and/or accurately than their original algorithms. © 2023 Elsevier Inc.

Virtual toxicology escape room: A novel method for providing toxicology education

Background: The Coronavirus disease 2019 pandemic led to unprecedented changes to medical education as educators adapted to a world necessitating precautions and social distancing. In response to the pandemic, the Emergency Medicine Residents' Association (EMRA) committees' educational programming in association with the American College of Emergency Physicians 2020 Scientific Assembly (ACEP20), initially scheduled to be held in Dallas, TX, between October 26-29, 2020, transitioned to a fully virtual conference. Escape rooms have become popular recreational activities over the last several years. In-person escape rooms are structured around working in teams to solve a series of puzzles in a fictional scenario that allows participants to "escape" the room upon completion. The teamwork and problem-solving skills utilized in escape rooms lend themselves to use in medical education. The traditional in-person escape room format has previously been applied to toxicology for the purposes of providing engaging toxicology education to emergency medicine (EM) residents. Method(s): The researchers developed and led the first nationwide virtual toxicology escape room during ACEP20 using the Zoom platform. The activities consisted of one web-portal linking to a sequence of four Google Forms multiple-choice question quizzes and four games made on Wordwall.net, a virtual educational activity creator. Six teams of 5 residents and medical students from residency programs across the country registered and participated for a total of 30 participants. Teams were split into Zoom breakout rooms, each moderated by at least one medical toxicologist and/or medical toxicology fellow. A survey was sent to participants to assess their overall experience with the activity. Result(s): Every team completed all eight activities within 45 min. This activity demonstrates the feasibility of a large-scale, realtime competitive virtual escape room to engage participants and deliver toxicology education. The lessons learned from exploring virtual sessions like this one will be valuable tools in the future of medical education. Ten participants completed the survey. 80% of respondents reported that the event increased their interest in toxicology. 90% agreed that the format was easy to navigate, instructions were clear, questions were understandable, and toxicologists were well utilized in the event. Conclusion(s): Toxicology-themed escape rooms have potential as virtual activities to educate EM residents on essential toxicology knowledge. While the small survey response rate limits the generalizability of this data, these initial results are promising and suggest that virtual escape rooms may be a viable option for increasing interest in toxicology among resident physicians.

Physio6: A Sensor-Based Monitoring System for 6-Minute Walking Test in the Era of COVID-19

Coronavirus disease of 2019 (COVID-19) is still severe nowadays, and plentiful COVID-19 patients need careful rehabilitation. The 6-minute walking test (6MWT) is a common clinical trial that requires the patient to walk as far as possible in a corridor for 6 minutes, significantly indicating patients' cardiopulmonary disease conditions and rehabilitation. A traditional 6MWT provides the 6-minute walking distance (6MWD) as the primary result for clinical analysis. In this paper, we propose Physio6, a sensor-based monitoring system for 6MWT, which monitors one patient's various physiological signals and indicates her/his condition during the test. The system also provides the functions of early warning based on physiological signal monitoring and automatically or manually recording the adverse events, such as hypoxia or dyspnea. Moreover, Physio6 is able to communicate with the existing systems in hospitals, and to generate a comprehensive report that summarizes the performance of the patient in the current 6MWT and even in the past ones. Our system has been deployed in four hospitals. Compared with the conventional distance-based measurement, our preliminary validation reveals that the extracted physiological parameters are promisingly valuable for clinical decision-making. System quality and device comfort are also confirmed by questionnaires. The potential of leveraging this system to perform the remote 6MWT at home/in communities as a solution of COVID-19 patient rehabilitation monitoring is also discussed. © 2021 IEEE.

Deep learning for drug repurposing: Methods, databases, and applications

Drug development is time-consuming and expensive. Repurposing existing drugs for new therapies is an attractive solution that accelerates drug development at reduced experimental costs, specifically for Coronavirus Disease 2019 (COVID-19), an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, comprehensively obtaining and productively integrating available knowledge and big biomedical data to effectively advance deep learning models is still challenging for drug repurposing in other complex diseases. In this review, we introduce guidelines on how to utilize deep learning methodologies and tools for drug repurposing. We first summarized the commonly used bioinformatics and pharmacogenomics databases for drug repurposing. Next, we discuss recently developed sequence-based and graph-based representation approaches as well as state-of-the-art deep learning-based methods. Finally, we present applications of drug repurposing to fight the COVID-19 pandemic and outline its future challenges. This article is categorized under: Data Science > Artificial Intelligence/Machine Learning

Mannose Binding Lectin (MBL) and MBL Associated Serine Protease-2 (MASP-2) Amplify SARS-CoV-2 Spike Protein Uptake and Epithelial Cell Injury during Cigarette Smoke Exposure

RationaleThe clinical syndrome associated with SARS-CoV2, known as COVID-19 is characterized by a spectrum of hypercoagulability and complement-mediated microvascular injury in severe but also in mild COVID-19 disease(1-4). Studies have demonstrated that lectin complement pathway (driven by MBL/MASP2 complex) is responsible for the complement-mediated injury via MBL binding of the SARS-CoV virion(5) and via deposition of MBL, MASP-2, and C4 seen in the skin and lung specimens of COVID-19 individuals, where SARS-CoV-2 spike protein (SP) co-localized with C4(4, 6). We hypothesize that in smokers, MBL binding to SARS-CoV-2 and MASP-2 cleavage of SP increase viral internalization with subsequent epithelial cell injury and in-situ complement activation.MethodsWe studied ACE-2 expression in lung homogenates of smokers (n=2), mild COPD (n=2), moderate and severe COPD (n=8) by western blotting and qPCR. We used A549 epithelial cells exposed to air control (AC) or CS (10%, 2h) and primary alveolar type 2 (AT2) from smokers and never-smokers to analyze ACE-2 expression by FACS and western blotting, and cell injury by western blotting before and after treatment with his-tagged SARS-CoV-2 SP (15ug/mL, 2h), recombinant human MBL (2ug/mL, 2h), and serum-derived MBL/MASP-2 complex (50% non-heat-inactivated serum). ResultsIn-vivo, CS increases ACE-2 expression in lung homogenates of smokers and COPD patients vs. healthy individuals (p<0.5). Ex-vivo, CS extract increases ACE-2 expression in A549 and AT2 epithelial cells as detected by FACS and western blotting. Moreover CS-exposed A549 epithelial cells demonstrate higher SP - ACE-2 co-localization, especially after treatment with recombinant MBL. In the presence of recombinant MBL and serum-derived MBL/MASP-2 complex we demonstrated higher co-localization of SP with MBL at the plasma membrane and higher expression of cell injury markers (RAGE, cPARP, and p62/LC3B2) of CS-exposed epithelial cells. Interestingly, transitional AT2 from smokers, expressing AT1 (Cav1) and AT2 (Muc1) markers, had the highest ACE-2 membrane expression by FACS vs. transitional AT2 from never-smokers, AT1, AT2 primary human cells. ConclusionsOur results indicate that MBL and MASP-2 of lectin pathway are linked to higher SARS-CoV-2 SP epithelial uptake and injury in smokers and COPD-ers with COVID-19 disease, suggesting that CS-induced airway inflammation and in-situ complement activation increase distal lung ACE-2 expression and AT2 injury significantly tallying airway injury in COVID-19.

Robust Deep Gaussian Process-based Probabilistic Electrical Load Forecasting against Anomalous Events

The abnormal events, such as the unprecedented COVID-19 pandemic, can significantly change the load behaviors, leading to huge challenges for traditional short-term forecasting methods. This paper proposes a robust deep Gaussian processes (DGP)-based probabilistic load forecasting method using a limited number of data. Since the proposed method only requires a limited number of training samples for load forecasting, it allows us to deal with extreme scenarios that cause short-term load behavior changes. In particular, the load forecasting at the beginning of abnormal event is cast as a regression problem with limited training samples and solved by double stochastic variational inference DGP. The mobility data are also utilized to deal with the uncertainties and pattern changes and enhance the flexibility of the forecasting model. The proposed method can quantify the uncertainties of load forecasting outcomes, which would be essential under uncertain inputs. Extensive comparison results with other state-of-the-art point and probabilistic forecasting methods show that our proposed approach can achieve high forecasting accuracies with only a limited number of data while maintaining excellent performance of capturing the forecasting uncertainties. IEEE

Progress in researches on arbidol in anti-vital treatments

At present, the pneumonia caused by the novel coronavirus (2019-nCoV) infection has developed into a serious public health problem. In vitro studies and clinical treatment have shown that arbidol has anti-2019-nCoV activity, which attracted much attention. Arbidol is a small molecule indole derivative developed by the former Soviet Union, which was approved for the prevention and control of Flu-A and Flu-B. Recent studies have found that arbidol has antiviral activity against a variety of viruses. Because of its unique antiviral effect, it provides a new breakthrough for antiviral therapy. For this reason, this article reviews the progress of antiviral research on arbidol.

Changes of clinical characteristics of asymptomatic patients with positive SARS-Cov-2 nucleic acid test during treatment cycle and related risk factors

Objective: This study was designed to explore the clinical characteristics, outcomes, and related influencing factors for asymptomatic patients with positive Severe Acute Respiratory Syndrome Corona Virus 2 (SARS-Cov-2) nucleic acid test. Methods: Clinical data of 1568 patients with positive SARS-Cov-2 nucleic acid test (SNAT) were collected retrospectively. The patients were assigned to an asymptomatic group and a symptomatic group according to the existence of clinical symptoms when they got positive result in nucleic acid test, and the clinical data of the two groups were analyzed and compared. In addition, the data of asymptomatic patients who showed clinical symptoms later and the results of two-week follow-up after cure were analyzed. Results: Among all enrolled patients, there were 1489 patients with positive symptoms and 79 asymptomatic patients, including 34 patients who developed symptoms during treatment. Logistic analysis revealed that age ≤45 years (OR=2.722, P<0.001), history of diabetes mellitus (OR=0.446, P=0.007), and history of cancer (OR=0.259, P=0.008) were independent factors for asymptomatic presentation in patients with positive SNAT, and age ≥46 years (OR=1.562, P=0.012) and history of hypertension (OR=2.077, P<0.001) were risk factors for the occurrence of clinical symptoms in asymptomatic patients with positive SNAT during hospitalization. During the follow-up after cure, 8 patients got reoccurring positive SNAT result. Conclusion: Asymptomatic patients with positive SNAT are mostly young and middle-aged people, and old age and hypertension are risk factors for the occurrence of positive clinical characteristics in asymptomatic patients.

A review on the identification of COVID-19, SARS and MERS

COVID-19 is a global pandemic, which is the third outbreak and epidemic of infectious disease caused by coronavirus in this century and constitutes a major threat to human health.In this paper, COCOVID-19, Severeacute respiratory syndrome (SARS) and Middle East Respiratory syndrome (MERS) were analyzed to distinguish their clinical features, diagnosis, prognosis and prevention, so as to better prevent and treat related diseases. © 2020 Chinese Medical Association

[Differential circRNA expression profiles in peripheral blood mononuclear cells among mild and severe influenza-associated pneumonia patients].

Objective: To explore the difference in the expression profile of circular RNA in peripheral blood mononuclear cells between patients with mild and severe influenza pneumonia. Methods: From December 2018 to March 2019, 10 inpatients with mild and 10 inpatients with severe influenza pneumonia admitted to the Department of Infection and Clinical Microbiology of Beijing Chaoyang Hospital were included. Clariom™ D gene chip was used to explore the circRNA expression profiles of peripheral blood mononuclear cells (PBMC) isolated from the patients. The absolute value of the fold change (FC value)>2 and P<0.05 were used as the criteria to screen the differentially expressed circRNA, and the gene ontology (GO) enrichment analysis and the Kyoto Encyclopedia of Gene and Genome database (Kyoto Encyclopedia of Genes and Genomes, KEGG) signal pathway enrichment analysis were also performed. Results: The age of mild patients [M (P25, P75)] was 62.0 (34.5, 69.8) years old, including 4 males; the age of severe patients [M (P25, P75)] was 50.0 (37.0, 60.0) years old, all were males. A total of 137 differentially expressed circRNAs in PBMCs of mild and severe patients were screened. The numbers of up-regulated and down-regulated circRNAs in mild patients were 101 and 36, respectively. Among them, hsa_circ_0091073 (FC value=160.898, P<0.05) was the most significantly up-regulated circRNA and hsa_circ_0092219 (FC value =-17.630, P<0.05) was the most significantly down-regulated circRNA. GO enrichment analysis showed that a total of 111 secondary GO items were significantly associated with related differential expression of circRNA (P<0.05). The GO terms associated with upregulated circRNAs included DNA-templated transcription, regulation of DNA-templated transcription, regulation of transcription from RNA polymerase Ⅱ promoter, etc.; The GO terms associated with downregulated circRNAs included neutrophil degranulation, killing of cells of other organism, defense response to fungus, etc. KEGG signaling pathway analysis showed that there were 37 metabolic pathways related to differentially expressed circRNAs (P<0.05). Signaling pathways related to up-regulated circRNAs included nuclear factor-κB (NF-κB) signaling pathway, mitogen-activated protein kinase (MAPK) signaling pathway, tumor necrosis factor (TNF) signaling pathway, etc. Signaling pathways related to down-regulation of circRNAs included cancer transcription disorders, folate carbon pool, and other types of O-glycan biosynthesis. Conclusion: The expression of circRNA in PBMC of mild and severe influenza pneumonia patients is significantly different, and it may play a role in the pathogenic mechanism of influenza pneumonia through multiple signal pathways.