Evaluation of COVID-19 Vaccines in Primary Prevention Against Infections and Reduction in Severity of Illness Following the Outbreak of Sars-Cov-2 Omicron Variant in Shanghai

Objectives: To evaluate COVID-19 vaccines in primary prevention against infections and lessening the severity of illness following the most recent outbreak of the SARS-CoV-2 Omicron variant in Shanghai. Method(s): To investigate whether inactivated vaccines were effective in protecting against COVID-19 infections, we estimated the odds ratio (OR) of the vaccination in COVID-19 cases vs. matched community-based healthy controls. To evaluate the potential benefits of vaccination in lowering the risk of symptomatic infection (vs. asymptomatic), we estimated the relative risk (RR) of symptomatic infections among diagnosed patients. We also applied the multivariate stepwise Logistic regression analyses to measure the risk of disease severity (symptomatic vs. asymptomatic and moderate/severe vs. mild) in COVID-19 patient cohort with vaccination status as an independent variable while controlling for potential confounding factors. Result(s): Out of the 153,544 COVID-19 patients included in the analysis, 118,124 (76.9%) patients had been vaccinated and 143,225(93.3%) were asymptomatic patients. Of the 10,319 symptomatic patients, 10,031(97.2%), 281(2.7%) and 7(0.1%) experienced mild, moderate, and severe infections, respectively. There is no evidence that the vaccination helped protect from infections (OR=0.82, p=0.613). The vaccination, however, offered a small but significant protection against symptomatic infections (RR=0.92, p < 0.001) and halved the risk of moderate/severe infections (OR=0.48, 95% CI: 0.37 - 0.61). Older age (> 60 years) and malignant tumors were significantly associated with moderate/severe infections. Gender also appeared to be a risk factor for symptomatic infections, with females being associated with a lower risk for moderate/severe illness. Conclusion(s): Inactivated COVID-19 vaccines helped provide a small but significant protection against symptomatic infections and halved risk of moderate/severe illness among symptomatic patients. The vaccination was not effective in blocking COVID-19 Omicron variant community spread.Copyright © 2023

Clinical Characteristics of Patients with Sars-Cov-2 Omicron Variant and COVID-19 Vaccination with Clinical Outcome Findings in Shanghai, China: A Single Center, Retrospective, Observational Study

Objectives: This study aimed to determine disease severity, clinical features, clinical outcome in hospitalized patients with the Omicron variant and evaluate the effectiveness of one-dose, two-dose, and three-dose inactivated vaccines in reducing viral loads, disease course, ICU admissions and severe diseases. Method(s): Retrospective cohort analysis was performed on 5,170 adult patients (>=18 years) identified as severe acute respiratory syndrome coronavirus 2 positive with Reverse Transcription Polymerase Chain Reaction admitted at Shanghai Medical Center for Gerontology between March 2022 and June 2022. COVID-19 vaccination effectiveness was assessed using logistic regression models evaluating the association between the risk of vaccination and clinical outcomes, adjusting for confounders. Result(s): Among 5,170 enrolled patients, the median age was 53 years, and 2,861 (55.3%) were male. 71.0% were mild COVID-19 cases, and cough (1,137 [22.0%]), fever (592 [11.5%]), sore throat (510 [9.9%]), and fatigue (334 [6.5%]) were the most common symptoms on the patient's first admission. Ct values increased generally over time and 27.1% patients experienced a high viral load (Ct value< 20) during their stay. 105(2.0%) of these patients were transferred to the intensive care unit after admission. 97.1% patients were cured or showed an improvement in symptoms and 0.9% died in hospital. The median length of hospital stay was 8.7+/-4.5 days. In multivariate logistic analysis, booster vaccination can significantly reduce ICU admissions and decrease the severity of COVID-19 outcome when compared with less doses of vaccine (OR=0.75, 95%CI, 0.62-0.91, P<=0.005;OR=0.99, 95%CI, 0.99-1.00, p<0.001). Conclusion(s): In summary, the most of patients who contracted SARSCoV-2 omicron variant had mild clinical features and patients with vaccination took less time to lower viral loads. As the COVID-19 pandemic progressed, an older and less vaccinated population was associated with higher risk for ICU admission and severe disease.Copyright © 2023

Lipid nanoparticle library towards development next generation genomic medicines

Ionizable amino lipids are a major constituent of the lipid nanoparticles for delivering nucleic acid therapeutics (e.g., DLin-MC3-DMA in ONPATTRO , ALC-0315 in Comirnaty , SM-102 in Spikevax ). Scarcity of lipids that are suitable for cell therapy, vaccination, and gene therapies continue to be a problem in advancing many potential diagnostic/therapeutic/vaccine candidates to the clinic. Herein, we describe the development of novel ionizable lipids to be used as functional excipients for designing vehicles for nucleic acid therapeutics/vaccines in vivo or ex vivo use in cell therapy applications. We first studied the transfection efficiency (TE) of LNP-based mRNA formulations of these ionizable lipid candidates in primary human T cells and established a workflow for engineering of primary immune T cells. We then adapted this workflow towards bioengineering of CAR constructs to T cells towards non-viral CAR T therapy. Lipids were also tested in rodents for vaccine applications using self-amplifying RNA (saRNA) encoding various antigens. We have then evaluated various ionizable lipid candidates and their biodistribution along with the mRNA/DNA translation exploration using various LNP compositions. Further, using ionizable lipids from the library, we have shown gene editing of various targets in rodents. We believe that these studies will pave the path to the advancement in nucleic acid based therapeutics and vaccines, or cell gene therapy agents for early diagnosis and detection of cancer, and for targeted genomic medicines towards cancer treatment and diagnosis.

Advances in particulate matter filtration: Materials, performance, and application

Air-borne pollutants in particulate matter (PM) form, produced either physically during industrial processes or certain biological routes, have posed a great threat to human health. Particularly during the current COVID-19 pandemic, effective filtration of the virus is an urgent matter worldwide. In this review, we first introduce some fundamentals about PM, including its source and classification, filtration mechanisms, and evaluation parameters. Advanced filtration materials and their functions are then summarized, among which polymers and MOFs are discussed in detail together with their antibacterial performance. The discussion on the application is divided into end-of-pipe treatment and source control. Finally, we conclude this review with our prospective view on future research in this area. (c) 2022 Institute of Process Engineering, Chinese Academy of Sciences. Publishing services by Elsevier B.V. on behalf of KeAi Communications Co., Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Coronavirus Disease 2019 and Thyroid Diseases.

Since the outbreak of coronavirus disease 2019 (COVID-19), a number of COVID-19 related thyroid disorders have been reported, including subacute thyroiditis, autoimmune thyroid disease, non-thyroidal illness syndrome and some unexplained thyroid dysfunction. This review aimed to summarize clinical characteristics of COVID-19 related thyroid disorders and to discuss some possible mechanisms.Copyright © 2022, Peking Union Medical College Hospital. All rights reserved.

Challenges in the construction of a tunnel under crossing a channel in Singapore

To increase the conveyance capacity to Western Singapore and to meet long-term water needs in a more cost-effective manner, four new transmission pipelines consisting of 2 numbers of 2200 mm diameter and 2 numbers of 1200mm diameter water pipes will be needed by 2024 to convey water from a Water Reclamation Plant to existing networks in the western region of Singapore. Out of the several possible routes studied, the most cost-effective and technically feasible route was selected by laying the proposed 1.6km-long pipelines that under crosses a channel via a 6m diameter subsea tunnel. This paper outlines the challenges the team faced throughout the project thus far. It also examines the difficulties such as the construction of a 56m-deep launching shaft near a highly sensitive 700mm diameter Gas Transmission Pipeline (GTP) and at a location with high groundwater;and manpower and supply disruptions caused by the COVID-19 pandemic situation. © 2023 The Author(s).

Monintoring Student Depression by Mobile Devices with Autoencoder Networks

The timely assessment of mental health is difficult since we lack the objective measurements of symptoms, especially for the Covid-19 pandemic quarantined students. Fortunately, smart phones can capture the real-world data such as the GPS traces and the phone active time et.al that link the behavioral patterns to the mental health. However, recent studies are based on a very small size of participants and only collect fewer phone features, which means that the effective predicting models which require various features are hardly adopted. In this paper, we develop an android application to record multidimensional data of users as well as a PHQ-9 and a SAS questionary, and we distribute it to 176 college students to collect larger scale data when in quarantine period. To address the unprecise problem of handcrafted feature extraction, we design an autoencoder machine learning model to monitor the student mental health. Extensive experiments indicate that the performance of the proposed method improves its F-1 score for PHQ-9 and SAS by 5% and 6% to the state of the current studies, respectively. © 2023 IEEE.

Diagnostic value of sputum nucleic acid amplification testing for COVID-19 a meta-analysis

Objective: To systematically evaluate the diagnostic value of nucleic acid test in sputum for COVID-19 and to determine the suitable population for sputum specimens. Method(s): PubMed, CNKI, Scopus, Web of Science, medRxiv and bioRxiv databases were searched for the diagnostic value of sputum nucleic acid test for COVID-19 from December 2019 to April 2022. Two researchers independently screened the literature, extracted data, and evaluated the risk of bias with QUADAS-2 in the included studies. We used sensitivity, specificity, AUC and DOR to evaluate the diagnostic value of sputum specimens. Result(s): A total of 25 studies were included, including 10,731 subjects. Meta-analysis results showed that: The combined sensitivity (SEN), specificity (SPE), diagnostic odds ratio (DOR), and area under operating characteristic curve (AUC) of sputum nucleic acid for the diagnosis of COVID-19 were 89.2% (95% CI, 86.6-91.4), 97.5% (95% CI, 97.2-97.8), 41.4 (95% CI, 11.7-145.9), 0.9474 (95% CI, 0.8964-0.9846). The results of subgroup analysis showed that the Asian group's DOR was 36.835 (95% CI, 10.83-134.570), and the Non-Asian group's DOR was 66.294 (95% CI, 0.719-6109.09). The DOR was 27.207 (95% CI, 2.860-258.780) in the OPS group and 44.165 (95% CI, 4.828-403.970) in the NPS group. DOR of mild patients was 84.255 (95% CI, 9.975-711.690), the DOR of the severe group was 14.216 (95% CI, 3.527-57.142) and was 19.464 (95% CI, 0.724-522.920) in the cured group. Conclusion(s): Current evidence shows that sputum nucleic acid test is of high diagnostic value for COVID-19. Study area and severity of disease are the influencing factors for the diagnostic accuracy of the sputum nucleic acid test. Due to the limitations on the number and quality of the included studies, the above conclusions need to be verified by more high-quality studies.Copyright © 2023, E-Century Publishing Corporation. All rights reserved.

Difference of Clinical Characteristics in Patients with Omicron and Delta Variants of SARS-CoV-2 in Beijing, China

Background Delta and Omicron are two main variants that have been prevalent since 2021. However, the Omicron variant of severe acute respiratory syndrome coronavirus 2 shows a less severe clinical presentation and high transmissibility. Therefore, we carried out this retrospective study to evaluate Omicron severity compared with the Delta variant and further comprehend the differences in clinical characteristics in patients with the Omicron variant. Methods We extracted clinical data and compared clinical severity, symptoms, vaccination status, laboratory parameters, viral shedding time, and computed tomography (CT) imaging between the two groups of patients, which included 109 COVID-19 cases with the Delta variant and 183 cases with the Omicron variant, from January 19 to April 1, 2022, in Beijing Ditan Hospital. In addition, the Beijing Center for Disease Prevention and Control conducted whole-genome sequencing. Results We obtained 94 strains of variants of concern/Delta and 110 strains of variants of concern/Omicron. For the 110 Omicron strains, three were assigned as BA.1.1, 53 as BA.2, and 54 as BA.2.2. Among patients with the Delta variant, 54% (59/109) were moderate, which was significantly higher than that of patients with the Omicron variant (7% (12/183), P < 0.001). The number of patients with mild symptoms in the Omicron group was significantly higher than in the Delta group (80% vs. 35%, P < 0.001). Compared with the Omicron group, patients with underlying diseases or obesity, 60 years or older, or unvaccinated in the Delta group had more severe disease, and there was a significant difference between the two groups. The viral shedding time in the Omicron group was shorter than in the Delta group ((11.9 ± 5.9) vs. (14.0 ± 5.8) days, P = 0.003). Among the 183 patients in the Omicron group, 104 (57%) had dry or sore throat symptoms, more than those in the Delta group (34% (37/109);P < 0.001). In the Delta group, patients in the moderate group had more fever and cough symptoms than those in the mild group. The remission time of CT imaging in the Omicron group was shorter than in the Delta group ((9.0 ± 5.2) vs. (13.2 ± 4.2) days, P = 0.018). Conclusions Patients with Delta variants are more likely to have pneumonia, mainly with fever and cough symptoms, while patients with the Omicron variant are mostly mild, with more prominent dry or sore throat symptoms. In addition, patients with the Omicron variant have a short viral shedding time and rapid absorption of pneumonia. © Wolters Kluwer Health, Inc. All rights reserved.

Causes analysis and coping strategies for psychological crisis in perintal maternal with COVID‑19

Coronavirus disease 2019(COVID-19) epidemic situation is a public health emergency, it brings serious psychological crisis to the perintal maternal, the severe psychological crisis of patients will be detrimental to their health. In the article, the authors analyzed the causes of the psychological crisis from various aspects for the perintal maternal with COVID-19, put forward some strategies on how to effectively copy with the mental crisis, and finally presented the necessary considerations for certain fields which were underestimated in clinical work now. © 2022 Editorial Board of Medical Journal of Wuhan University. All rights reserved.

Clinical Efficacy of Modified Sanxiaoyin in Treatment of Mild or Moderate COVID-19 Patients:Based on Retrospective Analysis.

Objective: To retrospectively analyze the clinical data of 52 patients with coronavirus disease-2019 COVID-19 and explore the clinical efficacy of modified Sanxiaoyin on mild/moderate COVID-19 patients. Method(s): The propensity score matching method was used to collect the clinical data of mild or moderate COVID-19 patients enrolled in the designated hospital of the Second Hospital of Jingzhou from December 2019 to May 2020. A total of 26 eligible patients who were treated with modified Sanxiaoyin were included in the observation group,and the 26 patients treated with conventional method were the regarded as the control. The disappearance of clinical symptoms,disappearance time of main symptoms,efficacy on traditional Chinese medicineTCMsymptoms,hospitalization duration,laboratory test indicators,and CT imaging changes in the two groups were compared. Result(s): The general data in the two groups were insignificantly different and thus they were comparable. After 7 days of treatment,the disappearance rate of fever,cough, fatigue,dry throat,anorexia,poor mental state,and poor sleep quality in the observation group was higher than that in the control groupP<0.05,and the difference in the disappearance rate of expectoration and chest distress was insignificant. For the cases with the disappearance of symptoms,the main symptomsfever, cough,fatigue,dry throat,anorexia,chest distressdisappeared earlier in the observation group than in the control groupP<0.01. After 7 days of treatment,the scores of the TCM symptom scale of both groups decreasedP<0.01,and the decrease of the observation group was larger that of the control groupP<0.01. All patients in the two groups were cured and discharged. The average hospitalization duration in the observation group12.79+/-2.68dwas shorter than that in the control group15.27+/-3.11dP<0.01. The effective rate in the observation group92.31%,24/26was higher than that in the control group76.92%,20/26. After 7 days of treatment,the lymphocyteLYMcount increasedP<0.05,and white blood cellWBCcount and neutrophilNEUTcount decreased insignificantly in the two groups. Moreover,levels of C-reactive protein CRP,erythrocyte sedimentation rateESR,and procalcitoninPCTreduced in the two groups after treatmentP<0.01and the reduction in the observation group was larger than that in the control group P<0.01. Through 7 days of treatment,the total effective rate on pulmonary shadow in the observation group 90.00%,18/20was higher than that in the control group77.27%,17/22P>0.05and the improvement of lung shadow in the observation group was better than that in the control groupP<0.01. Conclusion(s):Modified Sanxiaoyin can significantly alleviate fever,cough,fatigue,anorexia,chest distress,poor sleep quality,and other symptoms of patients with mild or moderate COVID-19,improve biochemical indicators,and promote the recovery of lung function. This paper provides clinical evidence for the application of modified Sanxiaoyin in the treatment of mild or moderate COVID-19.Copyright © 2022, China Academy of Chinese Medical Sciences Institute of Chinese Materia Medica. All rights reserved.

A Novel Machine Learning-assisted Pairs Trading Approach for Trading Risk Reduction

The cryptocurrency market has been growing rapidly in recent years. The volume of transactions and the number of participants in the cryptocurrency market makes it huge enough that we cannot ignore it. At the same time, the global stock market has also reached a new height in the past two years. However, due to the COVID epidemic and other political and economic-related factors in the last two years, the uncertainty in the capital market remains high, and short-term large fluctuations occur frequently;thus, many investors have suffered substantial losses. Pairs trading, an advanced statistical arbitrage method, is believed to hedge the risk and profit off the market regardless of market condition. Amongst the vast literature on pairs trading, there have been investors trading a pair of cryptocurrencies or a pair of stocks using machine learning or empirical methods. This research probes the boundary of utilizing machine learning methods to do pairs trading with one stock asset and another cryptocurrency. Briefly, we built an assets pool with both stocks and cryptocurrencies to find the best trading pair. In addition, we applied mainstream machine learning models to the trading strategy. We finally evaluated the accuracy of the proposed method in prediction and compared their returns based on the actual U.S. Stock and Cryptocurrency Market data. The test results show that our method outperforms other state-of-the-art methods. © 2022 IEEE.

VMCTE: Visualization-Based Malware Classification Using Transfer and Ensemble Learning

The Corona Virus Disease 2019 (COVID-19) effect has made telecommuting and remote learning the norm. The growing number of Internet-connected devices provides cyber attackers with more attack vectors. The development of malware by criminals also incorporates a number of sophisticated obfuscation techniques, making it difficult to classify and detect malware using conventional approaches. Therefore, this paper proposes a novel visualization-based malware classification system using transfer and ensemble learning (VMCTE). VMCTE has a strong anti-interference ability. Even if malware uses obfuscation, fuzzing, encryption, and other techniques to evade detection, it can be accurately classified into its corresponding malware family. Unlike traditional dynamic and static analysis techniques, VMCTE does not require either reverse engineering or the aid of domain expert knowledge. The proposed classification system combines three strong deep convolutional neural networks (ResNet50, MobilenetV1, and MobilenetV2) as feature extractors, lessens the dimension of the extracted features using principal component analysis, and employs a support vector machine to establish the classification model. The semantic representations of malware images can be extracted using various convolutional neural network (CNN) architectures, obtaining higher-quality features than traditional methods. Integrating fine-tuned and non-fine-tuned classification models based on transfer learning can greatly enhance the capacity to classify various families of malware. The experimental findings on the Malimg dataset demonstrate that VMCTE can attain 99.64%, 99.64%, 99.66%, and 99.64% accuracy, F1-score, precision, and recall, respectively. © 2023 Tech Science Press. All rights reserved.

Pyroptosis in the lung and spleen of patients died from COVID-19

The purpose of this study was to investigate the expression of pyroptosis-related factors (NLRP3, IL-18, NF-kappa B, HMGB-1, and GSDMD) in patients who died of COVID-19. The expression levels of NLRP3, IL-18, NF-kappa B, HMGB-1, and GSDMD in lung and spleen tissues of the COVID-19 group and the control group were detected by tissue immunofluorescence. The control group includes lung tissues and spleen tissues of two patients who died unexpectedly without SARS-CoV-2 infection, and the COVID-19 group includes the lung and spleen tissues of three patients who died of SARS-CoV-2 virus infection. The positive rates of NF-kappa B, NLRP3, IL-18, and GSDMD in the lung tissues from the control group and COVID-19 group were 9.8% vs 73.4% (p = 0.000), 5.5% vs 63.6% (p = 0.000), 24.4% vs 76.2% (p = 0.000), and 17.5% and 46.8% (p = 0.000) respectively. The positive rates of NF-kappa B, NLRP3, IL-18, HMGB-1, and GSDMD in the spleen tissues from the control group and COVID-19 group were 20.6% vs 71.2% (p = 0.000), 18.9% vs 72.0% (p = 0.000), 15.2% vs 64.8% (p = 0.000), 27.6% vs 69.2% (p = 0.000), and 23% and 48.8% (p = 0.000), respectively. The positive rates of SARS-CoV-2 spike protein in the CD68 positive cells of the lung and spleen in the control group and COVID-19 group were 2.5% vs 56.8% (p = 0.000);3.0% vs 64.9% (p = 0.000) respectively. The rates of NF-kappa B positive nuclei in the control group and COVID-19 group were 13.4% vs 51.4% (p = 0.000) in the lung and 38.2% vs 59.3% (p = 0.000) in the spleen. The rates of HMGB-1 positive cytoplasm in the control and the COVID-19 group were 19.7% vs 50.3% (p = 0.000) in the lung and 12.3% vs 45.2% (p = 0.000) in the spleen. The targets of SARS-CoV-2 are the lung and spleen, where increased macrophages could be involved in the up-regulation of pyroptosis-related inflammatory factors such as NF-kappa B, HMGB-1, NLRP3, IL-18, and GSDMD.

Simulation Analysis of Infectious Disease Trend Based on Improved SEIR Model

Scholars have carried out a lot of research in the field of using data processing methods to analyze the evolution characteristics and development trends of infectious diseases. The research on data model method is more in-depth, that is, according to the specific characteristics of infectious diseases, suitable data models are designed and combined with different parameters to analyze infectious diseases, mainly including infectious disease data models based on statistical theory or dynamic theory. The former is mostly used in the case of insufficient initial data. Local analysis is carried out by means of a priori or assumptions to achieve global prediction. The latter mainly includes SIR model, complex network model, and cellular automata model. SIR model is the most in-depth research. Scholars have constructed or optimized Si model, SIS model, SEIR model, IR model, and other derivative models based on SIR model in combination with the characteristics of viruses. In this paper, the data source is Wuhan epidemic information released by Health Commission of Hubei Province. Combined with the specific characteristics of COVID-19, the traditional dynamic propagation model is optimized, and an improved SEIR model is constructed. The results of the improved SEIR model are in good agreement with the actual epidemic trend in Wuhan. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

Promoting Green Buildings and Low-Carbon Design Strategies of Green B&B Rooms for Sustainable Tourism after COVID-19

COVID-19 opened a window of opportunity to change the green development of the hospitality industry. For many years, Chinese tourists have been the world's largest source of outbound tourists. Therefore, this study attempted to improve built-environment strategies for green rooms at B&Bs using the empirical statistics of Chinese tourists after the end of COVID-19 control measures and different green B&B standards, combining IPA (importance-performance analysis). For the lack of a green built-environment study from a tourism perspective, this study can be used mainly for improving the green satisfaction of urban B&Bs as it attempted to fill the gaps in research on green B&B rooms. This study will significantly help improve the quality of green rooms for the B&B industry in the future, and it also provides an improved green B&B room sample for other countries and regions. Moreover, it is an optimistic attempt at hospitality and tourism recovery. © 2023 by the authors.

Optimized hierarchical radial basis function neural networks by developing coronavirus herd immunity optimizer for solid oxide fuel cells

A new blackbox technique has been presented in this article for model estimation of solid oxide fuel cells (SOFCs) for providing better results. The proposed method is based on a hierarchical radial basis function (HRBF). The presented method is then developed by a new modified metaheuristic called developed coronavirus herd immunity algorithm (DCHIA). The suggested model has been named DCHIA-HRBF. The proposed model is then trained by some data and prepared for identification and prediction. The model is then analyzed and put in comparison with several latest techniques for validation of the efficiency of the technique. It is also verified by the empirical data to prove its validation with the real data. The results show that the best cost for the performance index which is the network error, is achieved by the proposed developed coronavirus herd immunity algorithm with about 119.442, which is satisfying for the considered function and target against the other state-of-the-art methods. As a result, the simulation results specified that the suggested DCHIA-HRBF delivers high effectiveness as an identifier and prediction tool for the SOFCs. © 2023 John Wiley & Sons, Ltd.

Molecular epidemiological analysis of COVID-19 imported cases in Ruili from July to November, 2021

Objective To analyze the epidemiological and genomic characteristics of COVID-19 cases imported by land in Ruili, and to provide reference for border epidemic prevention and control in Yunnan Province. Methods We collected information about SARS-CoV-2 infected individuals from overseas land in Ruili, Yunnan from July to November, 2021. The epidemiological characteristics were statistically analyzed. The second-generation sequencing platform of Illumina was used to conduct high-through-put sequencing on the selected 40 positive samples and to analyze their genotyping and variation characteristics. Results During the study period,Ruili City reported 796 COVID-19 cases from abroad.The median age of COVID-19 cases was 28.5 years (Interquantile range 10, range 1–85). The gender ratio between men and women was 4.61 : 1, Most of these infected individuals engaged in business services, accounting for 49.75% (396/796) , 95.60% of COVID-19 cases were mild and moderate cases. The sequencing results of 34 cases can be divided into three clades according to Nextstrain typing method, including 24 cases belong to 21A(Delta) clade, 9 cases belong to 21I(Delta) clade and 1 case belongs to 20I (Alpha V1) clade. Conclusions The virus genotypes of the cases in this study were mainly divided into three branches and there were some differences among them, most of which were Delta mutants.We should continue to implement border control measures and continue to monitor the virus mutation of imported cases, so as to evaluate the threat of the mutant strain to the current situation of epidemic prevention and control in Yunnan Province. © 2023, Publication Centre of Anhui Medical University. All rights reserved.

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