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Eliminating pathogen exposure is an important approach to control outbreaks of epidemics such as COVID-19 (coronavirus disease 2019). To deal with pathogenic environments, using disinfection robots is a practicable choice. This research formulates a 3D (three-dimensional) spatial disinfection strategy for a disinfection robot. First, a disinfection robot is designed with an extensible control framework for the integration of additional functions. The robot has eight degrees of freedom that can handle disinfection tasks in complex 3D environments where normal disinfection robots lack the capability to ensure complete disinfection. An ingenious clamping mechanism is designed to increase flexibility and adaptability. Secondly, a new coverage path planning algorithm targeted at the spraying area is used. This algorithm aims to achieve an optimal path via the rotating calipers algorithm after transformation between a 2D (two-dimensional) array and 3D space. Finally, the performance of the designed robot is tested through a series of simulations and experiments in various spaces that humans usually live in. The results demonstrate that the robot can effectively perform disinfection tasks both in computer simulation and in reality.
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This study utilizes the enclosed and stable environment of underground space for long-term sustainable planning for urban epidemics and disasters. Owing to the COVID-19 epidemic, cities require long-term epidemic-disaster management. Therefore, this study proposed a strategy for integrating multiple functions to plan a comprehensive Underground Resilience Core (URC). A planning and assessment methods of URC were proposed. With this methodology, epidemic- and disaster- URCs were integrated to construct a comprehensive-URC in underground spaces. The results show: (1) Epidemic-resilient URCs adopting a joint progressive approach with designated hospitals can rapidly suppress an epidemic outbreak. (2) The regularity of the morphology of underground spaces determines the area of the URC. Bar-shaped underground spaces have the potential for planning disaster-URCs. (3) The URC planning efficiency ranking is as follows: Bar shapes lead overall, T shapes are second under seismic resilience, and Cross shapes are second under epidemic resilience. (4) The potential analysis of planning a comprehensive-URC in the underground parking in Chinese cities showed that the recovery time can be advanced from 29% to 39% and the comprehensive resilience can be improved by 37.63%. The results of this study can serve as sustainable urban planning strategies and assessment tools for long-term epidemic-disaster management.
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Wild animals are considered reservoirs for emerging and reemerging viruses, such as the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Previous studies have reported that bats and ticks harbored variable important pathogenic viruses, some of which could cause potential diseases in humans and livestock, while viruses carried by reptiles were rarely reported. Our study first conducted snakes' virome analysis to establish effective surveillance of potential transboundary emerging diseases. Consequently, Adenoviridae, Circoviridae, Retroviridae, and Parvoviridae were identified in oral samples from Protobothrops mucrosquamatus, Elaphe dione, and Gloydius angusticeps based on sequence similarity to existing viruses. Picornaviridae and Adenoviridae were also identified in fecal samples of Protobothrops mucrosquamatus. Notably, the iflavirus and foamy virus were first reported in Protobothrops mucrosquamatus, enriching the transboundary viral diversity in snakes. Furthermore, phylogenetic analysis revealed that both the novel-identified viruses showed low genetic similarity with previously reported viruses. This study provided a basis for our understanding of microbiome diversity and the surveillance and prevention of emerging and unknown viruses in snakes.
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Since the first study on computer-mediated communication tools in support of language learning was published in 1992, asynchronous and synchronous tools have been widely adopted;however, few reviews have been conducted to explore the research status in this field. As COVID-19 has increased the use of online tools in education, the need to understand how asynchronous and synchronous tools are being used in language education has grown. In this bibliometric analysis, we reviewed asynchronous and synchronous online language learning (ASOLL) by analyzing the trends, topics, and findings of 319 articles on ASOLL. The results indicate that interest in ASOLL has increased over the past three decades with ASOLL for oral proficiency development and collaborative ASOLL being the two main research issues. Interest in three topics collaborative ASOLL, emotions, and corrective feedback - was especially apparent. The review contributes to the understanding of ASOLL while providing practical implications for using information communication technologies to enhance language learning.
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This study draws on corpus methodology to investigate people's reactions to COVID-19 vaccination using the data of Macau netizens' comments on a YouTube channel. Four main topics under discussion were identified based on the word lists. Meanwhile, people were concerned about the activity of vaccines and were also engaged in heated debates on both domestic and foreign vaccines according to the collocation of "疫苗” yìmiáo (vaccine). The discussion topics and concerns varied along with time, evidenced by the results of word lists and collocates of each month. It is also noticeable that some misinformation on vaccines burgeoned and faded before and after the mass vaccination of Macau residents. The supportive voices for the (Chinese) vaccines were building up their momentum over time. This phenomenon lends support to the effective persuasion of gain-framed messages in advocating safe behaviour based on Prospect Theory. Our research has revealed that the corpus-based study of online comments can be leveraged to uncover people's social behaviour in the pandemic context. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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[Background] Front-line medical staff are an important group in fighting against Coronavirus Disease 2019 (COVID-19), and their mental health should not be ignored. [Objective] This study investigates the current situation and influencing factors of post-traumatic stress disorder (PTSD) among front-line anti-epidemic medical staff during COVID-19 epidemic. [Methods] Medical staff who had participated in fighting against the COVID-19 epidemic wereselected from three grade III Class A hospitals and four grade II Class A hospitals in a city of Hubei Province by convenient sampling method in May 2020. The survey was conducted online using the Post-traumatic Stress Checklist-Civilian Version (PCL-C) as the main survey tool to investigate current situation and characteristics of PTSD among these participants. A total of 1120 questionnaires were collected, of which 1071 were valid, and the effective rate was 95.6%. [Results] Of the 1071 participants, the average age was (32.59+/-5.21) years;the ratio of male to female was 1: 5.02;the ratio of doctor to nurse was 1:5.8;nearly 70% participants came from grade III Class A hospitals;married participants accounted for 75.4%;most of them held a bachelor degree or above (86.5%);members of the Communist Party of China (CPC) accounted for 22.9%;50.9% had junior titles;the working years were mainly 5-10 years (42.8%);more than 80.0% participants volunteered to join the front-line fight;95.1% participants received family support;43.0% participated in rescue missions;78.1% participants fought the epidemic in their own hospitals;more than 60% participants considered the workload was greater than before;34.4% participants fought in the front-line for 2-4 weeks, and 23.5% participants did for more than 6 weeks. There were 111 cases of positive PTSD syndromes (PCL-C total score >=38) with an overall positive rate of 10.4%, and the scores of reexperience [1.40 (1.00, 1.80)] and hypervigilance [1.40 (1.00, 2.00)] were higher than the score of avoidance [1.14 (1.00, 2.57)]. The results of univariate analysis revealed that PTSD occurred differently among participants grouped by age, political affiliation, working years, anti-epidemic activities location, accumulated working hours in fighting against COVID-19, having child parenting duty, voluntariness, family support, whether family members participated in front-line activities, and rescue mission assignment (P<0.05). The results of logistic regression analysis showed that the incidence rates of reporting PTSD syndromes in medical personnel aged 31-40 years (OR=0.346, 95%CI: 0.164-0.730) and aged 41 years and above (OR=0.513, 95%CI: 0.319-0.823) were lower than that in those aged 20-30 years;the incidence rates of reporting PTSD syndromes in medical staff who were CPC members (OR=0.499, 95%CI: 0.274-0.909), volunteered to participate (OR=0.584, 95%CI: 0.360-0.945), and received family support (OR=0.453, 95%CI: 0.222-0.921) were lower than those did not (P<0.05);the incidence rates of reporting PTSD syndromes among medical workers who had child parenting duty (OR=2.372, 95%CI: 1.392-4.042), whose family members participated in front-line activities (OR=1.709, 95%CI: 1.135-2.575), and who participated in rescue missions (OR=1.705, 95%CI: 1.133-2.565) were higher than those who did not (P<0.05). [Conclusion] The positive PTSD syndrome rate is 10.4% in the front-line anti-epidemic medical staff. Age, political affiliation, voluntariness, family support, having child parenting duty, with a family members participating in the fight, and rescue mission assignment are the influencing factors of PTSD.Copyright © 2021, Shanghai Municipal Center for Disease Control and Prevention. All rights reserved.
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In this paper, we reported on the lattice distortion, surface morphologies, vacancy defects and electrochemical performance that had been observed in Na3V2(PO4)2F3 prepared at different annealing temperatures. X-ray diffraction indicated that all the samples were single phase materials with tetragonal structure and exhibited lattice distortion with the increase of annealing temperatures. A possible mechanism causing the strain-induced lattice distortion had been discussed. Moreover, scanning electron microscopy and positron annihilation techniques were used to study the grain size and vacancy defects as a function of annealing temperatures. The superior electrochemical performance of Na3V2(PO4)2F3 electrode was obtained at the annealing temperature of 350 degrees C with 167.73 F center dot g-1 specific capacitance and 85% capacitance retention. The better electrochemical performance was due to the synergistic effects of grain size and vacancy defect regulated by the annealing temperatures. These results could provide experimental basis for enhancing electrochemical performance of Na3V2(PO4)2F3 in sodium-ion battery area applications. (c) 2023 Elsevier B.V. All rights reserved.
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Objective: To predict the protection probability of different clinical outcomes after reinfection with Omicron variant in symptomatic and unvaccinated COVID-19 patients who infected with prototype strain. Methods: The data used in this study were derived from a systematic review and meta-analysis which systematically searched PubMed, Embase, Web of Science, and Europe PMC databases, included published and uploaded studies of dynamic changes of neutralizing antibodies in symptomatic COVID-19 patients from 1 January 2020 to 2 October 2022 and extracted the literature information, study design, serological experiment information and antibody results. According to the scatter distribution characteristics of antibody titer data, a generalized additive model based on Gaussian distribution was used to fit the titer value of neutralizing antibody based on logarithmic conversion and the dynamic change pattern of neutralizing antibody in symptomatic and unvaccinated COVID-19 patients infected with prototype strain over time was obtained. In this study, the fitted antibody titers of patients on the 28th, 51st, and 261st day after symptom onset was selected to predict the protection probability. Results: Neutralizing antibodies produced in symptomatic and unvaccinated patients infected with prototype strain could provide protection against Omicron reinfection, and the probability of protection gradually decreased with time. Neutralizing antibody level on day 28 after symptom onset provided protection probability of 30.3% (95%CI: 20.0%-45.5%) against reinfection, 51.5% (95%CI: 33.4%-75.9%) against symptomatic reinfection, and 91.2% (95%CI: 77.1%-97.7%) against severe reinfection caused by Omicron BA.5. The protection probability against Omicron BA.1, BA.4 and BA.5 reinfections decreased significantly 261 days after symptom onset, showing 9.6%-12.9%, 18.4%-23.9% and 63.1%-70.3% against three clinical outcomes, respectively. At the same time point and against the same clinical outcome, the protection probability of BA.1 was the highest, followed by BA.4 and BA.5. Conclusions: Neutralizing antibodies induced in symptomatic and unvaccinated COVID-19 patients previously infected with the prototype strain have limited protection probability against Omicron BA.5 reinfections and symptomatic reinfections. The protection probability against Omicron BA.5 reinfections is 30.3% 28 days after symptom onset and decreases to about 10% after 261 days. However, the protection probability against severe reinfections is considerable, with over 90% 28 days after symptom onset and still exceeding 60% after 261 days.
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COVID-19 , Reinfection , Humans , SARS-CoV-2 , Antibodies, Neutralizing , Probability , Antibodies, ViralABSTRACT
Objective: To investigate how well do the middle school students in Wuhan know and perform COVID-19 prevention behaviors during the epidemic, and to identify the influencing factors that impact the wellness of students' performance on mask-wearing, hand washing, and other health-related behaviors. Method: We surveyed 21 middle schools in Wuhan using a self-developed questionnaire, evaluated the students' prevention behaviors, and used logistic regression to identify the influencing factors. Results: We investigated 6 858 students with an average age of (14. 5±1. 5) years, including 3 584 male students (accounting for 52. 3%). Grade, parents' education, and submission time are significantly related to the wellness of the three types of health behaviors (P<0. 05). Junior high school students showed a better performance in handwashing and other health-related behaviors than senior high school students (P<0. 05). Parents' education showed a significant impact on students' prevention behaviors in all aspects (P<0. 05). Conclusion: Enhancement is needed for the education of prevention behaviors among middle school students. Schools should pay more attention to students whose parents are of the lower level of education. © 2023 Editorial Board of Medical Journal of Wuhan University. All rights reserved.
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Objective: To investigate the incidence rates of anxiety and depression among the COVID-19 patients and their association with clinical features and laboratory variables. Methods: A total of 371 COVID-19 patients were recruited from Wuhan Leishenshan Hospital from Jan 20 to May 10, 2020. The anxiety and depression were assessed by using the Hosptial Anxiety and Depression Score (HAD), the Self-rating Anxiety Scale (SAS), and Self-rating Depression Scale (SDS). The clinical features and laboratory variables were collected through electronic medical record. Statistical analyses were used to investigate the influence factors associated with anxiety and depression. Results: Among the 371 COVID-19 patients, the frequency of anxiety measured by HAD or SAS was 22. 91% and 24. 26%, respectively. The frequency of depression based on HAD or SDS was 16. 17% and 9. 43%, respectively. There were more female unmarried individuals in the anxiety or depression group. Anxiety or depression scores were significantly inversely correlated with the time for nucleic acid test turning negative. D-dimer and interleukin-6 (IL-6) were significantly elevated in the individuals with anxiety and depression. Statistically significant downregulations of lymphocyte counts, hemoglobin, and creatinine were found in anxiety and depression group. There was a negative association between creatinine and anxiety or depression scores. One unit upregulation of IL-6 and downregula-tion of lymphocyte counts could increase the hazard odds ratio of anxiety or depression by 10. 7% and 68. 9%, respectively. Conclusion: The COVID-19 patients with anxiety or depression symptoms had several different clinical features and laboratory findings in comparison with the patients without, which could lead to a poor prognosis of this disease. Clinicians should pay more attention to these indicators for anxiety or depression. Targeted psychological interventions should be implemented to minimize the negative impact of the psychological burden and to improve the quality life and disease outcome. © 2023 Editorial Board of Medical Journal of Wuhan University. All rights reserved.
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Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor;complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance. © Wolters Kluwer Health, Inc. All rights reserved.
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On December 13, 2020, Yutian County People's hospital reported one imported malaria case in Hotan, Xinjiang. The patient had worked and lived in Yaounde, Cameroon, from January to September 2020. He was infected with malaria twice in March and May 2020. Antimalarial treatment was administrated by the team doctor for 2-3 days in each treatment. The treatment was stopped after the symptoms improved. The patient returned to China on September 16 and was hospitalized on December 13 due to a high fever of 39! and upper respiratory symptoms. Multiple detections of COVID-19 nucleic acid showed negative results. Peripheral blood from the patient was taken for Plasmodium rapid diagnostic test (RDT), which showed a positive result suggesting non Plasmodium falciparum infection. Ring stage P. ovale was found in the blood smear. Nested PCR showed positive for P. ovale. A diagnosis of imported ovale malaria was made. The patient was administrated with 4 dihydroartemisinin piperaquine tablets and 3 primaquine phosphate tablets daily. The malaria parasite test became negative after 8 days of treatment. The patient was followed up for 3 months after discharge and had no symptoms of chills or fever.Copyright © 2022, National Institute of Parasitic Diseases. All rights reserved.
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INTRODUCTION AND OBJECTIVE: In 2018, The US Preventive Services Task Force (USPSTF) changed its recommendations for prostate specific antigen (PSA) screening from "non-recommended" to "shared decision-making among men aged 55-69". Thereafter, COVID-19 Pandemic disrupted cancer care with evidence suggesting overall reduced access to and utilization of health care services including preventive screening. We aim to examine the impacts of both events on PSA screening for men aged 55-69. METHOD(S): We analyzed 2013, 2015, 2018, 2019, and 2021 National Health Interview Survey data. Men >54 who reported PSA testing within 12 months preceding survey were considered to have undergone screening. Adjusted difference in differences (DID) analyses were performed to compare changes in screening in men aged 55-69 with reference to men >70 between 2015 and 2019 (pre- and post- 2018 USPSTF recommendation) and between 2019 and 2021 (pre- and post-Pandemic). RESULT(S): A total of 24,308 men were included. PSA screening prevalence was 35.4% (95%CI: 33.7%, 37.1%), 32.1% (95%CI: 30.3%, 33.9%), 33.3% (95%CI: 31.6%, 34.9%), 37.2% (95%CI: 35.7%, 38.8%), and 34.9% (95%CI: 33.3%, 36.5%) respectively for included years. From 2015 to 2019, PSA screening increased 4.6% among men aged 55-69 (95%CI: 1.7, 7.5%) and increased 6.5% among men >70 (95% CI: 2.7, 10.4%). From 2019 to 2021, PSA screening decreased 3.1% among men aged 55-69 (95%CI: 0.58%, 5.8%);PSA screening also decreased 0.8% among older men but did not reach significance (95% CI: -2.6%, 4.2%). DID analysis did not show difference in changes between men aged 55-69 in reference to men >70 from both 2015 to 2019 (DID=-1.9%, 95%CI, -6.7%, 2.9%) and 2019 to 2021 (DID =-2.3%, 95%CI, -6.5%, 1.9%). CONCLUSION(S): We saw an increase in PSA screening after 2018 USPSTF recommendations among its target population e men aged 55-69 and also among older men >70. In contrast, the period from 2019 to 2021 saw a significant decrease in PSA screening in those aged 55-69. The lack of significant DID between groups as well as the downward trend of PSA screening in men >70 together suggest an overall trend of decrease in PSA screening post-Pandemic.
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With the full arrival of the digital era, fueled by both information technology and business marketing, rumors are produced and spread endlessly on social networks. During the recent novel coronavirus pneumonia epidemic, online rumors have continued to flourish. Most existing studies on traditional rumor detection rely on a large number of features in practical applications. However, the current severe epidemic scenarios have limited rumor information features, and it remains a challenging problem to detect epidemic rumors with high accuracy using only limited information. As a result, we propose a novel Few-shot Rumor Detection model (FRD) for the novel coronavirus pneumonia, which is combined with meta-learning to be able to accurately identify rumors as soon as possible in crises. Specifically, we started by using the BERT+BiLSTM combination for rumor text feature extraction and representation to generate the historical rumor sample-wise vector and epidemic rumor sample-wise vector;secondly, the prototypical network was introduced to summarize the historical rumor data, and the feature vectors of samples belonging to the same category were averaged to obtain the prototype representation of historical rumor category;finally, we utilize the modified cosine similarity measure function to calculate the distance between the class-wise vector of historical rumor text and the sample-wise vector of epidemic rumor, and complete the rumor detection according to the nearest neighbor method. Our experimental results on English datasets show that the FRD rumor detection model proposed in this paper is superior to other baseline algorithms in terms of accuracy, precision, recall and macro F1 value. From the comparison of experimental results, the FRD model can effectively improve conventional rumor detection methods, and better realize the early detection of sudden epidemic rumors. © 2022 IEEE.
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The pandemic outbreak of COVID-19 has posed a threat to public health globally, and rapid and accurate identification of the viruses is crucial for controlling COVID-19. In recent years, nanomaterial-based electrochemical sensing techniques hold immense potential for molecular diagnosis with high sensitivity and specificity. In this review, we briefly introduced the structural characteristics and routine detection methods of SARS-CoV-2, then summarized the associated properties and mechanisms of the electrochemical biosensing methods. On the above basis, the research progress of electrochemical biosensors based on gold nanomaterials, oxide nanomaterials, carbon-based nanomaterials and other nanomaterials for rapid and accurate detection of virus were reviewed. Finally, the future applications of nanomaterial-based biosensors for biomolecular diagnostics were pointed out.
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Lupus nephritis (LN) is one of the most common and serious clinical manifestations of systemic lupus erythe-matosus (SLE), which causes serious damage to the kidneys of patients. To effectively assist the pathological diagnosis of LN, many researchers utilize a scheme combining multi-threshold image segmentation (MIS) with metaheuristic algorithms (MAs) to classify LN. However, traditional MAs-based MIS methods tend to fall into local optima in the segmentation process and find it difficult to obtain the optimal threshold set. Aiming at this problem, this paper proposes an improved water cycle algorithm (SCWCA) and applies it to the MIS method to generate an SCWCA-based MIS method. Besides, this MIS method uses a non-local means 2D histogram to represent the image information and utilizes Renyi's entropy as the fitness function. First, SCWCA adds a sine initialization mechanism (SS) in the initial stage of the original WCA to generate the initial solution to improve the population quality. Second, the covariance matrix adaptation evolution strategy (CMA-ES) is applied in the population location update stage of WCA to mine high-quality population information. To validate the excellent performance of the SCWCA-based MIS method, the comparative experiment between some peers and SCWCA was carried out first. The experimental results show that the solution of SCWCA was closer to the global optimal solution and can effectively deal with the local optimal problems. In addition, the segmentation experiments of the SCWCA-based MIS method and other equivalent methods on LN images showed that the former can obtain higher-quality segmented LN images.
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The demand for same-day delivery (SDD) has increased rapidly in the last few years and has particu-larly boomed during the COVID-19 pandemic. The fast growth is not without its challenge. In 2016, due to low concentrations of memberships and far distance from the depot, certain minority neighborhoods were excluded from receiving Amazon's SDD service, raising concerns about fairness. In this paper, we study the problem of offering fair SDD service to customers. The service area is partitioned into differ-ent regions. Over the course of a day, customers request for SDD service, and the timing of requests and delivery locations are not known in advance. The dispatcher dynamically assigns vehicles to make de-liveries to accepted customers before their delivery deadline. In addition to overall service rate ( utility ), we maximize the minimal regional service rate across all regions ( fairness ). We model the problem as a multi-objective Markov decision process and develop a deep Q-learning solution approach. We introduce a novel transformation of learning from rates to actual services, which creates a stable and efficient learn-ing process. Computational results demonstrate the effectiveness of our approach in alleviating unfairness both spatially and temporally in different customer geographies. We show this effectiveness is valid with different depot locations, providing businesses with an opportunity to achieve better fairness from any location. We also show that the proposed approach performs efficiently when serving heterogeneously wealthy districts in the city.(c) 2022 Elsevier B.V. All rights reserved.
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Vaccination uptake has become the key factor that will determine our success in containing the coronavirus pneumonia (COVID-19) pandemic. Efficient distribution of vaccines to inoculation spots is crucial to curtailing the spread of the novel COVID-19 pandemic. Normally, in a big city, a huge number of vaccines need to be transported from central depot(s) through a set of satellites to widely scattered inoculation spots by special-purpose vehicles every day. Such a large two-echelon vehicle routing problem is computationally difficult. Moreover, the demands for vaccines evolve with the epidemic spread over time, and the actual demands are hard to determine early and exactly, which not only increases the problem difficulty but also prolongs the distribution time. Based on our practical experience of COVID-19 vaccine distribution in China, we present a hybrid machine learning and evolutionary computation method, which first uses a fuzzy deep learning model to forecast the demands for vaccines for each next day, such that we can predistribute the forecasted number of vaccines to the satellites in advance;after obtaining the actual demands, it uses an evolutionary algorithm (EA) to route vehicles to distribute vaccines from the satellites/depots to the inoculation spots on each day. The EA saves historical problem instances and their high-quality solutions in a knowledge base, so as to capture inherent relationship between evolving problem inputs to solutions;when solving a new problem instance on each day, the EA utilizes historical solutions that perform well on the similar instances to improve initial solution quality and, hence, accelerate convergence. Computational results on real-world instances of vaccine distribution demonstrate that the proposed method can produce solutions with significantly shorter distribution time compared to state-of-the-arts and, hence, contribute to accelerating the achievement of herd immunity.
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Biomarker detection has attracted increasing interest in recent years due to the minimally or non-invasive sampling process. Single entity analysis of biomarkers is expected to provide real-time and accurate biological information for early disease diagnosis and prognosis, which is critical to the effective disease treatment and is also important in personalized medicine. As an innovative single entity analysis method, nanopore sensing is a pioneering single-molecule detection technique that is widely used in analytical bioanalytical fields. In this review, we overview the recent progress of nanopore biomarker detection as new approaches to disease diagnosis. In highlighted studies, nanopore was focusing on detecting biomarkers of different categories of communicable and noncommunicable diseases, such as pandemic COVID-19, AIDS, cancers, neurologic diseases, etc. Various sensitive and selective nanopore detecting strategies for different types of biomarkers are summarized. In addition, the challenges, opportunities, and direction for future development of nanopore-based biomarker sensors are also discussed.Copyright © 2023 Elsevier B.V.
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In the current environment where COVID-19 is serious, the space, place and resources required for teaching nuclear power plants are restricted to a great extent. To solve such problems and improve the utilization of education resources, this study improved an accident simulator for nuclear power plants based on the concept of cloud technology. We build the Browser / Server architecture so that the platform has successfully implemented multiterminal, multiplatform and multiuser simultaneous applications. Through the simulation results of the Small Break Loss of Coolant Accident (SBLOCA) and the test results of platform performance by PCTran-Cloud, the correctness of PCTran-Cloud in the accident simulation function and results were verified. In general, PCTran-Cloud has the characteristics of high scalability, high concurrency and high security. The platform can provide an environment for the training and education of nuclear power professionals. © 2022 IEEE.