Model predictive control of bus platoons in a circular route considering dispatching, holding and boarding limits

Public transport forms the backbone of the city's operation. Proper planning and investment of public transport can create additional jobs to revitalize and recover cities from covid-19. In this paper, we propose a combined dispatching-operation bus model predictive control strategy, where a rolling horizon mechanism is adopted to control the bus system in a real-time manner. Either a bus platoon or a single bus is allowed to be dispatched in each trip, and bus re-dispatching is captured in the system to realistically reflect the real-world. Also, the additional bus initial constraints allow control to be applied at any time when buses are either driving on the road or loading at the stop. Model complexity is investigated by solving the optimization problem under various prediction horizons, number of buses and bus stops. Furthermore, the comparison experiment with a high-frequency fixed dispatching method is performed on the Singapore bus line 179A developed in SUMO simulator to illustrate the effectiveness of the proposed method. © 2022 IEEE.

Phage-Derived Oncolytic Viruses with 3C from Seneca Valley Virus for Targeted Therapy of Cervical Cancer

Cancer gene therapy based on various gene delivery vectors has some potential but also has obvious disadvantages. In this study, a new M13 phage-based oncolytic virus is constructed that carried the RGD peptides to target tumor cells and the 3C gene of Seneca Valley virus (SVV) preceded by a eukaryotic initial transcriptional region (ITR) to transcribe an oncolytic protein to kill tumor cells. Recombinant virus particles of 1200 nm in length are obtained in large quantities by transfecting the recombinant M13 phage plasmid into the host BL2738 and are investigated in vitro in tumor cells and in vivo in tumor-bearing mice to evaluate their antitumor effect. The experiments using Hela cells confirm that the engineered M13 phage can target and enter Hela cells, and express the SVV 3C protein, resulting in apoptosis of target cells by upregulating the expression of caspase 3. Furthermore, the results of experiments in vivo also show that the recombinant phage significantly inhibits the enhanced tumor volume in nude mice compared to the control groups. The M13 phage may be engineered to fuse with a variety of oncolytic proteins to inhibit the growth of tumor cells in the future, providing a promising phage-based targeted oncolytic reagent.

Sequential Nucleophilic Addition and Regioselective Ring-Expansion Reactions of α-Diazophosphonates with Isatins: Access to 4-Phosphonylated-3-hydroxyquinolin-2(1H)-ones

A sequential protocol of α-diazophosphonates with isatins to access a series of α-diazo-β-hydroxyphosphonate derivatives via the inorganic base catalysis was reported. The resulting α-diazo-β-hydroxyphosphonates could then be readily transformed to 4-phosphonylated-3-hydroxyquinolin-2(1H)-ones with moderate to excellent yields through a catalyst-free regioselective ring-expansion rearrangement. Control experiment demonstrates that intramolecular cyclization pathway is more reasonable for the ring-expansion process. In addition, a benzo[b]thiophene-derived isatin featured with the inhibition of SARS-CoV Mpro was also suitable for this transformation and generated the corresponding scaffolds with potential anti-virus activities for further development. © 2022 Wiley-VCH GmbH.

Design, Preparation and Immune Characterization of SARS-CoV-2 Multi-Epitope Chimeric Protein

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) can cause respiratory symptoms such as fever, cough and dyspnea after infection, and Coronavirus Disease 2019 (COVID-19), severe acute respiratory syndrome, and even death can occur in severe cases.SARS-CoV-2 infection has no specific treatment drugs, mainly rely on vaccination to block its transmission.In various structural proteins of SARS-CoV-2, Spike protein (S) and Nucleocapsid protein (N) are the main antigenic proteins, which are also important candidate proteins for developing SARS-CoV-2 vaccine and antibody detection reagents.To express chimeric protein containing multiple epitopes of SARS-CoV-2 by prokaryotic expression system, and to verify the immunogenicity of the chimeric protein, antigenic epitopes of SARS-CoV-2 structural proteins were analyzed and screened by molecular biology software, the selected antigenic epitopes were connected in tandem, and expressed high efficiently in E.coli as a chimeric protein by genetic engineering technology.The soluble chimeric protein of high purity was obtained after purification and renaturation.Mice were immunized with the purified chimeric protein together with MF59 adjuvant, aluminum adjuvant or no adjuvant at different doses respectively.Humoral immunity and cellular immunity induced by the chimeric protein were evaluated by detecting the antibody titer of antiserum and the level of related cytokine.The expressed chimeric protein was in the form of inclusion body and exists in the sediment, soluble chimeric protein was obtained after renaturation.The specific antibodies with high titer were produced in the immunized mice, and strong cellular immunity was induced also.Higher concentration of chimeric protein had better elicited immune effect than the lower concentration of chimeric protein.The immune effect induced by the chimeric protein with MF59 adjuvant was no different from that induced with aluminum adjuvant.This study provides novel ideas for the design and renaturation of SARS-CoV-2 chimeric protein, and the chimeric protein is expected to be used for the development of SARS-CoV-2 recombinant protein vaccine and diagnosis reagent.

Design of Food-Energy-Water-Waste Nexus Systems in New York State under COVID-19 Pandemic

This article addresses food-energy-water-waste nexus (FEWWN) optimization under the COVID-19 pandemic to alleviate the public health and environmental concerns from increasing food waste generation using waste-to-energy technologies. Food waste generation has noticeably increased during the pandemic across the globe. To alleviate the associated health and environmental concerns, food waste could be converted into electricity and heat through FEWWN systems using waste-to-energy facilities, such as anaerobic digesters and combined heat and power units in wastewater treatment plants and livestock farms. In this work, a multi-period multi-objective optimization model is proposed for the design of efficient nexus systems under various impacts of the pandemic. To illustrate the applicability of the proposed modelling framework, a case study for New York State is presented. The optimized nexus systems could potentially reduce the food waste disposal amounts by 38%. A clear trade-off between the objectives is revealed by the Pareto-optimal solutions. The minimum total cost for the FEWWN system is $27.1 million;the optimal unit processing profit is $11.9 per ton processed food waste. Spatial analyses illustrate a strong correlation between facility selections and their processing capacities. Sensitivity analysis revealed that electricity price and biogas yield are the most important factors for the economic objectives. © 2021 Elsevier B.V.

Successful features of crowdfunding campaigns: An analysis of requests for Coronavirus food relief

Crowdfunding is an emerging industry in the past decades, which proliferates and has attracted an enormous population from the public to be involved in various funding projects in multiple fields such as business entrepreneurship, healthcare, and fintech. Meanwhile, charitable crowdfunding platforms such as GoFundMe, Indiegogo, and Kickstarter have allowed internet users to provide help and donation to the fundraisers directly. As the year 2020 is surrounded by the COVID-19 global pandemic spreading out the world, the topic of coronavirus relief has surged. Thus, it is worthy of evaluating the crowdfunding campaign's effectiveness during the coronavirus context by making a connection between fundraising activities and coronavirus relief. This paper aims to investigate the effects of various factors affecting a donation-based crowdfunding campaign for coronavirus relief of food donation in the United States and determine the significant factors affecting the campaign's success rate. To achieve this research purpose, secondary data were extensively collected from the crowdfunding platform GoFundMe for regression analysis. The sample data was derived from crowdfunding campaigns launched from March 1st, 2020, to May 31st, 2020. During this period, the United States was severely affected by the COVID-19 pandemic with an exponentially surged number of confirmed cases. This paper derives the independent variables that have been examined from previous studies and further applies in the coronavirus context to identify whether these factors are significant influencers to the success of crowdfunding campaigns for coronavirus relief of food donation. The factors being examined include target funding amount, the existence of spelling mistakes, the presence of pictures, video, social network sites, project updates, comments between fundraisers and backers, and links to external websites. That the significant factors contributing to a successful funding project are similar, as identified in previous reward-based and equity crowdfunding studies. On the other hand, several independent variables' effectiveness varied between the normal scenario and the coronavirus context, as such variables demonstrate a much compelling role to attract donors for the coronavirus relief activations. The analysis is valuable and worthy of different viewpoints. First, understanding the donor's motivation and the success features of funding projects is valuable for fundraisers to have a strategic mindset for decision-making criteria when initiating funding projects to attract more donors and the amount of money. Second, because of the lack of literature focusing on examining the success features for donation-based crowdfunding campaigns, this study fills the gap and further focus on the crowdfunding activations in the context of coronavirus food relief in the US. Therefore, this study provides significant insight to understand the dynamics of the donation-based crowdfunding campaign and provides a recommendation to develop coronavirus relief more efficiently. © 2020 International Consortium for Electronic Business. All rights reserved.

Supervised framework for COVID-19 classification and lesion localization from chest CT

Background: Quick and precise identification of people suspected of having COVID-19 plays a key function in imposing quarantine at the right time and providing medical treatment, and results not only in societal benefits but also helps in the development of an improved health system. Building a deep-learning framework for automated identification of COVID-19 using chest computed tomography (CT) is beneficial in tackling the epidemic. Aim: To outline a novel deep-learning model created using 3D CT volumes for COVID-19 classification and localization of swellings. Methods: In all cases, subjects' chest areas were segmented by means of a pre-trained U-Net;the segmented 3D chest areas were submitted as inputs to a 3D deep neural network to forecast the likelihood of infection with COVID-19;the swellings were restricted by joining the initiation areas within the classification system and the unsupervised linked elements. A total of 499 3D CT scans were utilized for training worldwide and 131 3D CT scans were utilized for verification. Results: The algorithm took only 1.93 seconds to process the CT amount of a single affected person using a special graphics processing unit (GPU). Interesting results were obtained in terms of the development of societal challenges and better health policy. Conclusions: The deep-learning model can precisely forecast COVID-19 infectious probabilities and detect swelling areas in chest CT, with no requirement for training swellings. The easy-to-train and high-functioning deep-learning algorithm offers a fast method to classify people affected by COVID-19, which is useful to monitor the SARS-CoV-2 epidemic.

An update on the status of COVID-19: a comprehensive review.

The last two decades have witnessed two large-scale pandemics caused by coronaviruses, including severe acute respiratory syndrome (SARS) and the Middle East respiratory syndrome (MERS). At the end of 2019, another novel coronavirus, designated as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), hit Wuhan, a city in the center of China, and subsequently spread rapidly to the whole world. Latest reports revealed that more than 800 thousand people in over 200 countries are involved in the epidemic disease by SARS-CoV-2. Due to the high mortality rate and the lack of optimum therapeutics, it is crucial to understand the biological characteristics of the virus and its possible pathogenesis to respond to the SARS-CoV-2. Rapid diagnostics and effective therapeutics are also important interventions for the management of infection control. However, the rapid evolution of SARS-CoV-2 exerted tremendous challenges on its diagnostics and therapeutics. Therefore, there is an urgent need to summarize the existing research results to guide decision-making on the prioritization of resources for research and development. In this review, we focus on our current understanding of epidemiology, pathogenesis, diagnostics and therapeutics of coronavirus disease 2019 (COVID-19).