Tweet topics and sentiments relating to COVID-19 vaccination among Australian Twitter users: Machine learning analysis

Background: COVID-19 is one of the greatest threats to human beings in terms of health care, economy, and society in recent history. Up to this moment, there have been no signs of remission, and there is no proven effective cure. Vaccination is the primary biomedical preventive measure against the novel coronavirus. However, public bias or sentiments, as reflected on social media, may have a significant impact on the progression toward achieving herd immunity. Objective: This study aimed to use machine learning methods to extract topics and sentiments relating to COVID-19 vaccination on Twitter. Methods: We collected 31,100 English tweets containing COVID-19 vaccine–related keywords between January and October 2020 from Australian Twitter users. Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. We also performed sentiment analysis to understand the overall sentiments and emotions related to COVID-19 vaccination in Australia. Results: Our analysis identified 3 LDA topics: (1) attitudes toward COVID-19 and its vaccination, (2) advocating infection control measures against COVID-19, and (3) misconceptions and complaints about COVID-19 control. Nearly two-thirds of the sentiments of all tweets expressed a positive public opinion about the COVID-19 vaccine; around one-third were negative. Among the 8 basic emotions, trust and anticipation were the two prominent positive emotions observed in the tweets, while fear was the top negative emotion. Conclusions: Our findings indicate that some Twitter users in Australia supported infection control measures against COVID-19 and refuted misinformation. However, those who underestimated the risks and severity of COVID-19 may have rationalized their position on COVID-19 vaccination with conspiracy theories. We also noticed that the level of positive sentiment among the public may not be sufficient to increase vaccination coverage to a level high enough to achieve vaccination-induced herd immunity. Governments should explore public opinion and sentiments toward COVID-19 and COVID-19 vaccination, and implement an effective vaccination promotion scheme in addition to supporting the development and clinical administration of COVID-19 vaccines

An efficient ant colony system based on receding horizon control for the aircraft arrival sequencing and scheduling problem

The aircraft arrival sequencing and scheduling (ASS) problem is a salient problem in air traffic control (ATC), which proves to be nondeterministic polynomial (NP) hard. This paper formulates the ASS problem in the form of a permutation problem and proposes a new solution framework that makes the first attempt at using an ant colony system (ACS) algorithm based on the receding horizon control (RHC) to solve it. The resultant RHC-improved ACS algorithm for the ASS problem (termed the RHC-ACS-ASS algorithm) is robust, effective, and efficient, not only due to that the ACS algorithm has a strong global search ability and has been proven to be suitable for these kinds of NP-hard problems but also due to that the RHC technique can divide the problem with receding time windows to reduce the computational burden and enhance the solution's quality. The RHC-ACS-ASS algorithm is extensively tested on the cases from the literatures and the cases randomly generated. Comprehensive investigations are also made for the evaluation of the influences of ACS and RHC parameters on the performance of the algorithm. Moreover, the proposed algorithm is further enhanced by using a two-opt exchange heuristic local search. Experimental results verify that the proposed RHC-ACS-ASS algorithm generally outperforms ordinary ACS without using the RHC technique and genetic algorithms (GAs) in solving the ASS problems and offers high robustness, effectiveness, and efficienc

Design and Development of an RFID-based HIS - A Case Study

The Healthcare industry involves critical activities where small mistakes could cause huge loss of life and incur massive financial losses. Improving operational efficiency and enhancing data correctness of patients are the prime targets of using hospital information system (HIS). Radio Frequency Identification (RFID) technology, with a unique ability to perform automatic data collection without any human intervention, has gained great interest in the healthcare industry. In this research, an RFID‐enabled HIS is proposed for improving operations in a hospital. This research presents the fundamentals of RFID, the benefits and its challenges, and also demonstrates three improved signature applications. It aims at providing the healthcare industry with a comprehensive understanding of RFID and its suitability for healthcare applications. The proposed system is considered to be suitably operational, practical, and affordable for healthcare organizations not only in China and Hong Kong, but also in other countries

Isolation and characterization of new genetic types of Toxoplasma gondii and prevalence of Trichinella murrelli from black bear (Ursus americanus)

Black bears (Ursus americanus) are hosts for two important zoonotic parasites, Toxoplasma gondii and Trichinella spp. and bears are hunted for human consumption in the USA. Little is known of the genetic diversity of T. gondii circulating in wildlife. In the present study, antibodies to T. gondii were found in juice from tongues of 17 (25.7%) of 66 wild black bear from Maryland during the hunting season of 2010 and 2011. Antibodies to T. gondii were assessed by the modified agglutination test. Tongues of 17 seropositive bears were bioassayed in mice and viable T. gondii was isolated from three samples. These three T. gondii isolates (TgBbMd1-3) were further propagated in cell culture and DNA isolated from culture-derived tachyzoites was characterized using 11 PCR-RFLP markers (SAG1, 5′ - and 3′ -SAG2, alt.SAG2, SAG3, BTUB, GRA6, c22-8, c29-2, L358, PK1 and Apico). Results revealed three genotypes. TgBbMd1 is a Type 12 strain (ToxoDB PCR-RFLP genotype #4) and TgBbMd2 is ToxoDB PCR- RFLP genotype #216, and TgBbMd3 is a Type II clonal strain (ToxoDB PCR-RFLP genotype #1). The isolate TgBbMd2 was highly virulent for outbred Swiss Webster mice; all infected mice died of acute toxoplasmosis. Results indicate that mouse virulent strains of T. gondii are circulating in wildlife in the USA. These 66 tongues in addition to tongues collected during hunts in previous years were further investigated for the presence of muscle larvae of Trichinella spp. Tongues from 40 bears in 2005, 41 in 2006, 51 in 2007, 56 in 2008, 68 in 2009, 67 in 2010, and 66 in 2011 were subjected to digestion with pepsin/HCl and microscopic examination. Two bears were infected with Trichinella spp.; one in 2008 and one in 2009. Genotyping of collected muscle larvae revealed that the infecting species in both cases was Trichinella murrelli

Developing Large-Scale Research in Response to an Oil Spill Disaster: a Case Study

Research conducted in the wake of a disaster can provide information to help mitigate health consequences, support future recovery efforts, and improve resilience. However, a number of barriers have prevented time-sensitive research responses following previous disasters. Furthermore, large-scale disasters present their own special challenges due to the number of people exposed to disaster conditions, the number of groups engaged in disaster response, and the logistical challenges of rapidly planning and implementing a large study. In this case study, we illustrate the challenges in planning and conducting a large-scale post-disaster research study by drawing on our experience in establishing the Gulf Long-term Follow-up (GuLF) Study following the 2010 Deepwater Horizon disaster. We describe considerations in identifying at-risk populations and appropriate comparison groups, garnering support for the study from different stakeholders, obtaining timely scientific and ethics review, measuring and characterizing complex exposures, and addressing evolving community health concerns and unmet medical needs. We also describe the NIH Disaster Research Response (DR2) Program, which provides a suite of resources, including data collection tools, research protocols, institutional review board guidance, and training materials to enable the development and implementation of time-critical studies following disasters and public health emergencies. In describing our experiences related to the GuLF Study and the ongoing efforts through the NIH DR2 Program, we aim to help improve the timeliness, quality, and value of future disaster-related data collection and research studies

The Dependence of the Superconducting Transition Temperature of Organic Molecular Crystals on Intrinsically Non-Magnetic Disorder: a Signature of either Unconventional Superconductivity or Novel Local Magnetic Moment Formation

We give a theoretical analysis of published experimental studies of the effects of impurities and disorder on the superconducting transition temperature, T_c, of the organic molecular crystals kappa-ET_2X and beta-ET_2X (where ET is bis(ethylenedithio)tetrathiafulvalene and X is an anion eg I_3). The Abrikosov-Gorkov (AG) formula describes the suppression of T_c both by magnetic impurities in singlet superconductors, including s-wave superconductors and by non-magnetic impurities in a non-s-wave superconductor. We show that various sources of disorder lead to the suppression of T_c as described by the AG formula. This is confirmed by the excellent fit to the data, the fact that these materials are in the clean limit and the excellent agreement between the value of the interlayer hopping integral, t_perp, calculated from this fit and the value of t_perp found from angular-dependant magnetoresistance and quantum oscillation experiments. If the disorder is, as seems most likely, non-magnetic then the pairing state cannot be s-wave. We show that the cooling rate dependence of the magnetisation is inconsistent with paramagnetic impurities. Triplet pairing is ruled out by several experiments. If the disorder is non-magnetic then this implies that l>=2, in which case Occam's razor suggests that d-wave pairing is realised. Given the proximity of these materials to an antiferromagnetic Mott transition, it is possible that the disorder leads to the formation of local magnetic moments via some novel mechanism. Thus we conclude that either kappa-ET_2X and beta-ET_2X are d-wave superconductors or else they display a novel mechanism for the formation of localised moments. We suggest systematic experiments to differentiate between these scenarios.Comment: 18 pages, 5 figure

Search for black holes and other new phenomena in high-multiplicity final states in proton-proton collisions at root s=13 TeV

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Search for high-mass diphoton resonances in proton-proton collisions at 13 TeV and combination with 8 TeV search

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Search for heavy resonances decaying into a vector boson and a Higgs boson in final states with charged leptons, neutrinos, and b quarks

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