Synthetic Lies: Understanding AI-Generated Misinformation and Evaluating Algorithmic and Human Solutions

Large language models have abilities in creating high-volume human-like texts and can be used to generate persuasive misinformation. However, the risks remain under-explored. To address the gap, this work first examined characteristics of AI-generated misinformation (AI-misinfo) compared with human creations, and then evaluated the applicability of existing solutions. We compiled human-created COVID-19 misinformation and ed it into narrative prompts for a language model to output AI-misinfo. We found significant linguistic differences within human-AI pairs, and patterns of AI-misinfo in enhancing details, communicating uncertainties, drawing conclusions, and simulating personal tones. While existing models remained capable of classifying AI-misinfo, a significant performance drop compared to human-misinfo was observed. Results suggested that existing information assessment guidelines had questionable applicability, as AI-misinfo tended to meet criteria in evidence credibility, source transparency, and limitation acknowledgment. We discuss implications for practitioners, researchers, and journalists, as AI can create new challenges to the societal problem of misinformation. © 2023 Owner/Author.

[Epidemiological characteristics of a 2019-nCoV outbreak caused by Omicron variant BF.7 in Shenzhen].

Objective: To explore the epidemiological characteristic of a COVID-19 outbreak caused by 2019-nCoV Omicron variant BF.7 and other provinces imported in Shenzhen and analyze transmission chains and characteristics. Methods: Field epidemiological survey was conducted to identify the transmission chain, analyze the generation relationship among the cases. The 2019-nCoV nucleic acid positive samples were used for gene sequencing. Results: From 8 to 23 October, 2022, a total of 196 cases of COVID-19 were reported in Shenzhen, all the cases had epidemiological links. In the cases, 100 were men and 96 were women, with a median of age, M (Q1, Q3) was 33(25, 46) years. The outbreak was caused by traverlers initial cases infected with 2019-nCoV who returned to Shenzhen after traveling outside of Guangdong Province.There were four transmission chains, including the transmission in place of residence and neighbourhood, affecting 8 persons, transmission in social activity in the evening on 7 October, affecting 65 persons, transmission in work place on 8 October, affecting 48 persons, and transmission in a building near the work place, affecting 74 persons. The median of the incubation period of the infection, M (Q1, Q3) was 1.44 (1.11, 2.17) days. The incubation period of indoor exposure less than that of the outdoor exposure, M (Q1, Q3) was 1.38 (1.06, 1.84) and 1.95 (1.22, 2.99) days, respcetively (Wald χ2=10.27, P=0.001). With the increase of case generation, the number and probability of gene mutation increased. In the same transmission chain, the proportion of having 1-3 mutation sites was high in the cases in the first generation. Conclusions: The transmission chains were clear in this epidemic. The incubation period of Omicron variant BF.7 infection was shorter, the transmission speed was faster, and the gene mutation rate was higher. It is necessary to conduct prompt response and strict disease control when epidemic occurs.

Cu2O based on core-shell nanostructure for enhancing the fire-resistance, antibacterial properties and mechanical properties of epoxy resin

The hazards of epoxy resin (EP) are not only reflected in the large amount of smoke and heat released during combustion, but also in the long survival time of bacterial on their surfaces at a time when COVID-19 are prevalent. Therefore, it is crucial to improve the antibacterial properties and fire-resistance of EP. Herein, this paper reports a multifunctional nanoparticle (Cu2O@KF) to overcome this issue. It is found that Cu2O@KF can confer great fire-resistance (LOI = 34.7% and pHRR reduced by 56.3%), antibacterial properties (over 99.99% antibacterial efficiency), and mechanical properties (hardness and Young's modulus increased by 80.0% and 24.0%, respectively) at a low loading level (7 wt%). These ideal characteristics are derived from the multi-synergistic properties among Cu2O and KF. © 2022

Impact of the COVID-19 pandemic and generational heterogeneity on ecommerce shopping styles – A case study of Sacramento, California

The COVID pandemic has accelerated the growth of ecommerce and reshaped shopping patterns, which in turn impacts trip-making and vehicle miles traveled. The objectives of this study are to define shopping styles and quantify their prevalence in the population, investigate the impact of the pandemic on shopping style transition, understand the generational heterogeneity and other factors that influence shopping styles, and comment on the potential impact of the pandemic on long-term shopping behavior. Two months after the initial shutdown (May/June 2021), we collected ecommerce behavioral data from 313 Sacramento Region households using an online survey. A K-means clustering analysis of shopping behavior across eight commodity types identified five shopping styles, including ecommerce independent, ecommerce dependent, and three mixed modes in-between. We found that the share of ecommerce independent style shifted from 55% pre-pandemic to 27% during the pandemic. Overall, 30% kept the same style as pre-pandemic, 54% became more ecommerce dependent, and 16% became less ecommerce dependent, with the latter group more likely to view shopping an excuse to get out. Heterogeneity was found across generations. Pre-pandemic, Millennials and Gen Z were the most ecommerce dependent, but during the pandemic they made relatively small shifts toward increased ecommerce dependency. Baby Boomers and the Silent Generation were bimodal, either sticking to in-person shopping or shifting to ecommerce-dependency during the pandemic. Post-pandemic intentions varied across styles, with households who primarily adopt non-food ecommerce intending to reverse back to in-person shopping, while the highly ecommerce dependent intend to limit future in-store activities. © 2023 The Authors

Transmission and infection risk of various pathogen-laden expiratory droplets in a coach bus with COVID-19

The study about droplet transmission in crowded, poorly ventilated buses and the resulting infection risk(IR) remains rare. Based on a COVID-19 outbreak which the index patient located at bus rear, we performed CFD simulations to study the effect of initial droplet diameters and hourly ventilation rate(ACH) on droplet transmission and IR. The outdoor pressure differential creates the natural ventilation enters from theskylight at bus rear and exits from the front one. With increased ACH, the IR of tracer gas reduced quickly, from 11.1-15.3% under 0.62ACH to 1.3-3.1% under 5.66ACH. Furthermore, the IR of 100µm/50µm droplets was almost independent of ACH as most droplets were deposited due to gravity. Furthermore, 5µm droplets are more widely dispersed than larger droplets, and can spread further with increasing ACH with a low IR(≤0.4%). Unlike general rooms, most droplets are deposited on the route passing through the long-distance bus space(~9.46m). But the tracer gas will not deposit, so the tracer gas can only be used to simulate the fine droplet dispersion process in the long-distance bus. Our research results provide a reference for future research on droplet transmission in the bus environment, and also provide a guidance for epidemic prevention. © The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (http://creativecommons.org/licenses/by/4.0/)

Research on the Influencing Factors of Adoption Intention of Information Technology for Pandemic Prevention among the Elderly in Public Health Emergency

[Purpose/Significance] This paper takes the elderly aged 60 and above in Guangxi as the research object to explore the factors that affect their adoption of information technology for pandemic prevention and control. It is helpful to improve the elderly's ability to apply information technology, and promote the construction and development of information technology to prevent a pandemic. [Method/Process] Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) model, this paper added pandemic risk perception, technology anxiety, resistance to change as new variables to construct the model of influencing factors of the elderly's adoption intention of information technology for COVID-19 pandemic prevention and control, designed and collected 210 valid questionnaires, used SPSS 21.0 software to finish the descriptive statistical analysis, and used SmartPLS 3.0 software to finish the reliability and validity analysis of the questionnaires, and constructed a Structural Equation Model to verify the model. [Results/Conclusions] The study found that the risk perception, performance expectancy, effort expectancy, social influence and facilitating conditions had a significant impact on the elderly's behavioral intention of information technology for COVID-19 pandemic prevention and control, and technology anxiety, resistance to change had no significant impact on the behavioral intention. Finally, this paper puts forward countermeasures and suggestions based on the research findings. © 2022 by the Author(s).

Collaborative Truck-Drone Routing for Contactless Parcel Delivery During the Epidemic

The COVID-19 pandemic calls for contactless deliveries. To prevent the further spread of the disease and ensure the timely delivery of supplies, this paper investigates a collaborative truck-drone routing problem for contactless parcel delivery (CRP-T&D), which allows multiple trucks and multiple drones to deliver parcels cooperatively in epidemic areas. We formulate a mixed-integer programming model that minimizes the delivery time, with the consideration of the energy consumption model of drones. To solve CRP-T&D, we develop an improved variable neighborhood descent (IVND) that combines the Metropolis acceptance criterion of Simulated Annealing (SA) and the tabu list of Tabu Search (TS). Meanwhile, the integration of K-means clustering and Nearest neighbor strategy is applied to generate the initial solution. To evaluate the performance of IVND, experiments are conducted by comparing IVND with VND, SA, TS, variants of VND, and large neighborhood search (LNS) on instances with different scales. Several critical factors are tested to verify the robustness of IVND. Moreover, the experimental results on a practical instance further demonstrate the superior performance of IVND. IEEE

Chinese travellers' mobility decision-making processes during public health crisis situations: a Bayesian network model

Travellers' mobility decisions are fraught with uncertainty and instability during public health crises. However, existing studies have not revealed the internal mechanism of travellers' mobility changes in a public health crisis. This paper established and trained a Bayesian network model from multiple data to analyse Chinese travellers' mobility decision-making processes under COVID-19 and simulated the changes in mobility decisions in different scenarios. The results show that travellers reformulate mobility decisions in response to various information and negotiate between social customs and personal needs. Mobility can be modified through risk communication and habits adaptation. Bayesian network models provide a methodological contribution to causal exploration and scenario prediction.

OPTIMIZATION OF VACCINATION FOR COVID-19 IN THE MIDST OF A PANDEMIC

During the Covid-19 pandemic a key role is played by vaccination to combat the virus. There are many possible policies for prioritizing vaccines, and different criteria for optimization: minimize death, time to herd immunity, functioning of the health system. Using an age-structured population compartmental finite-dimensional optimal control model, our results suggest that the eldest to youngest vaccination policy is optimal to minimize deaths. Our model includes the possible infection of vaccinated populations. We apply our model to real-life data from the US Census for New Jersey and Florida, which have a significantly different population structure. We also provide various estimates of the number of lives saved by optimizing the vaccine schedule and compared to no vaccination.

Structure-Based Discovery and Structural Basis of a Novel Broad-Spectrum Natural Product against the Main Protease of Coronavirus

Over the past 20 years, the severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome CoV (MERS-CoV), and SARS-CoV-2 emerged, causing severe human respiratory diseases throughout the globe. Developing broad-spectrum drugs would be invaluable in responding to new, emerging coronaviruses and to address unmet urgent clinical needs. Main protease (Mpro;also known as 3CL(pro)) has a major role in the coronavirus life cycle and is one of the most important targets for anti-coronavirus agents. We show that a natural product, noncovalent inhibitor, shikonin, is a pan-main protease inhibitor of SARS-CoV-2, SARS-CoV, MERS-CoV, human coronavirus (HCoV)-HKU1, HCoV-NL63, and HCoV-229E with micromolar half maximal inhibitory concentration (IC50) values. Structures of the main protease of different coronavirus genus, SARS-CoV from the betacoronavirus genus and HCoV-NL63 from the alphacoronavirus genus, were determined by X-ray crystallography and revealed that the inhibitor interacts with key active site residues in a unique mode. The structure of the main protease inhibitor complex presents an opportunity to discover a novel series of broad-spectrum inhibitors. These data provide substantial evidence that shikonin and its derivatives may be effective against most coronaviruses as well as emerging coronaviruses of the future. Given the importance of the main protease for coronavirus therapeutic indication, insights from these studies should accelerate the development and design of safer and more effective antiviral agents. IMPORTANCE The current pandemic has created an urgent need for broad-spectrum inhibitors of SARS-CoV-2. The main protease is relatively conservative compared to the spike protein and, thus, is one of the most promising targets in developing anticoronavirus agents. We solved the crystal structures of the main protease of SARSCoV and HCoV-NL63 that bound to shikonin. The structures provide important insights, have broad implications for understanding the structural basis underlying enzyme activity, and can facilitate rational design of broad-spectrum anti-coronavirus ligands as new therapeutic agents.

RSFAD: A Large-Scale Real Scenario Face Age Dataset in the wild

Age estimation is a hot and challenging research topic in the computer vision community. Several facial datasets annotated with age and gender attributes became available in recent years. However, the statistical information of these datasets reveal the unbalanced label distribution which inevitably introduce bias during model training. In this work, we manually collect and label a large-scale age dataset called Real Scenario Face Age Dataset (RSFAD) which contains 85, 044 facial images captured from surveillance cameras in the wild. Due to the COVID-19, we not only label the apparent age group and gender but also label the breathing mask, and the label distribution of RSFAD dataset is almost uniform which is the first age dataset to the best of our knowledge. In addition, we investigate the impact of age, gender and mask distribution on age group estimation by comparing GDEX CNN model trained on several different datasets. Our experiments show that the RSFAD dataset has good performance for age estimation task and also it is suitable for being an evaluation benchmark. © 2021 IEEE.

Annual report of thoracic surgery services at the Shanghai Chest Hospital in 2020

Background: The thoracic surgery team of the Shanghai Chest Hospital has been publishing its annual report since 2018, summarizing the services and major progress over the last year. Methods: All patients receiving thoracic surgery services at the Department of Thoracic Surgery and the Department of Oncological Surgery at the Shanghai Chest Hospital in 2020 were enrolled. The number of surgical resections, types of surgical procedures, disease histological types, and perioperative outcomes were collected and compared with the results from previous years. Results: In the year 2020, the thoracic team of the Shanghai Chest Hospital faced the unprecedented challenge of the coronavirus disease 2019 (COVID-19) epidemic. A total of 15,664 patients received thoracic surgeries at the Shanghai Chest Hospital, only an 8.0% decrease compared with the previous year of 2019. These included 13,493 pulmonary procedures, 1,075 esophageal procedures, 969 mediastinal procedures, 66 tracheal procedures, 2 lung transplantations, and 59 other procedures. The rate of minimally invasive surgeries among all procedures was 91.1%, including 721 robotic-assisted thoracic surgeries, both of which increased from the year before. In addition, the average length of hospital stay continuously decreased, being only 3.82 days after pulmonary surgery and 10.96 days after esophageal surgery. Meanwhile, the quality of thoracic surgery has improved, with continuously lower rates of perioperative complications and an in-hospital mortality rate of only 0.14%. Conclusions: The services provided and progress made in 2020 by the thoracic surgery team of the Shanghai Chest Hospital were reviewed in this annual report, reflecting a consistent effort to help our patients with high-standard services and state-of-the-art surgical techniques. © 2022 Shanghai Chest. All rights reserved.

Afraid to travel after COVID-19? Self-protection, coping and resilience against pandemic 'travel fear '

COVID-19 has generated an unprecedented level of public fear, likely impeding tourism industry recovery after the pandemic is over. This study explores what trigger the public's pandemic 'travel fear' and how people impose self-protection, coping and resilience related to travel. The study integrates theories including protection motivation theory, coping and resilience theories to address the research aim. Using a quota sampling, an online survey of 1208 respondents across mainland China was conducted. Results found that threat severity and susceptibility can cause 'travel fear', which leads to protection motivation and protective travel behaviors after the pandemic outbreak. Findings also revealed that 'travel fear' can evoke different coping strategies, which increases people's psychological resilience and adoption of cautious travel behaviors. Several strategies are provided on how to mitigate people's 'travel fear' and encourage travel in a post-COVID-19 world.

China's experience in COVID-19 prevention and control among children in its different regions.

OBJECTIVE: To summarize the experience of three Chinese cities (Wuhan, Shanghai and Haikou) and provide a reference for global efforts to combat COVID-19 spread among children. MATERIALS AND METHODS: Through collecting the measures and outcomes of preventing and controlling COVID-19 in China's three hospitals, we compared the effect of different strategies. RESULTS: From January to March 2020, the number of suspected and confirmed COVID-19 cases in Wuhan increased exponentially, and Wuhan Children's Hospital as a whole was transformed into a designated quarantine and treatment facility, which is the "Wuhan Model". Shanghai has more children's hospitals with better capabilities to tackle public health emergency. Besides, it is far away from Wuhan and had a small caseload. Children's Hospital of Fudan University, a facility in Shanghai to treat pediatric infectious diseases, is famous for its well-equipped building for infectious disease treatment and professional medical team, and therefore no major transformation was required. That is the "Shanghai Model". Haikou is located on an island. Amid the outbreak, large numbers of tourists and travelers from Hubei had already arrived in Haikou. Hainan Women and Children's Medical Center, as the only pediatric care hospital in Hainan Province, did not have a separate building for infectious disease treatment. After a citywide survey of the medical resources and facilities available, a temporarily idle hospital 3 kilometers away from Hainan Women and Children's Medical Center was requisitioned as the quarantine and treatment facility for pediatric cases. That is the "Hainan Model". The three models enabled the treatment of all suspected and confirmed cases and no fatality was reported. CONCLUSIONS: The COVID-19 coping strategies for children should be designed according to the existing conditions of the local children's hospitals and the risk levels of the epidemic.