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The spread of online misinformation threatens public health, democracy, and the broader society. While professional fact-checkers form the first line of defense by fact-checking popular false claims, they do not engage directly in conversations with misinformation spreaders. On the other hand, non-expert ordinary users act as eyes-on-the-ground who proactively counter misinformation - recent research has shown that 96% counter-misinformation responses are made by ordinary users. However, research also found that 2/3 times, these responses are rude and lack evidence. This work seeks to create a counter-misinformation response generation model to empower users to effectively correct misinformation. This objective is challenging due to the absence of datasets containing ground-truth of ideal counter-misinformation responses, and the lack of models that can generate responses backed by communication theories. In this work, we create two novel datasets of misinformation and counter-misinformation response pairs from in-the-wild social media and crowdsourcing from college-educated students. We annotate the collected data to distinguish poor from ideal responses that are factual, polite, and refute misinformation. We propose MisinfoCorrect, a reinforcement learning-based framework that learns to generate counter-misinformation responses for an input misinformation post. The model rewards the generator to increase the politeness, factuality, and refutation attitude while retaining text fluency and relevancy. Quantitative and qualitative evaluation shows that our model outperforms several baselines by generating high-quality counter-responses. This work illustrates the promise of generative text models for social good - here, to help create a safe and reliable information ecosystem. The code and data is accessible on https://github.com/claws-lab/MisinfoCorrect. © 2023 Owner/Author.
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Geopolitics is shaping the international education landscape. International education has trationally been used as a tool to boost transnational cooperation, foster multilateral and global ties, and reduce tensions between nations. Such a role has been eroded and international education has been weaponised in the context of escalating political turbulences and disputes over the COVID-19 pandemic. In particular, the relationship between Australia and China, with international student flows interrupted due to COVID-19, is overshadowed by escalating geopolitical tensions in the Indo-Pacific region. Based on a qualitative study, this article examines stakeholders' views on the responses of the Australian international education sector and universities to emerging geopolitical tensions. The conjuncture of geopolitics, COVID-19 and Australia's former government responses magnified a sense of crisis for universities and the international education sector as it was at risk because of their financial reliance on international students. Based on the findings, recommendations are made for the framing of a reciprocal, coordinated, responsive and empathetic international education sector to mitigate geopolitical risks and ensure more sustainable and ethical development for the sector.
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Previous studies extensively examined the role of accessibility to metro in shaping house prices but largely overlooked the contribution of accessibility by metro. In addition, limited studies examined the moderating effect of COVID-19 on the price effects of to-metro and by-metro accessibility. Based on multilevel hedonic price and quantile regression models, this study scrutinizes the association between to-metro accessibility, by-metro accessibility, and house prices in Chengdu, China, and examines the moderating role of COVID-19 in this association. We show that by-metro accessibility significantly influences house prices. COVID-19 significantly influences the value of to-metro accessibility but marginally affects that of by-metro accessibility. The value of to-metro accessibility is disproportionately affected by the pandemic. Specifically, small or low-priced houses are less affected than big or high-priced houses. In other words, the flattening of the to-metro price gradient is more discernible for big or high-priced houses. The changing preference of residents has also been verified by the decreases in house transaction volume in metro-adjacent areas. © 2022 Elsevier Ltd
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Objective To assess imported risk of COVID-19 in Hainan province from January 10 to March 7 in 2020, and to assess the effect of "The Normalization Prevention and Control" (measures during the Spring Festival Travel Rush (SFTR) in Hainan in 2021. Methods The daily reported imported cases in Hainan province, the daily reported cases in other 30 province of China, and the Baidu Migration Index were collected to calculated into the Imported Risk Index (IRI) to quantitatively assess the imported risk of Hainan province. Based on the analysis of the relationship between the imported risk index and imported cases, an imported case prediction model was constructed to fit the number of imported cases in "emergency containment" stage in Hainan. And number of imported cases during the Spring Festival Travel rush in 2021 was predicted by this model to compared with the actual number, which was to evaluate the "Normalization Prevention and Control" measures in this model was also used to assess the effect of "Normalization Prevention and Control" measures during the SFTR in 2021. Results Totally 112 imported cases were reported in Hainan. The average IRI was 0.98. Haikou, Sanya and Danzhou have the highest imported risk. Except Haikou, the imported risk index of all cities and counties reached the maximum value around January 24th. The generalized additive model based on the lag 4 days and lag 5 days was best fitted with the actual imported cases number (R2adjust1=83.50%, R2adjust2=82.00%, MRE=17.61%). If "Emergency Containment" strategy was still adopted, there were 10 COVID-19 cases imported into Hainan during the SFTR in 2021. Under the "Normalization Prevention and Control" strategy, virtually no imported cases were found in Hainan. Conclusions Tourism cities such as Haikou and Sanya have high imported risks. Hubei and Guangdong provinces are the main imported provinces. The Generalized Additive Model based on the Imported Risk Index can better fit with the imported cases number of COVID-19 in Hainan Province in "emergency containment". Compared with the "Emergency Containment" strategy, the "Normalization Prevention and Control" strategy adopted during the SFTR in 2021 reduced imported cases in Hainan by about 10. © 2022. China Tropical Medicine. All rights reserved.
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The spread of COVID-19 has sparked racism and hate on social media targeted towards Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterspeech in mitigating this spread. In this work, we study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, the largest dataset of anti-Asian hate and counterspeech spanning 14 months, containing over 206 million tweets, and a social network with over 127 million nodes. By creating a novel hand-labeled dataset of 3,355 tweets, we train a text classifier to identify hateful and counterspeech tweets that achieves an average macro-F1 score of 0.832. Using this dataset, we conduct longitudinal analysis of tweets and users. Analysis of the social network reveals that hateful and counterspeech users interact and engage extensively with one another, instead of living in isolated polarized communities. We find that nodes were highly likely to become hateful after being exposed to hateful content in the year 2020. Notably, counterspeech messages discourage users from turning hateful, potentially suggesting a solution to curb hate on web and social media platforms. Data and code is available at http://claws.cc.gatech.edu/covid. © 2021 ACM.
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Not only coughing and sneezing, but even normal breathing can produce aerosols, because rupture of liquid plugs forms microdroplets during pulmonary airway reopening. Aerosols are important carriers of various viruses, such as influenza, SARS, MERS, and COVID-19. To control airborne disease transmission, it is important to understand aerosol formation, which is related to the pressure drop, liquid plug, and film. In addition, the detrimental pressure and shear stress at the airway wall produced in the process of airway reopening have also attracted a lot of attention. In this paper, we proposed a multiphase lattice Boltzmann method to numerically simulate pulmonary airway reopening, in which the gas-liquid transition is directly driven by the equation of state. After validating the numerical model, two rupture cases with and without aerosol formation were compared and analyzed. We found that injury of the epithelium in the case with aerosol formation was almost the same as that without aerosol formation, even though the pressure drop in the airway increased by about 50%. Further investigation showed that the aerosol size and maximum differences of the wall pressure and shear stress increased with pressure drop in the pulmonary airway. A similar trend was observed when the thickness of the liquid plug became larger, while an opposite trend occurred when the thickness of the liquid film increased. The model can be extended to study generation and transmission of bioaerosols carrying the influenza or coronavirus. © 2022 Elsevier Ltd
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In the era of pandemic cinephilia, when social distancing, lockdown, isolation, quarantine, and online platforms have become the new normal, cinephiles' collective longing for community, communication, connection, and contact through the love of cinema has become both dangerous and precious. Three parts constitute the introduction, which is situated in a wide, transnational and translocal context. The first part samples global roundtables that have arised from pandemic cinephilia. The second part maps and samples global Chinese cinephilic communities-including Film 101 Workshop, Rear Window, Deep Focus, O Cinephiles, and DIRECTUBE-since the digital turn in the 1990s. The aim is to problematize the Deep Focus collective by examining its complex relationship with both capital and censorship. The third part gives a roadmap for this special issue on global Chinese cinephilia.
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This article reviews social regulatory and redistributive policies in China that aim at fostering digital inclusion of persons with disabilities. We examine the emerging Chinese policies and how China has responded to the impacts of the coronavirus disease (COVID-19) on digital inclusion in terms of redistribution, market regulation, involvement of persons with disabilities and disabled people's organizations (DPOs), and awareness-raising campaigns. The policy review demonstrates that the Chinese policy framework contains a few redistributive initiatives, for example, cash transfer programs, and free distribution of information and communications technology (ICT). These have the potential to increase the uptake of ICT among persons with disabilities. The Chinese policy framework also includes provisions to ensure consultation with individual persons with disabilities and DPOs in the deliberation and implementation of ICT accessibility policies. While China has initiated awareness-raising campaigns among market actors about the importance of digital inclusion, so far, the Chinese government has adopted little legal regulation of the market to foster accessibility to ICT. The article thus argues that some of the limitations may be due to the way state-market relations have developed since the economy opened up in 1978. Apart from the growing benefits of several cash transfer programs, we have not seen major changes or adjustments to the current policy framework during the efforts to mitigate the impact of COVID-19 on digital inclusion.
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The recent and projected upward trends in the frequency and intensity of climate-induced events in cities have enhanced the focus on adaptation. In addition to enhancing the capacity of cities to prepare for and absorb risks, adaptation measures provide multiple co-benefits. However, health co-benefits are among the least explored. These are now seen as increasingly important with the renewed focus on public health since the COVID-19 pandemic. This study reviews literature focused on the health co-benefits of urban climate change adaptation measures. Health co-benefits of seven different categories of adaptation measures are discussed. Results showed that existing evidence is mainly related to some categories such as critical infrastructure, nature-based solutions, and urban planning and design measures. Other adaptation categories like early warning systems;policy, management & governance, including local adaptation policies;and measures and strategies related to ‘knowledge, perceptions & behavior’ that mainly involve people's understanding and individual responses to climate change, are relatively underexplored. Moreover, it was discussed that some adaptation measures may result in health trade-offs and these needs to be further studied. Overall, through identifying health co-benefits, results of this review can make a strong case for further promotion of climate change adaptation in cities. © 2021
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Objective: To evaluate the related factors to virus clearance time in patients with critical COVID‑19. Methods: A total of 63 patients with critical COVID‑19 who had viral clearance were enrolled from Feb 1 to Mar 20, 2020, in Renmin Hospital of Wuhan University. Univariate analyses were used to compare the related factors between groups with different viral clearance time (≤30 days viral clearance group versus >30 days viral clearance group). COX regression analysis was also used to evaluate the factors related to virus clearance time. Results: A total of 63 critical patients with COVID‑19 who had viral clearance were collected, including 35 male and 28 female. The mean age was (63.65±14.06) years, range from 29 to 89 years. The median viral clearance time was 27 days ( IQR, 21~36 days). In univariate analysis, the following factors had significant differences between ≤30 days viral clearance group and >30 days viral clearance group (all P <0.05) as: age>70 years old, COPD, WBC>9.5×109/L, LYM<0.6×109/L, CRP>50 mg/L, D‑dimer>5 mg/L, CK>200 U/L, LDH>300 U/L, CD4+ T‑cell<250 cells/μL, CD8+ T‑cell<150 cells/μL, corticosteroid treatment and high flow oxygen therapy. Multivariate analysis confirmed that age>70 years old ( HR : 0.207, 95% CI : 0.090‑0.479), LYM<0.6×109/L ( HR : 0.276, 95% CI : 0.116‑0.656), D‑dimer>5 mg/L ( HR : 0.243, 95% CI : 0.105‑0.563), and ALT>50 U/L ( HR : 0.483, 95% CI : 0.239‑0.973) were inconducive to the elimination of the virus. Conclusion: Critical COVID‑19 patients have longer hospital stays and significantly different virus clearance time. There are many factors that affect viral clearance time. As adverse factors, age>70 years old, LYM<0.6×109/L, D‑dimer >5 mg/L and ALT>50 U/L may prolong the viral clearance time. Early detection of related factors and timely treatment are beneficial to shorten the time of viral clearance and improve the prognosis of the disease. © 2021, Editorial Board of Medical Journal of Wuhan University. All right reserved.
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In order to guard against the 2019-nCoV new coronavirus, this paper proposes a novel intelligent robot for epidemic identification and prevention. To examine people's health more comprehensively, an infrared thermal imaging camera is equipped on the humanoid eyes-head robot platform that has the ability to hear, speak and watch. The robot not only has common capabilities such as face recognition, cough detection, mask detection, and heart rate detection, but also epidemic prevention and detection capabilities such as respiratory frequency and body temperature detection.
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Fact checking by professionals is viewed as a vital defense in the fight against misinformation. While fact checking is important and its impact has been significant, fact checks could have limited visibility and may not reach the intended audience, such as those deeply embedded in polarized communities. Concerned citizens (i.e., the crowd), who are users of the platforms where misinformation appears, can play a crucial role in disseminating fact-checking information and in countering the spread of misinformation. To explore if this is the case, we conduct a data-driven study of misinformation on the Twitter platform, focusing on tweets related to the COVID-19 pandemic, analyzing the spread of misinformation, professional fact checks, and the crowds response to popular misleading claims about COVID-19.In this work, we curate a dataset of false claims and statements that seek to challenge or refute them. We train a classifier to create a novel dataset of 155,468 COVID-19-related tweets, containing 33,237 false claims and 33,413 refuting arguments. Our findings show that professional fact-checking tweets have limited volume and reach. In contrast, we observe that the surge in misinformation tweets results in a quick response and a corresponding increase in tweets that refute such misinformation. More importantly, we find contrasting differences in the way the crowd refutes tweets, some tweets appear to be opinions, while others contain concrete evidence, such as a link to a reputed source. Our work provides insights into how misinformation is organically countered in social platforms by some of their users and the role they play in amplifying professional fact checks. These insights could lead to development of tools and mechanisms that can empower concerned citizens in combating misinformation. The code and data can be found in this link.1 © 2020 IEEE.
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There are plenty of parking spaces in big cities, but we often find nowhere to park. The reason is the lack of prediction of parking behavior. If we could provide parking behavior in advance, we can ease this parking problem that affects human well-being. We observe that parking lots have periodic parking patterns, which is an important factor for parking behavior prediction. Unfortunately, existing work ignores such periodic parking patterns in parking behavior prediction, and thus incurs low accuracy. To solve this problem, we propose PewLSTM, a novel periodic weather-aware LSTM model that successfully predicts the parking behavior based on historical records, weather, environments, weekdays, and events. PewLSTM consists of two parts: a periodic weather-aware LSTM prediction module and an event prediction module, for predicting parking behaviors in regular days and events. Based on 910,477 real parking records in 904 days from 13 parking lots, PewLSTM yields 93.84% parking prediction accuracy, which is about 30% higher than the state-of-the-art parking behavior prediction method. We have also analyzed parking behaviors in events like holidays and COVID-19;PewLSTM can also handle parking behavior prediction in events and reaches 90.68% accuracy. IEEE
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In January 2020, a new coronavirus epidemic broke out in China, when the emission characteristics of air pollution have changed significantly. To study the characteristics of PM2.5 components under this scenario, a series of online observation instruments were used in Zhengzhou, Anyang, and Xinxiang cities from January 1 to February 13, 2020. The study period is divided into pre-holiday (January 1 to 23), mid-holiday outbreak (January 24 to 31), and post-holiday outbreak (February 1 to 13) based on the Spring Festival holiday and the outbreak of the epidemic. Affected by the outbreak and favorable meteorological conditions, the concentrations of other pollutants except O3 in the three cities during the post-holiday outbreak were significantly lower than those during pre-holiday, especially NO2 decreased by 65%, 52%, and 72% and PM2.5 decreased by 51%, 55%, and 54%, respectively. Note that the pollutants remained high concentration, indicating that a large improvement in winter air quality in Henan Province will face great challenges in the future. Secondary inorganic aerosols and organic matter were the main components of PM2.5 during the observation periods. During the mid-holiday outbreak, the three cities were less affected by fireworks, and the contribution of nitrate and dust decreased slightly compared to before the pre-holiday. After the holiday, the proportions of nitrate decreased by 10.6%, 4.1%, and 4% in Zhengzhou, Anyang, and Xinxiang, respectively. In contrast, the proportions of sulfate and secondary organic carbon increased. Taking Zhengzhou City as an example to analyze the formation of nitrate, compared to pre-holiday, the proportions of nitrate under different pollution levels in the post-holiday outbreak have decreased, but nitrate was still the highest proportion of PM2.5 during the polluted period. The characteristics of diurnal variation indicate that the increase in O3 concentration and humidity in the atmosphere during the post-holiday outbreak may promote the conversion of NO2. Therefore, the next step should be to adopt the coordinated management and control of PM2.5 and O3 and pay attention to the coordinated reduction of NO2 and VOCs. © 2020, Editorial Board of China Environmental Science. All right reserved.
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Since the end of 2019, the global pandemic of COVID-19 has attracted much attention on bats(Chiroptera), and even people are frequently frowned upon when talking about bats.Bats are extremely diverse in ecology and taxonomy, accounting for ~20% of mammalian diversity worldwide.Bats play an important role in pest control, seed transmission, plant pollination, offering a great economic benefit to human society.Moreover, bats bear important scientific research value in health and longevity, biomimetic, language evolution, and more.There are more than 140 species of bats in China, ranking China one of the top countries in terms of bat species diversity of the world.In recent decades, Chinese researchers have made great progresses in diverse fields such as bat taxonomy, ecology, ethology, evolutionary biology, neurobiology, and viral pathogens.However, researches focusing on ecosystem services and conservation of bats were very scarce.Due to logging and plants harvesting, over-hunting, habitat destruction, urbanization, agricultural activities, climate change, and so forth, bats in China are largely threatened: 51% of bat species have been listed as Near Threatened or above(Critically Endangered, Endangered, Vulnerable).We argue that successful bat conservation in China must first strengthen basic research, particularly in assessing the population status and trends of bat species and establishing a monitoring network for bat diversity.Additionally, a combination of conservation efforts, including the protection of bat habitats, construction of artificial bat habitats, improvement of relevant laws and regulations, and enhancement of public education on bats, are vital to ensuring sustainable bat populations in China. © 2020, Science Press. All right reserved.
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Objective: Pelvic high-resolution magnetic resonance imaging (MRI) has now become a standard method for evaluating the efficacy of neoadjuvant treatment for locally advanced rectal cancer (LARC). However, this traditional morphological qualitative assessment method based on T2-weighted imaging (T2WI) is not effective in predicting pathological complete remission (pCR). The purpose of this study is to investigate whether combining the magnetic resonance tumor regression grade (mrTRG) with apparent diffusion coefficient (ADC) can improve diagnostic value for pCR after preoperative neoadjuvant chemoradiotherapy (nCRT) of LARC. Methods: This was a diagnostic study. Clinicopathological data of 134 LARC patients who received nCRT and radical surgery in the First Affiliated Hospital of Kunming Medical University from January 2017 to December 2019 were retrospectively analyzed. All the patients underwent MRI which included T2WI and DWI sequences before and 8 weeks after nCRT. Two radiologists independently drew ROIs on T2WI and DWI to estimate mrTRG stage and calculate the mean ADC value. Receiver operating characteristics (ROC) method was applied to evaluate the predict value of mrTRG combined with mean ADC value for pCR. Results: Of 134 LARC patients, 85 were male and 49 were female with median age of 58 (28-82) years. After nCRT, MRI suggested 21 patients (15.7%) had clinical complete remission (cCR), e.g. mrTRG stage 1-2. Postoperative pathology revealed 31 (23.1%) patients had pCR. The evaluations of mrTRG and ADC value by the two readers were highly consistent, and the intra-group correlation coefficients were 0.83 (95% CI: 0.703-0.881) and 0.96 (95% CI: 0.989-0.996), respectively. There was a negative correlation between mrTRG and pCR (r(s)=-0.505, P<0.01), and a positive correlation between mean ADC value and pCR (r(s)=0.693, P<0.01). The ROC curve showed that mrTRG alone had a medium predictive value for pCR, with an area under the curve (AUC) of 0.832 (95% CI: 0.743-0.921); the mean ADC value had a higher predictive value for pCR, with AUC of 0.906 (95% CI: 0.869-0.962). The predictive value of the combined model of mrTRG and ADC value for pCR was significantly better than that of mrTRG alone (P=0.015), and the AUC was 0.908 (95% CI: 0.849-0.968). Conclusion: Both mrTRG and mean ADC value can be non-invasive methods to predict the efficacy of nCRT for LARC. Combining the mean ADC value with mrTRG can result in better pCR prediction.
Subject(s)
Neoadjuvant Therapy , Rectal Neoplasms , Aged , Aged, 80 and over , Chemoradiotherapy , Diffusion Magnetic Resonance Imaging , Female , Humans , Magnetic Resonance Imaging , Male , Middle Aged , Rectal Neoplasms/drug therapy , Rectal Neoplasms/therapy , Retrospective Studies , Treatment OutcomeABSTRACT
Background: Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury and acute respiratory failure. Methods: Inhibition of angiotensin-converting enzyme 2 (ACE2) caused by the spike protein of SARS-CoV-2 is the most plausible mechanism of lung injury in COVID-19. We performed drug repositioning analysis to identify drug candidates that reverse gene expression pattern in L1000 lung cell line HCC515 treated with ACE2 inhibitor. We confirmed these drug candidates by similar bioinformatics analysis using lung tissues from patients deceased from COVID-19. We further investigated deregulated genes and pathways related to lung injury, as well as the gene-pathway-drug candidate relationships. Results: We propose two candidate drugs, COL-3 (a chemically modified tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for treating lung injuries in COVID-19. Further bioinformatics analysis shows that 12 significantly enriched pathways (P-value <0.05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues. These include signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and chemokine signaling pathways. All 12 pathways are targeted in COL-3 treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42 have reduced expression. CGP-60474 shares 11 of 12 pathways with COL-3 and common target genes such as RHOA. It also uniquely targets other genes related to lung injury, such as CALR and MMP14. Conclusions: This study shows that ACE2 inhibition is likely part of the mechanisms leading to lung injury in COVID-19, and that compounds such as COL-3 and CGP-60474 have potential as repurposed drugs for its treatment.
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The 2019 novel coronavirus (2019-nCov) has caused increasing number of infected cases globally. This study was performed to analyze information regarding the transmission route and presence of viral nucleic acids on several clinical samples. Confirmed 2019-nCov-infected cases were identified in Dongyang and were treated according to guidelines for the diagnosis of 2019-nCov infection released by the National Health Commission. Information regarding the contacts that the infected people had was collected to determine whether it caused clustered cases. A series of successive nucleic acid examination of feces, oropharyngeal swabs, and sputum was also performed, and the results were analyzed. A total of 19 confirmed cases of 2019-nCov infection were identified in Dongyang, Zhejiang Province, China. Five cases showed severe symptoms, and the remaining ones showed mild manifestations. Ten cases infected from two asymptomatic individuals were clustered into two groups. Among 14 cases with consecutive nucleic acid test results, four patients showed positive results in feces after their negative conversion in oropharyngeal swabs. Asymptomatic individuals with the virus could cause 2019-nCov clustered cases, and the clustered cases may differ from sporadic cases on age and length of hospitalization. In addition, nucleic acids in feces last longer than those in oropharyngeal swabs.