Leveraging Volunteer Fact Checking to Identify Misinformation about COVID-19 in Social Media

Identifying emerging health misinformation is a challenge because its manner and type are often unknown. However, many social media users correct misinformation when they encounter it. From this intuition, we implemented a strategy that detects emerging health misinformation by tracking replies that seem to provide accurate information. This strategy is more efficient than keyword-based search in identifying COVID-19 misinformation about antibiotics and a cure. It also reveals the extent to which misinformation has spread on social networks

Conceptual articles may disrupt the field of marketing: Evidence from a GPT-assisted study

Marketing scholars have underscored the importance of conceptual articles in providing theoretical foundations and new perspectives to the field. This paper supports the argument by employing two network-based measures - the number of citations and the disruption score - and comparing them for conceptual and empirical research. With the aid of a large language model, we classify conceptual and empirical articles published in a substantial set of marketing journals. The findings reveal that conceptual research is not only more frequently cited but also has a greater disruptive impact on the field of marketing than empirical research. Our paper contributes to the understanding of how marketing articles advance knowledge through developmental approaches

Wallets' explorations across non-fungible token collections

Non-fungible tokens (NFTs), which are immutable and transferable tokens on blockchain networks, have been used to certify the ownership of digital images often grouped in collections. Depending on individual interests, wallets explore and purchase NFTs in one or more image collections. Among many potential factors of shaping purchase trajectories, this paper specifically examines how visual similarities between collections affect wallets' explorations. Our model shows that wallets' explorations are not random but tend to favor collections having similar visual features to their previous purchases. The model also predicts the extent to which the next collection is close to the most recent collection of purchases with respect to visual features. These results are expected to enhance and support recommendation systems for the NFT market

Measuring national capability over big science's multidisciplinarity: A case study of nuclear fusion research

In the era of big science, countries allocate big research and development budgets to large scientific facilities that boost collaboration and research capability. A nuclear fusion device called the "tokamak" is a source of great interest for many countries because it ideally generates sustainable energy expected to solve the energy crisis in the future. Here, to explore the scientific effects of tokamaks, we map a country's research capability in nuclear fusion research with normalized revealed comparative advantage on five topical clusters-material, plasma, device, diagnostics, and simulation-detected through a dynamic topic model. Our approach captures not only the growth of China, India, and the Republic of Korea but also the decline of Canada, Japan, Sweden, and the Netherlands. Time points of their rise and fall are related to tokamak operation, highlighting the importance of large facilities in big science. The gravity model points out that two countries collaborate less in device, diagnostics, and plasma research if they have comparative advantages in different topics. This relation is a unique feature of nuclear fusion compared to other science fields. Our results can be used and extended when building national policies for big science.11Yscopu

Understanding the Consumption of Antimicrobial Resistance–Related Content on Social Media: Twitter Analysis

Background: Antimicrobial resistance (AMR) is one of the most pressing concerns in our society. Today, social media can function as an important channel to disseminate information about AMR. The way in which this information is engaged with depends on a number of factors, including the target audience and the content of the social media post. Objective: The aim of this study is to better understand how AMR-related content is consumed on the social media platform Twitter and to understand some of the drivers of engagement. This is essential to designing effective public health strategies, raising awareness about antimicrobial stewardship, and enabling academics to effectively promote their research on social media. Methods: We took advantage of unrestricted access to the metrics associated with the Twitter bot @AntibioticResis, which has over 13,900 followers. This bot posts the latest AMR research in the format of a title and a URL link to the PubMed page for an article. The tweets do not contain other attributes such as author, affiliation, or journal. Therefore, engagement with the tweets is only affected by the words used in the titles. Using negative binomial regression models, we measured the impact of pathogen names in paper titles, academic attention inferred from publication counts, and general attention estimated from Twitter on URL clicks to AMR research papers. Results: Followers of @AntibioticResis consisted primarily of health care professionals and academic researchers whose interests comprised mainly AMR, infectious diseases, microbiology, and public health. Three World Health Organization (WHO) critical priority pathogens—Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacteriaceae—were positively associated with URL clicks. Papers with shorter titles tended to have more engagements. We also described some key linguistic characteristics that should be considered when a researcher is trying to maximize engagement with their publication. Conclusions: Our finding suggests that specific pathogens gain more attention on Twitter than others and that the levels of attention do not necessarily correspond to their status on the WHO priority pathogen list. This suggests that more targeted public health strategies may be needed to raise awareness about AMR among specific pathogens. Analysis of follower data suggests that in the busy schedules of health care professionals, social media offers a fast and accessible gateway to staying abreast of the latest developments in this field

Analysis of mitigation effect of the open- and closed-type check dam

Debris flow caused by intense rainfall can damage facilities and endanger human life. Accordingly, several models have been developed to predict and mitigate the debris flow damage, for which check-dam construction is essential. There are two types of check dams: open type and closed type. The former is suitable for granular debris flow containing little water, whereas the latter is suitable for water-laden debris flows. However, it is challenging to site the check dam to realize optimal mitigation effects. Therefore, we determined the best check dam location to reduce debris flow damage considering the two types. In this study, we simulated the Raemian apartment basin for the Mt. Umyeon landslides, which occurred in 2011. Constructing the open- and closed type dam at the upper side of the catchment produced the best performance

Continuous testing of silica-PEI adsorbents in a lab.-scale twin bubbling fluidized-bed system

In this study, a lab.-scale twin bubbling fluidized-bed system (TBS) has been used continuously to test the performance for CO2 adsorption of silica-PEI (S.PEI) adsorbents, containing 40 wt.% of PEI, which were supplied by the University of Nottingham (UNOTT). The TBS comprises bubbling-bed adsorption and desorption reactors, a riser for pneumatic conveying of solids from the adsorption to the desorption reactor, and a cyclone for solid-gas separation. The adsorbent prepared using PEI with a molecular mass of 800 (S.PEI-0.8K) was a preliminarily tested for almost 24 h at the given operating conditions by varying the inlet sorbent/CO2 mass ratio at the adsorber to analyse the CO2 removal efficiency in the adsorption reactor and the dynamic sorption capacity of the adsorbent. A 180-h continuous test was then carried out by changing various experimental conditions such as the H2O concentration, reaction temperature, solid layer height, reaction gas flow rate, and inlet sorbent/CO2 mass ratio at the adsorber using PEI with a molecular mass of 5000 (S.PEI-5K) adsorbent. In this test, a CO2 removal efficiency of above 80% and a dynamic sorption capacity greater than 6.0 wt.% were achieved

An informationally structured room for robotic assistance

The application of assistive technologies for elderly people is one of the most promising and interesting scenarios for intelligent technologies in the present and near future. Moreover, the improvement of the quality of life for the elderly is one of the first priorities in modern countries and societies. In this work, we present an informationally structured room that is aimed at supporting the daily life activities of elderly people. This room integrates different sensor modalities in a natural and non-invasive way inside the environment. The information gathered by the sensors is processed and sent to a centralized management system, which makes it available to a service robot assisting the people. One important restriction of our intelligent room is reducing as much as possible any interference with daily activities. Finally, this paper presents several experiments and situations using our intelligent environment in cooperation with our service robot. © 2015 by the authors

Performance of a silica-polyethyleneimine adsorbent for post-combustion CO2 capture on a 100 kg scale in a fluidized bed continuous unit

© 2020 Elsevier B.V. Polyethyleneimine (PEI)/silica adsorbents have been considered as a promising candidate for post-combustion CO2 capture, but the limited process study has been performed on a pilot-scale unit. Herein we report the 150 h continuous test results using a 100 kg sample of silica-PEI on a fluidized bed continuous unit. The CO2 removal efficiency and dynamic sorption capacity were evaluated continuously by changing a number of variables. For the sorption reactor, the changing variables were inlet H2O concentrations of 0–8.3 vol%, inlet CO2 concentrations of 12.0–21.5 vol%, bed temperatures of 50–70 °C and the bed differential pressures of 176–370 mmH2O. For the desorption reactor operated at the bed temperature of 129–130 °C, inlet H2O concentrations of 8.0–13.5 vol%, inlet CO2 concentrations of 14.6–81.2 vol% and bed differential pressures of 430–580 mmH2O were used. During continuous operation, CO2 removal efficiencies of over 90% were achieved with dynamic sorption capacities of 7.5 wt%. Solid sample collected during continuous operation were analyzed by TGA and 13C NMR to identity the decrease of CO2 adsorption capacity and the extent of thermo-oxidative side reactions. Slow oxidative degradation of the silica-PEI occurred because the transporting adsorbent was exposure to the non-humidified air in the solid transport system