On the Performance Evaluations of Cooperative Retransmission Scheme for Cell-Edge Users of URLLC in Multi-Carrier Downlink NOMA Systems

Non-orthogonal multiple access (NOMA) has a key feature that the cell-center user (CCU) has prior information about the messages of the cell-edge user (CEU) in the same user-pair. It means that CCU can be used for retransmission when the CEU requests retransmission. As ultra-reliability and low-latency communication (URLLC) requires high-reliability constraints (e.g., 99.999%), using CCU for retransmission can be useful to satisfy the reliability constraint. In this study, to ensure the reliability of CEU, cooperative retransmission (CR) scheme for downlink NOMA systems is proposed. And the CR scheme is evaluated with Block error rate (BLER) considering reliability and with packet loss rate (PLR) in terms of reliability and latency constraints. And the evaluation results showed that the proposed CR scheme can satisfy the target BLER for URLLC low SNR compared to the conventional retransmission scheme, and showed the improved PLR compared to the conventional retransmission scheme in low SNRs.

Understanding the landscape and propagation of COVID-19 misinformation and its correction on Sina Weibo

The prevalence of health misinformation on social media could significantly influence individuals' health behaviors. To examine the prevalent topics, propagation, and correction of coronavirus disease 2019 (COVID-19) misinformation, automated content analyses were conducted for posts on Sina Weibo, which is China's largest microblogging site. In total, 177,816 posts related to COVID-19 misinformation during the COVID-19 outbreak in China were analyzed. The structural topic modeling identified 23 valid topics regarding COVID-19 misinformation and its correction, which were further categorized into three general themes. Sentiment analysis was conducted to generate positive and negative sentiment scores for each post. The zero-inflated Poisson model indicated that only the negative sentiment was a significant predictor of the number of comments (β = 0.003, p < 0.001) but not reposts. Furthermore, users are more prone to repost and comment on information regarding prevention/treatment (e.g., traditional Chinese medicine preventing COVID) as well as potential threats of COVID-19 (e.g., COVID-19 was defined as an epidemic by World Health Organization). Health education and promotion implications are discussed.

The Impact of Retransmission and Modality on Communicating Health Research Findings via Social Media

Social media is an increasingly popular tool for disseminating health research findings to members of the general public and may contribute to improving the effectiveness of science communication. This study was designed to investigate how retransmission (i.e., social media content shared by a familiar, credible organization) and modality (i.e., how the message is delivered) influence the effectiveness of communicating health research findings via social media. The findings from a 2 (source) X 3 (modality) X 2 (topic) mixed factorial design experiment (N= 517) indicated that source had a significant effect, such that posts that were retransmitted by a credible organization resulted in greater perceived source credibility, greater perceived message effectiveness, and greater likelihood of an individual to engage with the post on Facebook. Modality significantly increased perceived source credibility and perceived message effectiveness when posts were retransmitted by a credible source, indicating that modality made a difference when messages were elaborated as a function of the retransmission. Also, the topic of the post had a significant impact on the study's dependent variables of interest. Overall, the findings illustrate the potential of retransmission and modality as message features that can improve communication of health research findings on social media. Theoretical and practical implications are discussed.

Optimal Number of Message Transmissions forProbabilistic Guarantee of Latency in the IoT

The Internet of Things (IoT) is now experiencing its first phase of industrialization. Industrial companies are completing proofs of concept and many of them plan to invest in automation, flexibility and quality of production in their plants. Their use of a wireless network is conditioned upon its ability to meet three Key Performance Indicators (KPIs), namely a maximum acceptable end-to-end latency L, a targeted end-to-end reliability R and a minimum network lifetime T. The IoT network has to guarantee that at least R% of messages generated by sensor nodes are delivered to the sink with a latency ≤L, whereas the network lifetime is at least equal to T. In this paper, we show how to provide the targeted end-to-end reliability R by means of retransmissions to cope with the unreliability of wireless links. We present two methods to compute the maximum number of transmissions per message required to achieve R. MFair is very easy to compute, whereas MOpt minimizes the total number of transmissions necessary for a message to reach the sink. MFair and MOpt are then integrated into a TSCH network with a load-based scheduler to evaluate the three KPIs on a generic data-gathering application. We first consider a toy example with eight nodes where the maximum number of transmissions MaxTrans is tuned per link and per flow. Finally, a network of 50 nodes, representative of real network deployments, is evaluated assuming MaxTrans is fixed. For both TSCH networks, we show that MOpt provides a better reliability and a longer lifetime than MFair, which provides a shorter average end-to-end latency. MOpt provides more predictable end-to-end performances than Kausa, a KPI-aware, state-of-the-art scheduler.

To Retweet or Not to Retweet: Understanding What Features of Cardiovascular Tweets Influence Their Retransmission

Twitter is one of the largest social networking sites (SNSs) in the world, yet little is known about what cardiovascular health related tweets go viral and what characteristics are associated with retransmission. The current study aims to identify a function of the observable characteristics of cardiovascular tweets, including characteristics of the source, content, and style that predict the retransmission of these tweets. We identified a random sample of 1,251 tweets associated with CVD originating from the United States between 2009 and 2015. Automated coding was conducted on the affect values of the tweets as well as the presence/absence of any URL, mention of another user, question mark, exclamation mark, and hashtag. We hand-coded the tweets' novelty, utility, theme, and source. The count of retweets was positively predicted by message utility, health organization source, and mention of user handle, but negatively predicted by the presence of URL and nonhealth organization source. Regarding theme, compared to the tweets focusing on risk factor, tweets on treatment and management predicted fewer retweets while supportive tweets predicted more retweets. These findings suggest opportunities for harnessing Twitter to better disseminate cardiovascular educational and supportive information on SNSs.

Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks

This paper embeds a bi-fold contribution for Underwater Wireless Sensor Networks (UWSNs); performance analysis of incremental relaying in terms of outage and error probability, and based on the analysis proposition of two new cooperative routing protocols. Subject to the first contribution, a three step procedure is carried out; a system model is presented, the number of available relays are determined, and based on cooperative incremental retransmission methodology, closed-form expressions for outage and error probability are derived. Subject to the second contribution, Adaptive Cooperation in Energy (ACE) efficient depth based routing and Enhanced-ACE (E-ACE) are presented. In the proposed model, feedback mechanism indicates success or failure of data transmission. If direct transmission is successful, there is no need for relaying by cooperative relay nodes. In case of failure, all the available relays retransmit the data one by one till the desired signal quality is achieved at destination. Simulation results show that the ACE and E-ACE significantly improves network performance, i.e., throughput, when compared with other incremental relaying protocols like Cooperative Automatic Repeat reQuest (CARQ). E-ACE and ACE achieve 69% and 63% more throughput respectively as compared to CARQ in hard underwater environment.

A cross-hazard analysis of terse message retransmission on Twitter

For decades, public warning messages have been relayed via broadcast information channels, including radio and television; more recently, risk communication channels have expanded to include social media sites, where messages can be easily amplified by user retransmission. This research examines the factors that predict the extent of retransmission for official hazard communications disseminated via Twitter. Using data from events involving five different hazards, we identity three types of attributes--local network properties, message content, and message style--that jointly amplify and/or attenuate the retransmission of official communications under imminent threat. We find that the use of an agreed-upon hashtag and the number of users following an official account positively influence message retransmission, as does message content describing hazard impacts or emphasizing cohesion among users. By contrast, messages directed at individuals, expressing gratitude, or including a URL were less widely disseminated than similar messages without these features. Our findings suggest that some measures commonly taken to convey additional information to the public (e.g., URL inclusion) may come at a cost in terms of message amplification; on the other hand, some types of content not traditionally emphasized in guidance on hazard communication may enhance retransmission rates.

Attracting Views and Going Viral: How Message Features and News-Sharing Channels Affect Health News Diffusion

This study examined how intrinsic as well as perceived message features affect the extent to which online health news stories prompt audience selections and social retransmissions, and how news-sharing channels (e-mail vs. social media) shape what goes viral. The study analyzed actual behavioral data on audience viewing and sharing of New York Times health news articles, and associated article content and context data. News articles with high informational utility and positive sentiment invited more frequent selections and retransmissions. Articles were also more frequently selected when they presented controversial, emotionally evocative, and familiar content. Informational utility and novelty had stronger positive associations with e-mail-specific virality, while emotional evocativeness, content familiarity, and exemplification played a larger role in triggering social media-based retransmissions.