Both the superstructures of virtual discourse in radiation oncology and the entities occupying influential positions in the social media landscape of radiation oncology remain poorly characterized.NodeXL Pro was used to prospectively sample all tweets with the hashtag #radonc every 8 to 10 days during the course of 1 year . Twitter handles were grouped into conversational clusters using the Clauset-Newman-Moore community detection algorithm. For each sample period, the top 10 #radonc Twitter influencers, defined using betweenness centrality, were categorized. Influencers were scored in each sample period according to their top 10 influence rank and summarized with descriptive statistics. Linear regression assessed for characteristics that predicted higher influence scores among top influencers.In the study, 684,000 tweets were sampled over 38 periods. #radonc tweets took on the crowd superstructure of a hub-and-spoke broadcast network formed when prominent individuals are widely repeated by many audience members. Professional societies were the most influential category of Twitter handles with an average influence score of 7.63 out of 10 (standard deviation [SD] = 1.94). When industry handles were present among top 10 influencers, they exhibited the second highest average influence scores , followed by individuals with scores of 5.28 (SD = 0.43). The categories of influencers were stable during the course of 1 year. The role of attending physician, radiation oncology specialty, male sex, academic practice, and US-based handles in North America were predictors of higher influence score.Twitter influencers in radiation oncology represent a diverse group of people and organizations, but male academic radiation oncologists based in North America occupy particularly influential positions in virtual communities broadly characterized as “hub and spoke” broadcast networks. Periodic network-based analyses of the social media discourse in radiation oncology are warranted to maintain an awareness of the handles that are influencing discussions on Twitter and ensure that social media utilization continues to contribute to the field of radiation oncology in a meaningful way. Social media is increasingly being used by both radiation oncologistsAs a consequence of these expanding uses of social media, vast networks of discourse have emerged on Twitter, where influence is exerted over opinions and potentially clinical decision-making. However, all voices are not equally influential on Twitter, and despite significant increases in Twitter content, very little is known about the people and institutions that occupy influential positions in the rapidly expanding social media landscape of radiation oncology. We sought to use network analysis to characterize the most influential Twitter handles using the hashtag #radonc during the course of a year.NodeXL Pro software  was created to support open scholarship related to social media and to generate and host open data. We used this software to prospectively sample tweets with the hashtag #radonc over the course of one year . 18,000 tweets are captured per sampling, resulting in an 8- to 10-day lookback period for each NodeXL Pro sampling. Twitter was thus sampled every 8 to 10 days to minimize both gaps and overlap in Twitter activity. This resulted in a total of 38 sampling periods during the course of the year. Institutional Review Board approval was waived given that all information analyzed was publicly available.NodeXL Pro was used to graphically visualize conversational superstructures with the hashtag #radonc for each period sampled. Twitter handles were grouped into conversational clusters using the Clauset-Newman-Moore community detection algorithm, as previously described.Influencers were defined using network measures of “betweenness centrality,” which is a validatedFor each sample period, the top 10 Twitter influencers using the hashtag #radonc were identified using betweenness centrality and categorized according to the schema in Data used for characterization were obtained from the Twitter user's profile and online searches. Handles were considered academic if they had an academic appointment with a title of professor, associate professor, or assistant professor. If title was not listed on the website, they were assumed to be academic if they worked at a teaching hospital or an academic center. Clinical oncologists in the United Kingdom were considered radiation oncologists for the purpose of this analysis. All resident physician handles were categorized as academic. Sex was determined by self-identification on Twitter, on academic profiles, and in cases of ambiguity, using an algorithmic assessment of sex probabilities based on first name.For each period sampled, influence was scored on a 10-point scale according to handle rank in the top 10 list . Rank scores for each period of the study year were grouped according to the previously established categories and summarized using descriptive statistics. Only categories present in a given period were included in the influence score calculation for that period. Scores were also used to generate stacked barplots, which summarize the proportion of influence scores in each of the 38 periods. Descriptive statistics also summarized the Twitter handles with the highest influence scores during the entire study year.Finally, linear regression analysis was applied to evaluate the relationship between influence score as a response variable and independent variables including period and categorical influencer characteristics. Likelihood ratio test was conducted to assess the overall significance of categorical variables with 3 or more levels. The significance level was set at 5%. All statistical analyses were carried out using R 3.6.0.A total of 684,000 tweets were considered for analysis. Network crowd diagrams from four periods sampled during the study year are shown in A broadcast network is characterized by Twitter commentary around the publishing of new information, creating a distinctive “hub and spoke” structure exemplified in panels A and D of For periods where a given influencer category was present in the top 10 list, descriptive statistics of average influence scores in each category are presented in When the scores from top Twitter influences from each period were considered in aggregate, an anonymized list of top Twitter handles for the entire study year is presented in P < .001), whereas professional societies had significantly higher scores . No differences in influence emerged between individuals, robots, hospitals, and industry . Resident physicians  and Twitter handles with other roles , including patients and researchers, were both less influential compared with attending physicians. Among handles that could be classified according to specialty, radiation oncologists were similarly influential as those from other specialties but were significantly more influential than industry handles . Male sex predicted for influence , albeit with a relatively small difference in average influence score, as did academic practice compared with nonacademic  and industry  groups. With the exception of Oceania, all other regions were home to handles with significantly lower influence scores compared with the North American reference . Across all categories, influence did not change significantly with time . The likelihood ratio test demonstrated the overall significance for the aforementioned categorical variables with 3 or more levels (Table E1).When considering characteristics of Twitter handles that predict for influence, as shown in Our findings, driven by network analysis of #radonc Tweets, demonstrate that social media influencers in radiation oncology represent a diverse group of people and institutions from fields not necessarily limited to radiation oncology. They include handles that are managed by industry, hospitals, medical journals, and even robots. Categories of influencers were relatively stable during the study period, rather than dynamic, with academic radiation oncologists comprising a major influential group after ASTRO. Twitter also appears to be an emerging space for resident physicians to influence conversations in radiation oncology. The most consistent influential handle was the ASTRO account.In an environment where social media discourse may exert a profound effect not only on intellectual exchange in radiation oncology,Our analysis of Twitter influencers yielded several novel findings that merit contextualization.Our report is the first to present data regarding the overall superstructures of social media conversations in radiation oncology. Based on the taxonomy set forth by the Social Media Research Foundation, we uncovered that the predominant conversational landscape has features of a hub-and-spoke broadcast network. This finding confirms what many have suspected about the virtual discourse in radiation oncology: it is characterized by a largely unpolarized crowd of discussants with an educational hub and spoke organization which is well-suited for the dissemination of information from trusted experts within the field. This is in alignment with our finding that academic radiation oncologists in large part comprise the most consistent cohort of #radonc influencers, a finding that also predates the advent of social media. Markedly absent from the conversational superstructure are polarized crowds where little common ground is shared between handles. Although Twitter debates about controversial topics may receive significant attention, it is important to remember that the public discourse about opposing views can be educational, that knowledge-sharing is the dominant #radonc conversational configuration, and that the prevailing patterns of Twitter discoutse suggests a commitment to curing cancer collaboratively, both in the clinic and virtually.We quantitatively demonstrated that top Twitter influencers are a heterogeneous group of individuals and nonindividuals from varying countries, specialties, practice settings, and levels of training. The relative proportions among categories of influencers did not change significantly over time. Events such as professional meetings,,Despite the diverse categories of radiation oncology influencers, there are some features that consistently predict for an influential role on Twitter. These include male sex, geographic base in the United States, and academic practice, in line with other work.Although no resident physicians enter into the top 10 influencers overall, individual residents and the Association of Residents in Radiation Oncology handle both made the top 10 influencer list over several sampled periods, suggesting that radiation oncologists in training are wielding notable influence on virtual platforms. Accordingly, social media may offer residents a more accessible avenue for sharing their perspectives, as well as opportunities for direct engagement with patients, providers, policymakers, and other stakeholders in radiation oncology to influence perceptions. The opportunities to influence on social media also likely face fewer barriers compared with day-to-day interactions within academic institutions, where hierarchy is customary. Resident engagement through social media is likely to increase in the future, as a recent survey study demonstrated that residents perceive that social media provides novel educational content and may even help with career development.Although the content of Tweets was not formally evaluated in this investigation, it is noteworthy when examining the list of top influential handles that over half of those individuals specialize in the management of lung cancer or are active proponents of stereotactic body radiation therapy. The use of stereotactic body radiation therapy in lung cancer, particularly for operable patients, has been an area of debate and may be a reason for the frequency of posts on this topic. This observation indicates that controversial topics may be more likely to engage Twitter users who are interested in radiation oncology. It may also identify an opportunity to broaden the scope of influential conversations on Twitter.It is interesting that professional societies, such as ASTRO, demonstrate higher influential scores than people. This may be due to ASTRO's role in supporting radiation oncologists across all disease sites. It may also be a result of ASTRO's representation of composite views that may engender greater trust and thus more easily influence conversations on Twitter compared with the views of individuals. Although it may be reassuring to some that a large, professional body occupies the dominant influential footprint on Twitter, other work has shown that even ASTRO's use of Twitter lags behind other professional societies such as American Society of Clinical Oncology and Society of Surgical Oncology,,Although other reports have considered Twitter activity in the context of specific campaigns (such as #WomenWhoCurieAlthough measured activity on Twitter provides a readout of what's being read and discussed, the clinical and professional effect of Twitter influence is uncertain and challenging to quantify. Prior reports have demonstrated no correlation between Twitter influence and H-index, but it may be of interest to assess whether Twitter influence “influences” other career-based metrics including grant acquisition, time to promotion, time to partnership, or time in the search for employment. These studies may be particularly meaningful given recent interest,Twitter influence is likely dynamic in the long-term, and a limitation of this analysis is that it only representes a detailed snapshot over a single year and thus may not reflect future or past influencer patterns in radiation oncology. However, it does hilight future related research opportunities to periodically monitor the social media discourse of our field and maintain a self-awareness of the character and content of our virtual communities, especially given that influencers are occasionally outside of the radiation oncology community. And finally, while efforts to more optimally identify and categorize relevant social media content through hashtags are ongoing,Although the degree to which influential Twitter discourse effects patient outcomes remains uncertain, this analysis demonstrates that it is feasible to globally evaluate influential handles and study them over time to understand which entities are influencing the discourse of radiation oncology. In a field as dynamic as radiation oncology, as more users become engaged in conversations on Twitter,


As monotherapy is insufficient for some patients, the existing fixed-dose combination (FDC) requires two or more daily administrations with declining adherence. The present study compared the efficacy and safety of netarsudil/latanoprost FDC with monotherapy of its individual components in patients with glaucoma.A systematic literature search was performed for studies comparing netarsudil/latanoprost fixed-dose combination (FDC) vs. monotherapy in patients with glaucoma. The primary endpoints included intraocular pressure (IOP), intraocular pressure reduction percentage (IOPR%) and adverse events (AEs).P < 0.00001) and higher IOPR% . When comparing FDC with latanoprost, both mean diurnal IOP  and diurnal IOP across 3 time points were significantly lower with FDC than with latanoprost, while FDC induced significantly higher IOPR% . Incidence of total AEs was similar between netarsudil and FDC, but higher with FDC than with latanoprost.Three randomized controlled trial studies (RCTs) involving 1,692 patients  were included in this meta-analysis. FDC was more effective than netarsudil, with significantly lower diurnal IOP over three time points , mean diurnal IOP (MD = −2.36 , Netarsudil/latanoprost FDC appears to be superior to netarsudil or latanoprost alone, with better ocular hypotensive effects. However, there are concerns that netarsudil/latanoprost FDC was associated with a significantly higher incidence of AEs specifically compared with latanoprost.https://www.crd.york.ac.uk/PROSPERO/display_record.php?RecordID=311956. Glaucoma has long been regarded as a major eye disease that can cause blindness . As the TM, recently approved by the FDA (US Food and Drug Administration), has already been evaluated to solve the current problem in the former study, but controversies remain  to compare the IOP-lowering efficacy and safety of netarsudil/latanoprost FDC with its individual components for treating patients with OAG or OHT.PRISMA  guidelines were followed in the conduct of this meta-analysis. (PROSPERO registration number: CRD42022311956).Relevant articles were retrieved using the following electronic databases: (1) EMBASE; (2) Ovid MEDLINE; (3) PubMed; (4) Web of Science; (5) ScienceDirect; (6) The Cochrane Library; and (7) Google Scholar. The following terms were used: “glaucoma,” “Netarsudil,” and “Latanoprost.” The last search was on January 25th, 2022. The detailed search results are shown in Study eligibility criteria for inclusion in this meta-analysis are listed as follows. (1) Population: patients with OAG or OHT; (2) Intervention and comparison: netarsudil/latanoprost FDC vs. monotherapy (latanoprost or netarsudil) once daily; (3) Outcome parameters: diurnal IOP over the three time points , mean diurnal IOP, IOP reduction percentage (IOPR%), AEs; (4) Study design: only RCTs published in English were included. If two or more articles were from the same population, we selected the paper published most recently. In addition, abstracts only, animal research, articles with duplicated data, meta-analyses, and review articles with no original data were excluded.baseline − IOPpointend-, SDIOPR = (baseline × SDpointend-)1/2, while the IOPR% and SD of the IOPR% (SDIOPR%) were estimated by IOPR% = IOPR/IOPbaseline, SDIOPR% = SDIOPR/IOPbaseline , mean diurnal IOP and IOPR% from baseline to the endpoint. We utilized existing IOPR% data directly if they were available in the original study. If not, we applied the following principles for calculation: IOPR = IOPbaseline . The eyebaseline . For theAll data were collected by two investigators independently. The information included the article characteristics , participant characteristics , duration of follow-up, IOP measurements and number of AEs. Discussions were held to resolve any disagreements.The RCTs were evaluated for methodological quality with the risk-of-bias tool in the Cochrane Handbook for Systematic Reviews of Interventions (version 5.1.0) . All incWe examined the quality of evidence for the outcomes based on the Grading of Recommendations Assessment, Development and Evaluation (GRADE) guidelines, which consider risk of bias, publication bias, indirectness, inconsistency and imprecision. The evidence was divided into high, medium, low, or very low levels .P < 0.05 indicates statistical significance. Heterogeneity in this study was examined with the I2 statistic and χ2 test. If the heterogeneity was acceptable , the fixed-effects model was adopted. If not, a random-effects model was employed. We inspected publication bias with Begg's and Egger's tests  and Cochrane Review Manager . Comparisons between FDC and monotherapy were grouped by the component of monotherapy (FDC vs. netarsudil and FDC vs. latanoprost). Subgroup analysis of IOPR% was conducted to determine whether the results would change according to follow-up duration, loss to follow-up rate, nation, number of patients, publication year, and trial center. The weighted mean difference (WMD) was measured for continuous variables , while the risk ratio (RR) was estimated for dichotomous variables such as AEs. The outcomes were all presented with a 95% confidence interval (CI). 's tests , 17.In all, 144 articles were initially identified. After applying the exclusion criteria, 3 articles were included in the present meta-analysis, as shown in P < 0.0001, I2 = 84%; 10:00 a.m.: MD = −2.43 , P < 0.00001, I2 = 24%; 4:00 p.m.: MD = −1.90 , P < 0.00001, I2 = 57%, P < 0.00001, I2 = 62%, P < 0.00001, I2 = 48%; For efficacy, IOP was significantly lower in the FDC group than in the netarsudil group across all 3 diurnal time points . We did not observe any significant difference between the two groups  and IOPR%  were in favor of FDC rather than latanoprost  The number of study participants included in this study was insufficient, and limited RCTs were included. In addition, all three of the multicenter clinical trials included in the analysis were conducted in North America, which may cause potential ethnic bias. (2) Owing to the lack of long-term observations, no significant systemic safety issues were reported. Therefore, we do not know whether this novel FDC, compared with monotherapy, increases the risk of systemic side effects similar to other FDCs. (3) As the duration of follow-up was not long enough (no more than 1 year), we lacked information about the comparison of long-term efficacy between FDC and monotherapy. (4) Only POAG and OHT patients were included, and further comparison of efficacy and safety for specific patients diagnosed with other glaucoma types might be necessary. (5) We cannot absolutely rule out the potential bias presented in the results of the included studies . (6) Considering the promotion in less-developed regions or countries, the evaluation of cost–effectiveness is also greatly warranted. Additionally, few existing studies have elucidated the issue of whether the effects of netarsudil/latanoprost FDC at different concentrations vary, which is vital for future clinical practice. Despite several Rho-kinase inhibitors having been discovered, only two are approved for treating glaucoma (Netarsudil in the USA and Ripasudil in Japan) while no available rho-kinase inhibitor as well as related clinical trial were approved in China currently. However, as some clinical practice is well-documented, it's promising that Rho-kinase inhibitors become available commercially in China in the future.In summary, netarsudil/latanoprost FDC appears to be better than netarsudil, with a better IOP reduction efficacy . However, netarsudil/latanoprost FDC was associated with a significantly higher incidence of AEs, especially compared with latanoprost, which was primarily manifested in eye disorders such as conjunctival hyperemia. Furthermore, for both ocular AEs and systemic side effects, all relevant safety issues were of mild severity, and most of them were self-limiting. Therefore, we believe that the safety of netarsudil/latanoprost FDC was acceptable. Overall, as demonstrated in the present study, with the help of this novel netarsudil/latanoprost FDC, the improvements in treatment adherence and efficacy in patients with glaucoma are promising.The original contributions presented in the study are included in the article/WZ had full access to all of the data in the manuscript and takes responsibility for the integrity of the data and the accuracy of the data analysis. NL, XJ, MH, and ZF: drafting of the manuscript. NL and WZ: critical revision of the manuscript for important intellectual content and statistical analysis. NL, YW, and WZ: supervision. All authors: concept and design and acquisition, analysis, or interpretation of data. All authors read and approved the final manuscript.This study was supported by Natural Science Foundation of Jiangxi Province (Grant No: 20212BAB206050), Science and technology planning project of Health Commision of Jiangxi Province (Grant No: 202110045), and Science and technology planning project of Jiangxi Administration of traditional Chinese Medicine (Grant No: 2020B0108). The funding had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


RationaleThe increasing prevalence of pediatric mental health presentations in pediatric emergency departments (PED) requires improved integration of evidence-based management strategies. Social media, specifically Twitter, has shown potential to aid in closing the knowledge translation (KT) gap between these evidence-based management strategies and pediatric emergency medicine (PEM) providers.Aims and objectivesThe primary outcome of this study is to evaluate the effectiveness of Twitter as a KT dissemination tool in PEM. The exploratory outcomes were to assess how to effectively implement Twitter in KT, explore ways in which Twitter can maximize the global reach of OpenHEARTSMAP and whether Twitter can lead to increased adoption of OpenHEARTSMAP.MethodsA one-week prospective promotion on Twitter was conducted to disseminate the OpenHEARTSMAP tool using 15 topic-related hashtags  versus one post wherein 15 different Twitter users were mentioned in 15 different comments . A one-week control period immediately prior to posting was employed for comparisons.ResultsDuring the Twitter week, visits per day to OpenHEARTSMAP increased by 175%; mean time spent on the website increased by 212%; and mean page actions per visit increased by 130%. The greatest increase in visits occurred on the first day of Tweeting. Arm 2 received the greatest engagements. Within arm 1, the category of pediatrics received the most engagements (hashtag #Peds was most popular). Arm 1 received 455 impressions compared to 2071 in arm 2. No new users registered an account on the OpenHEARTSMAP website, which is required to physically use the tool.ConclusionTwitter can be an effective KT tool to increase awareness of research, the first step of KT, in the domain of PEM mental health care. Strategies for success include building a robust Twitter following; posting during peak healthcare-related Twitter traffic times; employing hashtags coinciding with current events; and targeting posts by tagging users who need not necessarily be generally well-known opinion leaders. Knowledge translation (KT) and the KT gapWhile scientific evidence has expanded over the past few decades, the gap between knowledge and action in all areas of medicine has widened. Reports have described a lag of approximately 17 years between research publication and implementation, with only 14% of new discoveries reaching bedside practice . This gaThe immense volume of published research coupled with limited resource access and time constraints have been cited as barriers to evidence uptake. This contributes to poor awareness, or knowledge, of published literature - the critical first step in KT . AttitudThe role of social media in KTSocial media is a collection of online websites and applications where “users contribute, retrieve, and explore content generated by fellow users…for users, thus allowing knowledge and support to flow more effectively” . In contTwitter in KTTwitter is considered the most popular social media platform for healthcare communication . Choo etEmergency medicine has been a pioneer for free open-access medical education (FOAMed) . TwitterPediatric emergency medicine (PEM) mental health and HEARTSMAPCurrently, as many as one in five children and adolescents suffers from a neuropsychiatric condition . PediatrAccordingly, researchers have recommended the need for a standardized mental health-screening questionnaire with corresponding follow-up or discharge instructions ,17,18. TResearch gap informing this studyKT in PEM is an emerging field and there is a paucity of literature as to specific effective methods to disseminate PEM knowledge, which is the first step of KT . To our Study aimsA one-week prospective social media promotion was conducted with a primary aim of determining the effectiveness of Twitter as a KT dissemination method in PEM in increasing awareness of the HEARTSMAP tool.Exploratory aims were to determine which Twitter implementation strategy leads to maximal end-user interaction; to determine which Twitter implementation strategy leads to maximal global reach of HEARTSMAP; and to determine whether Twitter leads to increased use of HEARTSMAP.Awareness, the primary aim of this study, forms the first component of the KT pathway, while adoption forms the last step of KT . ImplemeOpenHEARTSMAPhttps://openheartsmap.ca. Clinicians can register online at no cost to become an OpenHEARTSMAP user after submitting basic professional demographic information. Complete access to the tool requires successful completion of three training cases embedded within the registration process.To broaden the global reach and utility of HEARTSMAP, a publicly accessible version called OpenHEARTSMAP was created. The tool is available at Study interventionUsing our established @HEARTSMAP_ Twitter account with 52 followers, 15 hashtag-specific Tweets (arm 1) and one generic Tweet without hashtags in which 15 different comments were made tagging 15 different users (arm 2) were posted as two KT dissemination strategies. All Tweets were written in less than 280 characters and contained: a traceable link to OpenHEARTSMAP, a visual component to increase dissemination and a call to action for viewers to retweet our post , 23. ComStudy armsIn arm 1, the 15 hashtag-specific Tweets referenced five different topic categories related to OpenHEARTSMAP as well as current events  to determine whether hashtag use specific to a particular period of time is influential: FOAMed, pediatrics, emergency medicine, mental health and COVID-19, with three Tweets per category . COVID-In arm 2, one generic Tweet containing our message without hashtags was tagged to 15 different users who fall into five different topic categories of accounts related to OpenHEARTSMAP: FOAMed accounts, pediatric opinion leaders, emergency medicine opinion leaders, mental health opinion leaders or organizations, and COVID-19-related opinion leaders, with three tags per category. FOAMed accounts were identified as described above. Opinion leader accounts or organizations were identified upon consultation with experienced physicians at our hospital. These accounts were identified based upon their popularity (number of followers) and/or the opinion leaders’ personal knowledge of influential individuals and organizations in the field of emergency medicine. The selected accounts were: @LITFLblog; @emcrit and @ALiEMteam (FOAMed); @dzungxvo-Dr. Dzung X Vo., @offcall99-Dr. Badrinath Narayan, @QdQwerty-Dr. Quynh Doan (pediatric opinion leaders); @Tingdan-Dr. Danial Ting; @Brent_Thoma-Dr. Brent Thoma, @TChanMD-Dr. Theresa Chan (emergency opinion leader); @Tylerblack23-Dr. Tyler Black, @Skye_Barbic-Skye Barbic and @CMHA_NTL ; and @picardonhealth-Andre Picard, @adriandix-Adrian Dix and @drsanjaygupta-Dr. Sanjay Gupta (COVID-19-related opinion leaders).Sample tweetOpenheartsmap.caOpenHEARTSMAP makes it easier for any provider, anywhere, to assess psychosocial presentations amongst children and youth in the emergency department, especially during this pandemic. Please retweet to spread the word! (#____) Sample tagged post(@____) We considered the OpenHEARTSMAP tool, created by physicians at British Columbia's Children's Hospital in Vancouver, might be of interest to you during these times. Please do retweet this post to help spread the word, thank you!Outcome measuresDuring the one-week promotion, daily metrics were collected from Twitter’s analytic tool and from the OpenHEARTSMAP web analytics page.Primary Outcome - AwarenessOpenHeartsmap.ca website link through a different website), direct entry, search engines or Twitter.The effectiveness of Twitter as a knowledge dissemination tool to increase awareness was measured by the total number of ‘page visits’, ‘average visit duration’ and ‘page actions’ on the OpenHEARTSMAP webpage. The method of access to the OpenHEARTSMAP website was also examined through websites , by measuring Twitter interaction metrics of ‘engagements’  for each Tweet.Reach was measured for each Tweet using the metric ‘impressions’ .Adoption of OpenHEARTSMAP was quantified by the number of online registrations and forms completed of the OpenHEARTSMAP tool.Data analysisPrimary OutcomeFor measuring awareness, the mean baseline number of ‘page visits’, ‘visit duration,’ and ‘page actions per visit’ to OpenHEARTSMAP were collected for one week prior to the promotion and at the completion of the one-week promotion. Percent changes were calculated. The change in method of access to OpenHEARTSMAP was also compared between the control week and Twitter week. Changes to the primary outcome metrics were analyzed using a paired sample t-test. Normally distributed continuous explanatory variables were described using parametric tests. Results were considered statistically significant with p values < 0.05. All statistical analyses were performed using RStudio .Exploratory OutcomesFor implementation, each Tweet was ranked according to the sum number of ‘engagements’ within each category after the one-week promotion to identify the most popular KT Twitter strategy (hashtags or generic Tweet with tagged users) and topic category that enabled maximal user interaction.For reach, the ‘impressions’ were summed per arm to grossly identify which Twitter KT strategy (hashtags or tagging) led to the largest reach.For adoption, the mean baseline number of online registrations and forms completed for one week prior to the promotion and at the completion of the one-week promotion. Percent changes were calculated. The change in method of access to OpenHEARTSMAP was also compared between the control and Twitter weeks and taken into account.Ethical considerationsApproval was obtained by the University of British Columbia Children and Women’s Research Ethics Board (H17-00748).Primary outcomeDuring the control week, an average of 1.6 visits per day was recorded on the OpenHEARTSMAP website, for a total of 13 visits  headed the call to action to retweeted our post. Of the eight retweets, more than half were from non-followers of the @HEARTSMAP_ account, yet still came across our Tweet from those who do follow us and retweeted. These findings support the notion of Twitter as an effective dissemination tool through a snowball effect, where one may not need to be personally connected to users in order to disseminate a clinical idea. This presents the notion that building a robust and engaged Twitter following might be helpful in clinical KT, more so than actively seeking out users to retweet a post.Within study arm 1, the topic category of pediatrics received the most engagement (#Peds as the most popular) followed by topic categories COVID-19 and mental health. The topic categories of emergency medicine and FOAMed received no engagements. These findings suggest that using relevant hashtags coinciding with local or current events may be an effective engagement strategy . Furthermore, using the highest trending hashtag within a topic was less effective than employing hashtags that are trending within a topic, yet not the most used. This could potentially be explained by the fact that the general popularity of highly used hashtags results in rapid dilution of any single Tweet.Reach was measured for each Tweet using impressions. Arm 2 of our study had more than four and a half times as many impressions. Despite these results, it cannot be concluded that tagging users in a Tweet is a more successful strategy for KT. For one, this Tweet for arm 2 happened to be the first Tweet that was posted at 09:00 PST, which, based on parallel data from the OpenHEARTSMAP website visit times, generally marks a higher traffic time which also coincides with the highest healthcare-related traffic times . This coAdoption, or use, of OpenHEARTSMAP was quantified by the number of online registrations and forms completed of the OpenHEARTSMAP tool. There was no change in the number of completed forms between the control week and the Twitter dissemination week and one new registration on the OpenHEARTSMAP website during the control week. While adoptability, or behavioural change, is the ultimate measure of successful KT, this study focused on awareness as the primary measure of KT, therefore these results do not take away from our findings of Twitter as an effective KT tool to increase awareness of PEM research. Our findings are comparable to Hawkins et al. who explored whether social media could increase journal subscriptions and readership . They diLimitationsWhile our primary objective was to drive traffic to our website using Twitter, the small numbers in this study preclude us from drawing definitive associations between Twitter and website metrics which have previously been suggested to correlate poorly . FurtherTwitter can be an effective KT tool to increase awareness of research, the first step of KT, in the domain of PEM mental health care. During our Twitter promotion, there were increases in visits, mean time spent and mean page action per visit to the OpenHEARTSMAP webpage. Strategies for successful dissemination via Twitter derived from this study include building a robust following; posting during peak healthcare-related Twitter traffic times; employing hashtags coinciding with current events rather than employing the most trending hashtags; and targeting posts by tagging users, who need not necessarily be generally known opinion leaders.


According to the results, the presented hybrid bagged model-based SMD technology achieved 98 percent accuracy.e-mail service providers and consumers find it challenging to distinguish between spam and nonspam e-mails. The purpose of spammers is to spread false information by sending annoying messages that catch the attention of the public. Various spam identification techniques have been suggested and evaluated in the past, but the results show that the more research in this regard is required to enhance accuracy and to reduce training time and error rate. Thus, this research proposes a novel machine learning-based hybrid bagging method for e-mail spam identification by combining two machine learning methods: random forest and J48 (decision tree). The proposed framework categorizes the e-mail into ham and spam. The database is split into multiple sets and provided as input to each method in this procedure. Moreover, tokenization, stemming, and stop word removal are performed in the preprocessing stage. Further, correlation feature selection (CFS) is employed in this research to select the required features from the preprocessed data. The effectiveness of the presented method is evaluated in terms of true-negative rates, accuracy, recall, precision, false-positive rate,  Over the years, e-mail has proven to be an immensely important method of communication, offering near-instant access to anyone around the world with an Internet connection. According to Tschabitscher, there was about 5 billion monthly active e-mail account in 2017, with that number likely to rise to over 5.5 billion per month in 2019. The investigator also points out that, even though over 270 billion e-mails are being sent every day, around 57 percent of them are trash. To detect spam or phishing e-mails, there seem to be several emerging machine learning algorithms and also strategies that closely match immune defense mechanisms, but overall effectiveness has been a big worry. The majority of the strategies are effective in preventing spam, but they also prevent certain nonspam communications, known as ham. This is an issue since it may result in the users losing pertinent data. Diverse kinds of e-mail assaults, including phishing, e-mail spoofing, and variations of spam e-mails, such as a covert redirect, clone phishing, spear phishing, and whaling, are continually bombarding customers worldwide. To make the warning message get sent from a valid user, e-mail spoofing frequently entails faking the e-mail header (the from portion). Spammers use mail impersonating since individuals are more likely to read an e-mail if it appears to be from someone they know [Spamming, which would be described as the practice of delivering unwanted communications to a large group of people, is on the rise right now. Since reputational risk and economical disruptions are one of the spammers' highest significant things, the spam influx has prompted academia scholars to investigate this issue as a promising proposed study. As a result, both organizations and people require effective and trustworthy junk e-mail filtration solutions. To respond to the growing volume of unwanted e-mails, these computers must apply sophisticated tactics. For a long period, spam e-mail identification has indeed been intensively researched . There aMany e-mail providers have included an automated trash detection performance based on the previous e-mail transmitted records as the premise of classification. Nevertheless, there are still e-mail servers, especially those run by individuals, that do not have trash detection performance. This is because not all private e-mail products include phishing identification as one of their application software packages by the standard. As a result, a spam detection mechanism should be developed and implemented as a software program or an add-on component. However, owing to the inherent flexibility of unsolicited messages by use of mail systems, the efficacy of trash identifying systems has frequently been restricted, or in some cases made useless or corrupted, necessitating the development of stronger spam identification techniques . Many spIndividuals and businesses gain greatly from the advancement of technological advancement. Simultaneously, technological advancement acts as a conduit for illicit activity. While hacker or virus utilization is a specialized talent that necessitates behaviors that are not performed by the average individual, social engineering is not as technically demanding. As a result, social engineering is becoming increasingly prevalent. In the third period of 2019, social engineering attacks have been the most common hazard to individuals and the second most common threat to businesses . In mostEvery day, people are inundated with hundreds of commercials. Users know how to avoid and decrease their access to information and messages that are uninteresting or unreliable throughout the term. Personal factors are one technique for advertisers to pique the interest of the customer base . MarketeAnother benefit of marketing comes from the ability to identify a particular targeted audience due to self-characteristics such as age and sexuality available on profile pages. Nevertheless, there is little study on personalized social media ads, and future studies should go beyond statistics to include information specific to social media. Conventional systems for gathering customer data may provide marketers with limited or erroneous data about customers. Because social media profiles are based on voluntary self-disclosure of private details, there is the potential for purposeful distortion, allowing for the creation of fake accounts, online trolls, and chatbots. As a result, aggregating SNS information may result in mistakes in customer profiles and focused marketing . The folTheir daily lives are becoming increasingly reliant on social media. Our communication through these platforms has only grown in tandem with their fast expansion. Twitter is among the most widely used social media platforms in the Middle East. Tweet, like other social networking sites, is susceptible to spam profiles that distribute part of the strategy. Leading to a shortage of appropriate technology that serves the Arabic language, Arab countries have been among the most attacked. Furthermore, because Arabic is a sophisticated language with multiple varieties and significant grammatical rules, retrieving text data might be difficult. Several recent researches have looked into inventive ways to reduce spamming in tweets. The research collected Arabic datasets appropriate for junk identification to tackle the problem of identifying spamming identities in Arab on tweet. Utilizing Twitter's subscription application programming interface, the database included information from premium content. Abandoned identities were flagged, and information was labeled. A hybrid approach that is based on deep learning algorithms was developed, which has numerous benefits, along with more efficient and timely outcomes while using fewer system resources. Text-based statistical analyses were performed using a convolution neural network (CNN) approach, while information was analyzed using a basic neural network-based framework. When the two algorithms' outputs were pooled, they categorized identities as spam or not spam. The suggested approach surpassed the best designs evaluated thus far in the research, achieving an efficiency of 94.28 percent with the hybrid algorithm employing superior extracted features. In interaction via social media platforms like Twitter, several Arabic accents and informal idioms intersect. This makes it more difficult to identify spam identities utilizing solely text-based characteristics and therefore necessitates several earlier processes to acquire correct categorization. Additional research into a preprocessing stage that might accommodate Arabic accents with minimum impact on intentions and interpretation would have been beneficial. This is considered the major limitation of spam accounts combined with the text and meta-based deep learning framework proposed by .In numerous businesses, especially marketing, the categorization, and suggestion method for recognizing social networking site (SNS) members' preferences play an important part. Customized adverts help firms stick in a sea of digital advertising by increasing relevancy to customers and eliciting positive reactions . The comSingle-modal spam filtering algorithms have obtained a maximum classification performance for picture and text junk in the latest days. To remain undetected by single-modal spamming filtering techniques, fraudsters introduce garbage data into the multi-modality component of an e-mail and blend it to lower the single-modal spam detection processor architectures' classification performance, so achieving the goal of dodging identification. In light of this, the latest product known as multimodal design obtained from the numerical fusing (MMA-MF) has been presented, which employs a multimodal fusing strategy to ensure that trash can be efficiently filtered whether it has been concealed in word or phrase. To filter trash, the approach integrates a convolutional neural network (CNN) with a long short-term memory (LSTM) framework. The visual and textual components of an e-mail were processed individually to use the long short-term and convolutional neural network models to generate two categorizations posterior distribution, which are then merged into a hybrid framework to estimate if the message is trash or otherwise. Researchers are using a grid search optimization algorithm to determine the most appropriate hyper-parameters for the MMA-MF designer's hyper-parameters and a k-fold cross-validation technique to assess the effectiveness of the algorithm. The findings of the experiments reveal that this approach outperforms typical spam detection algorithms, with accuracies ranging from 92.65 to 98.49 percent. Researchers believe using the novel methodology, as well as the one-class classification algorithm and the few-shot pedagogical practices, to address the problem of the discrepancy between the number of spam and nonspam e-mails, and we will keep collecting extra realistic combined electronic mail data sources to enhance the system framework of the prototype so that it could function better at phishing detection .Spam e-mail makes it difficult for users of e-mail accounts to receive critical data. e-mail spam prevention has indeed been implemented in public mail servers using a variety of ways. However, not all e-mail systems offer to spam e-mail significant findings for the usage of a limited amount of enterprise e-mail addresses. To safeguard e-mail users from junk, the system administrator should implement a distinct or module junk mail detection rate. The goal of this research is to find the most effective strategy for identifying spam e-mails. To determine the most effective technique for identifying spam e-mail, researchers used machine learning techniques such as decision tree, logistic regression, and random forest, and evaluated the findings. The speed of train and test procedures, and the reliability of spam message detection are used to determine effectiveness. According to the findings of this investigation, the random forest approach has an outstanding outcome, with a testing data velocity of 0.19 seconds and a 98 percent reliability. This finding could be utilized as a basis for the formulation of various algorithms for spam filtering. The limitation of the research is the researcher assumed that more specific algorithms, like the approximate solution and the database process, would be used to enhance efficiency [Smart objects supply the preponderance of computational services near to the end customers for the next-generation Internet of things. These gadgets with built-in knowledge may make autonomous choices in the context where they are placed by applying diverse AI methodologies. In response to these challenges, researchers propose a cognitive incursion prevention mechanism that prevents brand loyalty is important from infiltrating the web address bar image data, hence maintaining the legitimacy of search engine result pages. By addressing three separate levels, namely, data collecting services, edge computing services, and cloud services, the proposed model provides ambient knowledge for web data filtering and identifies web spam. The goal is to identify harmful images. The average, image gradient, and volatility of a picture are first retrieved, and afterward, the received information is analyzed in the proposed framework. For the performance evaluation of the proposed method, deep learning techniques are being used. It achieved a 98.77 percent accuracy when tested on a real-time available dataset .The e-mail is classified by the classification model based on its content and other criteria. The procedure of feature extraction and selection is critical for the majority of classification issues. In the categorization process, characteristics are quite important. The correlation-oriented feature extraction (CFS) approach is utilized for features extracted in this research . For effThe suggested spam mail identification structure is predicated on the machine learning approach's efficiency. Firstly, electronic mail information is gathered through a spam mail identifying scheme. The e-mail information gathered is unorganized and unfiltered. e-mail information must be preprocessed in terms of reducing operations and providing an exact outcome. To obtainnecessary information, the information is automatically by eliminating text content, stemmed, and term text categorization. Each categorization technique uses the database, which is arbitrarily partitioned into multiple sets. To assess the ultimate classifier performance, the bagging method integrates the categorization performance of the different machine learning techniques .The basics of the random forest and J48 decision tree algorithms are explained in this part.k” randomly picked attributes to examine for creating each decision point and mentioned inThe random forest technique implements bagging by building each tree in an ensemble of decision trees from the bootstrap sampling of data from the training dataset. The length of each random subset of texts is determined by repeating randomized systematic sampling till its bootstrapping sample equals the size of the image training dataset. Just a random selection number of features is examined while creating each decision component for each decision tree . The yesWhenever the classification is undecided as to whether a text is a junk, the unpredictability is highest. Here is an instance of a simple spam detection random model mentioned in Algorithm 1.Unlike many other decision tree optimization models, the random forest algorithm dataset is divided set iteratively when it is no longer effective to minimize the randomness of each leaf node . To use a voting approach, the full ensembles of decision nodes are then utilized to classify fresh communications .Random forest is a higher-level variation of CART that uses the bootstrap bagging approach and random feature selection. In this approach, a forest is created from a large number of trees, which are subsequently analyzed to produce categorization input data . The outThe technique creates judgment nodes higher in the tree whenever examples of originally thought unsupervised classification are detectedWhen the data collected correspond to a single class, the algorithm is used to generate a prediction model with a leaf node and requests that category be consideredIf the characteristics or obtained features do not give any mutual information, a judgment node is generated just above the current tree using predicted valuesThe J48 classification is predicated on the notion of probability and is a decision tree classification. It is a multiclass classifier that uses the training knowledge to generate decision trees. For the categorization of the new data element, the decision tree built utilizing J48 is based on the training examples feature values. J48 is based on the idea that dividing data into numerous sets allows any feature characteristic to be utilized to generate a decision . The metThe root of the tree, internal nodes, and leaf nodes make up a tree structure. Leaf nodes indicate the class, while nodes in the network indicate the constraints attached to characteristics and traits . A samplF is the decision tree. Splitting requirement is an attribute selection strategy in this method that divides the data objects into certain individual courses.DT is the collection of training examples in Algorithm 2, and The process of the spam mail detection (SMD) program for classifying e-mail into ham and spam messages is depicted in this part. The SMD network is comprised of strong division capabilities that were first established with the hybrid bagged method concept. The feature identification is executed using a correlation-based feature selection technique, and the analysis is performed using a unique hybrid bagging methodology .The bagging strategy is a hybrid method in which the categorization aim is served by a decision tree-based J48 algorithm and random forest. The database e-mail spamming code project machine learning and AI assert were primarily seen as the information training and testing data in this study. This database is provided to competition competitors as a reference for effectively detecting spam e-mails. Information is then classified as trash or nonspam intended to assist in the detection and verification of results using machine learning methods. Again, for the spam mail detection technique, an e-mail database is created . From thThe message database under consideration is unprocessed. As a result, it must be preprocessed until being considered anymore. There are 3 phases in the preprocessing stage. The tokenization of the text information is measured first. Tokens are words that are separated from the rest of the phrase. Stop words are eliminated from the tokenized phrases. Inappropriate phrases with no linguistic meaning are known as stop words. During preprocessing, a document with around 670 stop words is routinely generated, and words are eliminated from the content. Stemming is the third stage in the preprocessing component. The stemming method removes a word from its root word. Stop word removal and stemming are key preprocessing processes since they significantly decrease the search area for effective extracting features .Feature selection is an important concern that has sparked a bit more articles. That has three objectives: (i) improving classification predictive performance, (ii) developing a better and more cost classifier, and (iii) gaining a greater understanding of fundamental processes related to information production. Two recommended strategies for reducing the feature set size are dimensionality reduction and relevant feature selection. Although relevant feature selection entails extracting a subset characteristic, image compression entails combining the original features and functionality linearly . In everc is the feature set with n number of features and a is the set of training.Text data with extracted features are primarily thought of as a bag of visuals. The term frequency technique is used to display the total number of terms in a material. All phrases are counted for recurrence, and those with a recurrence under a certain level are removed. The plan proves the words' utility while concurrently dipping the search area . Utilizirac and the average correlation feature-feature is denoted as rcc.Here, the average correlation feature class is denoted as The classification design is the fourth and final system. For categorization, a hybrid bagged technique combining the decision tree-based J48 algorithm with the random forest is being examined. The bagged strategy, also known as the bootstrapping aggregating method, reduces variability by combining numerous repeating subsets of the same database. Multiple models have been created in this method by arbitrarily partitioning the e-mail database into two independent sample mail data sources: SD1 and SD2. Separate classifiers are trained using each instance of e-mail collection. The outcome of the entire process is the average of two categorization systems' results. For multiclass recognition and classification, the J48 method and random forest are utilized . The meaOnly with the assistance of the accompanying instance, a complete explanation of the components of the spam mail detection (SMD) process is achieved . An instThe obtained measurements of the spam mail detection (SMD) method are mentioned in this report. For the experiments, an e-mail database of 1000 e-mails is used, including 500 e-mails in each of the two classification methods . Three tF-measure, and false-negative rate are computed. The effectiveness of the spam mail detection system is assessed using the criteria listed in The overall outcome of a spam mail recognition model is the combination of both models' forecasts, resulting in a system that is efficient and dependable. The efficiency characteristics are used to assess the effectiveness of the implemented method spam mail detection technique. To analyze the efficiency of the spam mail detection technique, measures such as accuracy, false-positive rate, recall, precision, true-negative rate, F-score.The algorithm received an average accuracy of 95 percent, which is the average of the two classification systems' efficiency. Random forest classifier has an accuracy of 84 percent, with precision and recall values of 86 percent and 82 percent, correspondingly. The J48 method, on the other hand, achieves 92 percent accuracy, with precision and recall values of 94 percent and 90 percent, correspondingly. The assessed outcomes of the three trials are presented in By comparing the J48 decision tree method to the random forest and the hybrid bagged method, the findings in Tables 47Today, spammers are among the most demanding and unpleasant issues related to communication and information technologies. Paid trolls abuse this communications device by sending spam e-mails, which has a negative impact on productions and numerous Internet consumers. This research presents a spam mail detection mechanism that uses a hybrid bagging technique for execution. Random forest and decision tree (J48) are the categorization techniques employed in this technique. The hybrid bagging method-based spam mail detection system attained an overall rate of 95 percent, indicating that the testing findings are superior when using simply the J48 method. The idea of enhancing technique could have been used for future studies to improve the system's effectiveness. The enhancing strategy substitutes the weak classifier's learning features with those of the classification model, enhancing overall design competence. In future consideration, the researcher assumed that even more sophisticated techniques, like the evolutionary algorithm and the dataset procedure, will be more widely used to enhance effectiveness.


Cephalotus follicularis, has evolved cup-shaped leaves and a carnivorous habit completely independently from other lineages of pitcher plants. It is the only species in the family Cephalotaceae and is restricted to a small region of Western Australia. Here, we used metabarcoding to characterize the bacterial and eukaryotic communities living in C. follicularis pitchers at two different sites. Bacterial and eukaryotic communities were correlated in both richness and composition; however, the factors associated with richness were not the same across bacteria and eukaryotes, with bacterial richness differing with fluid color, and eukaryotic richness differing with the concentration of DNA extracted from the fluid, a measure roughly related to biomass. For turnover in composition, the variation in both bacterial and eukaryotic communities primarily differed with fluid acidity, fluid color, and sampling site. We compared C. follicularis-associated community diversity with that of Australian Nepenthes mirabilis, as well as a global comparison of Southeast Asian Nepenthes and North American Sarracenia. Our results showed similarity in richness with communities from other pitcher plants, and specific bacterial taxa shared among all three independent lineages of pitcher plants. Overall, we saw convergence in richness and particular clades colonizing pitcher plants around the world, suggesting that these highly specialized habitats select for certain numbers and types of inhabitants.The Albany pitcher plant,  Sarracenia (family Sarraceniaceae) and Nepenthes (family Nepenthaceae) have now been characterized across numerous studies . A study of aquatic organisms, ranging from bacteria to fish, found higher dispersal limitation in larger organisms  characterize the bacteria and eukaryotes associated with C. follicularis pitchers using DNA metabarcoding, and to assess how they are affected by site and host characteristics and (2) investigate possible convergence in community richness and shared taxa due to the very distinctive and similar life form among pitcher plants. We ask: What organisms live in C. follicularis pitchers? How do growing site and characteristics of the pitcher fluid impact community composition and structure? Do different factors affect bacterial and eukaryotic communities? Are C. follicularis pitcher communities similar to those found in Australian Nepenthes? Do we see convergent interactions such as those found in Sarracenia and Nepenthes?To the best of our knowledge, this is the first metabarcoding study characterizing the entire bacterial and eukaryotic communities of C. follicularis pitchers, split evenly between two sites roughly 20 km apart near Albany, Western Australia designated Gull Rock Road (GRR) and Two Peoples Bay . We haphazardly selected 20 healthy pitchers on different plants at each site that had no visible damage. Although it is difficult to gauge pitcher time-since-opening in the field without marking unopened pitchers and returning over time, we aimed to select pitchers of different ages to get a full representation of the existing diversity. The entire pitcher fluid from each pitcher was collected using a sterile pipette for each sample and was transferred to sterile tubes. Fluid color was noted qualitatively by a single researcher and total volume was recorded before removing an aliquot of fluid for pH measurement and sequencing. We measured the pH of the samples with Macherey-Nagel pH-Fix 4.5–10.0 and BDH VWR Analytical pH-Test 0.0–6.0 indicator strips. We preserved samples with a 1:1 volume of cetyl trimethylammonium bromide (CTAB) buffer at room temperature before transporting them to the laboratory and freezing them until DNA extraction. In addition to these samples of C. follicularis, 21 N. mirabilis pitchers were sampled near Bramston Beach, Queensland, Australia in May 2016 following the same protocol as the C. follicularis sample collection.In January 2016, we collected fluid samples from 40 healthy We extracted DNA from sample fluids using a phenol-chloroform bead-beating extraction method . DNA extC. follicularis and N. mirabilis) have been deposited in the Sequence Read Archive NCBI BioProject PRJNA810039.Amplicon sequence data for the Australian samples  were analyzed together in the same way. We used QIIME2 versions 2018.4 and 2019.10  on the BC. follicularis communities first, creating a subset of just these samples and rarefying at 4,039 sequences for 16S and 2,704 for 18S. We ran generalized linear models (GLMs) using a Gamma distribution (log link function) to examine the association of bacterial and eukaryotic richness , the volume of pitcher fluid in p = 0.06006). Pitcher fluid pH and the total extracted DNA concentration from each sample also did not differ by site , and fluid pH also  did not significantly differ by fluid color . Fluid pH and DNA concentration were not correlated with volume ; however, fluid pH and DNA concentration were correlated with each other , with more acidic pitchers having lower DNA concentrations . Rarefaction curves showed that all samples reached a plateau in diversity before our rarefaction cutoff , Diptera (flies), Araneae (spiders), and Adinetida (rotifers). The two most common fungal families found were Aspergillaceae and Mortierellaceae.The effective number of species is a measure of alpha diversity or species richness that is calculated as the exponential of the Shannon diversity of species or, as in this case, ASVs. This measure of richness also incorporates the evenness of the community. For bacteria, the effective number of species per sample ranged from 2.5 to 56.7, with a median of 11.1 and a mean of 13.7 . EukaryoVariation in richness in each of the two broad taxonomic groups is associated with different factors. When controlling for other variables, bacterial but not eukaryotic richness significantly varies with color of the pitcher fluid  but not site, volume or DNA concentration, while the 18S GLM indicates that eukaryotic richness significantly varies only with DNA concentration . Effect R2 = 0.04215, p = 0.010; Eukaryotes R2 = 0.04755, p = 0.001; r = 0.2837, p = 0.001; Eukaryotes r = 0.3903, p = 0.001; R2 = 0.16485, p = 0.001; Eukaryotes R2 = 0.12727, p = 0.001). In eukaryotes, there is a significant interaction between site and fluid color , while in bacteria, the interaction shows a trend that is not significant . Community compositions of bacteria and eukaryotes are both not significantly correlated with pitcher fluid volume, and, similar to species richness , only eukaryotic community composition (beta diversity) varies significantly with DNA concentration  by site, which explains ~4–5% of the existing variation  were enriched in yellow fluids .Mortierella (phylum Mucoromycota) enriched at the TPB site. As with bacteria, eukaryotic taxa—specifically different groups of green algae—significantly differed with the color of the pitcher fluid: Chlorophyta were generally enriched in green fluid, Chlorophyta plus a Cocomyxa species in brown fluid and Cocomyxa dispar in yellow fluid. In addition to the green algae, Vannellida (an order of freshwater and marine amoebae) was enriched in both green and brown fluids, and Araeolaimida (freshwater nematodes) were enriched in green fluids  show a clear, strong signal of high relative abundance across all three pitcher plant genera .Our rationale for selecting and presenting a comparison sample is largely heuristic. The closest pitcher plants to N. mirabilis at one site near Bramston Beach hosted communities similar to those of C. follicularis with regard to bacterial taxa, with Gammaproteobacteria and Alphaproteobacteria at similar relative abundances and the highest representation. However, there were relatively more taxa in the class Bacteroidia in N. mirabilis, and fewer in the classes Actinobacteria and Acidobacteriia (N. mirabilis had relatively more Metazoa (mostly represented by insects) and fewer Fungi , and likely also in C. follicularis. Limitations of our current study prevented us from sampling the same pitchers at different successional stages; however, we aimed to select healthy pitchers of different ages to get a full representation of the existing diversity. Future studies in C. follicularis could sample across different seasons and successional stages.Pitcher communities change over successional time, from pitcher opening to senescence. This successional change has been well-documented only in ea e.g., , but occSarracenia alata system, pitcher communities—and arthropods in particular—have co-diversified with their host plants across a biogeographic barrier  could be specialists in the pitcher habitats; however, host specificity in bacteria is rare and difficult to test. It is more likely that they are present due to environmental filtering as a result of host convergence with regard to the pitcher habitat. Pitchers are not just passive receptacles, they affect the habitat inside justment . A recenmportant . Similarmportant . Howevermportant , where aC. follicularis, Nepenthes and Sarracenia pitcher communities in very different parts of the world—Australia, Southeast Asia and North America—suggests that pitchers in general cultivate a particular habitat that selects for a similar microbiome, regardless of location or evolutionary history  to LB. The collection of Nepenthes mirabilis samples was funded by a Bolitho Scholarship from the Harvard University Committee on Australian Studies. Partial funding for the DNA extraction and amplification and initial analyses was provided by The Museum of Comparative Zoology, Harvard University Herbaria, and Arnold Arboretum Grant-in-aid of Undergraduate Research and Harvard College Research Program Undergraduate Summer Funding to EB. LB and JB are currently funded by an NSF award 2025250, and LB is also supported by the NSF Idaho EPSCoR Program and award number OIA-1757324. Published by a grant from the Wetmore Colles Fund.The collection of The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


The finite element method and a step-by-step algorithm have been implemented in the proposed field model of coupled phenomena in the considered brake. The nonlinearity of the magnetic circuit and rheological properties of a magnetorheological fluid (MR fluid) as well as the influence of temperature on the properties of materials have been taken into account. To solve equations of the obtained field model, the Newton–Raphson method and the coupled block over-relaxation method have been implemented. The elaborated algorithm has been successfully used in the analysis of the phenomena in the considered magnetorheological brake. The accuracy of the developed model and its usefulness have been verified by a comparative analysis of the results of simulation and laboratory tests carried out for the developed prototype of the studied brake.The paper presents a field model of coupled phenomena occurring in an axisymmetric magnetorheological brake. The coupling between transient fluid dynamics and electromagnetic and thermal fields as well as mechanical equilibrium equations is taken into account. The magnetic field in the studied brake is of an excited hybrid manner, i.e., by the permanent magnets (PMs) and current  This operation range can be used during emergency braking. The proposed HEMRFB has many advantages such as quiet operation, lower power consumption than in the electromagnet-driven brakes, easy braking torque regulation, and an ability to achieve quasilinear control characteristics by proper design of the magnetic circuit [The paper presents the authors’ concept of a hybrid excited magnetorheological brake (HEMRFB) , develophe fluid ,7,8. Owihe fluid ,15,16,17he fluid ,19. To dElectromagnetic devices with an MR fluid are investigated in many scientific institutions around the world. The research work conducted at these institutions focuses on the analysis of the operating states of existing devices and on methods to improve their functional performance. At the same time, work is also underway to develop new designs of devices ,21,22,23In the paper, a field model of coupled hydrodynamic, electromagnetic, thermal, and mechanical phenomena has been proposed and discussed. The proposed model has been developed to analyze the steady and transient states of the axisymmetric MR brake with a hybrid excitation system. In order to verify the proposed field model of coupled phenomena in the considered device, an elaborated algorithm and software, as well as a prototype of the brake, have been designed and tested.Because of the high nonlinearities of the magnetic circuit and rheological properties of MR fluids, the phenomena occurring in devices with an MR fluid should be considered in terms of fields. In the MR brake considered, the velocity field of the fluid is dependent on the angular rotor velocity, as well as the yield stress distribution in the MR fluid. This shear stress in the fluid is dependent on both the distribution of magnetic flux density in the area with the fluid due to its rheological properties and the field of deformation of the fluid’s velocity. The resulting shear stress counteracts the rotor motion in the MR brake and is directly related to brake antitorque. Therefore, in the numerical model of an MR transducer, the stresses in the fluid and its velocity field should be coupled with the electromagnetic field. It should be emphasized that this coupling is bidirectional since the value of the transmitted torque influences the dynamics of the moving parts of the brake. Moreover, it should be highlighted that the fluid dynamic and electromagnetic phenomena in MR transducers are highly affected by the dependence of material properties on temperature. In order to precisely reproduce the phenomena, the conductivity of the regions with eddy currents, their magnetic permeability, winding resistance, and magnetic flux produced by the permanent magnets, as well as the viscosity and yield stress of an MR fluid, should be considered as a function of the temperature distribution.Due to the strong coupling between the electromagnetic thermal and fluid velocity fields, the analysis of the phenomena in devices with MR fluids is a challenging and complex task in terms of the numerical implementation of the proposed models. Even more complicated is the transient nature of these fields and the nonlinearity of the equations describing them. So far, a comprehensive approach to the problem of solving time-dependent coupled field phenomena in MR devices has not yet been the subject of research discussed in the open literature. It can be observed that in the research area subjected to the analysis of MR transducers, the field approach is applied only for selected phenomena , while simplified models of fluid dynamics or temperature fields are incorporated ,20,24,34Only one paper  presentsr, z, υ has been introduced—see In this paper, an MR brake with an axisymmetric structure has been considered see . Therefol = 2πr, φ = 2πrAυ, Aυ is the component of magnetic vector potential A in the υ-direction, w = i/scJ is the current density in the excitation winding, i is the current value in the winding, cs is the cross-section area of the winding wire, rM and zM are the components of magnetization vector M in the regions with PMs, μ is the magnetic permeability of the medium, and γ is the conductivity of the region with the eddy currents. For the MR fluid, the conductivity γ is equal to 0.The equation system describing the transient electromagnetic field can be given in the following form ,35,36,37r is less than 10.The magnetization characteristics of the considered fluids are nonlinear—see 0 is the magnetic permeability of the vacuum, B represents the vector of magnetic flux density, H is the vector of magnetic field intensity, and M represents the magnetization vector.In the proposed approach, the magnetic properties of magnetic soft materials and PMs are expressed by Equations (2) and (3), respectively:u is the supply voltage vector, R is the matrix of loop resistances, i is the vector of loop current, and Since most electrical devices are powered from a voltage source, the electromagnetic field equations must be supplemented with equations describing the current flow in the excitation circuit windings:In order to describe fluid dynamics, a phenomenological approach has been used. In this approach, the fluid is treated as a continuum, the properties of which are described as density ρ, dynamic viscosity ξ, and magnetic permeability μ ,21,30,33In the case of the studied brake, Equation (5) should be solved by taking into account the nonslip boundary conditions D [B in MRF for a one-dimensional (1D) model of the fluid is presented in p for p = tg(β) and B.In the elaborated field model for the rheological properties of an MR fluid, the equivalent dynamic viscosity of the fluid has been applied ,42,43. Ih fluids ,40,43. Aadient D ,43 and fB on fluid yield stress τ0 for a few selected types of MRFs is shown in B. It should also be highlighted that the response of the fluid rheological properties to a change in the magnetic field is fast and occurs in microseconds [The impact of the magnetic flux density oseconds ,4,9.In the proposed field model of an MR fluid, the equivalent value of the dynamic viscosity of the fluid can be expressed as ,43:(6a)ξ0(B) in Equation  is calculated on the basis of the vector distribution of magnetic flux density B, determined by solving an electromagnetic field model, i.e., Equations (1) and (4). The norms τ and the share rate tensor D, respectively, refs. [The yield stress τy, refs. ,42 may bA typical family of characteristics aT for the considered brake design is much smaller than the critical ac,T there are no conditions for the convective effect in the MRF. For this reason, the heat transfer problem can be simplified to temperature diffusion and can be expressed by the following equation assuming cylindrical symmetry [c.As mentioned above, the conductivity γ of ferromagnetic elements of the magnetic circuit and the magnetic permeability of material μ as well as the resistances of the windings and the rheological properties of the fluid depend on the temperature symmetry ,25,28:(9hp describes the heat sources resulting from the dissipation of (a) mechanical energy in the viscous fluid, (b) electrical energy in the winding and conductive elements of the transducer, and (c) mechanical energy in the seals and bearings. The heat sources in the studied HEMRFB can be calculated from the following formula [J are the friction torques, volumes of the seal and bearing, and current density.The symbol  formula ,33:(10)pnq at the boundary is proportional to the difference in the temperatures h represents the coefficient of the convection heat transfer, and Problem (9) must be solved by taking into account a natural boundary condition on the external surface of the considered MR brake ,42. In tbJ represents the inertia of the brake rotor and the load, frT represents the total braking torque generated by the brake bearings and seals, while inT represents the driving torque.In the performance analysis of the proposed HEMRFB, Equations (1), (4), (5) and (9) describing the electromagnetic fluid flow and thermal phenomena have to be solved together with the equation of brake dynamics. For the considered HEMRFB, the equation for the dynamics of movable elements can be expressed as follows: cT was calculated from the integral of the stress tensors along the closed surface s placed in the MR fluid and covering the rotor, using the formula:τeυ, τυ in the above formula describe, respectively, tangentially to the external surface s of the rotor, the stress in the fluid and the electromagnetic stress acting in the direction υ.The value of torque S, S′, and S″ are the coefficient matrices for the equations describing the magnetic, hydrodynamic, and thermodynamic field, respectively; φ, ϕ, and θ are the vectors of the nodal values φ, ϕ, and ϑ, respectively, p = d/dt, G is the matrix of conductances of elementary rings formed by the mesh, Mm is the vector of magnetomotive force in the regions with permanent magnets, wT is the matrix that transforms the potentials φ into flux linkages in the windings, G′ is the matrix whose elements depend on the dimensions of the elementary rings and fluid density ρ, G″ is the matrix whose elements depend on the dimensions of the elementary rings and heat capacity c, P is the vector of the nodal heat sources, H is the vector of boundary conditions, and K and F represent the coefficient matrices, which describe the heat transport to the surroundings of the brake [The equations of the presented field model of the MR brake with hybrid excitation are coupled through the viscosity function and time ,36,37. The brake ,28,42.,R i.e., the matrix describing the resistances of windings, the elements of conductance matrix ,G and the elements of matrix S in Equation (13) depend on temperature. Calculating the values of elements of matrices R and G, it is assumed that the winding resistance R(ϑ) and the conductivity γ(ϑ) of steel are obtained from the well-known relationsR20°C is the resistance of the winding at 20 °C, γ20°C is the conductivity of steel at 20 °C, and αR and αγ are the thermal coefficients of the resistivity of copper and steel, respectively [In the formulated problem, the elements of matrix αRϑ−20,1γϑ=γ20°C1ectively ,28.S can be treated as a “magnetic” stiffness matrix of elements that depend on the geometry of the applied mesh and magnetic permeability μ of materials. In the proposed approach, it is taken into account that the magnetic permeability of the applied materials is a function of the two physical quantities: material temperature ϑ and magnetic field intensity H. The value of μ of the material can be determined based on the family of B(H) curves measured at a given temperature ϑ. To calculate μ, these characteristics can be given in a tabular form. However, to minimize the calculation time, it is beneficial to introduce the analytical formulas of μ  that approximate the measured characteristics. The formulas approximating the influence of temperature and magnetic field intensity H on permeability should reproduce the phenomenon of losing the ferromagnetic properties of the material after reaching the Curie temperature ϑC. In such a case, the relative permeability should be equal to unity. The following expression was implemented in the proposed approach for calculating the magnetic permeability of the ferromagnetic materials [c1 and c2 were selected in such a way so that the curve relation presented in (18) reflected the measurement results as closely as possible.The matrix aterials ,44:(18)μk. When determining the elements of matrix S″, it is presumed that the abovementioned relation is calculated according to the following formula [k20°C represents the material thermal conductivity at 20 °C and χ is the thermal conductivity coefficient. The proposed model and developed algorithm assume that temperature influences the value of the thermal conductivity of materials  formula ,28:(19)kThe most convenient way, which takes into account the influence of temperature on the PM material properties, is to use a set of demagnetization characteristics determined for several temperatures. An example of a set of demagnetization characteristics provided for the applied material VACODYM HR 677 is shown in B on shear stress for fluid MRF 132LD are given in D on the equivalent viscosity ξz is shown in B and velocity of deformation D, can be approximated by means of the linear function:ξ is the temperature coefficient of viscosity changes and ξz  is the viscosity for the reference temperature ϑ0 and magnetic flux density B.Temperature also affects the rheological properties of an MR fluid, as confirmed by tests of fluids MRF 132LD and MRF 132AD performed at the Poznan University of Technology. The exemplary results of the test presenting the influence of temperature ϑ and magnetic flux density S′ and H, presented in Equation (14). In the elaborated model of coupled phenomena, the influence of temperature on the material heat capacity c and the influence of mechanical stress in magnetic materials on magnetic permeability μ are neglected.Equation (20) is used to calculate the elements of matrices In order to solve the equations describing the discussed field model of an MR transducer in the time domain, the authors applied the time-stepping method. The backward difference scheme was introduced for the approximation of the time derivatives in Equations (13)–(15).n denotes the current time step and Δt is the length of the time step.The following system of nonlinear algebraic matrix equations is obtained by time discretization:in,n = TinT(nt), c,n = TcT(nt), and fr,n = TfrT(nt).To solve the dynamics of the movable elements of the brake (11), the time derivatives were approximated using the following explicit formula :(24)JbαnFor the applied numerical scheme, the angular velocity ω of the rotor can be calculated as follows:c,nT in Equation (24) is calculated using expression (12). In the studied HEMRFB, the axial symmetry of the magnetic field distributions was assumed; therefore, the component Bυ of the magnetic flux density B is equal to zero and the electromagnetic component in (12) τeυ, resulting from the Maxwell stress tensor, is also equal to zero.The braking torque z reaches an infinite value in the regions where the share rate is zero m is the exponential growth parameter.The main problem in obtaining a numerical solution to the MR fluid flow field given in Equation (5) is the presence of a surface separating the shear and nonshear fluid regions . The locEquation a,b are rm = 100 as a value large enough to obtain accurate solutions [This approach provided a good approximation of the Bingham fluid properties for both low and high shear stresses τ. Extensive numerical experiments led to the determination of olutions ,20. Due olutions ,29,46,47The proposed field model of coupled phenomena and the elaborated algorithm for solving the equations of the formulated model were implemented in the form of a developed computer program written in the Object Pascal programming language. The developed tool allows for manual discretization of the considered transducer geometry as well as import of discretization meshes from the GiD environment . To solvThe designed brake contained magnetorheological fluids produced by Lord Corporation and marked with the symbol MRF 132AD. The external diameter of the elaborated brake was 250 mm. In the analysis of the MR brake, the influence of temperature on the electromagnetic and rheological material properties was taken into account. Moreover, the same mesh was used in the calculation of the electromagnetic and thermal fields. The paper analyzed the influence of mesh density on the results of the calculations. This density was gradually increased until a difference between two consecutively calculated values of currents or torques was observed. In addition, it was assumed that the delay values for which the fluid reacts to the changes in the magnetic field are neglected. I = 0 A. The calculations were performed for the rotational speed of the brake shaft equal to 475 rpm. The results of the calculations are given in I equal to 2.3 A. For this value of the current, the braking torque generated by the brake was equal to 2.8 Nm. In First, the elaborated authored program was applied to calculate the electromagnetic field, the velocity field of the fluid, and the braking torque for the current value in the winding T(I) of the considered brake, the relationship between the braking torque T and the exciting current I at a constant rotational speed was tested. The measurements were repeated for different values of rotational speed in both rotational directions of the rotor. It has been found that the direction of rotation does not have any influence on the torque value. When calculating the T(I) fr + Tc= T(I) characteristic, it was assumed that the component cT(I) is determined on the basis of the stress distribution in the MR fluid—see Equation (12). The component frT was obtained based on the measurements performed at the test stand. When determining the total braking torque frT produced by seals and bearings, the brake was not filled with an MR fluid. The comparison of the calculated and measured control characteristics for rated rotational speed is shown in I = 0 A. Good concordance between the calculations and measurements has been obtained.In order to determine the steady-state control characteristic Next, the transient states of the hybrid MR brake were investigated. The reaction time, determined during the process of switching off the supply voltage, was analyzed. It was assumed that before switching off the voltage, the current in the coil was equal to 2.3 A. The measured and calculated waveforms of the current and torque are shown in A heating test was carried out to define the effect of temperature on the brake and its parameters during a typical work cycle. In the investigations, a typical duty cycle of the elevator was mapped as 180 runs per hour with a 40% share of traveling time in the total cycle time . The cyca = 23 °C. The obtained temperature rises Δϑ = ϑ − ϑa of the brake subassemblies were less than 23 °C. The obtained increases in temperature are not dangerous to the fluid and permanent magnets. They can be dangerous if the ambient temperature increases.The temperature has an influence on the brake parameters. It has been observed that the braking torque in the “warm” state (110 Nm) is about 6% lower than the braking torque in the “cold” state (117 Nm). The decrease in the braking torque along with the increase in temperature is caused by (a) a decrease in fluid viscosity and (b) a decrease in the magnetic flux, generated by permanent magnets. The resistance of the winding in the ambient temperature was equal to 24 Ω. An increase in temperature resulted in a resistance increase of about 15%. The recorded and calculated curves of temperature increase in (a) the housing, (b) MR fluid, and (c) windings are shown in The paper presents and discusses a coupled field model of phenomena in a magnetorheological brake with hybrid excitation. An algorithm for solving model equations has been proposed. On the basis of the given authored algorithm, computer software has been developed and implemented. The carried-out analysis of the operation of the studied MR brake has considered the nonlinear, rheological, magnetic, and thermal properties of the used materials, eddy currents induced in massive conductive elements, fluid dynamics, and mechanical equilibrium equations. The influence of temperature on the electromagnetic and rheological properties of the used materials has been taken into account. The conducted comparative analysis between the simulation results and measurements of the brake performance shows good concordance and confirms the validity of the model.The presented field model and the elaborated software enable a more detailed analysis of the phenomena occurring in a brake with an MR fluid than in classical analytical models. According to the authors, the approach proposed in this paper can be helpful in the design and/or optimization process of other types of electromagnetic transducers in which the working medium is an MR fluid (MRF transducers), such as clutches or dampers. Nevertheless, it should be noted that due to the relatively high computational complexity of coupled field analysis , application of simpler lumped parameter models in the initial stages’ design and optimization calculations of MRF transducers may be convenient. The effectiveness of similar strategies for the design of electromagnetic transducers has been discussed among others in , where aThe experimental and simulation results obtained confirm the suitability of the proposed brake for use in elevators . However, it should be stated that the development of this technology also depends on the “durability” of an MRF. Due to high-reliability requirements, the insufficient durability of rheological parameters may limit the implementation of this technology with time. Another important aspect that needs to be studied before implementation is the analysis of the robustness of the proposed HEMRFB.The design solutions for the research results presented in the paper have been described in a patent Piech, Z.; Szelag, W. Elevator Brake with Magneto-Rheological Fluid. US8631917B2, 21 January 2014.