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Objective: This study investigated (i) factors predicting the seeking and sharing of vaccinerelated information, and (ii) the effect of an accuracy-sensitisation prime on sharing intentions. Design:This was a preregistered online survey with 213 participants. Participants were randomly assigned to an intervention group (who were exposed to an accuracy-sensitisation prime) or a control group. Design: This was a preregistered online survey with 213 participants. Participants were randomly assigned to an intervention group (who were exposed to an accuracy-sensitisation prime) or a control group. Main Outcome Measures: Measures included decision-making style, COVID-19 anxiety, and percentages of pro and anti-vaccine friends. We also measured preferences to seek pro or anti-vaccine-related information and sharing intentions with respect to this information. Results: Compared with those seeking both pro and anti-vaccine information, participants seeking only pro-vaccine information had lower hypervigilance and buck-passing and higher COVID-19 anxiety. The likelihood of sharing anti-vaccine information was positively predicted by the percentage of one's anti-vaccine friends, the size of one's social network, and conservative political orientation. Conversely, the likelihood of sharing pro-vaccine information was positively predicted by the percentage of one's pro-vaccine friends, and liberal political orientation. Participants sensitised to accuracy were significantly more likely to share provaccine information; however, accuracy-sensitisation had no effect on anti-vaccine information sharing. Conclusions: Individuals who seek anti-vaccine information have a tendency towards disorganised and impulsive decision-making. Accuracy-sensitisation may prime people to internalise a norm promoting truth-sharing. [ABSTRACT FROM AUTHOR]

This study examined factors influencing students’ intention to use ChatGPT using UTAUT2 model. The cross-sectional study is based on responses collected from 578 students selected through convenience sampling at a university in Nepal through a structured questionnaire. Using PLS-SEM, the study found that habit (β = 0.315, p

The long-awaited introduction of the AI Act, notwithstanding its originality, does not introduce any regulation outside the existing framework. It supplements the safeguards provided in numerous sectors of the EU legislation, inter alia, consumer protection. An examination of the basic EU law along with national legislation of the most influential legal orders, i.e. the French and German one, and model rules of the Draft Common Frame of Reference (DCFR) confirms that the new AI Act sheds light on pre-existing vague legal concepts. In this respect, this novel piece of legislation promotes a better understanding of traditional notions of law applicable to the modern digital reality without introducing totally new rules. Accordingly, certainty of law is reinforced where consumer protection had languished, not because of legislative shortage, but for facts and situations described as necessary conditions of certain rights were contested on the basis of contrary possible interpretations of decisive terms. Ultimately, the very importance of the AI act regarding consumer protection lies not in the introduction of new rights and obligations, but in a multiple practical assistance to the implementation of existing rules adjusting thus the traditional legal concepts with technological development beyond their original scope.

On most online platforms, just about anyone can disseminate plastic surgery (PS) content regardless of their educational or professional background. This study examines the general public's perceptions of the accuracy of online PS content and the factors that contribute to the discernment of credible information. The Amazon Mechanical Turk crowdsourcing platform was used to survey adults in the United States. The survey assessed respondent demographics, health literacy (HL), and perceptions of online PS content accuracy. T -tests, Chi-square tests, and post hoc analyses with Bonferroni corrections assessed differences between HL groups. Multivariate linear regressions assessed associations between sociodemographic variables and perceptions of online content. In total, 428 (92.0%) of 465 complete responses were analyzed. The median age of respondents was 32 y (interquartile range: 29-40). Online sources were predominantly perceived to have a high degree of accuracy, with mean scores of various platforms ranging from 3.8 to 4.5 (1 = not accurate at all; 5 = extremely accurate). The low HL group perceived social media sites and review sites to be more accurate than the high HL respondents, particularly for Reddit (P = 0.004), Pinterest (P = 0.040), and Snapchat (P = 0.002). There is a concerning relationship between low HL and the perceptions of the accuracy of online PS sources. This study underscores the need for education campaigns, the development of trustworthy online resources, and initiatives to improve HL. By fostering a more informed public, individuals seeking PS can make better informed decisions. • The general public considers social media platforms to have high degrees of accuracy. • Respondents with low health literacy perceived social media and review sites to be more accurate compared to the high health literacy group. • The findings underscore the need for public education campaigns to promote the dissemination of accurate information and initiatives to improve health literacy. [ABSTRACT FROM AUTHOR]

The long-awaited introduction of the AI Act, notwithstanding its originality, does not introduce any regulation outside the existing framework. It supplements the safeguards provided in numerous sectors of the EU legislation, inter alia, consumer protection. An examination of the basic EU law along with national legislation of the most influential legal orders, i.e. the French and German one, and model rules of the Draft Common Frame of Reference (DCFR) confirms that the new AI Act sheds light on pre-existing vague legal concepts. In this respect, this novel piece of legislation promotes a better understanding of traditional notions of law applicable to the modern digital reality without introducing totally new rules. Accordingly, certainty of law is reinforced where consumer protection had languished, not because of legislative shortage, but for facts and situations described as necessary conditions of certain rights were contested on the basis of contrary possible interpretations of decisive terms. Ultimately, the very importance of the AI act regarding consumer protection lies not in the introduction of new rights and obligations, but in a multiple practical assistance to the implementation of existing rules adjusting thus the traditional legal concepts with technological development beyond their original scope. [ABSTRACT FROM AUTHOR]

This study examines the roles of sports fan identity and political affiliation on the perceived accuracy of mediated information during a global pandemic, which adversely affected the sports world through national and international league stoppages and newly developed health and safety protocols. A 4 (news source) × 3 (pandemic term) experimental design was incorporated. 420 subjects read one of twelve factually accurate sports articles but with differing media outlets (MSNBC, Fox News, Associated Press, Bleacher Report) and pandemic terminology of differing anti-Asian sentiments (COVID-19, Chinese coronavirus, Wuhan Virus). Results demonstrated that manipulation of media source and pandemic term did not influence perceived information accuracy, but that one's social identification did alter results. Shifts in media accuracy depended on whether facts were incongruent with one's identity, while xenophobic language was more likely to be accepted if the information came from an acceptable and parallel media source. Ramifications for journalism ethics and media literacy are offered, highlighting the increased role one's identity has in information processing in modern media. [ABSTRACT FROM AUTHOR]

This study explored the potential of ChatGPT in the search for reliable references. Results showed that the reliability of ChatGPT's references vary across different source types. For journal articles, they were all fabricated and not compliant with APA 7 format. Webpages did not match actual existing sites. However, for books, the generated references correctly corresponded to real, existing ones. In the case of journal websites, the links within the responses were functional. Although this exploration gained interesting insights, researchers are strongly recommended not to depend on ChatGPT for references due to accuracy issues and must undertake manual, scholarly searches. [ABSTRACT FROM AUTHOR]

Employee burnout is considered a serious problem in today’s organizations, having severe repercussions both on individual and operational levels. A large number of studies have been conducted to identify antecedents and consequences of burnout but were mostly carried out in medical and other helping professions. This research aims to explore the burnout of employees working in Croatian companies by developing a multidimensional model that explores the influence of three elements that are considered typical features of today’s modern, post-pandemic workplace: information overload, demands at work, and multitasking. In addition, it observes the influence of burnout on employee decision-making style and the moderating effects of information accuracy and time pressure on the burnout-decision-making relationship. A total of 567 employees working in various industries and carrying out different professions completed an online survey, and linear regression analysis was applied to analyze the data. The results confirmed the direct positive effect of information overload and demands at work on burnout and the direct positive effect of burnout on poor decision-making style. This study is one of the first studies conducted in Croatia on employees in the business sector, so it contributes to the field with important theoretical implications and practical and managerial recommendations. [ABSTRACT FROM AUTHOR]

Abstract Purpose This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. The objective of this study is to present an overview of the literature on how ChatGPT handles information about sports trauma, considering both its strengths and limitations. Methods A review method is used in this study. Well-known online databases such as PubMed, ScienceDirect, Springer and Google Scholar were searched for the relevant studies. In addition, ChatGPT application was accessed to provide the concise information on the research topic. Results Search strategy resulted in 30 articles on the topic. Among them only seven studies revealed the potential applications of ChatGPT in sports. The other five studies presented the current status on ChatGPT and sports trauma. The results show that ChatGPT generates information on several types of sports trauma that align with the published literature. However, some limitations of ChatGPT are identified such as its tendency to provide general information about sprains and lack of updated statistics on sports trauma. This study also identified some serious concerns such ethical considerations, data privacy and security regarding the ChatGPT application in sports industry. Conclusion Despite having some limitations, the ChatGPT application has potential to be used in healthcare, and particularly in sports trauma. The implications of this study guide scholars for the development of enhanced AI systems, which are tailored to redress the challenges of sports trauma.

Abstract Objective: This systematic review aimed to summarise the level of quality and accuracy of nutrition-related information on websites and social media and determine if quality and accuracy varied between websites and social media or publishers of information. Design: This systematic review was registered with PROSPERO (CRD42021224277). CINAHL, MEDLINE, Embase, Global Health and Academic Search Complete were systematically searched on 15 January 2021 to identify content analysis studies, published in English after 1989, that evaluated the quality and/or accuracy of nutrition-related information published on websites or social media. A coding framework was used to classify studies’ findings about information quality and/or accuracy as poor, good, moderate or varied. The Academy of Nutrition and Dietetics Quality Criteria Checklist was used to assess the risk of bias. Setting: N/A. Participants: N/A. Results: From 10 482 articles retrieved, sixty-four were included. Most studies evaluated information from websites (n 53, 82·8 %). Similar numbers of studies assessed quality (n 41, 64·1 %) and accuracy (n 47, 73·4 %). Almost half of the studies reported that quality (n 20, 48·8 %) or accuracy (n 23, 48·9 %) was low. Quality and accuracy of information were similar on social media and websites, however, varied between information publishers. High risk of bias in sample selection and quality or accuracy evaluations was a common limitation. Conclusion: Online nutrition-related information is often inaccurate and of low quality. Consumers seeking information online are at risk of being misinformed. More action is needed to improve the public’s eHealth and media literacy and the reliability of online nutrition-related information.

Purpose: This paper is focused on the role of ChatGPT an artificial intelligence (AI) language model in the area of sports trauma. Sports trauma represents some significant concerns due to its prevalence and impacts. The objective of this study is to present an overview of the literature on how ChatGPT handles information about sports trauma, considering both its strengths and limitations. Methods: A review method is used in this study. Well-known online databases such as PubMed, ScienceDirect, Springer and Google Scholar were searched for the relevant studies. In addition, ChatGPT application was accessed to provide the concise information on the research topic. Results: Search strategy resulted in 30 articles on the topic. Among them only seven studies revealed the potential applications of ChatGPT in sports. The other five studies presented the current status on ChatGPT and sports trauma. The results show that ChatGPT generates information on several types of sports trauma that align with the published literature. However, some limitations of ChatGPT are identified such as its tendency to provide general information about sprains and lack of updated statistics on sports trauma. This study also identified some serious concerns such ethical considerations, data privacy and security regarding the ChatGPT application in sports industry. Conclusion: Despite having some limitations, the ChatGPT application has potential to be used in healthcare, and particularly in sports trauma. The implications of this study guide scholars for the development of enhanced AI systems, which are tailored to redress the challenges of sports trauma. [ABSTRACT FROM AUTHOR]

The article examines the problem of ensuring the reliability of information in an integrated report. The need for sustainable development has led to the emergence of integrated accounting and analytical systems that combine financial and non-financial information to support transparency of information and trust in the enterprise. Integrated accounting and analytical systems can facilitate processes such as planning, forecasting, analysis, and task execution. Integrated reporting is a forward-looking report that presents strategy, management, performance indicators, development prospects and business risks, and requires the creation of a quality internal audit service to provide control of actions and technical support for the analysis and consolidation of information. The requests of information users require transparency and reliability from integrated reporting, therefore, to ensure the fulfillment of these requirements, the enterprise must use special mechanisms and procedures, an internal audit of integrated reporting in particular. Ensuring reliability can be implemented through both external and internal audits. Companies are working to provide external guarantees on the quality of integrated reports through external independent audits and internal audits, which have the effect of reducing information asymmetry and facilitating risk assessment. Internal audit helps ensure the accuracy and reliability of data in integrated reporting, taking on a strategic role in preparing the company for the implementation and use of this report, which helps to ensure a quality level of information confirmation and ensure the trust of interested parties.

Objective: This systematic review aimed to summarise the level of quality and accuracy of nutrition-related information on websites and social media and determine if quality and accuracy varied between websites and social media or publishers of information. Design: This systematic review was registered with PROSPERO (CRD42021224277). CINAHL, MEDLINE, Embase, Global Health and Academic Search Complete were systematically searched on 15 January 2021 to identify content analysis studies, published in English after 1989, that evaluated the quality and/or accuracy of nutrition-related information published on websites or social media. A coding framework was used to classify studies' findings about information quality and/or accuracy as poor, good, moderate or varied. The Academy of Nutrition and Dietetics Quality Criteria Checklist was used to assess the risk of bias. Setting: N/A. Participants: N/A. Results: From 10 482 articles retrieved, sixty-four were included. Most studies evaluated information from websites (n 53, 82·8 %). Similar numbers of studies assessed quality (n 41, 64·1 %) and accuracy (n 47, 73·4 %). Almost half of the studies reported that quality (n 20, 48·8 %) or accuracy (n 23, 48·9 %) was low. Quality and accuracy of information were similar on social media and websites, however, varied between information publishers. High risk of bias in sample selection and quality or accuracy evaluations was a common limitation. Conclusion: Online nutrition-related information is often inaccurate and of low quality. Consumers seeking information online are at risk of being misinformed. More action is needed to improve the public's eHealth and media literacy and the reliability of online nutrition-related information. [ABSTRACT FROM AUTHOR]

Meta‐information is information about information that can be used as cues to guide judgments and decisions. Three types of meta‐information that are routinely used in intelligence analysis are source reliability, information credibility, and classification level. The first two cues are intended to speak to information quality (in particular, the probability that the information is accurate), and classification level is intended to describe the information's security sensitivity. Two experiments involving professional intelligence analysts (N = 25 and 27, respectively) manipulated meta‐information in a 6 (source reliability) × 6 (information credibility) × 2 (classification) repeated‐measures design. Ten additional items were retested to measure intra‐individual reliability. Analysts judged the probability of information accuracy based on its meta‐informational profile. In both experiments, the judged probability of information accuracy was sensitive to ordinal position on the scales and the directionality of linguistic terms used to anchor the levels of the two scales. Directionality led analysts to group the first three levels of each scale in a positive group and the fourth and fifth levels in a negative group, with the neutral term "cannot be judged" falling between these groups. Critically, as reliability and credibility cue inconsistency increased, there was a corresponding decrease in intra‐analyst reliability, interanalyst agreement, and effective cue utilization. Neither experiment found a significant effect of classification on probability judgments. [ABSTRACT FROM AUTHOR]

As crowdsourced user-generated content becomes an important source of data for organizations, a pressing question is how to ensure that data contributed by ordinary people outside of traditional organizational boundaries is of suitable quality to be useful for both known and unanticipated purposes. This research examines the impact of different information quality management strategies, and corresponding data collection design choices, on key dimensions of information quality in crowdsourced user-generated content. We conceptualize a contributor-centric information quality management approach focusing on instance-based data collection. We contrast it with the traditional consumer-centric fitness-for-use conceptualization of information quality that emphasizes class-based data collection. We present laboratory and field experiments conducted in a citizen science domain that demonstrate trade-offs between the quality dimensions of accuracy, completeness (including discoveries), and precision between the two information management approaches and their corresponding data collection designs. Specifically, we show that instance-based data collection results in higher accuracy, dataset completeness, and number of discoveries, but this comes at the expense of lower precision. We further validate the practical value of the instance-based approach by conducting an applicability check with potential data consumers (scientists, in our context of citizen science). In a follow-up study, we show, using human experts and supervised machine learning techniques, that substantial precision gains on instance-based data can be achieved with post-processing. We conclude by discussing the benefits and limitations of different information quality and data collection design choices for information quality in crowdsourced user-generated content. [ABSTRACT FROM AUTHOR]

Vernal keratoconjunctivitis, Patient information, Information accuracy, ChatGPT Keywords: Vernal keratoconjunctivitis; ChatGPT; Patient information; Information accuracy EN Vernal keratoconjunctivitis ChatGPT Patient information Information accuracy 3041 3043 3 10/04/23 20231001 NES 231001 Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s00417-023-06078-1. [Extracted from the article]

An exponential growth in the usage of the internet and e-commerce has led to the creation of many e-commerce retail malls. In addition to promotional schemes and prices, these e-commerce retailers use online information quality and website design to differentiate themselves from other retail players. Therefore, the objective of this research is to investigate how e-commerce information quality (information trust and information accuracy) and website design influence customer satisfaction, and how customer satisfaction subsequently influences user shopping loyalty in South Korea. Using an online survey, data were obtained from 600 users of e-commerce shopping malls in Korea. Results from structural equation modeling showed that information trust, information accuracy and website design had a positive influence on customer satisfaction, which subsequently led to user shopping loyalty. This paper has useful implications for e-commerce retail malls. One important implication is that e-commerce retailers must endeavor to provide trustworthy information, accurate information and a comfortable website design to attract and retain customers. [ABSTRACT FROM AUTHOR]

Background: The COVID-19 pandemic has triggered stigmatic attitudes against health care workers. Some forms of social media may play a role in disseminating stigmatizing messages. Objective: We aimed to investigate the association between COVID-19 information sources and stigma against health care workers among college students during the pandemic. Methods: A cross-sectional, observational study was conducted using a web-based platform in the Tohoku region of Japan. College students aged ≥20 years were asked to complete the questionnaire between August 18 and October 31, 2020. Stigma against health care workers was evaluated using a modified Japanese version of the Social Distance Scale. Participants were also asked to rate their perceived vulnerability to infection using the Japanese version of the Perceived Vulnerability to Disease scale. Results: A total of 281 students from 8 colleges completed the web-based survey. There were 139 (49.5%) participants who used Twitter, 187 (66.5%) who used news websites, and 46 (16.4%) who used the websites of public health agencies as COVID-19 information sources. After adjusting for age, sex, department, and Perceived Vulnerability to Disease scores, the level of stigma did not differ between students who used Twitter and those who did not. Students who used the websites of public health agencies showed a significantly less stigmatic attitude than those who did not. Conclusions: Fact-checking and directing visitors to credible information sources from public health agencies may have prevented the formation of stigmatic attitudes toward health care workers. An effective strategy to enable easy access to information provided by public agencies should be integrated into widespread web-based platforms. [ABSTRACT FROM AUTHOR]

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Large organizations, including listed businesses, financial service providers as well as public services entities are increasingly disclosing information on their environmental, social and governance (ESG) issues through corporate websites or via social media. Therefore, this research uses valid measures from the Elaboration Likelihood Model (ELM) to explore the individuals' attitudes toward online corporate social responsibility (CSR) communications. The data were gathered from a structured questionnaire among three hundred ninety‐two respondents (n = 392). A structural equations modeling partial least squares (SEM‐PLS 3) approach was used to analyze the data. The findings revealed that the timeliness, relevance and accuracy of information as well as the source expertise were highly significant antecedents that were affecting the research participants' attitudes toward CSR communications. This contribution implies that there is scope for content curators to publish quality online information on their business activities to improve their trustworthiness and positive credentials among stakeholders. [ABSTRACT FROM AUTHOR]

In recent years, misinformation sharing has become the focus of public debate and academic research. We aim to explore whether individuals prefer to share accurate information or not, and discover what factors increase people's preferences for sharing accurate information. Combining behavioral economics experiments and psychology experiments, we construct "an information search-information sharing-information feedback experiment" to examine individuals' behavior of sharing accurate information and its influencing factors. A total of 210 students are recruited for the laboratory experiment. Our results show that when individuals can control the accuracy of the information they obtain through their efforts, they are more willing to share accurate information with others. We also find that positive feedback from information receivers can promote the accuracy of information shared by individuals, and this effect works through reciprocity norms. Individuals with higher reciprocity are more willing to share accurate information, especially in the treatment with the role of reciprocity norms enhanced by feedback. These findings indicate that individuals who are willing to obtain accurate information prefer to share information, and information feedback can enhance this preference through reciprocity norms. This study captures individuals' behavior and preference characteristics with regard to the accuracy of the information they share in the era of highly developed network interaction. [ABSTRACT FROM AUTHOR]

In this paper, equilibrium strategies and optimal balking strategies of customers in a constant retrial queue with multiple vacations and the N-policy under two information levels, respectively, are investigated. We assume that there is no waiting area in front of the server and an arriving customer is served immediately if the server is idle; otherwise (the server is either busy or on a vacation) it has to leave the system to join a virtual retrial orbit waiting for retrials according to the FCFS rules. After a service completion, if the system is not empty, the server becomes idle, available for serving the next customer, either a new arrival or a retried customer from the virtual retrial orbit; otherwise (if the system is empty), the server starts a vacation. Upon the completion of a vacation, the server is reactivated only if it finds at least N customers in the virtual orbit; otherwise, the server continues another vacation. We study this model at two levels of information, respectively. For each level of information, we obtain both equilibrium and optimal balking strategies of customers, and make corresponding numerical comparisons. Through Particle Swarm Optimization (PSO) algorithm, we explore the impact of parameters on the equilibrium and social optimal thresholds, and obtain the trend in changes, as a function of system parameters, for the optimal social welfare, which provides guiding significance for social planners. Finally, by comparing the social welfare under two information levels, we find that whether the system information should be disclosed to customers depends on how to maintain the growth of social welfare. [ABSTRACT FROM AUTHOR]

In this paper, the methods of determination of various information criteria in reconnaissance data processing have been considered. The methods of determination of a reliability of the reconnaissance information source, of quantitative assessment and analysis of properties of a reconnaissance source have been offered. These methods can be applied in combat front zone for reconnaissance data gathering and processing, for assessment of data accuracy The method of quantitative assessment and analysis of reconnaissance data accuracy and assemble has been offered in consideration of the entropy of reconnaissance data. This method can be applied for reconnaissance data processing. The problem of information value loss in reconnaissance data processing has been considered. The calculation method of reconnaissance information accuracy has been considered in one example. These methods will increase the effectiveness and rationality of using of the reconnaissance forces and means.

Teleworking has rapidly grown and become the prevailing work mode. Married teleworkers may experience increased work-family conflict, while single teleworkers may experience loneliness. This study aims to investigate how teleworkers' information reception quality (Time 1) influences their work-family conflict (Time 2), loneliness (Time 2), and well-being (Time 3) from the perspective of the job demands-resources model. The data were collected through a three-point survey involving 462 participants working from home in Taiwan. The results indicate a negative association between information accuracy and work-family conflict. Work-family conflict, in turn, mediates the relationship between information accuracy and well-being. Information timeliness, as the moderator, weakens the connection between information accuracy and work-family conflict. Additionally, information timeliness is negatively related to loneliness. Loneliness mediates the relationship between information timeliness and well-being. Information accuracy, as the moderator, strengthens the association between information timeliness and loneliness. No impact of information on family-work conflict was observed. Our findings suggest that organizations that convey precise and punctual messages to employees have distinct routes for reducing work-family interference and loneliness and ultimately improving employees' well-being in remote work contexts. This study contributes to the wider telework literature through information experience. • This study explores how teleworkers' information reception affects work-family conflict, loneliness, and well-being. • Accurate information reduces work-family conflict; timely information lessens loneliness. • Work-family conflict mediates accuracy's impact on well-being; loneliness mediates timeliness's impact on well-being. • Timeliness weakens accuracy's impact on work-family conflict; accuracy strengthens timeliness's effect on loneliness. [ABSTRACT FROM AUTHOR]

Previous literature shows that managers, evaluating employees, insufficiently differentiate between strong and weak performers, which causes disadvantageous organizational outcomes. Bol et al. (Acc Organ Soc 51:64–73, 2016) demonstrate in an independent bonuses context that when these managers can base their evaluations on accurate information, they differentiate more when allocating bonuses, but only when evaluation outcomes are transparent. Our experiment replicates and extends Bol et al. (2016) in a fixed bonus pool context. We investigate the effects of information accuracy and whether managers get the opportunity to write a justification to their different employees when making their bonus allocations as an alternative way to create transparency. We hypothesize and find that justification increases managers' differentiation in bonus allocations, but only—as in Bol et al. (2016)—when performance information accuracy is high. With a path analysis we disentangle the underlying process: we find that justification increases managers' expectations that employees will perceive the differentiation in the bonus allocations as fair, especially when information accuracy is high. Finally, such managers' expectations are positively related to the degree to which they differentiate in their bonus allocations. [ABSTRACT FROM AUTHOR]

This research interrogates the discourses that frame our understanding of deepfakes and how they are situated in everyday public conversation. It does so through a qualitative analysis of popular news and magazine outlets. This project analyzes themes in discourse that range from individual threat to societal collapse. This article argues how the deepfake problem discursively framed impacts the solutions proposed for stemming the prevalence of deepfake videos online. That is, if fake videos are framed as a technical problem, solutions will likely involve new systems and tools. If fake videos are framed as a social, cultural, or as an ethical problem, solutions needed will be legal or behavioral ones. As a conclusion, this article suggests that a singular solution is inadequate because of the highly interrelated technical, social, and cultural worlds, in which we live today. [ABSTRACT FROM AUTHOR]

Background: Artificial intelligence (AI) chatbots, such as ChatGPT-4, have shown immense potential for application across various aspects of medicine, including medical education, clinical practice, and research., Objective: This study aimed to evaluate the performance of ChatGPT-4 in the 2023 Taiwan Audiologist Qualification Examination, thereby preliminarily exploring the potential utility of AI chatbots in the fields of audiology and hearing care services., Methods: ChatGPT-4 was tasked to provide answers and reasoning for the 2023 Taiwan Audiologist Qualification Examination. The examination encompassed six subjects: (1) basic auditory science, (2) behavioral audiology, (3) electrophysiological audiology, (4) principles and practice of hearing devices, (5) health and rehabilitation of the auditory and balance systems, and (6) auditory and speech communication disorders (including professional ethics). Each subject included 50 multiple-choice questions, with the exception of behavioral audiology, which had 49 questions, amounting to a total of 299 questions., Results: The correct answer rates across the 6 subjects were as follows: 88% for basic auditory science, 63% for behavioral audiology, 58% for electrophysiological audiology, 72% for principles and practice of hearing devices, 80% for health and rehabilitation of the auditory and balance systems, and 86% for auditory and speech communication disorders (including professional ethics). The overall accuracy rate for the 299 questions was 75%, which surpasses the examination's passing criteria of an average 60% accuracy rate across all subjects. A comprehensive review of ChatGPT-4's responses indicated that incorrect answers were predominantly due to information errors., Conclusions: ChatGPT-4 demonstrated a robust performance in the Taiwan Audiologist Qualification Examination, showcasing effective logical reasoning skills. Our results suggest that with enhanced information accuracy, ChatGPT-4's performance could be further improved. This study indicates significant potential for the application of AI chatbots in audiology and hearing care services., (© Shangqiguo Wang, Changgeng Mo, Yuan Chen, Xiaolu Dai, Huiyi Wang, Xiaoli Shen. Originally published in JMIR Medical Education (https://mededu.jmir.org).)

In this paper, the methods of determination of various information criteria in reconnaissance data processing have been considered. The methods of determination of a reliability of the reconnaissance information source, of quantitative assessment and analysis of properties of a reconnaissance source have been offered. These methods can be applied in combat front zone for reconnaissance data gathering and processing, for assessment of data accuracy The method of quantitative assessment and analysis of reconnaissance data accuracy and assemble has been offered in consideration of the entropy of reconnaissance data. This method can be applied for reconnaissance data processing. The problem of information value loss in reconnaissance data processing has been considered. The calculation method of reconnaissance information accuracy has been considered in one example. These methods will increase the effectiveness and rationality of using of the reconnaissance forces and means. [ABSTRACT FROM AUTHOR]

Successful transport-on-demand (TOD) requires having sufficient capacity in the right location to meet demand when it occurs. Consumer and recovery vehicle locations are variable, and the vehicle recovery service is contracted out in the service supply chain. This research aims to identify how different variables/factors influence backlogs during busy periods and service performance. A case study of a vehicle recovery company was undertaken using observation and analysis of historical data to map the process. Discrete event simulation (DES) was used to model several processes to evaluate the operational impact of changes. We find that ensuring complete and accurate information transmission over the chain supports the TOD service by enhancing the ‘allocation’ activity of the dispatch center staff; i.e., pairing vehicles to consumer requirements. Simple changes to how information is collected, shared, and used in the service supply chain can significantly reduce the percentage of jobs taking more than a given time.

• The dual-purpose manufacturer can enable the retailer to proactively share information. • Information sharing can change the profit crisis of becoming a dual-purpose manufacturer. • The dual-purpose manufacturer in the market can promote win–win results (namely, benefiting itself and society) While the information issues among for-profit firms are well known, the extent to which the presence in the market of dual-purpose manufacturers, defined as companies that focus on social welfare as well as their own interests, affects the information strategies of retailers is unclear. A better understanding of this relationship could shift the thinking on the disadvantages of the dual-purpose firm model. This study investigates how a retailer's information strategy may differ for a for-profit manufacturer compared with a dual-purpose one. By analyzing an established mathematical model, the results indicate that by sharing information, a retailer can make a dual-purpose manufacturer more profitable than a for-profit manufacturer. This may occur when the retailer proactively shares market information with the dual-purpose manufacturer and when the dual-purpose manufacturer uses an information compensation fee lower than that for the for-profit manufacturer to incentivize the retailer to share such information. Further, both social welfare and the consumer surplus are higher in the former case than in the latter, implying that the presence of a dual-purpose manufacturer in the market can promote win/win results by benefiting both itself and society. This study's findings enrich theories of information sharing and dual-purpose enterprises as well as suggest that information sharing is a useful management tool for practitioners to fully realize the development potential of dual-purpose enterprises. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) can significantly enhance various aspects of today’s electric power grid infrastructures for making reliable, efficient, and safe next-generation Smart Grids (SGs). However, harsh and complex power grid infrastructures and environments reduce the accuracy of the information propagating through IoT platforms. In particularly, information is corrupted due to the measurement errors, quantization errors, and transmission errors. This leads to major system failures and instabilities in power grids. Redundant information measurements and retransmissions are traditionally used to eliminate the errors in noisy communication networks. However, these techniques consume excessive resources such as energy and channel capacity and increase network latency. Therefore, we propose a novel statistical information fusion method not only for structural chain and tree-based sensor networks, but also for unstructured bidirectional graph noisy wireless sensor networks in SG environments. We evaluate the accuracy, energy savings, fusion complexity, and latency of the proposed method by comparing the said parameters with several distributed estimation algorithms using extensive simulations proposing it for several SG applications. Results prove that the overall performance of the proposed method outperforms other fusion techniques for all considered networks. Under Smart Grid communication environments, the proposed method guarantees for best performance in all fusion accuracy, complexity and energy consumption. Analytical upper bounds for the variance of the final aggregated value at the sink node for structured networks are also derived by considering all major errors.

Credit rating inflation is a prevalent issue in financial markets. Existing studies have attributed a cause of inflated rating to credit rating agencies’ biased conduct for their own benefits. In this paper, we propose a performance-based payment mechanism which can be used to align the incentives between the issuers seeking ratings and the rating agencies. Under the proposed mechanism, the issuer who brings in a risky project for rating can specify the level of information to be obtained by the rating agency; whereas, the rating agency can choose whether to report the acquired information truthfully. After the rating has been announced and the investment decision has been made, the project return is shared between the issuer and the rating agency according to the predetermined terms. We show that as long as the issuer carries a sufficiently large portion of the project return, the credit rating agency will have no incentive to inflate ratings. As a result, the accuracy of the rating as well as the expected return from the project can be significantly improved. [ABSTRACT FROM AUTHOR]

Agro-food logistics is increasingly challenged to ensure that a wide variety of high-quality products are always available at retail stores. This paper discusses high-density logistics issues caused by more frequent and smaller orders from retailers. Through a case study of the distribution process in a Dutch floricultural supply chain, we demonstrate that using inbound and outbound information flows to plan daily warehouse operations improves the logistics performance. A discrete-event simulation and a simulation-based scheduling algorithm are used as decision-support models to assess the value of information. The results indicate that the higher the density of logistics process, the higher the value of the information. Future research will investigate different uses of information as more types of information become available in the agro-food sector supply chains. [ABSTRACT FROM AUTHOR]

Different from conventional networks, DTN has several unique characteristics, such as node mobility, loose connectivity, and delay tolerability, etc. As mobile devices have become indispensable in daily life, there emerges a new interesting problem, which is how to take advantage of the portable and powerful facilities to share resources and information. The prevailing approach to process those queries is to use flooding methods because of their quick response and easy maintenance. However, this kind of approaches wastes a huge amount of communication bandwidth and battery power of mobile devices. To tackle this problem, an intelligence accuracy（IA） scheme was introduced to improve network query success rate. The IA scheme mimics natural behavior of human social networking features to promote efficiency of information collection. Experimental results show that the efficiency and effectiveness of the IA approach are as well as its scalability in a volatile environment.

Background: Mental health problems are recognized as a pressing public health issue, and an increasing number of individuals are turning to online communities for mental health to search for information and support. Although these virtual platforms have the potential to provide emotional support and access to anecdotal experiences, they can also present users with large amounts of potentially inaccurate information. Despite the importance of this issue, limited research has been conducted, especially on the differences that might emerge due to the type of content moderation of online communities: peer-led or expert-led., Objective: We aim to fill this gap by examining the prevalence, the communicative context, and the persistence of mental health misinformation on Facebook online communities for mental health, with a focus on understanding the mechanisms that enable effective correction of inaccurate information and differences between expert-led and peer-led groups., Methods: We conducted a content analysis of 1534 statements (from 144 threads) in 2 Italian-speaking Facebook groups., Results: The study found that an alarming number of comments (26.1%) contained medically inaccurate information. Furthermore, nearly 60% of the threads presented at least one misinformation statement without any correction attempt. Moderators were more likely to correct misinformation than members; however, they were not immune to posting content containing misinformation, which was an unexpected finding. Discussions about aspects of treatment (including side effects or treatment interruption) significantly increased the probability of encountering misinformation. Additionally, the study found that misinformation produced in the comments of a thread, rather than as the first post, had a lower probability of being corrected, particularly in peer-led communities., Conclusions: The high prevalence of misinformation in online communities, particularly when left uncorrected, underscores the importance of conducting additional research to identify effective mechanisms to prevent its spread. This is especially important given the study's finding that misinformation tends to be more prevalent around specific "loci" of discussion that, once identified, can serve as a starting point to develop strategies for preventing and correcting misinformation within them., (©Nicole Bizzotto, Peter Johannes Schulz, Gert-Jan de Bruijn. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 18.09.2023.)