Unreliable Sources Research Articles

Development of a top-lit-up-draft biomass gasifier as a sustainable heat source for effective drying of plantain slices in a cabinet dryer

This paper explored the development of a top-lit-up-draft biomass gasifier as a sustainable heat energy alternative to the traditional sun drying and the costly, unreliable heat energy sources such as grid-electricity and petrochemical fuels commonly used for cabinet dryers, especially in developing countries like Nigeria. The gasifier utilized the principle of top-lit-updraft biomass gasification system to thermochemically converts agricultural residues into clean heat energy. The designed gasifier has reactor diameter and height of 28cm and 90cm, fuel consumption rate of 55kg/hr, gasification airflow rate of 82.1m3/hr, DC fan motor of 15W, equipped with 30Ah battery power source, and capable of supplying heat energy of 260.16MJ/h. Performance testing using input variables of fuel loading (10kg-20kg), fan speed (4000rpm-6000rpm), and fuel type (palm-kernel shell, coconut shell, coconut husk, and wood shavings) assessed the gasifier responses such as fuel gasification time, flame temperature, thermal and combustion efficiencies, and carbon monoxide (CO) emission of the flame. Results revealed maximum thermal efficiency, peak flame temperature and longest gasification time of 86.02%, 8750C, and 130min respectively, when operated with palm-kernel shell at maximum fan speed and fuel loading, which emitted average CO of 1ppm lower than the least international air pollutant threshold of 9ppm. Highest combustion efficiency of 99.9% was attained using wood shavings at maximum fan speed and fuel loading. The results highlighted the potential of the gasifier as an effective heat source for drying applications, particularly for drying plantain slices in a cabinet dryer.

Information on HIV and Narration of U=U: a mixed method analysis on social media in Italy

Abstract Background Media play a pivotal role in disseminating accurate information, particularly regarding U=U (Undetectable = Untransmittable), to increase awareness and reduce stigma. This study analyses HIV Italian communication on Facebook and Instagram, with a focus on U=U evidence. Methods A mixed-method analysis examined posts on HIV, with linked articles, from Italian news sources from 01/2009 to 04/2023. News sources were categorised as “reliable” or “unreliable” using independent third-party classification. Topic analysis identified the main topics in the posts, while an inductive content analysis was conducted on linked articles regarding U=U. The language and the accuracy in explaining U=U was evaluated through a checklist. Results A total of 10,539 Facebook and 749 Instagram posts were analysed, with 716(7%) and 18(2%) from unreliable sources respectively. Reliable and unreliable content surged around World AIDS Day(WAD) on both platforms. On Facebook, the frequency of unreliable content increased over time, whereas on Instagram it was rare and recent. On Facebook, topics varied between reliable and unreliable sources. The 3 most frequent topics from reliable sources were WAD, voluntary HIV spread, and public figures with HIV; those from unreliable sources were Death and Migrant People; Luc Montagnier and COVID-19 Conspiracies; Public Figures with HIV. On Instagram, the first 3 topics were the Italian National Institute of Health and Prevention, WAD, and public figures with HIV. A total of 68 articles nominating U=U were found and analysed, revealing 4 main areas: U=U definition, Prevention, Impact on people living with HIV, and Stigma. The accuracy in explaining U=U was generally low, with 6 articles(8.8%) providing only a definition. Conclusions HIV communication in Italy is limited and centered around WAD, with persisting bias. The dissemination of the U=U evidence is lacking. Urgent action is needed to shift the narrative and emphasize this evidence Key messages • HIV communication in Italy is limited and concentrated around World AIDS day. • The U=U evidence is poorly disseminated, often providing only a definition and medical explanation.

Suitability of ChatGPT as a Source of Patient Information for Screening Mammography.

ChatGPT3.5 and ChatGPT4 were released publicly in late November 2022 and March 2023, respectively, and have emerged as convenient sources of patient health education and information, including for screening mammography. ChatGPT4 offers enhanced capabilities; however, it is only available by paid subscription. The purported benefits of ChatGPT for health education need to be objectively evaluated. To assess performance differences, ChatGPT3.5 and GPT4 were used between 13 April and 29 May 2023 to generate breast screening patient information sheets, which were evaluated using the Patient Education Materials Assessment Tool for printed materials (PEMAT-P) and the CDC Clear Communication Index (CDC Index) Score Sheet; and benchmarked against gold standard content in BreastScreen NSW's patient information sheet. Mean scores were reported for comparison. GPT3.5 provided the appropriate tone and currency of information but lacked accuracy, omitting key insights: PEMAT-P understandability 68.0% (SD = 6.56) and actionability 36.7% (SD=20.4); CDC Index 58.8% (SD = 15.3). GPT4 was deemed superior to GPT3.5 but included several key omissions: PEMAT-P understandability 75.0% (SD = 17) and actionability 53.3% (SD = 11.54); CDC Index 66.0% (SD = 4.1). Both ChatGPT versions exhibited poor understandability and actionability and were unclear in their messaging. Those with poor health literacy will not benefit from accessing current versions of ChatGPT and may be further disadvantaged if they do not have access to a paid subscription. ChatGPT is evidenced to be an unreliable and inaccurate source of information concerning breast screening that may undermine participation and risk increased morbidity and mortality from breast cancer. ChatGPT may increase the demand on health care educators to rectify misinformation.

Direct-drive photovoltaic electrodialysis via flow-commanded current control

Renewable powered, brackish groundwater desalination is an underutilized resource in the developing world, where there are unreliable energy sources and reliance on increasingly saline groundwater. Traditional renewable desalination technologies require sizable energy storage for sufficient water production, leading to increased cost, maintenance and complexity. We theorize and demonstrate a simple control strategy—flow-commanded current control—using photovoltaic electrodialysis (PV-ED) to enable direct-drive (little to no energy storage), optimally controlled desalination at high production rates. This control scheme was implemented on a fully autonomous, community-scale (2–5 m3 d−1) PV-ED prototype system and operated for 6 months in New Mexico on real brackish groundwater. The prototype fully harnessed 94% of the extracted PV energy despite featuring an energy storage to water productivity ratio of over 99% less than the median PV desalination systems in literature. Flow-commanded current control PV-ED provides a simple strategy to desalinate water for resource-constrained communities and has implications for decarbonizing larger, energy-intensive desalination industries.

Sexual and reproductive health: level of knowledge and source of information in adolescence.

To date, there is a lack of a structured national plan of sexual education in Italy, with large interregional differences and poor uniformity in the promotion and learning of sexual health. The aim of this study was to evaluate the level of knowledge on sexuality and reproductive function among adolescents before and after a sexual education program, considering gender differences in the results. A longitudinal and interventional study was conducted on high school students. Six sessions for each class were carried out by a multidisciplinary team. Anonymous questionnaires were administered to investigate basic knowledge of human sexuality and reproduction before and after intervention. Participants were high school students who completed the questionnaires. Outcomes included pre and posttest answers on the knowledge questionnaire in study population. We obtained data from 842 high school students (mean ± SD age, 16.11 ± 1.74years). The main informative sources on sexuality were social media in 37.9% of participants; family, school, and scientific material were the main source in 15.1%, 5.2%, and 4.4%, respectively. A total score of 12.6 ± 3.4 (range, 1-20) was obtained on the knowledge questionnaire; specifically, the score was higher in females than males (12.8 ± 3.4 vs 11.9 ± 3.4, P = .0001). In males and females, a statistically significant increase in level of knowledge was found after the multidisciplinary intervention (14.5 ± 3.6, P = .0001). The lack of sexual education programs in schools in Italy compels adolescents to refer to frequently unreliable sources, such as social media and peers, contributing to misinformation and adoption of risky sexual behaviors. This study is based on a large sample size and highlights the importance of sexual education programs. The main limitations are a greater representation of the female population and the inclusive nature of the school (ie, an artistic school), attracting students who identify with sexual minorities. Adolescents have limited knowledge about sexuality and reproduction, with a notable gender disparity; sexual education programs in schools, providing information from sexuality experts, led to a substantial increase in knowledge and a reduction in the gender gap.

Results of the Italian cross-sectional web-based survey "Nutrition and breast cancer, what would you like to know?" An attempt to collect and respond to patients' information needs, through social media.

Several studies have demonstrated that, following a breast cancer (BC) diagnosis, patients are eager to obtain information on cancer and nutrition, in order to ameliorate both their quality of life (QoL) and disease outcome. To avoid BC survivors to get wrong information from unreliable sources, healthcare providers need to be aware of patients' needs, to guide them toward optimal nutrition recommendations, aimed at preventing tumor recurrence and increasing survival rates. The cross-sectional web-based survey "Nutrition and breast cancer, what would you like to know?" has been conceived and conducted, in Italy, between the 2nd and the 25th of June 2023. The link to the 19-items questionnaire, structured in 6 sections, was distributed via social media (Facebook and Instagram), newsletter, institutional websites, and printed flyers. Patients' responses were collected and analyzed, reporting absolute and relative frequencies. A total of 1616 participants (98.9% female and 1.1% male), with an average age of 47.5 years, answered the survey. Only subjects who declared having previously received a BC diagnosis (N=1159, 71.7%) were included in the present analysis. Overall, the respondents showed a wide interest in understanding whether nutrition might help to manage therapy side effects, as well as knowing how specific diets, foods, nutrients, and supplements could affect disease onset, progression and prognosis. Importantly, the need to receive evidence-based information from the "referring physician/specialist" and "nutritionist/dietitian" was expressed by 95.8% and 88.8% of them, respectively. In this study, we primarily aimed at intercepting nutrition information needs and sources of an Italian BC survivors' group. Based on that, we first organized a proactive digital intervention, to respond via Instagram live broadcasts to patients' "cancer and nutrition"-related questions. Secondly, we arranged a healthcare providers dedicated-workshop focused on the latest evidence-based knowledge on nutrition and BC. It is crucial, in fact, that once healthcare professionals capture patients' information needs, they can respond with appropriate nutritional guidance, counseling and education programs, while counteracting misleading and incorrect messages.

DO CHATBOTS PROVIDE RELIABLE INFORMATION ABOUT MOBILE APPS IN AUDIOLOGY?

IntroductionIn light of the growing interest in utilizing AI for information retrieval, assessing the accuracy and reliability of tools such as chatbots is essential. This study aims to evaluate the efficacy of chatbots in providing accurate information about mobile applications (apps) in the field of audiology.Material and methodsThe responses of the Gemini and ChatGPT chatbots to eight open-ended questions posed in Polish and English were compared. Each answer was assessed for correctness.ResultsGemini_ENG achieved the highest correctness with a score of 5 points (62.5%), while ChatGPT_PL scored 2 points (25%), and both Gemini_PL and ChatGPT_ENG scored 1 point (12.5%). Chatbots were most effective in recommending apps for older adults, with three of the four chatbots providing accurate recommendations. However, they struggled when asked to recommend apps for non-English speakers, to describe apps, or to provide direct links, with none of them scoring points in these areas.ConclusionsChatbots are currently unreliable sources of information about audiology apps. Depending on the language, there is significant variability in response accuracy. A good example is that Gemini_ENG performed far better than Gemini_PL. A major issue for all of them was the frequent fabrication of data, including the creation of nonexistent app names and incorrect links.

Climate Risk and Vulnerability Assessment in Informal Settlements of the Global South: A Critical Review

This study investigated the climatic risks and vulnerabilities of informal settlements in the Global South, as well as the extent to which these risks impact the vulnerabilities. Using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2009 methodology and deductive content analysis, this study critically examined 69 documents, including 28 scholarly journal articles obtained from Scopus and ScienceDirect and 41 web-based releases identified through the Google search engine and snowballing technique. Document inclusion criteria focused on the relevance to climate risks and vulnerabilities, excluding non-peer-reviewed, non-English, and unreliable sources, as well as irrelevant studies. Seven major climate risks impacting informal settlements were identified: floods (44), temperature changes (41), storms (31), sea level rise (30), drought (28), rainfall (23), and landslides (14). The primary vulnerabilities highlighted were poor housing conditions (64), health risks (50), lack of basic services (49), inadequate sanitation (41), inadequate hygiene (39), and limited access to water (38). The combination of vulnerabilities and climate risks creates considerable direct, indirect, and low-level threats to informal settlements. Despite Asia, Africa, and Latin America’s vulnerability, most studies focused on formal and developed areas. The findings highlight the critical need for climate adaptation strategies in informal settlements of the Global South to ensure the United Nations Sustainable Development Goals (SDGs) are met.

A Qualitative Exploration of the Impact, Management, and Existing Psychological Support Available for Adults Living with Skin Conditions.

Skin conditions carry a significant physical, psychological, and social burden. People with skin conditions often engage in health-threatening behaviours that can worsen symptoms and increase cardiovascular disease risk. However, access to dedicated psychological and behaviour-change support is limited. The impact, management, and existing psychological support available to adults living with skin conditions was qualitatively explored to inform the development of a psychologically supportive digital intervention. Qualitative research involving a hybrid inductive- deductive approach was performed. Data collection and analysis were theoretically informed by the Common-Sense Model of Self-Regulation. Eight synchronous online group interviews with 43 English-speaking adults (≥ 18 years) with a range of skin conditions were conducted. Data were analysed using Reflexive Thematic Analysis. Three superordinate themes are outlined: (i) visibility underpinning life course impairment, (ii) seeking control amid uncertainty, and (iii) existing support for people with skin conditions. Skin conditions carry a substantial psychological burden, yet dermatology service provision is sub-optimal and patients often resort to seeking support from unreliable sources. Psychological support can have benefits, but barriers exist. This study reinforces the need for high-quality psychological support, and that patients wanted digital means to support effective self- management.

Evidence generalization-based discounting method: assigning unreliable information to partial ignorance

Conflict management is an important topic when dealing with unreliable sources information fusion in Dempster–Shafer theory. Discounting unreliable bodies of evidence has proven to be effective to decrease conflict. Based on the generalization of belief functions, a new generalization-based discounting method is proposed. When resolving conflicts with the same degree, our method can realize less information loss in comparison with other discounting methods. By simulating the process of resolving conflicts of randomly generated bodies of evidence, using entropy measurements and binary conflict as evaluation index, we show our method’s rationality and superiority. Finally, the hyperparameters of the conflict metrics are generated and generalization-based discounting is applied to classify real-world datasets. The improved classification performance further illustrates the usefulness of the method.

Feverphobia: Frecuency and related factors associated

Fever is common in childhood and there is a high level of concern on behalf of caregivers to manage it, this is called "feverphobia". The objective was to evaluate the presence of feverphobia and associated factors in the study population. Methods: observational, cross-sectional, prospective, and analytical study during 2021 to 2022 through an ad hoc survey self-administered to parents and/or caregivers of patients under 6 years of age who consulted the emergency room of the Dr. Roberto del Río Children's Hospital in Santiago, Chile. The association between sociodemographic variables, knowledge, attitudes, and fears regarding febrile children was analyzed by Chi square and Fisher’s test in addition to univariate logistic regression analysis. A total of 381 surveys were carried out. 98% presented some degree of feverphobia. A fever below 38°C was defined by 40.6%. Physical measures were used by 56% of caregivers. The main sequelae feared were convulsions in 82% and 42.7% reported that it could be lethal. A total of 92.1% used unreliable sources of information and 66% had never received education from health personnel on this subject. Logistic regression showed that being a parent, basic or high school level and a thermal threshold below 38°C were the most associated variables. Feverphobia is a current phenomenon in our population and health education to the parents and caregivers could prevent it.

System-level Probabilistic Remaining Useful Life Prognostics and Predictive Inspection Planning for Wind Turbines

Wind energy plays a crucial role in the energy transition. However, it is often seen as an unreliable source of energy, with many production peaks and lows. Some of the drivers of uncertainty in energy production are the unexpected wind turbine (WT) failures and associated unscheduled maintenance. To support an effective health management and maintenance planning of WTs, we propose an integrated data-driven framework for Remaining Useful Life (RUL) prognostics and inspection planning of WTs. We propose a Long-short term memory (LSTM) neural network with Monte Carlo dropout to estimate the distribution of the RUL of WTs, i.e. we develop probabilistic prognostics. Different from existing studies focused on prognostics for single components, we consider the simultaneous health-monitoring of multiple components of the WTs, thus seeing the turbine as an integrated system. The obtained prognostics are further included into a stochastic planning model which determines optimal moments for inspections. For this, we pose the problem of WT inspections as a renewal reward process. We illustrate our framework for four offshore WTs which are continuously monitored by Supervisory Control and Data Acquisition (SCADA) systems. The results show that LSTMs are able to estimate well the RUL of the WTs, even in the early phase of their usage. We also show that the prognostics are informative for maintenance planning and are conducive to conservative inspections.

Navigating the infodemic maze: Does information literacy reduce the infodemic?

The objective of this study was to examine how information literacy can aid in infodemic management in the context of university students in a developing country. A printed survey questionnaire was employed to collect data on information literacy and infodemic management from a sample population consisting of university students. A total of 300 responses were collected and analysed, and both descriptive and inferential statistics were used. The results brought about a wide set of findings. The study found that students in the Department of Information Science and Library Management at the University of Dhaka exhibited a high level of awareness of information literacy and the COVID-19 infodemic. Despite the prevalence of misinformation and disinformation related to COVID-19, the students did not tend towards unreliable sources of information. The study examined the positive effect of information literacy on infodemic management through a multiple regression analysis. The empirical findings can aid in navigating the spread of misinformation and disinformation in the context of other developing countries.

Unsupervised domain adaptation with weak source domain labels via bidirectional subdomain alignment

Unsupervised domain adaptation (UDA) enables knowledge transfer from a labeled source domain to an unlabeled target domain. However, UDA performance often relies heavily on the accuracy of source domain labels, which are frequently noisy or missing in real applications. To address unreliable source labels, we propose a novel framework for extracting robust, discriminative features via iterative pseudo-labeling, queue-based clustering, and bidirectional subdomain alignment (BSA). The proposed framework begins by generating pseudo-labels for unlabeled source data and constructing codebooks via iterative clustering to obtain label-independent class centroids. Then, the proposed framework performs two main tasks: rectifying features from both domains using BSA to match subdomain distributions and enhance features; and employing a two-stage adversarial process for global feature alignment. The feature rectification is done before feature enhancement, while the global alignment is done after feature enhancement. To optimize our framework, we formulate BSA and adversarial learning as maximizing a log-likelihood function, which is implemented via the Expectation–Maximization algorithm. The proposed framework shows significant improvements compared to state-of-the-art methods on Office-31, Office-Home, and VisDA-2017 datasets, achieving average accuracies of 91.5%, 76.6%, and 87.4%, respectively. Compared to existing methods, the proposed method shows consistent superiority in unsupervised domain adaptation tasks with both fully and weakly labeled source domains.

Strengths and Weaknesses of Open Source Data for Studying Terrorism and Political Radicalization

Compared to studying other forms of illegal violence, terrorism research faces unique data challenges. Notably, consistent police data are generally lacking, victims often have no direct knowledge of attacks and are sometimes killed, and perpetrators are difficult to interview and are often unreliable sources. In the face of these data challenges, the increasing availability of open source data on terrorist attacks and perpetrators has profoundly affected the scientific study of terrorism. Over time, a growing proportion of published academic research on terrorism—especially more heavily quantitative studies—relies on open source data. Moreover, the growing availability of individual-level terrorism data has allowed empirical tests of psychological and social-psychological theories of radicalization. In this paper, we assess the impact of open source data on the study of terrorism. We begin with an overview, providing a brief history of terrorist attack and perpetrator open source data bases. We then consider the major strengths and weaknesses of both types of open source data and suggest ways of countering the weaknesses. We close with observations about the impact of open source data on terrorism research and future opportunities for improvement.

Misinformation does not reduce trust in accurate search results, but warning banners may backfire

People rely on search engines for information in critical contexts, such as public health emergencies–but what makes people trust some search results more than others? Can search engines influence people’s levels of trust by controlling how information is presented? And, how does the presence of misinformation influence people’s trust? Research has identified both rank and the presence of misinformation as factors impacting people’s search behavior. Here, we extend these findings by measuring the effects of these factors, as well as misinformation warning banners, on the perceived trustworthiness of individual search results. We conducted three online experiments (N = 3196) using Covid-19-related queries, and found that although higher-ranked results are clicked more often, they are not more trusted. We also showed that misinformation does not damage trust in accurate results displayed below it. In contrast, while a warning about unreliable sources might decrease trust in misinformation, it significantly decreases trust in accurate information. This research alleviates some concerns about how people evaluate the credibility of information they find online, while revealing a potential backfire effect of one misinformation-prevention approach; namely, that banner warnings about source unreliability could lead to unexpected and nonoptimal outcomes in which people trust accurate information less.

Using website referrals to identify unreliable content rabbit holes

ABSTRACT Does the URL referral structure of websites lead users into ‘rabbit holes’ of unreliable content? Past work suggests algorithmic recommender systems on sites like YouTube lead users to view more unreliable content. However, websites without algorithmic recommender systems have financial and political motivations to influence the movement of users, potentially creating browsing rabbit holes. We address this gap using browser telemetry that captures referrals to a large sample of domains rated as reliable or unreliable information sources. Our results suggest the incentives for unreliable sites to retain and monetise users create rabbit holes. After landing on an unreliable site, users are very likely to be referred to another page on the site. Further, unreliable sites are better at retaining users than reliable sites. We find less support for political motivations. While reliable and unreliable sites are largely disconnected from one another, the probability of traveling from one unreliable site to another is relatively low. Our findings indicate the need for additional focus on site-level incentives to shape traffic moving through their sites.

Репрезентация категории косвенной эвиденциальности средствами стратегии уклонения в английском, русском, чувашском языках

This study conducts a contrastive typological analysis of linguistic markers of author’s and impersonal evidentiality in the English, Russian, and Chuvash languages. The research novelty lies in the systematic analysis of Chuvash indirect evidentiality markers in a comparative perspective. The study demonstrates that the “Nominative Case with Infinitive” construction, as a characteristic of author’s evidentiality in English, corresponds to Russian modal-suppositional and comparative particles, introductory words, and phrases (equivalent to the degree of certainty adverb “perhaps”), which express the speaker’s low assessment of the reported information’s reliability. In Russian, evidential particles, introductory words, and sentences (equivalent to the hearsay adverb “allegedly”) are used to indicate an unreliable source. The evidential particle “якобы” and the introductory word “мол” are common in speeches and statements. This approach to classifying evidentiality systems is also applicable to Chuvash. Modals, introductory words, and modal verb forms serve as lexical means of expressing author’s and impersonal evidentiality. The standard is to use two modal formants simultaneously. However, unlike English and Russian, evidentiality representations with negative meaning can be complex grammatical units represented by verbal analytical constructions. The findings suggest both universal and language-specific means of representing indirect evidentiality. Correlated representation of evidentiality and epistemic modality plays a significant semantic-pragmatic role in utterances as an effective evasion strategy.

Exploring the practice of Iranian adolescent females during menstruation and related beliefs: a qualitative study

BackgroundMenstruation is a natural occurrence that women experience during their reproductive years and may encounter many years throughout their lifespan. Many adolescent females lack accurate knowledge about menstruation, so they may face issues from receiving incorrect information from unreliable sources. Our study aimed to investigate the practices and beliefs surrounding menstruation among Iranian adolescent females.MethodsThis qualitative study was conducted using conventional content analysis. A purposeful sampling method was used to select 18 adolescent females from secondary and high schools located in the three regions of Neyshabur City-Iran. Data were collected through in-depth, semi-structured interviews.ResultsThree main themes were extracted, consisting of lifestyle and related beliefs, lake of support, and awareness and information.Conclusionsmisconceptions and wrong behaviors during menstruation indicate that the lake of knowledge an traditional factors influence adolescent girls’ health. The study provides the basis for intervention planning in this regard and different levels (individual, intrapersonal, health systems, and community).

Selecting reliable instances based on evidence theory for transfer learning

The aim of transfer learning is to improve the performance of learning models in the target domain by transferring knowledge from the related source domain. However, not all data instances in the source domain are reliable for the learning task in the target domain. Unreliable source-domain data may lead to negative transfer. To address this problem, we propose a novel strategy for selecting reliable data instances from the source domain based on evidence theory. Specifically, a mass function is formulated to measure the degree of ignorance and reliability of the source domain data with respect to the learning task in the target domain. By selecting reliable instances with low degree of ignorance from the source domain, the domain adaptation of the transfer learning models is enhanced. Moreover, the proposed data-selection strategy is independent of specific learning algorithms and can be regarded as a common preprocessing technique for transfer learning. Experiments on both simulated and real-world datasets validated that the proposed data selection strategy can improve the performance of various types of transfer learning methods.