Miracle-dz/UniFAR-FTUs huggingface dataset:
How Trust is Defined and its use in Human-Human and Human-Machine Interaction

Trust is a critical element in virtually all forms of interactions, including those between humans and machines. Yet aspects of trust do vary somewhat between definitions. The present work seeks to unify these disparate definitions of trust, comparing and contrasting between the major works. Overall, every definition of trust involves an individual in a position of vulnerability (the trustor) and a person on whom they must rely (the trustee) despite circumstances which may place the trustor in some kind of potential for harm. Such engagements are enacted in order to secure some form of gain from the trusting relationship. The ways in which these definitions influence empirical measurement (both qualitative and quantitative) are identified and elaborated on.
Anonymity in Questions and Answers about Health

Social Question & Answer (Q&A) sites are a unique source of health information that draw from personal, rather than professional experience. When people ask or answer questions about health using these sites, they may do so using their real name, or another type of identity such as pseudonymity (e.g., a username or nickname) or anonymity. People’s behavior may differ when they have a choice about which type of identity they choose, especially the context of different levels of sensitivity of content (e.g., health vs. non- health). In this work, we explore the relationship between different types of identity (e.g., anonymity and pseudonymity) and several Q&A metrics of user behavior on Yahoo Answers in the context of health and non-health content using path analysis. We find that health-related questions are more likely to be asked and answered anonymously. We also find that anonymous answers have more upvotes and downvotes than pseudonymous answers indicating more engagement. We conclude by suggesting that health Q&A sites and other online health communities may improve the quality of discussion by providing anonymity features and implementing moderation mechanisms.
Reported Order of Importance Does not Predict Fixation Order when Viewing Driving Scenes

Distracted driving and its negative effects on driving performance are well documented. Eye movement patterns of distracted drivers have also been studied, though insight into what the driver specifically looks at is not as well understood. Researchers have studied eye movement metrics like, eyes-off-road glance times, time-to-first-fixation, among others, over an entire drive, but not what the driver is looking at in a specific moment in time. The current study used eye tracking to investigate what objects and areas people looked at in driving scenes and what they reported they would look at later in the same scenes. The results suggest that people look where they say they would look, but not in the order they reported they would look. This finding demonstrates that participants may scrutinize scenes differently at various times, but attend to the same objects or areas, indicating an associated importance, semantic constraints, and relevance for driving.
Drivers’ Gaze Behaviors are Influenced by Vehicle Position

Drivers’ gaze behaviors in naturalistic and simulated driving tasks have been investigated for decades. Many studies focus on driving environment to explain a driver’s gaze. However, if there is a great need to use compensatory steering for lane-keeping, drivers could preferentially acquire information directly required for the task. Therefore, we assumed that a driver’s gaze behavior was influenced not only by the environment but also the vehicle position, especially the lateral position. To verify our hypothesis, we carried out a long-time driving simulator experiment, and the gaze behaviors of two participating drivers were analyzed. Results showed that gaze behavior—the fixation distance and the lateral deviation of the fixation—was influenced by the lateral deviation of the vehicle. Consequently, we discussed processes that determined drivers’ gaze behaviors.
An Eye Tracking-Based Forensic Analysis of Motorcyclist Conspicuity During a Left Turn Maneuver

Research has identified drivers’ failure to detect motorcyclists as a causal factor in collisions, with drivers often looking towards or at a motorcycle but reporting that they never saw the motorcycle. Driving is a complex task and it is important to understand where and how drivers allocate their attention. Using mobile eye tracking technology, the present study was conducted as part of the forensic analysis of a collision between a passenger vehicle and a motorcycle. Gaze patterns of eight individuals were recorded as they made left-hand turns across traffic. Data from this study indicated that half of the participants fixated the motorcycle. However, none of the participants appeared to detect the motorcycle-initiated motion towards them as they made their left turn. These findings suggest that drivers were able to peripherally detect the motorcycle but failed to see it or judged the motorcycle not to be an imminent threat.
Driver Response Times to Side Road Path Intrusions from SHRP-2 Naturalistic Database

In an age where all major manufacturers are trying to get a better understanding of when an emergency response should be triggered, it becomes imperative to learn how humans respond to emergency events. If one can understand driver behavior, systems can be designed around the user to either assist drivers where they fail to perform well or completely eliminate them from the accident avoidance maneuver. In this study, 169 crash and near crash events from the SHRP2 dataset were analyzed. The response behavior of drivers was measured in events where the through drivers’ path was intruded upon by another vehicle perpendicular to its path. Overall, drivers responded significantly faster when the other vehicle failed to stop, and at intersection locations.
Educational Data Mining and Learning Analytics for Improving Online Learning Environments

The proliferation of educational technology systems has led to the advent of a large number of datasets related to learner interaction. New fields have emerged which aim to use this data to identify interventions that could help the learners become efficient and effective in their learning. However, these systems have to follow user-centered design principles to ensure that the system is usable and the data is of high quality. Human factors literature is limited on the topics regarding Educational Data Mining (EDM) and Learning Analytics (LA). To develop improved educational systems, it is important for human factors engineers to be exposed to these data-oriented fields. This paper aims to provide a brief introduction to the fields of EDM and LA, discuss data visualization and dashboards that are used to convey results to learners, and finally to identify where human factors can aid other fields.
The Prediction of Collisions in Connected Vehicle Systems with A Long Short-Term Memory Model

The advances in connected vehicle systems (CVS) allow vehicles to communicate with each other and with infrastructures via wireless communication networks. This technology enables vehicles to detect potential hazards on the road, generate warnings, and assist the driver in taking preventive actions. To date, few mathematical models have been developed to predict the collision rates in connected vehicle systems. In this work, a Long Short-Term Memory model (LSTM) using time-series data of human drivers was developed to predict the collision rates in CVS by quantifying warning parameters and hazard scenario features. The model was validated with the driving performance data before and after warnings from thirty-two drivers in a behavioral experiment. The results indicated the LSTM model showed a prediction accuracy of 74% higher than SVM and logistic regression models. The LSTM model showed the potential to help optimize the warning algorithm in the connected vehicle systems to improve driver safety.
Come Closer: Experimental Investigation of Robots’ Appearance on Proximity, Affect and Trust in a Domestic Environment

From once being utopian, robots become more and more common in public and private social life. One area of application are robots, which are able to perform chores in domestic environments. To support users accustoming to the new robot companion, psychological mechanisms that enhance the interaction with robots need to be understood. In this research, the effects of robot’s height and manipulator position on proximity, affect and trust with regards to a humanoid robot were investigated in a laboratory experiment. Results indicated an effect of robot’s height on the comfort distance. On the other hand, a habituation effect after a second robot-human approach was found, in which the influence of the robot’s height on proximity diminished. Similar effects with an anxiety decrease and trending trust increase in the tall robot over time emphasize the importance of first encounters, which should be paid special attention to by designers of robotic systems.
Effects of Task Switching In Baggage Screeners

Using a visual search and decision-making task, we investigated common task switching effects on baggage screeners. Like the general population, baggage screeners perform best when there is no task switching as shown by a high sustained d’ and fast decision time. Although baggage screeners continue to improve throughout the task, task switching results in functional decay of the memory for the current decision-criterion.
Identifying roles in older adults’ emergency department transitions

Older adults frequently visit the emergency department (ED) and participate in multiple transitions of care following an ED visit. These transitions of care, e.g. to hospital, long-term care facility or home, represent patient safety risks because of communication and coordination failures between the various roles involved, but also provide opportunities for error detection and recovery and, therefore, resilience. The objective of this study was to identify and describe the multiple roles involved in older adult care transitions during an ED visit. As part of a large research project, we conducted patient-centered observations and interviewed ED clinicians and hospital administrators. We identified 16 ED roles involved in older adult care transitions out of the ED, including 4 roles solely focused on coordinating transitions. By better understanding the roles involved in ED care transitions, we can improve the design of team processes and technologies to support care of older adults throughout their care transitions.
Cyber Buzz: Examining Virality Characteristics of Cybersecurity Content In Social Networks

The Internet is a rich environment for information to spread rapidly and widely. The ability of cybersecurity content to achieve virality in social networks can be useful for measuring security awareness, policy adoption, or cybersecurity literacy. It may also reveal new and emerging cybersecurity events. Virality in online social networks can be characterized and measured many ways and have different causes. Leveraging existing research in social network virality measurements, we calculate and analyze virality measurements and correlations on an anonymized Reddit dataset, examining overall trends and characteristics of individual cybersecurity forums (subreddits). We reproduce content-based virality prediction algorithms and assess their performance, then introduce additional features beyond post title, including time of day, to improve prediction accuracy to ~71% for each of the virality scores. We examine the intersection of the virality facets to reveal correlations about the content and times when cybersecurity content is most viral.
Novel Fe-doped anatase TiO2 nanosheet hierarchical spheres with 94% {001} facets for efficient visible light photodegradation of organic dye

Novel Fe-incorporated anatase TiO2 nanosheet hierarchical spheres with predominant {001} facets were first prepared via a facile one-pot solvothermal route. The obtained {001}-0.1%Fe-AHSs exhibit excellent visible light photodegradation activity for methylene blue attributed to 94% {001} facets and uniformly incorporated Fe3+ ions in the TiO2 lattice.
Blink Rate as a Measure of Driver Workload during Simulated Driving

Cognitive distraction has been identified as a critical factor for automobile crashes in the United States. Previous research indicates that cognitive tasks such as phone conversations may take attention away from the driving task, degrading driving performance. One continuing issue with cognitive distraction research is establishing a reliable, continuous, online measure of driver workload. Blink rate is a potential candidate for such a measure. The present driving simulator experiment examines whether blink rate is sensitive to variations of driver workload while controlling the vehicle. Participants will navigate simulated environments while performing the auditory 0-and 2-back task with their blink and driving performance data continuously recorded during the drive. Blink and performance data will be compared not only between the different workload conditions, but also to predictions of a human driver performance workload model based on the Improved Performance Research Integration Tool (IMPRINT), developed by the US Army Research Laboratory.
Examining frustration and performance when priming user expectations and providing a technology malfunction

As digital technology develops, users create expectations for performance that may be violated when malfunctions occur. This project examined how priming expectations of technology performance (high v. low v. no) and experiences of technology malfunction (present v. not present) can influence feelings of frustration and performance on a task. A preliminary sample of 42 undergraduate participants completed a QR code scavenger hunt using the augmented reality mobile app, ARIS. Following the task, participants reported what they found for each scavenger hunt clue, their responses to failures in digital technology, and technology acceptance attitudes. Several factorial ANOVAs revealed a main effect for expectation on adaptive items of the RFDT scale and a main effect for malfunction on performance level. This suggests a potential contradiction between attitudes and behaviors when considering a common scenario involving technology.
Designing an Occupational Exposure Report for Aircraft Rescue and Firefighting

Despite the known carcinogenic hazards encountered by Aircraft Rescue and Firefighting (ARFF) personnel on the job, little is known about what reportable components should be documented from ARFF incidents. Interviews and focus groups were used to investigate ARFF firefighters’ knowledge of and behaviors related to occupational exposures. Two interviews and five focus group sessions were conducted with a total of 52 ARFF firefighters. We describe perceptions of occupational exposure risks among ARFF Firefighters in South Florida and characterize the variables needed for ARFF exposure reporting.
Zealous clout of COVID-19: analytical research at sixes and sevens

Abstract This New Year’s wake-up call warned us of Democles’ sword in the form of COVID-19, an epidemic turned pandemic. Seeming to reach a novel and awful landmark every day, governments across globe are fighting on toes to contain its spread. The pandemic is accelerating and information is being updated and changing by the hour. Till date shattering causalities across globe have been reported to World Health Organization. Nevertheless, the world is responding to this novel enemy with urgency and purpose. The challenge is great, but the response has been massive. Record characterisation and multiple sequences of this novel pathogen are being shared on global platform leading to a lot of diagnostics to get developed. Currently no treatment is effective against COVID-19 and there is a desperate need for international solidarity for valuable therapeutics. Present article briefs some milestones achieved by the killer virus thereby posing a challenge to medical science.
Risk for African Swine Fever Introduction Into Kazakhstan

African swine fever (ASF) is a disease of swine that is endemic to some African countries and that has rapidly spread since 2007 through many regions of Asia and Europe, becoming endemic in some areas of those continents. Since there is neither vaccine nor treatment for ASF, prevention is an important action to avoid the economic losses that this disease can impose on a country. Although the Republic of Kazakhstan has remained free from the disease, some of its neighbors have become ASF-infected, raising concerns about the potential introduction of the disease into the country. Here, we have identified clusters of districts in Kazakhstan at highest risk for ASF introduction. Questionnaires were administered, and districts were visited to collect and document, for the first time, at the district level, the distribution of swine operations and population in Kazakhstan. A snowball sampling approach was used to identify ASF experts worldwide, and a conjoint analysis model was used to elicit their opinion in relation to the extent at which relevant epidemiological factors influence the risk for ASF introduction into disease-free regions. The resulting model was validated using data from the Russian Federation and Mongolia. Finally, the validated model was used to rank and categorize Kazakhstani districts in terms of the risk for serving as the point of entry for ASF into the country, and clusters of districts at highest risk of introduction were identified using the normal model of the spatial scan statistic. Results here will help to allocate resources for surveillance and prevention activities aimed at early detecting a hypothetical ASF introduction into Kazakhstan, ultimately helping to protect the sanitary status of the country.
ABAP1 Plays a Role in the Differentiation of Male and Female Gametes in Arabidopsis thaliana

The correct development of a diploid sporophyte body and a haploid gametophyte relies on a strict coordination between cell divisions in space and time. During plant reproduction, these divisions have to be temporally and spatially coordinated with cell differentiation processes, to ensure a successful fertilization. Armadillo BTB Arabidopsis protein 1 (ABAP1) is a plant exclusive protein that has been previously reported to control proliferative cell divisions during leaf growth in Arabidopsis. Here, we show that ABAP1 binds to different transcription factors that regulate male and female gametophyte differentiation, repressing their target genes expression. During male gametogenesis, the ABAP1-TCP16 complex represses CDT1b transcription, and consequently regulates microspore first asymmetric mitosis. In the female gametogenesis, the ABAP1-ADAP complex represses EDA24-like transcription, regulating polar nuclei fusion to form the central cell. Therefore, besides its function during vegetative development, this work shows that ABAP1 is also involved in differentiation processes during plant reproduction, by having a dual role in regulating both the first asymmetric cell division of male gametophyte and the cell differentiation (or cell fusion) of female gametophyte.
Insomnia – A Heterogenic Disorder Often Comorbid With Psychological and Somatic Disorders and Diseases: A Narrative Review With Focus on Diagnostic and Treatment Challenges

Patients with insomnia complain of problems with sleep onset or sleep maintenance or early morning awakenings, or a combination of these, despite adequate opportunity and circumstances for sleep. In addition, to fulfill the diagnostic criteria for insomnia the complaints need to be associated with negative daytime consequences. For chronic insomnia, the symptoms are required to be present at least 3 days per week for a duration of at least 3 months. Lastly, for insomnia to be defined as a disorder, the sleep complaints and daytime symptoms should not be better explained by another sleep disorder. This criterion represents a diagnostic challenge, since patients suffering from other sleep disorders often complain of insomnia symptoms. For instance, insomnia symptoms are common in e.g., obstructive sleep apnea and circadian rhythm sleep-wake disorders. It may sometimes be difficult to disentangle whether the patient suffers from insomnia disorder or whether the insomnia symptoms are purely due to another sleep disorder. Furthermore, insomnia disorder may be comorbid with other sleep disorders in some patients, e.g., comorbid insomnia and sleep apnea (COMISA). In addition, insomnia disorder is often comorbid with psychological or somatic disorders and diseases. Thus, a thorough assessment is necessary for correct diagnostics. For chronic insomnia disorder, treatment-of-choice is cognitive behavioral therapy, and such treatment is also effective when the insomnia disorder appears comorbid with other diagnoses. Furthermore, studies suggest that insomnia is a heterogenic disorder with many different phenotypes or subtypes. Different insomnia subtypes may respond differently to treatment, but more research on this issue is warranted. Also, the role of comorbidity on treatment outcome is understudied. This review is part of a Research Topic on insomnia launched by Frontiers and focuses on diagnostic and treatment challenges of the disorder. The review aims to stimulate to more research into the bidirectional associations and interactions between insomnia disorder and other sleep, psychological, and somatic disorders/diseases.
Insights Into the Antiviral Pathways of the Silkworm Bombyx mori

The lepidopteran model silkworm, Bombyx mori, is an important economic insect. Viruses cause serious economic losses in sericulture; thus, the economic importance of these viruses heightens the need to understand the antiviral pathways of silkworm to develop antiviral strategies. Insect innate immunity pathways play a critical role in the outcome of infection. The RNA interference (RNAi), NF-kB-mediated, immune deficiency (Imd), and stimulator of interferon gene (STING) pathways, and Janus kinase/signal transducer and activator of transcription (JAK/STAT) pathway are the major antiviral defense mechanisms, and these have been shown to play important roles in the antiviral immunity of silkworms. In contrast, viruses can modulate the prophenol oxidase (PPO), phosphatidylinositol 3-kinase (PI3K)/protein kinase B (Akt), and the extracellular signal-regulated kinase (ERK) signaling pathways of the host to elevate their proliferation in silkworms. In this review, we present an overview of the current understanding of the main immune pathways in response to viruses and the signaling pathways modulated by viruses in silkworms. Elucidation of these pathways involved in the antiviral mechanism of silkworms furnishes a theoretical basis for the enhancement of virus resistance in economic insects, such as upregulating antiviral immune pathways through transgenic overexpression, RNAi of virus genes, and targeting these virus-modulated pathways by gene editing or inhibitors.