Miracle-dz/UniFAR-FTUs huggingface dataset:
ORR_A_199107 129..140

Valerie Sparkes Gemma M Whatling Paul Biggs Nidal Khatib Mohammad Al-Amri David Williams Rebecca Hemming Martina Hagen Ishaak Saleem Ramesh Swaminathan Cathy Holt 1School of Healthcare Sciences, Biomechanics and Bioengineering Research Centre Versus Arthritis, College of Biomedical and Life Sciences, Cardiff University, Cardiff CF24 0AB, UK; 2School of Engineering, College of Physical Sciences and Engineering, Cardiff University, Cardiff CF24 3AA, UK; 3Arthritis Research UK Biomechanics and Bioengineering Centre, Cardiff University, Cardiff CF10 3AT, UK; 4Medical Affairs, Pain Relief Category, GSK Consumer Healthcare S.A. , Nyon 1260, Switzerland Objective: To examine functional performance differences using kinematic and kinetic analysis between participants with and without knee osteoarthritis (OA) to determine which outcomes best characterize persons with and without knee OA. Methods: Participants with unilateral moderate knee OA (Kellgren–Lawrence grades 2 or 3) and controls without knee pain were matched for age, gender, and body mass index. Primary outcomes included temporal parameters, joint rotations and moments, and ground reaction forces assessed via 3D motion capture during walking and ascending/descending stairs. Secondary outcomes included timed functional activities (sit to stand; tying shoelaces), 48 hrs lower limb activity monitoring, and patient-reported outcome measures (Knee Injury and Osteoarthritis Outcome Score, Western Ontario and McMaster Universities Osteoarthritis Index, European Quality of Life–5 Dimensions). Results: Eight matched pairs were analyzed. Compared with controls, OA participants exhibited significant reductions in peak frontal hip and sagittal knee moments, and decreased peak anterior ground reaction force with the affected limb while walking. Ascending stairs, OA participants had slower speed, fewer strides per minute, longer cycle and stance times, and increased trunk range of motion (ROM) in assessments of both limbs; longer swing time and reduced ankle ROM in the affected limb; and increased knee frontal ROM in the unaffected limb. Descending stairs, OA participants had fewer strides per minute and decreased trunk transverse ROM in assessments of both limbs; increased knee frontal ROM in the affected limb; and longer strides, shorter stance and cycle times, increased trunk sagittal and decreased knee transverse ROMs in the unaffected limbs vs controls. Compared with controls, OA participants had slower walking cadence (120–130 vs 100–110 steps/min, respectively), took significantly longer on timed functional measures, and had significantly worse scores in patient-reported outcomes. Conclusion: Several objectives and patient-reported measures examined in this study could potentially be considered as outcomes in pharmacologic or physical therapy OA trials.
Hacks for Cost-Justifying Usability: "Fear-Setting" vs. "Goal-Setting"

This paper is designed to guide user-centered design professionals in running negotiations of usability cost justification with product owners. The paper introduces hacks that can be used by usability professionals to convince entrepreneurs or other decision makers to invest in usability improvements. The traditional cost-justifying usability approach focuses on emphasizing the potential profits that can be expected. This "goal-setting" approach, commonly represents a strong influence on the investment decision of young, nascent entrepreneurs. The new approach, which we are suggesting, is about avoiding losses and costs stemming from not taking any action. This is a "fear-setting" approach, which tends to influence the investment decisions of older and more experienced entrepreneurs. Usability professionals can thus identify and classify their audience regarding to age and years of experience in order to choose the most efficient mode of presenting justification of usability cost.
WRIST: Watch-Ring Interaction and Sensing Technique for Wrist Gestures and Macro-Micro Pointing

To better explore the incorporation of pointing and gesturing into ubiquitous computing, we introduce WRIST, an interaction and sensing technique that leverages the dexterity of human wrist motion. WRIST employs a sensor fusion approach which combines inertial measurement unit (IMU) data from a smartwatch and a smart ring. The relative orientation difference of the two devices is measured as the wrist rotation that is independent from arm rotation, which is also position and orientation invariant. Employing our test hardware, we demonstrate that WRIST affords and enables a number of novel yet simplistic interaction techniques, such as (i) macro-micro pointing without explicit mode switching and (ii) wrist gesture recognition when the hand is held in different orientations (e.g., raised or lowered). We report on two studies to evaluate the proposed techniques and we present a set of applications that demonstrate the benefits of WRIST. We conclude with a discussion of the limitations and highlight possible future pathways for research in pointing and gesturing with wearable devices.
Interacting with Autostereograms

Autostereograms are 2D images that can reveal 3D content when viewed with a specific eye convergence, without using extra-apparatus. We contribute to autostereogram studies from an HCI perspective. We explore touch inputs and output design options when interacting with autostereograms on smartphones. We found that an interactive help (i.e. to control the autostereogram stereo-separation), a color-based feedback (i.e. highlight of the screen), and a direct touch input can provide support for faster and more accurate interaction than a static help (i.e. static dots indicating the stereo-separation), an animated feedback (i.e., a 'pressed' effect), and an indirect input. In addition, results reveal that participants learn to perceive smaller and smaller autostereogram content faster with practice. This learning effect transfers across display devices (smartphone to desktop screen).
Acting as if Being Aware of Visitors' Attention Strengthens a Robotic Salesperson's Social Presence

Robotic salespersons have been adopted by many shops. However, due to the weakness of their social presence, they are easily ignored by visitors. Thus, we focused on such robots' behaviors that can strengthen their social presence in a real-world shop. In this research, our goal is to develop a model that can obtain visitors' replies to the robot's utterances. For this reason, we conducted a laboratory experiment and two field experiments. In the laboratory experiment, we found that the robot's ability to express that it can understand the degree of visitors' attention to the robot is important for improving its social presence. Afterward, we developed an engagement estimation model (EEM) based on the findings obtained from the laboratory experiment. We defined visitors' engagement as the probability that the visitors will reply to the robot's utterances. The EEM estimates the engagement from the visitors' real-time nonverbal data. In a laboratory experiment, the situation of being in the laboratory can make the interaction between the participants and the robot unnatural. Therefore, we developed a model based on data of visitors' nonverbal cues in the field experiment and examined whether the model works effectively in the real-world environment. As a result, the automatic greeting mode based on the EEM facilitated the participant's reply to the robot. Thus, we considered that this is because the automatic greeting mode could make a decision of the robot's next behavior precisely. It can be considered that the visitors may feel as if the robot could understand their degree of attention to the robot when the robot greets the visitors based on the automatic greeting mode. Therefore, the automatic greeting mode based on the EEM worked effectively in a real-world environment and could strengthen its social presence.
Hardware Implementation of a Shape Recognition Algorithm based on Invariant Moments

The present work shows the description of a simple fast shape detection algorithm and its implementation in hardware in a FPGA system. The detection algorithm is based on the concepts of Hús moments which are invariant to similarity transformations. The recognition algorithm is implemented by using a non-local means filter. The algorithm is implemented on a FPGA system by using a hardware description language. We present the different design stages of the algorithm implementation which is based on the finite state machine technique. This algorithm is able to recognize a target shape over a test image. Furthermore, this work, describes the advantages of the implementation in hardware, such as speed and parallelism in signal processing. Finally, we show some results of the implementation of this algorithm.
A Speech Promotion System by Using Embodied Entrainment Objects of Spoken Words and a Listener Character for Joint Attention

We have developed a speech promotion system that presents images retrieved based on spoken words on a display and shows the auto-generated nodding reaction of the search images with a listener character. The online image search function can respond to various utterances of the user. In this research, in order to speed up the time to present images, we prepare not only the online image search function but also the pre-stored image call function. Moreover, the listener character in the system moves to look at the image at the same time that it appears. This character's motion prompts the user to observe the image by joint attention guidance. Thus, the system promotes user's speech by the auto-generated nodding reaction of the listener character and images related to spoken words.
Real-Time Estimation of the Urban Air Quality with Mobile Sensor System

Recently, real-time air quality estimation has attracted more and more attention from all over the world, which is close to our daily life. With the prevalence of mobile sensors, there is an emerging way to monitor the air quality with mobile sensors on vehicles. Compared with traditional expensive monitor stations, mobile sensors are cheaper and more abundant, but observations from these sensors have unstable spatial and temporal distributions, which results in the existing model could not work very well on this type of data. In this article, taking advantage of air quality data from mobile sensors, we propose an real-time urban air quality estimation method based on the Gaussian Process Regression for air pollution of the unmonitored areas, pivoting on the diffusion effect and the accumulation effect of air pollution. In order to meet the real-time demands, we propose a two-layer ensemble learning framework and a self-adaptivity mechanism to improve computational efficiency and adaptivity. We evaluate our model with real data from mobile sensor system located in Beijing, China. And the experiments show that our proposed model is superior to the state-of-the-art spatial regression methods in both precision and time performances.
Determinants of Retail Online Shopping: Seller's Perspective

The underlying goal of the paper is to evaluate determinants that stimulate the activity of economic entities in the retail online shopping segment -- on the seller's side. In this respect, in the first part of the paper its authors attempt to define retail online shopping as an e-commerce segment in the chain of creating product value or final service -- in the seller-customer relations. Based on secondary data, shares of retail online sales have been indicated, as a percentage of total retail sales that also consider traditional commerce. These shares also include direct online sales through own web browsers of sellers or social media and indirect sales on the online market place. The authors have indicated transformations with regard to product preferences of customers who make their purchases online. Based on own research in the second part of the paper its authors have evaluated determinants that stimulate the activity of economic entities in the retail online sales segment. In the portfolio of these determinants, with regard to the subject of the research, the following have been distinguished: marketing determinants, competitive advantage sources, price cart and customer online servicing.
Lightweight Security Mechanisms for MPSoCs

Computational systems tend to adopt parallel architectures, by using multiprocessor systems-on-chip (MPSoCs). MPSoCs are vulnerable to software and hardware attacks, as infected applications and Hardware Trojans respectively. These attacks may have the purpose to gain access to sensitive data, interrupt a given application or even damage the system physically. The literature presents countermeasures using dedicated routing algorithms, cryptography, firewalls and secure zones. These approaches present a significant hardware cost (firewalls, cryptography) or are too restrictive regarding the use of MPSoC resources (secure zones). The goal of this paper is to present lightweight security mechanisms for MPSoCs, using four techniques: spatial isolation of applications; dedicated network to send sensitive data; traffic blocking filter; lightweight cryptography. These mechanisms protect the MPSoC against the most common software attacks, as Denial of Service (DoS) and spoofing (man-in-the-middle), and ensures confidentiality and integrity to applications. Results present low area and latency overhead, as well as the effectiveness of using the mechanisms to block malicious traffic.
Emotional Gripping Expression of a Robotic Hand as Physical Contact

This research aims at the emotional expression of a robotic hand through various gripping manners on the user's hand. The proposed system is implemented with a robotic hand's various haptic actuators to realize the change of the fingers' gripping force and the robotic hand's holding duration so that the user can haptically estimate the emotion of the robot. The system is expected to provide stress relief or emotional stability, especially for elderly or challenged people. Our experiments showed that the stronger gripping force was perceived as more hypersensitive and higher affinity and that a longer grasping time increased the higher affinity.
Desired Agent Embodiment in Various Smart House Tasks

The way a smart house system interacts with the user could limit the full potential a smart house is capable to provide, and an agent-mediated interface has been proved to broaden users' mental models. We designed four different conceptual smart house interfaces and surveyed to find out what kind of agent interface is desired under a wide variety of smart house needs.
Predicting Smartphone Users' General Responsiveness to IM Contacts Based on IM Behavior

History of conversations through instant messaging (IM) contains abundant information about the communication patterns of the dyad, including conversation partners' mutual responsiveness to messages. We have, however, not seen many examinations of using such information in modeling mobile users' responsiveness in IM communication. In this paper, we present an in-the-wild study, in which we leverage participants' IM messaging logs to build models predicting their general responsiveness. Our models based on data from 33 IM user achieved an accuracy of up to 71% (AUROC). In particular, we show that 90-day IM-communication patterns, in general, outperformed their 14-day equivalent in our prediction models, indicating better coherence between long-term IM patterns with their general communication experience.
I Think It's Her: Investigating Smartphone Users' Speculation about Phone Notifications and Its Influence on Attendance

Smartphone users' decisions about whether to attend to a notification after sensing it are under-researched. We therefore studied 33 Android users, and found that they speculated extensively about notifications' sources---i.e., which apps and which senders were responsible for them--- before attending to them. The participants' speculation about apps was both more common and more accurate than that about senders. They also were more likely to 1) perceive notifications as important, 2) attend to them, and 3) consider them beneficial if they speculated about them than if they did not or could not. Participants' speculations were based on the alert's inherent characteristics, context, and temporality. Inaccurate speculations were mainly caused by unclear signals, insufficient clues, and a multiplicity of possible sources. Ringer mode affected the accuracy of user speculation, but not its frequency or the frequency of attending to notifications.
How Do Online Price Affect Consumer Purchase: a Moderated Mediation Model

In order to understand how low price affect consumer purchases in China E-Business Market, this study constructs a mediation model that covers online price, perceived quality, and consumer purchase intention through empirical approaches, and discusses the moderating effect of brand awareness on this model. This study takes fast-moving consumer goods as an example to analyze the collected 241 online questionnaires using the AMOS and PROCESS program. The results show that the online price negatively predicts the purchase intention, and the perceived quality plays a mediating effect between the online price and the purchase intention. (1) In the case of high brand awareness, online price positively predicts the perceived quality, which in turn increases the purchase intention and reduces the negative predictive effect of online price on purchase intention. Conversely, in the case of low brand awareness, the online price has no significant effect on the perceived quality. (2) Compared with the brand with high brand awareness, perceived quality has a more pronounced predictive effect on the purchase intention of the brand with low brand awareness.
EOG Glasses: an Eyewear Platform for Cognitive and Social Interaction Assessments in the Wild

In this work we present the smart eyewear demo setup consisting of the software platform for cognitive and social interaction assessments in the wild, with several application cases and a demonstration of activity recognition in real-time. The platform is designed to work with Jins MEME, smart EOG enabled glasses, The user software is capable data logging, posture tracking and recognition of several activities, such as talking, reading and blinking. In this work we present several applications and studies that the platform has been used for.
Evaluation of Pacing for Dialog Robots to Build Trust Relationships with Human Users

This paper proposes a pacing system that makes dialog robots mimic the pacing technique in order to promote trust relationships between humans and robots. Pacing is a communicative technique that synchronizes breathing or how to speak with a person to build relationships among humans. The experiment was performed by comparing the impression of human subjects' conversation with a robot when the pacing system was applied or not applied. The evaluation used both subjective and objective perspectives. From the subjective perspective, the results show significant differences for the questionnaire items concerning "feeling friendliness," "feeling fun," "feeling an emotional connection," "feeling synchrony," "motivation to use" and "listening to the user" between the with and without pacing conditions. Also, from the objective perspective, there is a significant difference in sympathetic activity in heart rate variability.
Does Corporate Performance Influence the High Transfer Type Chosen by Companies?: Research of Empirical Data Based on Chinese Listed Companies

Based on the empirical data of Chinese listed companies, this paper investigates the relationship between a company's performance and its selection of different types of high transfer behaviours. The study found that the stronger the performance and profitability of a company, the more likely it is to follow a dividend distribution policy of high-proportion bonuses. The reason is that when poorly performing companies lack retained earnings, insiders are more likely to throw their shares with a high price through a distribution policy of high increase by transferring shares to achieve their own objectives.
Contamination and genotoxicity biomarker responses in bivalve mussels from the major Lithuanian rivers

European inland waters are under continuous threat of anthropogenic pollution. Determination of background level of biomarker response and subsequent classification of the impact increases the applicability of results. In the current study, we evaluate the range of chemical contamination by measuring the concentrations of metals, polycyclic aromatic hydrocarbons and polychlorinated biphenyls, and the levels of environmental genotoxicity by using the micronuclei and nuclear bud tests in bivalve mussels of the major Lithuanian rivers. Second, we aimed to evaluate the association between chemical contamination and genotoxicity biomarker responses. Finally, we set to determine the background level of genotoxic effects. Such value (summed frequency of MN and NB) was assessed—6‰. On that basis, we develop a scale of potential genotoxic impact and perform ranging sites into five categories. The results clearly indicate the existence of significant differences in the levels of chemical pollution and genotoxicity in different sites. Increased levels of studied parameters were assessed at the areas affected by municipal and industrial effluents, road runoff, combustion products, and in the area contaminated by accidental spillage. On the other hand, downstream decrease of contamination level, presumably associated with biological degradation and photochemical oxidation, were also observed. Genotoxicity parameters were associated with PAH and metal concentrations measured in mussel tissues as well as in sediments. Results also indicate that in situ genotoxicity assessment performed in the areas affected by long‐term contamination of municipal origin might be not sufficiently precise. Study highlights the necessity to combine genotoxicity assessment with chemical analysis. Environ. Mol. Mutagen. 61:338–354, 2020. © 2019 Wiley Periodicals, Inc.
Simian Foamy Virus Co-Infections

Foamy viruses (FVs), also known as spumaretroviruses, are complex retroviruses that are seemingly nonpathogenic in natural hosts. In natural hosts, which include felines, bovines, and nonhuman primates (NHPs), a large percentage of adults are infected with FVs. For this reason, the effect of FVs on infections with other viruses (co-infections) cannot be easily studied in natural populations. Most of what is known about interactions between FVs and other viruses is based on studies of NHPs in artificial settings such as research facilities. In these settings, there is some indication that FVs can exacerbate infections with lentiviruses such as simian immunodeficiency virus (SIV). Nonhuman primate (NHP) simian FVs (SFVs) have been shown to infect people without any apparent pathogenicity. Humans zoonotically infected with simian foamy virus (SFV) are often co-infected with other viruses. Thus, it is important to know whether SFV co-infections affect human disease.