Miracle-dz/UniFAR-FTUs huggingface dataset:
Systemic Immune-Inflammation Index Is Associated With Increased Urinary Albumin Excretion: A Population-Based Study

Background Systemic immune-inflammation index (SII) is a novel inflammatory marker, and inflammation has been reported to be related with renal damage. We aimed to investigate the possible relationship between SII and albuminuria. Methods The present cross-sectional study was conducted among adults with complete data about SII and urinary albumin-to-creatinine ratio (ACR) in 2005–2018 National Health and Nutrition Examination Survey (NHANES). SII was calculated as the platelet count × neutrophil count/lymphocyte count. Albuminuria was defined as ACR >30mg/g. Weighted multivariable regression analysis and subgroup analysis were conducted to explore the independent relationship between SII and albuminuria. Results A total of 36,463 individuals were included in our analysis; 9.56% participants were categorized as having albuminuria overall and increased with the higher SII tertiles (tertile 1, 7.83%; tertile 2, 8.49%; tertile 3, 12.13%; p for trend <0.0001). Multivariable logistic regression showed that a higher SII level was associated with increased likelihood of albuminuria independently (OR = 1.31; 95% CI, 1.17–1.48, p<0.0001) after full adjustment. Subgroup analysis and interaction test showed that there was no significant dependence of gender, age, body mass index, hypertension, diabetes, non‐alcoholic fatty liver disease, and estimated glomerular filtration rate (eGFR) on this positive association (all p for interaction >0.05). Conclusions SII was positively associated with increased urinary albumin excretion in US adults. Further large-scale prospective studies are still needed to analyze the role of SII in albuminuria.
Epidemiological Study of Tricuspid Regurgitation After Cardiac Transplantation. Does it Influence Survival?

Background: Tricuspid valve disease is the most frequent valvulopathy after heart transplantation (HTx). Evidence for the negative effect of post-transplant tricuspid regurgitation (TR) on survival is contradictory. The aim of this study was to analyze the causes of post-transplant TR and its effect on overall mortality. Methods: This is a retrospective observational study of all transplants performed in two Spanish centers (1009 patients) between 2000 and 2019. Of the total number of patients, 809 had no TR or mild TR and 200 had moderate or severe TR. The etiology of TR was analyzed in all cases. Results: The prevalence of moderate and severe TR was 19.8%. The risk of mortality was greater when TR was caused by early primary graft failure (PGF) or rejection (p < 0.05). TR incidence was related to etiology: incidence of PGF-induced TR was higher in the first period, while TR due to rejection and undefined causes occurred more frequently in three periods: in the first year, in the 10–14-year period following HTx, and in the long term (16–18 years). In the multivariable analysis, TR was significantly associated with mortality/retransplantation (HR:1.04, 95% CI:1.01–1.07, p:0.02). Conclusion: The development of TR after HTx is relatively frequent. The annual incidence depends on TR severity and etiology. The risk of mortality is greater in severe TR due to PGF or rejection. Graphical Abstract
Diagnostic Accuracy of Subtraction Coronary CT Angiography in Severely Calcified Segments: Comparison Between Readers With Different Levels of Experience

Purpose Subtraction coronary CT angiography (CCTA) may reduce blooming and beam-hardening artifacts. This study aimed to assess its value in improving the diagnostic accuracy of readers with different experience levels. Method We prospectively enrolled patients with target segment who underwent CCTA and invasive coronary angiography (ICA). Target segment images were independently evaluated by three groups of radiologists with different experience levels with CCTA using ICA as the standard reference. Diagnostic accuracy was measured by the area under the curve (AUC), using ≥50% stenosis as the cut-off value. Results In total, 134 target segments with severe calcification from 47 patients were analyzed. The mean specificity of conventional CCTA for each group ranged from 22.4 to 42.2%, which significantly improved with subtraction CCTA, ranging from 81.3 to 85.7% (all p < 0.001). The mean sensitivity of conventional CCTA for each group ranged from 83.3 to 88.0%. Following calcification subtraction, the mean sensitivity decreased for the novice (p < 0.001) and junior (p = 0.017) radiologists but was unchanged for the senior radiologists (p = 0.690). With subtraction CCTA, the mean AUCs of CCTA significantly increased: values ranged from 0.53, 0.54, and 0.61 to 0.70, 0.74, and 0.85 for the novice, junior, and senior groups (all p < 0.001). Conclusion Subtraction CCTA could improve the diagnostic accuracy of radiologists at all experience levels of CCTA interpretation.
Supplementation of Dietary Quercetin and Vitamin E Promotes the Intestinal Structure and Immune Barrier Integrity in Aged Breeder Hens

In aged animals, the physiological functions of the gastrointestinal tract (GIT) are reduced. Dietary intervention is necessary to re-activate GIT functions. The objective of this study was to investigate the impacts of dietary combination of quercetin (Q) and vitamin E (VE) on the intestinal structure and barrier integrity in aged breeder chickens. A sum of 400 (65-wks-old) Tianfu breeder hens were randomly allotted into four (4) groups with four (4) replicates, and fed with basal diet; basal diet supplemented with 0.4g/kg of Q; basal diet supplemented with 0.2g/kg of VE; and basal diet supplemented with the combination of Q (0.4 g/kg) and VE (0.2 g/kg) for 14 weeks. At the end of the 14th week, serum and gut segments were collected from eight hens per group for analyses. The results showed that Q+VE exerted synergistic effects on intestinal morphology by promoting villi height and crypt depth (P < 0.05), as well as mitigated the intestinal inflammatory damage of the aged hens, but decreased the concentration of serum D-lactate and diamine oxidase; and increased the levels of secretory immunoglobulin A (sIgA) and Mucin-2 mRNA (P < 0.05). Furthermore, the mRNA expression of intestinal tight junction proteins including occludin, ZO1, and claudin-1 was increased by Q+VE (P < 0.05). Moreover, Q+VE decreased the mRNA expression of the pro-inflammatory genes (TNF-α, IL-6, and IL-1β), and increased the expression of anti-inflammatory genes (IL-10 and IL-4) (P < 0.05). These results were consistent with the mRNA expression of Bax and Bcl-2. In addition, Q+VE protected the small intestinal tract from oxidative damage by increasing the levels of superoxide dismutase, total antioxidant capacity, glutathione peroxidase, catalase (P < 0.05), and the mRNA expression of SOD1 and GPx-2. However, Q+VE decreased malondialdehyde levels in the intestine compared to the control (P < 0.05). These results indicated that dietary Q+VE improved intestinal function in aged breeder hens, by protecting the intestinal structure and integrity. Therefore, Q+VE could act as an anti-aging agent to elevate the physiological functions of the small intestine in chickens.
Motivation for Collective Action in the Smart Living Business Ecosystem

While smart home services have been on the agenda for over three decades, advances in mobile technologies and concepts like Internet of things are creating a new wave of interest in the market. Traditionally, smart home applications were offered in stovepipe architectures by individual organizations, leading to a plethora of service platforms. Today, smart home service providers are increasingly looking to collaborate in order to jointly develop and share common service platforms. However, collective action literature asserts that such collaboration will only take place if the motives to collaborate outweigh the hurdles. In this paper, we study which motivational drivers lead to collective action for smart living services. We do so in a survey study among 140 home installation companies that are member of the major Dutch branch organization. We find that the tendency to collaborate is mainly driven by motives related to new business opportunities, and that more strategic and solidarity motives do not play a role.
Multimodal Error Correction for Speech-to-Text in a Mobile Office Automated Vehicle: Results From a Remote Study

Future users of automated vehicles will demand the ability to perform diverse and extensive non-driving related tasks. However, prevailing restrictions in the car require new interaction concepts to enable productive office work. Intelligent voice-based interfaces may be a solution to facilitate productivity while at the same time keeping the “driver in the loop” and thereby maintaining safety. In this work, we investigated the repair problem of productive speech-to-text input in a highly automated vehicle. We examined the user experience of selecting/navigating to an incorrectly recognized word using only speech, pointing and clicking on a touchpad, and using mid-air hand gestures. Results indicate that hand gestures (condition VaG) have high hedonic quality but are not considered viable for error correction in productive text input. On the other hand, the unimodal (Voice-only; baseline) and touchpad-based point-and-click (VaT) approaches to error correction were rated equally well in the hypothesized “mobile office” automated vehicle. The utilized remote study execution methodology proved to be a useful intermediary tool between pure online surveys and on-site studies for qualitative research during a pandemic but suffered from a lack of fidelity and options for objective usability and safety evaluation.
PowerMorph: QoS-Aware Server Power Reshaping for Data Center Regulation Service

Adoption of renewable energy in power grids introduces stability challenges in regulating the operation frequency of the electricity grid. Thus, electrical grid operators call for provisioning of frequency regulation services from end-user customers, such as data centers, to help balance the power grid’s stability by dynamically adjusting their energy consumption based on the power grid’s need. As renewable energy adoption grows, the average reward price of frequency regulation services has become much higher than that of the electricity cost. Therefore, there is a great cost incentive for data centers to provide frequency regulation service. Many existing techniques modulating data center power result in significant performance slowdown or provide a low amount of frequency regulation provision. We present PowerMorph, a tight QoS-aware data center power-reshaping framework, which enables commodity servers to provide practical frequency regulation service. The key behind PowerMorph is using “complementary workload” as an additional knob to modulate server power, which provides high provision capacity while satisfying tight QoS constraints of latency-critical workloads. We achieve up to 58% improvement to TCO under common conditions, and in certain cases can even completely eliminate the data center electricity bill and provide a net profit.
Expressive Communication: Evaluating Developments in Generative Models and Steering Interfaces for Music Creation

There is an increasing interest from ML and HCI communities in empowering creators with better generative models and more intuitive interfaces with which to control them. In music, ML researchers have focused on training models capable of generating pieces with increasing long-range structure and musical coherence, while HCI researchers have separately focused on designing steering interfaces that support user control and ownership. In this study, we investigate how developments in both models and user interfaces are important for empowering co-creation where the goal is to create music that communicates particular imagery or ideas (e.g., as is common for other purposeful tasks in music creation like establishing mood or creating accompanying music for another media). Our study is distinguished in that it measures communication through both composer’s self-reported experiences, and how listeners evaluate this communication through the music. In an evaluation study with 26 composers creating 100+ pieces of music and listeners providing 1000+ head-to-head comparisons, we find that more expressive models and more steerable interfaces are important and complementary ways to make a difference in composers communicating through music and supporting their creative empowerment.
Hazard Notifications for Cyclists: Comparison of Awareness Message Modalities in a Mixed Reality Study

Cycling is an environmentally friendly means of transport with growing popularity. However, there is still potential for increased road safety in the future. We argue that by making assistance systems available to cyclists, accidents could be prevented. In this paper, we focus on potential accidents caused by vehicle doors opening in a cyclist’s path of travel, which can lead to serious injuries to the cyclist. Using a mixed-methods approach, we explored how messages informing about a potentially opening door ahead are perceived and understood regarding usability and intuitiveness in a bicycle simulator study (N=24). We investigated how visual messages, visual messages and auditory icons, and visual and voice messages on a head-mounted device are subjectively perceived. We also assessed our participants’ attitudes toward using such systems and mixed reality simulations for bicycle safety research in general. Our results show that participants preferred visual messages and auditory cues and found these types of notifications more enjoyable than visual messages alone. Furthermore, the results suggest that such a system would be used while cycling. Participants agreed that mixed reality simulation is suitable for testing/evaluating novel support systems and finding initial insights in the first step but confirmed that real-world testing on the road is mandatory nonetheless.
ImCasting: Nonverbal Behaviour Reinforcement Learning of Virtual Humans through Adaptive Immersive Game

This research work puts a focus on the user experience of an alternative method to teach nonverbal behaviour to Embodied Conversational Agents in immersive environments. We overcome the limitations of the existing approaches by proposing an adaptive Virtual Reality game, called ImCasting, in which the player takes an active role in improving the learning models of the agents. Specifically, we based our approach on the Human-in-the-loop framework with human preferences to teach the nonverbal behaviour to the agents through the system. We introduce game mechanisms built around all the tasks of this Machine Learning framework, designing how a human should interact within this framework in real-time. The study explores how a game interaction in an immersive environment can improve the user experience in performing this interactive task, sharing the same space with the learning agents. In particular, we focus on the involvement of the players as well as the usability of the system. We conducted a preliminary evaluation to compare the design of our system with a baseline system which does not use any game mechanisms in teaching the nonverbal behaviour to virtual agents. Results suggest that our design concept and the game story are more engaging, increasing the satisfaction usability factor perceived by the participants.
Informing App Design to Reduce Self-Management Challenges Identified for Chronic Disease

Self-managing chronic diseases is challenging for patients and involves handling a range of long-term treatments. Patients have many responsibilities to manage. Feeling overwhelmed by this information can lead to a sense of hopelessness and depression. Mobile apps can be beneficial support for chronically ill patients to self-manage their condition. Many apps are available for various purposes, such as fitness and daily wellbeing, but none are customised for chronically ill patients who need to manage their disease daily. The purpose of this paper is to propose an approach to identify the critical challenges faced by patients when self-managing their chronic illness. These challenges will inform the design of a cus-tomised mobile app that is user friendly and will assist patients in managing their disease efficiently and effectively. A qualitative interpretive approach analysed through the theoretical lens of the theory of planned behaviour (TPB) is the proposed methodology for this project. Interpretivism is about understanding people in their natural world. The social world of people with chronic illnesses is lonely and isolating. The TPB connects a persons’ attitudes and behaviour. Understanding chronically ill patients’ feelings of isolation and helplessness through data gathered by semi-structured open-ended interviews will enable a thematic analysis of the critical challenges chronically ill patients face. This paper provides a unique approach for identifying and analysing critical issues that the chronically ill face from a patient viewpoint. These issues will be used to customise the design of an app for self-management purposes.
Predicting Persuasiveness of Participants in Multiparty Conversations

Persuasiveness is an important capability in communication skills. This study aims to estimate the persuasiveness of participants in group discussions. First, human annotators rated the level of persuasiveness of each of four participants in group discussions. Next, multimodal and multiparty models were created to estimate the persuasiveness of each participant using speech, language, and visual (head pose) features using GRU-based neural network. The experimental results showed that multimodal and multiparty models performed better than unimodal and single-person models. The best performing multimodal multiparty model achieved 80% accuracy in predicting high/low persuasiveness, and 77% accuracy in predicting the most persuasive participant in the group.
Differentiating Endogenous and Exogenous Attention Shifts Based on Fixation-Related Potentials

Attentional shifts can occur voluntarily (endogenous control) or reflexively (exogenous control). Previous studies have shown that the neural mechanisms underlying these shifts produce different activity patterns in the brain. Changes in visual-spatial attention are usually accompanied by eye movements and a fixation on the new center of attention. In this study, we analyze the fixation-related potentials in electroencephalographic recordings of 10 participants during computer screen-based viewing tasks. During task performance, we presented salient visual distractors to evoke reflexive attention shifts. Surrounding each fixation, 0.7-second data windows were extracted and labeled as “endogenous” or “exogenous”. Averaged over all participants, the balanced classification accuracy using a person-dependent Linear Discriminant Analysis reached 59.84%. In a leave-one-participant-out approach, the average classification accuracy reached 58.48%. Differentiating attention shifts, based on fixation-related potentials, could be used to deepen the understanding of human viewing behavior or as a Brain-Computer Interface for attention-aware user interface adaptations.
ThermalDrive - Towards Situation Awareness over Thermal Feedback in Automated Driving Scenarios

We present ThermalDrive, a thermal interface that provided situational awareness information using thermal feedback on the face of the driver. A prototype is built to simulate the autonomous driving and the thermal interface in virtual reality. We conduct an experiment to investigate the impact of displaying system situation awareness information via the thermal feedback in a VR driving simulation (16 participants). The initial results indicate that the thermal interface might be a suitable feedback mechanism to convey some information in autonomous driving. In particular, cold thermal feedback was effective in terms of notability and user preference.
Recommendations as Challenges: Estimating Required Effort and User Ability for Health Behavior Change Recommendations

Recommender Systems use implicit and explicit user feedback to recommend desired products or items online. When the recommendation item is a task or behavior change activity, several variables, such as the difficulty of the task and users’ ability to achieve it, in addition to user preferences and needs, determine the suitability of the recommendations. This paper focuses on how user ability and task difficulty concepts can be integrated into the recommendation process to personalize health activity recommendations. To this end, we compare five approaches, some borrowed from the sports and gaming world, and explore their application, advantages, and drawbacks. Through a study of two weeks, we obtained a suitable dataset to investigate how these algorithms can be used for a health recommender system (HRS) and which one is the most appropriate choice for an online HRS in terms of characteristics and flexibility required for behavior change related tailoring. We compared this choice with a baseline algorithm as part of a fully functional HRS to assess the feasibility and impact of integrating the user ability and required effort concepts on the user engagement with the recommendations in an online longitudinal study of two weeks. The results overall suggest that such integration is effective, and in addition to realizing health behavior change requirements, it improves user engagement with the recommendations.
The Diversity of Music Recommender Systems

While the algorithms used by music streaming services to provide recommendations have often been studied in offline, isolated settings, little research has been conducted studying the nature of their recommendations within the full context of the system itself. This work seeks to compare the level of diversity of the real-world recommendations provided by five of the most popular music streaming services, given the same lists of low-, medium- and high-diversity input items. We contextualized our results by examining the reviews for each of the five services on the Google Play Store, focusing on users’ perception of their recommender systems and the diversity of their output. We found that YouTube Music offered the most diverse recommendations, but the perception of the recommenders was similar across the five services. Consumers had multiple perspectives on the recommendations provided by their music service—ranging from not wanting any recommendations to applauding the algorithm for helping them find new music.
An Intelligent Pedagogical Agent to Foster Computational Thinking in Open-Ended Game Design Activities

Free-form Game-Design (GD) environments show promise in fostering Computational Thinking (CT) skills at a young age. However, such environments can be challenging to some students due to their highly open-ended nature. Our long-term goal is to alleviate this difficulty via pedagogical agents that can monitor the student interaction with the environment, detect when the student needs help and provide personalized support accordingly. In this paper, we present a preliminary evaluation of one such agent deployed in a real-word free-form GD learning environment to foster CT in the early K-12 education, Unity-CT. We focus on the effect of repetition by comparing student behaviors between no intervention, 1-shot, and repeated intervention groups for two different errors that are known to be challenging in the online lessons of Unity-CT environment. Our findings showed that the agent was perceived very positively by the students and the repeated intervention showed promising results in terms of helping students make less errors and more correct behaviors, albeit only for one of the two target errors. Based on these results, we provide insights on how to improve the delivery of the agent’s interventions in free-form GD environments.