Miracle-dz/UniFAR-FTUs huggingface dataset:
Observational Constraints on Quintessence: Thawing, Tracker, and Scaling models

For two types of quintessence models having thawing and tracking properties, there exist analytic solutions for the dark energy equation of state $w$ expressed in terms of several free parameters. We put observational bounds on the parameters in such scenarios by using the recent type Ia supernovae, cosmic microwave background, and baryon acoustic oscillations data. The observational constraints are quite different depending on whether or not the recent baryon acoustic oscillations data from BOSS are taken into account. With the BOSS data the upper bounds of today's values of $w$ ($={w}_{0}$) in thawing models is very close to $\ensuremath{-}1$, whereas without this data the values of ${w}_{0}$ away from $\ensuremath{-}1$ can still be allowed. The tracker equation of state ${w}_{(0)}$ during the matter era is constrained to be ${w}_{(0)}l\ensuremath{-}0.949$ at 95% C.L. even without the BOSS data, so that the tracker models with $w$ away from $\ensuremath{-}1$ are severely disfavored. We also study observational constraints on scaling models in which $w$ starts to evolve from 0 in the deep matter era and show that the transition to the equation of state close to $w=\ensuremath{-}1$ needs to occur at an early cosmological epoch. In the three classes of quintessence models studied in this paper, the past evolution of the Hubble parameters in the best-fit models shows only less than a 2.5% difference compared to $\ensuremath{\Lambda}\mathrm{CDM}$.
Magic Brush: An AI-based Service for Dementia Prevention focused on Intrinsic Motivation

This study proposes Magic Brush, an AI-based application for dementia prevention targeting middle-aged individuals who may be at risk for mild cognitive impairment (MCI) or dementia. In order to prevent dementia effectively at home, it is important to strengthen their intrinsic motivation. Promoting motivation is a critical issue in designing computerized cognitive therapy (CCT) for sustainability. Guided by self-determination theory, three main factors of intrinsic motivation were utilized as the main themes for the development: autonomy, competence, and relatedness. Especially, we focused on demotivating factors of low competence which are commonly shared among the elderly and developed a magic brush function equipped with neural style transfer technology to help disconnect the link between low competence and demotivation. The user study (n=35) targeting individuals aged over 50 was conducted with both quantitative and qualitative methods. In general, users reported positive experiences with Magic Brush. The results of Structural Equation Modeling analysis showed that intrinsic motivation is an important contributor to the intention to use together with perceived usefulness. Intrinsic motivation can be promoted by AI therapist likability and perception of one's own performance. Discussion and implications are provided in relation to using AI technology to promote motivation.
Designing for Shared Values: Exploring Ethical Dilemmas of Conducting Values Inclusive Design Research

Recent prevalence of values-inclusive design research introduces the potential of conducting research with those whose values conflict with researchers' own values. This is the scenario we have found ourselves in as we conduct values-inclusive participatory design to develop and deploy critical digital literacy education in a rural Appalachian community. We present provocations which outline the ethical concerns we have grappled with in pursuit of conducting fair and responsible research for our participants, indirect stakeholders, and ourselves. Through consideration of these provocations, we have developed a preliminary approach for managing a research relationship with those with whom we disagree which we call Designing for Shared Values. This approach is a conflict-avoidant method for negotiating values in values-inclusive design. It centers around reflexivity as a mechanism to account for one's own values and potential impacts of design research outcomes on indirect stakeholders, while maintaining responsibility to prioritize beneficial outcomes to research participants.
Relative Feedback Increases Disparities in Effort and Performance in Crowdsourcing Contests

Rankings and leaderboards are often used in crowdsourcing contests and online communities to motivate individual contributions but feedback based on social comparison can also have negative effects. Here, we study the unequal effects of such feedback on individual effort and performance for individuals of different ability. We hypothesize that the effects of social comparison differ for top performers and bottom performers in a way that the inequality between the two increases. We use a quasi-experimental design to test our predictions with data from Topcoder, a large online crowdsourcing platform that publishes computer programming contests. We find that in contests where the submitted code is evaluated against others' submissions, rather than using an absolute scale, top performers increase their effort while bottom performers decrease it. As a result, relative scoring leads to better outcomes for those at the top but lower engagement for bottom performers. Our findings expose an important but overlooked drawback from using gamified competitions, rankings, and relative evaluations, with potential implications for crowdsourcing markets, online learning environments, online communities, and organizations in general.
Intimate Narratives: An Assets-Based Approach to Develop Holistic Perspectives of Student Mothers' Lives and Their Use of Technology in Parenting

This paper details our collaborative approach in capturing a holistic understanding of parental technology use through an assets-based framework. We steer the focus away from the design of technology as the central force of technological innovation, and instead support participants to reflect and describe intimate details that highlight specific use-contexts of technology in their lives. We leverage a group of foreign graduate student mothers' self-described unique strengths to gain an in-depth account of their lived experiences with technology. As research participants and co-authors, our collaborators elicit intimate narratives about meaningful events in their lives, bringing social and cultural aspects of their lived experience to the forefront, and thus providing broader context of their use of technology. We detail and reflect upon our approach of promoting user agency by creating an affinity group, fostering a safe and intimate space for research engagement, and describe the implications of using our adapted research methodology in intimate settings. We conclude by highlighting the various ways in which technology facilitates foreign student parenting, as well as the ways in which it serves as a temporary band-aid solution, prompting consideration of larger social issues.
Designing a Medical Crowdfunding Website from Sense of Community Theory

A sense of community is important in encouraging people to contribute to a variety of causes and the communities that support them. Researchers have identified website design features that can engender a sense of community on sites to promote contributions. However, most findings about design features are based on observational empirical research testing single features at a time or on standard practice and rarely use integrated theories to provide rationale for their design suggestions. This work investigates ways to re-design an entire website---with a simulated medical crowdfunding interface entitled Community Journey---informed by Sense of Community Theory to increase site visitors' sense of community and contributions. A between-subjects experiment revealed that the Community Journey interface increased potential supporters' sense of community and their overall willingness to contribute via monetary donations, campaign shares, personal messages, and offline support. Think-aloud interviews identified the interface features responsible for the overall increase in willingness to contribute. Finally, we suggest theory driven design implications for creating websites to build a strong support community and to encourage various contributions.
"What is Your Envisioned Future?": Toward Human-AI Enrichment in Data Work of Asthma Care

Patient-generated health data (PGHD) is crucial for healthcare providers' decision making, as it complements clinical data by providing a more holistic view of patients' daily conditions. We interviewed 20 healthcare providers in asthma care to envision future technologies to support their PGHD use. We found that healthcare providers want future artificial intelligence (AI) systems to enhance their ability to treat patients by analyzing PGHD for profiling risk and predicting deterioration. Despite the potential benefits of AI, providers perceived various challenges of AI use with PGHD, including AI-driven data inequity, added burden, lack of trust toward AI, and fear of being replaced by AI. Clinicians wished for a future of co-dependent human-AI collaboration, where AI will help them to improve their clinical practice. In turn, healthcare providers can improve AI systems by making AI outputs more trustworthy and humane. Through the lens of data feminism, we discuss the importance of considering context and aligning the complex human infrastructure before designing or deploying PGHD-based AI systems in clinical settings. We highlight the opportunity to design for human-AI enrichment, where humans and AI not only partner with each other for improved performance, but also enrich each other to enhance each other's work overtime.
I Know I Am, But What Are You? How Culture and Self-Categorization Affect Emotions Toward Robots

As routinely working with robots spreads globally, it becomes important to understand how best to customize robots to each culture to maximize collaboration between humans and robots. In two distinct cultures (United States and Portugal) we examined group-based emotions toward robots with participants self-categorizing three different ways (ingroup, outgroup, and neutral). We tested and confirmed our baseline assumptions that Portuguese participants are more collectivistic and less individualistic, and feel closer with a team in negative, but not positive, scenarios, compared to United States participants. Supporting our hypotheses, the results showed that participants rated more positive emotions toward the robot in the ingroup condition than in the outgroup or neutral conditions. Moreover, an interaction effect between culture and self-categorization revealed that Portuguese participants had more positive group-based emotions toward the robot than United States participants when self-categorizing as an ingroup. We discuss the implications in terms of human-robot teaming and potential future research directions.
Influence of applied voltage and electrical conductivity on underwater pin-to-pin pulsed discharge

A parametric study of an underwater pulsed plasma discharge in pin-to-pin electrode configuration has been performed. The influence of two parameters has been reported, the water conductivity (from 50 to 500 µS cm−1) and the applied voltage (from 6 to 16 kV). Two complementary diagnostics, time resolved refractive index-based techniques and electrical measurements have been performed in order to study the discharge propagation and breakdown phenomena in water according to the two parameters. A single high voltage of duration between 100 µs and 1 ms is applied between two 100 µm diameter platinum tips separated by 2 mm and immersed in the aqueous solution. This work, which provides valuable new results, is of great interest to better understand the mechanisms of initiation and propagation of pin-to-pin discharge in water. For low conductivity (from 50 to 100 µS cm−1) results have confirmed two regimes of discharge (cathode and anode) and the increase of the applied voltage first makes the breakdown more achievable and then favors the apparition of the anode regime. For 500 µS cm−1 results have highlighted cathode regime for low applied voltage but a mixed regime (anode and cathode) for high applied voltage.
Reliance and Automation for Human-AI Collaborative Data Labeling Conflict Resolution

Human data labeling with multiple labelers and the resulting conflict resolution remains the norm for many enterprise machine learning pipelines. Conflict resolution can be a time-intensive and costly process. Our goal was to study how human-AI collaboration can improve conflict resolution, by enabling users to automate groups of conflict resolution tasks. However, little is known about whether and how people will rely on automation during conflict resolution. Currently, automation commonly uses labelers' majority vote labels for conflict resolution, as the top chosen label by most labelers is often correct. We envisioned a system where an AI would assist in finding cases where the labeler majority vote was wrong and where automation is supported for batches or groups of conflicts. In order to understand whether humans could use labeler and AI information effectively, we investigated how and when users rely on labeler and AI information and on automated group conflict resolution. We ran a study with 144 Mechanical Turk workers. We found that automation increased users' accuracy/time, use of automated conflict resolution was relatively similar regardless of whether the automation was based on labeler or AI selected labels, and providing labeler and AI selected labels may reduce inappropriate reliance on automation.
The Substance of Style: How Social Class-Based Styles of Interpersonal Interaction Shape Hiring Assessments at Large Technology Companies

Individuals' social class background shapes their life experiences and outcomes, including their familial upbringing and educational attainment. However, we know little about how social class background influences the hiring practices of professional settings, and specifically, the ways in which evaluators conceptualize a potential link between social class background and hiring. Through interviewing 50 evaluators at large technology companies, we find that only 19 of them discussed how social class background affects applicants' access to resources, and none articulated the ties between social class background and preferred interpersonal interactional styles. This is particularly troubling because all evaluators described assessing the key hiring criteria of "innovation potential" based on whether applicants display what we term a "transboundary interactional style. " This style involves demonstrating an ease with articulating cross-disciplinary ideas as well as facilitating back-and-forth scholarly conversations and debates. While evaluators characterized this style as stemming from applicants' individual personalities, we draw on past sociological literature to suggest that this style is also cultivated in upper-middle-class environments. Given technology companies' expressed desire to hire a diverse workforce by minimizing biases in evaluators' assessments, we conclude with ideas for evaluators to develop more equitable hiring practices.
Amazon Echo Show as a Multimodal Human-to-Human Care Support Tool within Self-Isolating Older UK Households

Although the use of voice assistants to support older adults at home shows promise, little is known about how the next generation of these devices, which also include displays, can support health and care needs. This question has become more important during COVID-19, when issues of social isolation for older adults have been exacerbated. During social distancing measures in the UK, eleven older adult households (16 participants) were interviewed before receiving an Amazon Echo Show, shortly after receiving it, and after three months of use. We identify ways in which this multi-modal device is used by people in social isolation to support social, care, and information needs in the home. We frame these findings within the growing research area of smart homes for health and care, and provide implications for the adoption, use and acceptance of these devices to support aging in place together.
Who's in the Crowd Matters: Cognitive Factors and Beliefs Predict Misinformation Assessment Accuracy

Misinformation runs rampant on social media and has been tied to adverse health behaviors such as vaccine hesitancy. Crowdsourcing can be a means to detect and impede the spread of misinformation online. However, past studies have not deeply examined the individual characteristics - such as cognitive factors and biases - that predict crowdworker accuracy at identifying misinformation. In our study (n = 265), Amazon Mechanical Turk (MTurk) workers and university students assessed the truthfulness and sentiment of COVID-19 related tweets as well as answered several surveys on personal characteristics. Results support the viability of crowdsourcing for assessing misinformation and content stance (i.e., sentiment) related to ongoing and politically-charged topics like the COVID-19 pandemic, however, alignment with experts depends on who is in the crowd. Specifically, we find that respondents with high Cognitive Reflection Test (CRT) scores, conscientiousness, and trust in medical scientists are more aligned with experts while respondents with high Need for Cognitive Closure (NFCC) and those who lean politically conservative are less aligned with experts. We see differences between recruitment platforms as well, as our data shows university students are on average more aligned with experts than MTurk workers, most likely due to overall differences in participant characteristics on each platform. Results offer transparency into how crowd composition affects misinformation and stance assessment and have implications on future crowd recruitment and filtering practices.
Careful Data Tinkering

In this paper, we describe and analyze the data practices of an activist non-profit, the Housing Justice League. We focus on their Tenant Power Hotline, a community outreach tool for tenants facing eviction and seeking organizing support. This research contributes to existing scholarship that examines data practices and the use of information and communication technologies in non-profit and grassroots organizations. To this existing scholarship, we share the structure of a counter-institution: an organization that strives to operate outside the non-profit industrial complex. We then interpret the work of Housing Justice League through the lens of care, identifying homebrewed databases and data fragmentations as negotiations between care and efficiency. We argue that care is enacted through the assemblage of the technical systems, and present tinkering as an alternative approach to developing data practices.
Towards Responsive Architecture that Mediates Place

Responsive architecture envisions the built environment to adapt to the changing needs of its occupants dynamically. Although it is increasingly feasible to move space-defining objects like room dividers by mobile robots, little is known about how or when such spatial adaptations should occur. We therefore measured the experience of 26 occupants while they performed six different activities inside an office breakout room that was being adapted by a robotically moving wall in either a reactive or proactive way. Based on these empirical findings, we propose how autonomous spatial adaptation should primarily aim to balance the spatial, situational and subjective qualities of the resulting sense of place. We also define eight distinct design recommendations that exploit the unique affordances of spatial adaptation. By asserting that future advances in human-building interaction (HBI) should be based on creating appropriate places rather than controlling functional spaces, we foresee how responsive architecture might become as compelling as its static counterpart.
Improving Students Argumentation Learning with Adaptive Self-Evaluation Nudging

Recent advantages from computational linguists can be leveraged to nudge students with adaptive self-evaluation based on their argumentation skill level. To investigate how individual argumentation self-evaluation will help students write more convincing texts, we designed an intelligent argumentation writing support system called ArgumentFeedback based on nudging theory and evaluated it in a series of three qualitative and quantitative studies with a total of 83 students. We found that students who received a self-evaluation nudge wrote more convincing texts with a better quality of formal and perceived argumentation compared to the control group. The measured self-efficacy and the technology acceptance provide promising results for embedding adaptive argumentation writing support tools in combination with digital nudging in traditional learning settings to foster self-regulated learning. Our results indicate that the design of nudging-based learning applications for self-regulated learning combined with computational methods for argumentation self-evaluation has a beneficial use to foster better writing skills of students.
Amplification of the coupling strength in a hybrid quantum system

Realization of strong coupling between two different quantum systems is important for fast transferring quantum information between them, but its implementation is difficult in some hybrid quantum systems. Here we propose a scheme to enhance the coupling strength between a single nitrogen-vacancy center and a superconducting circuit via squeezing. The main recipe of our scheme is to construct a unitary squeezing transformation by directly tuning the specifically-designed superconducting circuit. Using the experimentally accessible parameters of the circuit, we find that the coupling strength can be largely amplified by applying the squeezing transformations to the system. This provides a new path to enhance the coupling strengths in hybrid quantum systems.
TeamSpiritous - A Retrospective Emotional Competence Development System for Video-Meetings

Video-meetings essentially determine remote work life. However, video-meetings experience challenges originating from human emotions. Therefore, emotional competence, the ability to perceive, understand, and regulate emotions, is of the highest relevance. With limited transfer capacity of emotional information and various communication challenges, developing emotional competence, however, is complex. To overcome this complexity, we present TeamSpiritous, an individual, retrospective emotional competence development system for video-meetings. TeamSpiritous allows to upload and analyze recorded video-meetings on emotional processes and provides support for individual development of emotional competence. We evaluated TeamSpiritous quantitatively and qualitatively in a six-week, longitudinal field study with 47 participants from China and Germany. Results of our study show that intra- and interpersonal emotional competence significantly increased over time for the whole sample. In particular, intrapersonal emotion regulation and interpersonal emotion perception and understanding improved. Since remote work video-meetings are often multicultural, we also investigated cultural differences and observed in our results that the effects of TeamSpiritous exist beyond cultural backgrounds (China, Germany). With our work, we contribute with the design of TeamSpiritous and understanding of its effects on emotional competence development.